diff --git a/Autograd21GaPLightExtractor.ipynb b/Autograd21GaPLightExtractor.ipynb
index f52d8a88..73bb8047 100644
--- a/Autograd21GaPLightExtractor.ipynb
+++ b/Autograd21GaPLightExtractor.ipynb
@@ -388,7 +388,7 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m13:56:44 CEST\u001b[0m\u001b[2;36m \u001b[0mStarted working on Batch containing \u001b[1;36m3\u001b[0m tasks.                      \n"
+       "\u001B[2;36m13:56:44 CEST\u001B[0m\u001B[2;36m \u001B[0mStarted working on Batch containing \u001B[1;36m3\u001B[0m tasks.                      \n"
       ]
      },
      "metadata": {},
@@ -401,7 +401,7 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m13:56:47 CEST\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.075\u001b[0m for the whole batch.               \n"
+       "\u001B[2;36m13:56:47 CEST\u001B[0m\u001B[2;36m \u001B[0mMaximum FlexCredit cost: \u001B[1;36m0.075\u001B[0m for the whole batch.               \n"
       ]
      },
      "metadata": {},
@@ -415,8 +415,8 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m             \u001b[0m\u001b[2;36m \u001b[0mUse \u001b[32m'Batch.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed FlexCredit cost after   \n",
-       "\u001b[2;36m              \u001b[0mthe Batch has completed.                                          \n"
+       "\u001B[2;36m             \u001B[0m\u001B[2;36m \u001B[0mUse \u001B[32m'Batch.real_cost\u001B[0m\u001B[32m(\u001B[0m\u001B[32m)\u001B[0m\u001B[32m'\u001B[0m to get the billed FlexCredit cost after   \n",
+       "\u001B[2;36m              \u001B[0mthe Batch has completed.                                          \n"
       ]
      },
      "metadata": {},
@@ -443,7 +443,7 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m13:57:04 CEST\u001b[0m\u001b[2;36m \u001b[0mBatch complete.                                                   \n"
+       "\u001B[2;36m13:57:04 CEST\u001B[0m\u001B[2;36m \u001B[0mBatch complete.                                                   \n"
       ]
      },
      "metadata": {},
@@ -489,7 +489,7 @@
     "sims_ref = {axis: sims0[axis].updated_copy(structures=[substrate]) for axis in [\"x\", \"y\", \"z\"]}\n",
     "\n",
     "# run the simulations\n",
-    "ref_results = web.run_async(simulations=sims_ref, path_dir=\"data\")"
+    "ref_results = web.run(sims_ref, path=\"data\")"
    ]
   },
   {
@@ -572,7 +572,7 @@
     "def min_upward_flux(params: np.ndarray, beta: float) -> float:\n",
     "    \"\"\"Objective function for the inverse design\"\"\"\n",
     "    sims = make_sims(params, beta=beta)\n",
-    "    batch_results = web.run_async(simulations=sims, path_dir=\"data\", verbose=False)\n",
+    "    batch_results = web.run(sims, path=\"data\", verbose=False)\n",
     "\n",
     "    def flux_data(dim: str) -> np.ndarray:\n",
     "        return np.mean(batch_results[dim][\"field\"].flux.data)\n",
@@ -1400,7 +1400,7 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m14:58:19 CEST\u001b[0m\u001b[2;36m \u001b[0m\u001b[31mWARNING: No connection: Retrying for \u001b[0m\u001b[1;36m180\u001b[0m\u001b[31m seconds.                 \u001b[0m\n"
+       "\u001B[2;36m14:58:19 CEST\u001B[0m\u001B[2;36m \u001B[0m\u001B[31mWARNING: No connection: Retrying for \u001B[0m\u001B[1;36m180\u001B[0m\u001B[31m seconds.                 \u001B[0m\n"
       ]
      },
      "metadata": {},
@@ -2108,7 +2108,7 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m15:48:33 CEST\u001b[0m\u001b[2;36m \u001b[0mStarted working on Batch containing \u001b[1;36m3\u001b[0m tasks.                      \n"
+       "\u001B[2;36m15:48:33 CEST\u001B[0m\u001B[2;36m \u001B[0mStarted working on Batch containing \u001B[1;36m3\u001B[0m tasks.                      \n"
       ]
      },
      "metadata": {},
@@ -2121,7 +2121,7 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m15:48:36 CEST\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.156\u001b[0m for the whole batch.               \n"
+       "\u001B[2;36m15:48:36 CEST\u001B[0m\u001B[2;36m \u001B[0mMaximum FlexCredit cost: \u001B[1;36m0.156\u001B[0m for the whole batch.               \n"
       ]
      },
      "metadata": {},
@@ -2135,8 +2135,8 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m             \u001b[0m\u001b[2;36m \u001b[0mUse \u001b[32m'Batch.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed FlexCredit cost after   \n",
-       "\u001b[2;36m              \u001b[0mthe Batch has completed.                                          \n"
+       "\u001B[2;36m             \u001B[0m\u001B[2;36m \u001B[0mUse \u001B[32m'Batch.real_cost\u001B[0m\u001B[32m(\u001B[0m\u001B[32m)\u001B[0m\u001B[32m'\u001B[0m to get the billed FlexCredit cost after   \n",
+       "\u001B[2;36m              \u001B[0mthe Batch has completed.                                          \n"
       ]
      },
      "metadata": {},
@@ -2163,7 +2163,7 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m15:48:56 CEST\u001b[0m\u001b[2;36m \u001b[0mBatch complete.                                                   \n"
+       "\u001B[2;36m15:48:56 CEST\u001B[0m\u001B[2;36m \u001B[0mBatch complete.                                                   \n"
       ]
      },
      "metadata": {},
@@ -2222,7 +2222,7 @@
     "\n",
     "# resimulate the optimized design\n",
     "sims_opt = make_sims(params_final, beta=beta)\n",
-    "opt_results = web.run_async(simulations=sims_opt, path_dir=\"data\")\n",
+    "opt_results = web.run(sims_opt, path=\"data\")\n",
     "\n",
     "# extract the fluxes\n",
     "flux_opt = extract_fluxes(opt_results)"
@@ -2318,7 +2318,7 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m15:49:12 CEST\u001b[0m\u001b[2;36m \u001b[0mStarted working on Batch containing \u001b[1;36m3\u001b[0m tasks.                      \n"
+       "\u001B[2;36m15:49:12 CEST\u001B[0m\u001B[2;36m \u001B[0mStarted working on Batch containing \u001B[1;36m3\u001B[0m tasks.                      \n"
       ]
      },
      "metadata": {},
@@ -2331,7 +2331,7 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m15:49:16 CEST\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.156\u001b[0m for the whole batch.               \n"
+       "\u001B[2;36m15:49:16 CEST\u001B[0m\u001B[2;36m \u001B[0mMaximum FlexCredit cost: \u001B[1;36m0.156\u001B[0m for the whole batch.               \n"
       ]
      },
      "metadata": {},
@@ -2345,8 +2345,8 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m             \u001b[0m\u001b[2;36m \u001b[0mUse \u001b[32m'Batch.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed FlexCredit cost after   \n",
-       "\u001b[2;36m              \u001b[0mthe Batch has completed.                                          \n"
+       "\u001B[2;36m             \u001B[0m\u001B[2;36m \u001B[0mUse \u001B[32m'Batch.real_cost\u001B[0m\u001B[32m(\u001B[0m\u001B[32m)\u001B[0m\u001B[32m'\u001B[0m to get the billed FlexCredit cost after   \n",
+       "\u001B[2;36m              \u001B[0mthe Batch has completed.                                          \n"
       ]
      },
      "metadata": {},
@@ -2373,7 +2373,7 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m15:49:41 CEST\u001b[0m\u001b[2;36m \u001b[0mBatch complete.                                                   \n"
+       "\u001B[2;36m15:49:41 CEST\u001B[0m\u001B[2;36m \u001B[0mBatch complete.                                                   \n"
       ]
      },
      "metadata": {},
@@ -2431,7 +2431,7 @@
     "sims_binarized = make_sims(params_binarized, beta=beta)\n",
     "\n",
     "# run simulations\n",
-    "binarized_results = web.run_async(simulations=sims_binarized, path_dir=\"data\")\n",
+    "binarized_results = web.run(sims_binarized, path=\"data\")\n",
     "\n",
     "# extract results\n",
     "flux_binarized = extract_fluxes(binarized_results)"
@@ -2664,7 +2664,7 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m15:50:00 CEST\u001b[0m\u001b[2;36m \u001b[0mStarted working on Batch containing \u001b[1;36m3\u001b[0m tasks.                      \n"
+       "\u001B[2;36m15:50:00 CEST\u001B[0m\u001B[2;36m \u001B[0mStarted working on Batch containing \u001B[1;36m3\u001B[0m tasks.                      \n"
       ]
      },
      "metadata": {},
@@ -2677,7 +2677,7 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m15:50:03 CEST\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.156\u001b[0m for the whole batch.               \n"
+       "\u001B[2;36m15:50:03 CEST\u001B[0m\u001B[2;36m \u001B[0mMaximum FlexCredit cost: \u001B[1;36m0.156\u001B[0m for the whole batch.               \n"
       ]
      },
      "metadata": {},
@@ -2691,8 +2691,8 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m             \u001b[0m\u001b[2;36m \u001b[0mUse \u001b[32m'Batch.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed FlexCredit cost after   \n",
-       "\u001b[2;36m              \u001b[0mthe Batch has completed.                                          \n"
+       "\u001B[2;36m             \u001B[0m\u001B[2;36m \u001B[0mUse \u001B[32m'Batch.real_cost\u001B[0m\u001B[32m(\u001B[0m\u001B[32m)\u001B[0m\u001B[32m'\u001B[0m to get the billed FlexCredit cost after   \n",
+       "\u001B[2;36m              \u001B[0mthe Batch has completed.                                          \n"
       ]
      },
      "metadata": {},
@@ -2719,7 +2719,7 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m15:50:39 CEST\u001b[0m\u001b[2;36m \u001b[0mBatch complete.                                                   \n"
+       "\u001B[2;36m15:50:39 CEST\u001B[0m\u001B[2;36m \u001B[0mBatch complete.                                                   \n"
       ]
      },
      "metadata": {},
@@ -2780,7 +2780,7 @@
     "}\n",
     "\n",
     "# run the simulations\n",
-    "loaded_results = web.run_async(simulations=sims_loaded, path_dir=\"data\")\n",
+    "loaded_results = web.run(sims_loaded, path=\"data\")\n",
     "\n",
     "# extract results\n",
     "flux_loaded = extract_fluxes(loaded_results)\n",
@@ -2989,7 +2989,7 @@
         {
          "data": {
           "text/html": "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Uploading data for 3 tasks <span style=\"color: #f92672; text-decoration-color: #f92672\">━━━━━━━━━━━━━</span><span style=\"color: #3a3a3a; text-decoration-color: #3a3a3a\">╺━━━━━━━━━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\"> 33%</span> <span style=\"color: #808000; text-decoration-color: #808000\">0:00:02</span>\n</pre>\n",
-          "text/plain": "Uploading data for 3 tasks \u001b[38;2;249;38;114m━━━━━━━━━━━━━\u001b[0m\u001b[38;5;237m╺\u001b[0m\u001b[38;5;237m━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m 33%\u001b[0m \u001b[33m0:00:02\u001b[0m\n"
+          "text/plain": "Uploading data for 3 tasks \u001B[38;2;249;38;114m━━━━━━━━━━━━━\u001B[0m\u001B[38;5;237m╺\u001B[0m\u001B[38;5;237m━━━━━━━━━━━━━━━━━━━━━━━━━━\u001B[0m \u001B[35m 33%\u001B[0m \u001B[33m0:00:02\u001B[0m\n"
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-          "text/plain": "x               → \u001b[32msuccess      \u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[33m0:00:16\u001b[0m\ny               → \u001b[32msuccess      \u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[33m0:00:15\u001b[0m\nz               → \u001b[32msuccess      \u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[33m0:00:15\u001b[0m\n"
+          "text/plain": "x               → \u001B[32msuccess      \u001B[0m \u001B[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━\u001B[0m \u001B[35m100%\u001B[0m \u001B[33m0:00:16\u001B[0m\ny               → \u001B[32msuccess      \u001B[0m \u001B[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━\u001B[0m \u001B[35m100%\u001B[0m \u001B[33m0:00:15\u001B[0m\nz               → \u001B[32msuccess      \u001B[0m \u001B[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━\u001B[0m \u001B[35m100%\u001B[0m \u001B[33m0:00:15\u001B[0m\n"
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          "data": {
           "text/html": "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Downloading data for 3 tasks <span style=\"color: #3a3a3a; text-decoration-color: #3a3a3a\">━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">  0%</span> <span style=\"color: #808000; text-decoration-color: #808000\">0:00:02</span>\n</pre>\n",
-          "text/plain": "Downloading data for 3 tasks \u001b[38;5;237m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m  0%\u001b[0m \u001b[33m0:00:02\u001b[0m\n"
+          "text/plain": "Downloading data for 3 tasks \u001B[38;5;237m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001B[0m \u001B[35m  0%\u001B[0m \u001B[33m0:00:02\u001B[0m\n"
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@@ -3288,7 +3288,7 @@
         {
          "data": {
           "text/html": "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Downloading data for 3 tasks <span style=\"color: #f92672; text-decoration-color: #f92672\">━━━━━━━━━━━━╸</span><span style=\"color: #3a3a3a; text-decoration-color: #3a3a3a\">━━━━━━━━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\"> 33%</span> <span style=\"color: #808000; text-decoration-color: #808000\">0:00:03</span>\n</pre>\n",
-          "text/plain": "Downloading data for 3 tasks \u001b[38;2;249;38;114m━━━━━━━━━━━━\u001b[0m\u001b[38;2;249;38;114m╸\u001b[0m\u001b[38;5;237m━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m 33%\u001b[0m \u001b[33m0:00:03\u001b[0m\n"
+          "text/plain": "Downloading data for 3 tasks \u001B[38;2;249;38;114m━━━━━━━━━━━━\u001B[0m\u001B[38;2;249;38;114m╸\u001B[0m\u001B[38;5;237m━━━━━━━━━━━━━━━━━━━━━━━━━\u001B[0m \u001B[35m 33%\u001B[0m \u001B[33m0:00:03\u001B[0m\n"
          },
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@@ -3476,7 +3476,7 @@
         {
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+          "text/plain": "x               → \u001B[32msuccess      \u001B[0m \u001B[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━\u001B[0m \u001B[35m100%\u001B[0m \u001B[33m0:00:17\u001B[0m\ny               → \u001B[32msuccess      \u001B[0m \u001B[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━\u001B[0m \u001B[35m100%\u001B[0m \u001B[33m0:00:16\u001B[0m\nz               → \u001B[32msuccess      \u001B[0m \u001B[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━\u001B[0m \u001B[35m100%\u001B[0m \u001B[33m0:00:16\u001B[0m\n"
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+          "text/plain": "x               → \u001B[32msuccess      \u001B[0m \u001B[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━\u001B[0m \u001B[35m100%\u001B[0m \u001B[33m0:00:01\u001B[0m\ny               → \u001B[32msuccess      \u001B[0m \u001B[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━\u001B[0m \u001B[35m100%\u001B[0m \u001B[33m0:00:01\u001B[0m\nz               → \u001B[32msuccess      \u001B[0m \u001B[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━\u001B[0m \u001B[35m100%\u001B[0m \u001B[33m0:00:01\u001B[0m\n"
          },
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@@ -3534,7 +3534,7 @@
         {
          "data": {
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-          "text/plain": "x               → \u001b[32msuccess      \u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[33m0:00:18\u001b[0m\ny               → \u001b[32msuccess      \u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[33m0:00:17\u001b[0m\nz               → \u001b[32msuccess      \u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[33m0:00:17\u001b[0m\n"
+          "text/plain": "x               → \u001B[32msuccess      \u001B[0m \u001B[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━\u001B[0m \u001B[35m100%\u001B[0m \u001B[33m0:00:18\u001B[0m\ny               → \u001B[32msuccess      \u001B[0m \u001B[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━\u001B[0m \u001B[35m100%\u001B[0m \u001B[33m0:00:17\u001B[0m\nz               → \u001B[32msuccess      \u001B[0m \u001B[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━\u001B[0m \u001B[35m100%\u001B[0m \u001B[33m0:00:17\u001B[0m\n"
          },
          "metadata": {},
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@@ -3616,7 +3616,7 @@
         {
          "data": {
           "text/html": "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Uploading data for 3 tasks <span style=\"color: #3a3a3a; text-decoration-color: #3a3a3a\">━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">  0%</span> <span style=\"color: #808000; text-decoration-color: #808000\">0:00:02</span>\n</pre>\n",
-          "text/plain": "Uploading data for 3 tasks \u001b[38;5;237m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m  0%\u001b[0m \u001b[33m0:00:02\u001b[0m\n"
+          "text/plain": "Uploading data for 3 tasks \u001B[38;5;237m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001B[0m \u001B[35m  0%\u001B[0m \u001B[33m0:00:02\u001B[0m\n"
          },
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@@ -3698,7 +3698,7 @@
         {
          "data": {
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-          "text/plain": "Uploading data for 3 tasks \u001b[38;5;237m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m  0%\u001b[0m \u001b[33m0:00:02\u001b[0m\n"
+          "text/plain": "Uploading data for 3 tasks \u001B[38;5;237m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001B[0m \u001B[35m  0%\u001B[0m \u001B[33m0:00:02\u001B[0m\n"
          },
          "metadata": {},
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@@ -3727,7 +3727,7 @@
         {
          "data": {
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-          "text/plain": "Downloading data for 3 tasks \u001b[38;5;237m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m  0%\u001b[0m \u001b[33m0:00:07\u001b[0m\n"
+          "text/plain": "Downloading data for 3 tasks \u001B[38;5;237m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001B[0m \u001B[35m  0%\u001B[0m \u001B[33m0:00:07\u001B[0m\n"
          },
          "metadata": {},
          "output_type": "display_data"
@@ -3809,7 +3809,7 @@
         {
          "data": {
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-          "text/plain": "Uploading data for 3 tasks \u001b[38;2;249;38;114m━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[38;2;249;38;114m╸\u001b[0m\u001b[38;5;237m━━━━━━━━━━━━━\u001b[0m \u001b[35m 67%\u001b[0m \u001b[33m0:00:02\u001b[0m\n"
+          "text/plain": "Uploading data for 3 tasks \u001B[38;2;249;38;114m━━━━━━━━━━━━━━━━━━━━━━━━━━\u001B[0m\u001B[38;2;249;38;114m╸\u001B[0m\u001B[38;5;237m━━━━━━━━━━━━━\u001B[0m \u001B[35m 67%\u001B[0m \u001B[33m0:00:02\u001B[0m\n"
          },
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@@ -3838,7 +3838,7 @@
         {
          "data": {
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-          "text/plain": "Downloading data for 3 tasks \u001b[38;2;249;38;114m━━━━━━━━━━━━\u001b[0m\u001b[38;2;249;38;114m╸\u001b[0m\u001b[38;5;237m━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m 33%\u001b[0m \u001b[33m0:00:07\u001b[0m\n"
+          "text/plain": "Downloading data for 3 tasks \u001B[38;2;249;38;114m━━━━━━━━━━━━\u001B[0m\u001B[38;2;249;38;114m╸\u001B[0m\u001B[38;5;237m━━━━━━━━━━━━━━━━━━━━━━━━━\u001B[0m \u001B[35m 33%\u001B[0m \u001B[33m0:00:07\u001B[0m\n"
          },
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diff --git a/Autograd23FabricationAwareInvdes.ipynb b/Autograd23FabricationAwareInvdes.ipynb
index 56a25821..8e4784cd 100644
--- a/Autograd23FabricationAwareInvdes.ipynb
+++ b/Autograd23FabricationAwareInvdes.ipynb
@@ -18,10 +18,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
    "id": "c76c454e-e2c8-40ab-a4ed-e41a5e3e0d65",
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-09-26T15:39:59.604569Z",
+     "start_time": "2025-09-26T15:39:55.912073Z"
+    }
+   },
    "source": [
     "import autograd as ag\n",
     "import autograd.numpy as anp\n",
@@ -31,7 +34,9 @@
     "import tidy3d.web as web\n",
     "\n",
     "np.random.seed(2)"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": 1
   },
   {
    "cell_type": "markdown",
@@ -69,15 +74,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
    "id": "8e12ebf5",
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-09-26T15:40:08.527411Z",
+     "start_time": "2025-09-26T15:40:08.381918Z"
+    }
+   },
    "source": [
     "import webbrowser\n",
     "\n",
     "_ = webbrowser.open(\"https://www.prefabphotonics.com/signup\")"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": 2
   },
   {
    "cell_type": "markdown",
@@ -89,13 +99,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
    "id": "aa638e5d",
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-09-26T15:40:37.876179Z",
+     "start_time": "2025-09-26T15:40:37.874548Z"
+    }
+   },
    "source": [
     "# !prefab setup"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": 3
   },
   {
    "cell_type": "markdown",
@@ -109,56 +124,60 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
    "id": "4e8bb4f8",
-   "metadata": {},
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-09-26T15:41:10.772477Z",
+     "start_time": "2025-09-26T15:41:01.467242Z"
+    }
+   },
+   "source": [
+    "import prefab as pf\n",
+    "\n",
+    "device = pf.shapes.target()\n",
+    "prediction = device.predict(model=pf.models[\"ANT_NanoSOI_ANF1_d10\"], binarize=True)\n",
+    "device.plot()\n",
+    "prediction.plot()"
+   ],
    "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "Prediction: 100%|\u001b[32m██████████████████████████████\u001b[0m| 100/100 [00:03<00:00, 25.32%/s]\u001b[32m\u001b[0m\n"
-     ]
-    },
     {
      "data": {
       "text/plain": [
        "<Axes: xlabel='x (nm)', ylabel='y (nm)'>"
       ]
      },
-     "execution_count": 5,
+     "execution_count": 4,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
-      ]
+      ],
+      "image/png": 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"
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
-      "image/png": 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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
-      ]
+      ],
+      "image/png": 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"
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     }
    ],
-   "source": [
-    "import prefab as pf\n",
-    "\n",
-    "device = pf.shapes.target()\n",
-    "prediction = device.predict(model=pf.models[\"ANT_NanoSOI_ANF1_d10\"], binarize=True)\n",
-    "device.plot()\n",
-    "prediction.plot()"
-   ]
+   "execution_count": 4
   },
   {
    "cell_type": "markdown",
@@ -191,10 +210,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
    "id": "3d77b41c-91ac-49af-bc3d-cca78e938e3c",
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-09-26T15:41:30.064861Z",
+     "start_time": "2025-09-26T15:41:30.061363Z"
+    }
+   },
    "source": [
     "# material information\n",
     "n_si = 3.49\n",
@@ -252,7 +274,9 @@
     "# resolution information\n",
     "min_steps_per_wvl = 18\n",
     "dl_design_region = 0.015"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": 6
   },
   {
    "cell_type": "markdown",
@@ -266,10 +290,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
    "id": "207a7411-7aec-428c-9d80-2fa730874277",
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-09-26T15:41:34.333216Z",
+     "start_time": "2025-09-26T15:41:34.313483Z"
+    }
+   },
    "source": [
     "# define the waveguide ports\n",
     "wg_in = td.Structure(\n",
@@ -349,29 +376,39 @@
     "    boundary_spec=td.BoundarySpec.pml(x=True, y=True, z=True if Lz else False),\n",
     "    run_time=run_time,\n",
     ")"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": 7
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
    "id": "4400153f-b2b2-4ec7-97ea-34e82b5ddd1d",
-   "metadata": {},
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-09-26T15:41:37.814699Z",
+     "start_time": "2025-09-26T15:41:37.576237Z"
+    }
+   },
+   "source": [
+    "ax = sim_base.plot_eps(z=0.01)\n",
+    "ax.set_aspect(\"equal\")"
+   ],
    "outputs": [
     {
      "data": {
-      "image/png": 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",
       "text/plain": [
        "<Figure size 640x480 with 2 Axes>"
-      ]
+      ],
+      "image/png": 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"
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     }
    ],
-   "source": [
-    "ax = sim_base.plot_eps(z=0.01)\n",
-    "ax.set_aspect(\"equal\")"
-   ]
+   "execution_count": 8
   },
   {
    "cell_type": "markdown",
@@ -387,10 +424,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
    "id": "439f9a65-ec0b-4fab-bdc1-d6831108153e",
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-09-26T15:41:40.461846Z",
+     "start_time": "2025-09-26T15:41:40.366456Z"
+    }
+   },
    "source": [
     "from tidy3d.plugins.mode import ModeSolver\n",
     "from tidy3d.plugins.mode.web import run as run_mode_solver\n",
@@ -413,7 +453,9 @@
     "    freqs=freqs_design,\n",
     "    mode_spec=td.ModeSpec(num_modes=num_modes),\n",
     ")"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": 9
   },
   {
    "cell_type": "markdown",
@@ -425,157 +467,115 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
    "id": "682799a3-1e90-4b17-a0aa-c416a4171f9f",
-   "metadata": {},
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-09-26T15:56:52.201294Z",
+     "start_time": "2025-09-26T15:41:44.627426Z"
+    }
+   },
+   "source": [
+    "mode_data = run_mode_solver(\n",
+    "    mode_solver, reduce_simulation=True, results_file=\"data/mode_solver.hdf5\"\n",
+    ")"
+   ],
    "outputs": [
     {
      "data": {
+      "text/plain": [
+       "\u001B[2;36m17:41:45 CEST\u001B[0m\u001B[2;36m \u001B[0mMode solver created with                                          \n",
+       "\u001B[2;36m              \u001B[0m\u001B[33mtask_id\u001B[0m=\u001B[32m'fdve-9ab03835-92f4-42e6-8a5f-d21a30e41c42'\u001B[0m,              \n",
+       "\u001B[2;36m              \u001B[0m\u001B[33msolver_id\u001B[0m=\u001B[32m'mo-cbcdb702-9026-4ef1-b671-a476e6fd46df'\u001B[0m.              \n"
+      ],
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">15:39:02 EST </span>Mode solver created with                                           \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #808000; text-decoration-color: #808000\">task_id</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'fdve-bd79fa16-6098-46c5-aeb7-b41164b4bf2e'</span>,               \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #808000; text-decoration-color: #808000\">solver_id</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'mo-840d02cc-5271-46a1-9c82-dbd5870a36ce'</span>.               \n",
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">17:41:45 CEST </span>Mode solver created with                                          \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">              </span><span style=\"color: #808000; text-decoration-color: #808000\">task_id</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'fdve-9ab03835-92f4-42e6-8a5f-d21a30e41c42'</span>,              \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">              </span><span style=\"color: #808000; text-decoration-color: #808000\">solver_id</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'mo-cbcdb702-9026-4ef1-b671-a476e6fd46df'</span>.              \n",
        "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m15:39:02 EST\u001b[0m\u001b[2;36m \u001b[0mMode solver created with                                           \n",
-       "\u001b[2;36m             \u001b[0m\u001b[33mtask_id\u001b[0m=\u001b[32m'fdve-bd79fa16-6098-46c5-aeb7-b41164b4bf2e'\u001b[0m,               \n",
-       "\u001b[2;36m             \u001b[0m\u001b[33msolver_id\u001b[0m=\u001b[32m'mo-840d02cc-5271-46a1-9c82-dbd5870a36ce'\u001b[0m.               \n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "d18b949249a5434b81e4dcc36bfbc2e1",
-       "version_major": 2,
-       "version_minor": 0
-      },
       "text/plain": [
-       "Output()"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
+       "/home/marco/projects/tidy3d-notebooks/.venv/lib/python3.12/site-packages/rich/li\n",
+       "ve.py:231: UserWarning: install \"ipywidgets\" for Jupyter support\n",
+       "  warnings.warn('install \"ipywidgets\" for Jupyter support')\n"
       ],
-      "text/plain": []
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">/home/marco/projects/tidy3d-notebooks/.venv/lib/python3.12/site-packages/rich/li\n",
+       "ve.py:231: UserWarning: install \"ipywidgets\" for Jupyter support\n",
+       "  warnings.warn('install \"ipywidgets\" for Jupyter support')\n",
        "</pre>\n"
-      ],
-      "text/plain": [
-       "\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "6b5527f36dc849d487b0e7824ba7fe52",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "Output()"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
+      "text/plain": [],
       "text/html": [
        "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
-      ],
-      "text/plain": []
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
+      "text/plain": [],
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">15:39:04 EST </span>Mode solver status: success                                        \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m15:39:04 EST\u001b[0m\u001b[2;36m \u001b[0mMode solver status: success                                        \n"
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "5c1dd3d2ae1a4bad80c9717942b6ecb5",
-       "version_major": 2,
-       "version_minor": 0
-      },
       "text/plain": [
-       "Output()"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
+       "\u001B[2;36m17:41:54 CEST\u001B[0m\u001B[2;36m \u001B[0mMode solver status: queued                                        \n"
       ],
-      "text/plain": []
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">17:41:54 CEST </span>Mode solver status: queued                                        \n",
        "</pre>\n"
-      ],
-      "text/plain": [
-       "\n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
+    },
+    {
+     "ename": "KeyboardInterrupt",
+     "evalue": "",
+     "output_type": "error",
+     "traceback": [
+      "\u001B[31m---------------------------------------------------------------------------\u001B[39m",
+      "\u001B[31mKeyboardInterrupt\u001B[39m                         Traceback (most recent call last)",
+      "\u001B[36mCell\u001B[39m\u001B[36m \u001B[39m\u001B[32mIn[10]\u001B[39m\u001B[32m, line 1\u001B[39m\n\u001B[32m----> \u001B[39m\u001B[32m1\u001B[39m mode_data = \u001B[43mrun_mode_solver\u001B[49m\u001B[43m(\u001B[49m\n\u001B[32m      2\u001B[39m \u001B[43m    \u001B[49m\u001B[43mmode_solver\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mreduce_simulation\u001B[49m\u001B[43m=\u001B[49m\u001B[38;5;28;43;01mTrue\u001B[39;49;00m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mresults_file\u001B[49m\u001B[43m=\u001B[49m\u001B[33;43m\"\u001B[39;49m\u001B[33;43mdata/mode_solver.hdf5\u001B[39;49m\u001B[33;43m\"\u001B[39;49m\n\u001B[32m      3\u001B[39m \u001B[43m)\u001B[49m\n",
+      "\u001B[36mFile \u001B[39m\u001B[32m~/projects/tidy3d-notebooks/.venv/lib/python3.12/site-packages/tidy3d/web/api/mode.py:129\u001B[39m, in \u001B[36mrun\u001B[39m\u001B[34m(mode_solver, task_name, mode_solver_name, folder_name, results_file, verbose, progress_callback_upload, progress_callback_download, reduce_simulation, pay_type)\u001B[39m\n\u001B[32m    127\u001B[39m             console.log(\u001B[33mf\u001B[39m\u001B[33m\"\u001B[39m\u001B[33mMode solver status: \u001B[39m\u001B[38;5;132;01m{\u001B[39;00mstatus\u001B[38;5;132;01m}\u001B[39;00m\u001B[33m\"\u001B[39m)\n\u001B[32m    128\u001B[39m         prev_status = status\n\u001B[32m--> \u001B[39m\u001B[32m129\u001B[39m     \u001B[43mtime\u001B[49m\u001B[43m.\u001B[49m\u001B[43msleep\u001B[49m\u001B[43m(\u001B[49m\u001B[32;43m0.5\u001B[39;49m\u001B[43m)\u001B[49m\n\u001B[32m    130\u001B[39m     status = task.get_info().status\n\u001B[32m    132\u001B[39m \u001B[38;5;28;01mif\u001B[39;00m status == \u001B[33m\"\u001B[39m\u001B[33merror\u001B[39m\u001B[33m\"\u001B[39m:\n",
+      "\u001B[31mKeyboardInterrupt\u001B[39m: "
+     ]
     }
    ],
-   "source": [
-    "mode_data = run_mode_solver(\n",
-    "    mode_solver, reduce_simulation=True, results_file=\"data/mode_solver.hdf5\"\n",
-    ")"
-   ]
+   "execution_count": 10
   },
   {
    "cell_type": "markdown",
@@ -644,10 +644,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
    "id": "8ebd9a87-8928-48a6-bbe1-56d774a49c89",
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-09-26T15:56:57.072216Z",
+     "start_time": "2025-09-26T15:56:56.983258Z"
+    }
+   },
    "source": [
     "mode_index = 0\n",
     "mode_spec = td.ModeSpec(num_modes=mode_index + 1)\n",
@@ -656,7 +659,9 @@
     "sim_base = sim_base.updated_copy(mode_spec=mode_spec, path=\"sources/0\")\n",
     "for i in range(num_freqs_design):\n",
     "    sim_base = sim_base.updated_copy(mode_spec=mode_spec, path=f\"monitors/{i}\")"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": 11
   },
   {
    "cell_type": "markdown",
@@ -672,16 +677,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
    "id": "209f2e58-fd7d-42f7-bb6d-459f41511250",
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-09-26T15:56:59.464601Z",
+     "start_time": "2025-09-26T15:56:59.462665Z"
+    }
+   },
    "source": [
     "nx = int(lx / dl_design_region)\n",
     "ny = int(ly / dl_design_region)\n",
     "\n",
     "design_region_geo = td.Box(size=(lx, ly, lz), center=(0, 0, 0))"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": 12
   },
   {
    "cell_type": "markdown",
@@ -697,10 +707,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
    "id": "5bd171d0",
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-09-26T15:57:01.723260Z",
+     "start_time": "2025-09-26T15:57:01.716466Z"
+    }
+   },
    "source": [
     "FAB_MODEL = pf.models[\"ANT_NanoSOI_ANF1_d10\"]\n",
     "prediction_buffer = 0.16\n",
@@ -782,7 +795,9 @@
     "        n_prediction_buffer:-n_prediction_buffer,\n",
     "    ]\n",
     "    return params"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": 13
   },
   {
    "cell_type": "markdown",
@@ -798,10 +813,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
    "id": "761964ee-79d7-486a-8bbb-03d2917ff844",
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-09-26T15:57:09.003834Z",
+     "start_time": "2025-09-26T15:57:08.218447Z"
+    }
+   },
    "source": [
     "from tidy3d.plugins.autograd import make_filter_and_project, rescale\n",
     "\n",
@@ -842,7 +860,9 @@
     "    medium = td.CustomMedium(permittivity=eps_arr)\n",
     "\n",
     "    return td.Structure(geometry=design_region_geo, medium=medium)"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": 14
   },
   {
    "cell_type": "markdown",
@@ -856,10 +876,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
    "id": "1d67ccdc-758e-4648-aabc-4264b83086a1",
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-09-26T15:57:12.759261Z",
+     "start_time": "2025-09-26T15:57:12.756857Z"
+    }
+   },
    "source": [
     "def get_sim(params, beta, include_extra_mnts: bool = True, use_predict: bool = False):\n",
     "    design_region = make_custom_medium(params, beta=beta, use_predict=use_predict)\n",
@@ -882,7 +905,9 @@
     "        update_dict[\"monitors\"] = mnts_mode\n",
     "\n",
     "    return sim_base.updated_copy(**update_dict)"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": 15
   },
   {
    "cell_type": "markdown",
@@ -894,36 +919,49 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
    "id": "08846717-16bc-49ee-bcb3-dd5e1c30cd6c",
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-09-26T15:57:18.879742Z",
+     "start_time": "2025-09-26T15:57:18.820368Z"
+    }
+   },
    "source": [
     "params0 = np.random.random((nx, ny))\n",
     "sim0 = get_sim(params0, beta=beta0, use_predict=False)"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": 17
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
    "id": "65933269-50cd-4dea-b32d-25f39492c7dc",
-   "metadata": {},
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-09-26T15:57:20.001685Z",
+     "start_time": "2025-09-26T15:57:19.742129Z"
+    }
+   },
+   "source": [
+    "ax = sim0.plot_eps(z=0.01)\n",
+    "ax.set_aspect(\"equal\")"
+   ],
    "outputs": [
     {
      "data": {
-      "image/png": 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",
       "text/plain": [
        "<Figure size 640x480 with 2 Axes>"
-      ]
+      ],
+      "image/png": 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"
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     }
    ],
-   "source": [
-    "ax = sim0.plot_eps(z=0.01)\n",
-    "ax.set_aspect(\"equal\")"
-   ]
+   "execution_count": 18
   },
   {
    "cell_type": "markdown",
@@ -943,10 +981,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
    "id": "56ed21ad-0882-46ca-bc99-f1e4163fcc72",
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-09-26T15:57:22.494615Z",
+     "start_time": "2025-09-26T15:57:22.491160Z"
+    }
+   },
    "source": [
     "import xarray as xr\n",
     "\n",
@@ -985,7 +1026,9 @@
     "    avg_power_leaked = power_leaked / (num_freqs_design - 1)\n",
     "\n",
     "    return power_transmitted - leak_weight * avg_power_leaked"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": 19
   },
   {
    "cell_type": "markdown",
@@ -997,38 +1040,42 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
    "id": "7f7da424-d19e-4e0c-b95d-2ac7c877e246",
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-09-26T15:57:26.767680Z",
+     "start_time": "2025-09-26T15:57:26.765802Z"
+    }
+   },
    "source": [
     "from tidy3d.plugins.autograd import make_erosion_dilation_penalty\n",
     "\n",
     "beta_penalty = 10\n",
     "\n",
     "penalty = make_erosion_dilation_penalty(radius, dl_design_region, beta=beta_penalty)"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": 20
   },
   {
-   "cell_type": "markdown",
-   "id": "218ac455-3626-4399-a11d-1ba288fe63bf",
    "metadata": {},
+   "cell_type": "markdown",
    "source": [
     "### Total Objective Function\n",
     "\n",
     "Then we write an `objective` function that constructs our simulation, runs it, measures our metric, and subtracts our penalty.\n",
     "\n",
-    "> Note: due to the current limitations of the autograd support in tidy3d, when running broadband simulations, one must have only a single output 'port' in the forward simulation. Therefore, we split our problem into one simulation per output waveguide, and then run these in parallel using `web.run_async()`.\n",
+    "> Note: due to the current limitations of the autograd support in tidy3d, when running broadband simulations, one must have only a single output 'port' in the forward simulation. Therefore, we split our problem into one simulation per output waveguide, and then run these in parallel using `web.run()`.\n",
     "\n",
     "> **For FAID:** We set `use_predict=True` and `use_penalty=False`.\n"
-   ]
+   ],
+   "id": "e3f9588288594ba2"
   },
   {
-   "cell_type": "code",
-   "execution_count": 21,
-   "id": "3bba8bcc-4d2e-4268-a338-aab37513f5df",
    "metadata": {},
+   "cell_type": "code",
    "outputs": [],
+   "execution_count": null,
    "source": [
     "# useful for debugging, if you want to turn off the metric, penalty, or prediction\n",
     "use_penalty = False\n",
@@ -1043,7 +1090,7 @@
     "    if use_metric:\n",
     "        sim = get_sim(params, beta=beta, include_extra_mnts=False, use_predict=use_predict)\n",
     "        simulations = {f\"WDM_invdes_{key}\": sim for key in keys}\n",
-    "        batch_data = web.run_async(simulations, verbose=False, path_dir=\"data/\")\n",
+    "        batch_data = web.run(simulations, verbose=False, path=\"data\")\n",
     "        metric = 0.0\n",
     "        for mnt_index, (_, sim_data) in enumerate(batch_data.items()):\n",
     "            metric = metric + get_metric(\n",
@@ -1055,7 +1102,8 @@
     "        penalty_value = penalty(params)\n",
     "\n",
     "    return metric - penalty_weight * penalty_value"
-   ]
+   ],
+   "id": "1bc96ef40aea528a"
   },
   {
    "cell_type": "markdown",
@@ -1069,13 +1117,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
    "id": "3d210aba-1184-4191-a405-08c12531991c",
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-09-26T15:57:34.822888Z",
+     "start_time": "2025-09-26T15:57:34.821226Z"
+    }
+   },
    "source": [
     "grad_fn = ag.value_and_grad(objective)"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": 22
   },
   {
    "cell_type": "markdown",
@@ -1087,13 +1140,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
    "id": "c6602755-bcb7-4ef2-8532-c3690788e8ca",
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "jupyter": {
+     "is_executing": true
+    },
+    "ExecuteTime": {
+     "start_time": "2025-09-26T15:57:36.876899Z"
+    }
+   },
    "source": [
     "J, grad = grad_fn(params0, beta=1)"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "code",
diff --git a/Autograd4MultiObjective.ipynb b/Autograd4MultiObjective.ipynb
index 10b3a170..9927d346 100644
--- a/Autograd4MultiObjective.ipynb
+++ b/Autograd4MultiObjective.ipynb
@@ -198,9 +198,7 @@
    "cell_type": "markdown",
    "id": "56d3acce-0f8b-493d-9cf7-0568720827f5",
    "metadata": {},
-   "source": [
-    "And then we write our combined, multi-objective over all of the `dy` values.  We use the `web.run_async` function to run a list of these three simulations simultaneously."
-   ]
+   "source": "And then we write our combined, multi-objective over all of the `dy` values.  We use the `web.run` function to run a list of these three simulations simultaneously."
   },
   {
    "cell_type": "code",
@@ -213,7 +211,7 @@
     "    \"\"\"Average of O-th order diffracted power over all dy_sign values.\"\"\"\n",
     "    sims = {f\"sign = {dy_sign}\": make_sim(permittivity, dy_sign=dy_sign) for dy_sign in (-1, 0, 1)}\n",
     "\n",
-    "    batch_data = web.run_async(sims, path_dir=\"data\", verbose=True)\n",
+    "    batch_data = web.run(sims, path=\"data\", verbose=True)\n",
     "\n",
     "    power = sum(post_process(sim_data) for sim_data in batch_data.values()) / len(batch_data)\n",
     "    return power"
@@ -362,7 +360,7 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m12:20:19 CEST\u001b[0m\u001b[2;36m \u001b[0mStarted working on Batch containing \u001b[1;36m3\u001b[0m tasks.                      \n"
+       "\u001B[2;36m12:20:19 CEST\u001B[0m\u001B[2;36m \u001B[0mStarted working on Batch containing \u001B[1;36m3\u001B[0m tasks.                      \n"
       ]
      },
      "metadata": {},
@@ -375,7 +373,7 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m12:20:22 CEST\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.075\u001b[0m for the whole batch.               \n"
+       "\u001B[2;36m12:20:22 CEST\u001B[0m\u001B[2;36m \u001B[0mMaximum FlexCredit cost: \u001B[1;36m0.075\u001B[0m for the whole batch.               \n"
       ]
      },
      "metadata": {},
@@ -389,8 +387,8 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m             \u001b[0m\u001b[2;36m \u001b[0mUse \u001b[32m'Batch.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed FlexCredit cost after   \n",
-       "\u001b[2;36m              \u001b[0mthe Batch has completed.                                          \n"
+       "\u001B[2;36m             \u001B[0m\u001B[2;36m \u001B[0mUse \u001B[32m'Batch.real_cost\u001B[0m\u001B[32m(\u001B[0m\u001B[32m)\u001B[0m\u001B[32m'\u001B[0m to get the billed FlexCredit cost after   \n",
+       "\u001B[2;36m              \u001B[0mthe Batch has completed.                                          \n"
       ]
      },
      "metadata": {},
@@ -417,7 +415,7 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m12:22:42 CEST\u001b[0m\u001b[2;36m \u001b[0mBatch complete.                                                   \n"
+       "\u001B[2;36m12:22:42 CEST\u001B[0m\u001B[2;36m \u001B[0mBatch complete.                                                   \n"
       ]
      },
      "metadata": {},
@@ -464,7 +462,7 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m12:22:50 CEST\u001b[0m\u001b[2;36m \u001b[0mStarted working on Batch containing \u001b[1;36m3\u001b[0m tasks.                      \n"
+       "\u001B[2;36m12:22:50 CEST\u001B[0m\u001B[2;36m \u001B[0mStarted working on Batch containing \u001B[1;36m3\u001B[0m tasks.                      \n"
       ]
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      "metadata": {},
@@ -477,7 +475,7 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m12:22:55 CEST\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.075\u001b[0m for the whole batch.               \n"
+       "\u001B[2;36m12:22:55 CEST\u001B[0m\u001B[2;36m \u001B[0mMaximum FlexCredit cost: \u001B[1;36m0.075\u001B[0m for the whole batch.               \n"
       ]
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      "metadata": {},
@@ -491,8 +489,8 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m             \u001b[0m\u001b[2;36m \u001b[0mUse \u001b[32m'Batch.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed FlexCredit cost after   \n",
-       "\u001b[2;36m              \u001b[0mthe Batch has completed.                                          \n"
+       "\u001B[2;36m             \u001B[0m\u001B[2;36m \u001B[0mUse \u001B[32m'Batch.real_cost\u001B[0m\u001B[32m(\u001B[0m\u001B[32m)\u001B[0m\u001B[32m'\u001B[0m to get the billed FlexCredit cost after   \n",
+       "\u001B[2;36m              \u001B[0mthe Batch has completed.                                          \n"
       ]
      },
      "metadata": {},
@@ -519,7 +517,7 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m12:23:10 CEST\u001b[0m\u001b[2;36m \u001b[0mBatch complete.                                                   \n"
+       "\u001B[2;36m12:23:10 CEST\u001B[0m\u001B[2;36m \u001B[0mBatch complete.                                                   \n"
       ]
      },
      "metadata": {},
@@ -717,7 +715,7 @@
    "source": [
     "## Takeaways\n",
     "\n",
-    "The main thing to note here is that, using `web.run_async`, all of the individual simulations were uploaded at roughly the same time.\n",
+    "The main thing to note here is that, using `web.run`, all of the individual simulations were uploaded at roughly the same time.\n",
     "\n",
     "This means that the server is able to work on them concurrently rather than needing to wait for the previously uploaded one to finish. The time savings for applications with several simulations can be enormous.\n"
    ]
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+          "text/plain": "\u001B[1;32m↓\u001B[0m \u001B[1;34mjax_sim_vjp.hdf5\u001B[0m \u001B[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001B[0m \u001B[35m100.0%\u001B[0m • \u001B[32m6.2/6.2 kB\u001B[0m • \u001B[31m?\u001B[0m • \u001B[36m0:00:00\u001B[0m\n"
          },
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          "data": {
           "text/html": "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800000; text-decoration-color: #800000; font-weight: bold\">↑</span> <span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">simulation.hdf5.gz</span> <span style=\"color: #729c1f; text-decoration-color: #729c1f\">━━━━━━━━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">100.0%</span> • <span style=\"color: #008000; text-decoration-color: #008000\">1.2/1.2 kB</span> • <span style=\"color: #800000; text-decoration-color: #800000\">?</span> • <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\n</pre>\n",
-          "text/plain": "\u001b[1;31m↑\u001b[0m \u001b[1;34msimulation.hdf5.gz\u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100.0%\u001b[0m • \u001b[32m1.2/1.2 kB\u001b[0m • \u001b[31m?\u001b[0m • \u001b[36m0:00:00\u001b[0m\n"
+          "text/plain": "\u001B[1;31m↑\u001B[0m \u001B[1;34msimulation.hdf5.gz\u001B[0m \u001B[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━\u001B[0m \u001B[35m100.0%\u001B[0m • \u001B[32m1.2/1.2 kB\u001B[0m • \u001B[31m?\u001B[0m • \u001B[36m0:00:00\u001B[0m\n"
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@@ -2431,7 +2429,7 @@
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          "data": {
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-          "text/plain": "\u001b[1;31m↑\u001b[0m \u001b[1;34mjax_info.json\u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100.0%\u001b[0m • \u001b[32m174/174 bytes\u001b[0m • \u001b[31m?\u001b[0m • \u001b[36m0:00:00\u001b[0m\n"
+          "text/plain": "\u001B[1;31m↑\u001B[0m \u001B[1;34mjax_info.json\u001B[0m \u001B[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001B[0m \u001B[35m100.0%\u001B[0m • \u001B[32m174/174 bytes\u001B[0m • \u001B[31m?\u001B[0m • \u001B[36m0:00:00\u001B[0m\n"
          },
          "metadata": {},
          "output_type": "display_data"
@@ -2513,7 +2511,7 @@
         {
          "data": {
           "text/html": "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800000; text-decoration-color: #800000; font-weight: bold\">↑</span> <span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">simulation.hdf5.gz</span> <span style=\"color: #729c1f; text-decoration-color: #729c1f\">━━━━━━━━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">100.0%</span> • <span style=\"color: #008000; text-decoration-color: #008000\">1.2/1.2 kB</span> • <span style=\"color: #800000; text-decoration-color: #800000\">?</span> • <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\n</pre>\n",
-          "text/plain": "\u001b[1;31m↑\u001b[0m \u001b[1;34msimulation.hdf5.gz\u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100.0%\u001b[0m • \u001b[32m1.2/1.2 kB\u001b[0m • \u001b[31m?\u001b[0m • \u001b[36m0:00:00\u001b[0m\n"
+          "text/plain": "\u001B[1;31m↑\u001B[0m \u001B[1;34msimulation.hdf5.gz\u001B[0m \u001B[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━\u001B[0m \u001B[35m100.0%\u001B[0m • \u001B[32m1.2/1.2 kB\u001B[0m • \u001B[31m?\u001B[0m • \u001B[36m0:00:00\u001B[0m\n"
          },
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@@ -2542,7 +2540,7 @@
         {
          "data": {
           "text/html": "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">0: status = success <span style=\"color: #729c1f; text-decoration-color: #729c1f\">━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">100%</span> <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\n1: status = success <span style=\"color: #729c1f; text-decoration-color: #729c1f\">━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">100%</span> <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\n</pre>\n",
-          "text/plain": "0: status = success \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[36m0:00:00\u001b[0m\n1: status = success \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[36m0:00:00\u001b[0m\n"
+          "text/plain": "0: status = success \u001B[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001B[0m \u001B[35m100%\u001B[0m \u001B[36m0:00:00\u001B[0m\n1: status = success \u001B[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001B[0m \u001B[35m100%\u001B[0m \u001B[36m0:00:00\u001B[0m\n"
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@@ -2571,7 +2569,7 @@
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-          "text/plain": "\u001b[1;31m↑\u001b[0m \u001b[1;34mjax_info.json\u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100.0%\u001b[0m • \u001b[32m174/174 bytes\u001b[0m • \u001b[31m?\u001b[0m • \u001b[36m0:00:00\u001b[0m\n"
+          "text/plain": "\u001B[1;31m↑\u001B[0m \u001B[1;34mjax_info.json\u001B[0m \u001B[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001B[0m \u001B[35m100.0%\u001B[0m • \u001B[32m174/174 bytes\u001B[0m • \u001B[31m?\u001B[0m • \u001B[36m0:00:00\u001B[0m\n"
          },
          "metadata": {},
          "output_type": "display_data"
diff --git a/BatchModeSolver.ipynb b/BatchModeSolver.ipynb
index 58581b3d..9d56cd66 100644
--- a/BatchModeSolver.ipynb
+++ b/BatchModeSolver.ipynb
@@ -22,17 +22,45 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
    "id": "0e1026c9-79e0-4e85-bd27-a5f6f2096651",
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-10-29T13:54:14.770006Z",
+     "start_time": "2025-10-29T13:54:12.804838Z"
+    }
+   },
    "source": [
     "import matplotlib.pyplot as plt\n",
     "import numpy as np\n",
     "import tidy3d as td\n",
     "import tidy3d.web as web\n",
     "from tidy3d.plugins import waveguide"
-   ]
+   ],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "\u001B[2;36m14:54:13 CET\u001B[0m\u001B[2;36m \u001B[0m\u001B[31mWARNING: Using canonical configuration directory at                \u001B[0m\n",
+       "\u001B[2;36m             \u001B[0m\u001B[32m'/home/marco/.config/tidy3d'\u001B[0m\u001B[31m. Found legacy directory at            \u001B[0m\n",
+       "\u001B[2;36m             \u001B[0m\u001B[32m'~/.tidy3d'\u001B[0m\u001B[31m, which will be ignored. Remove it manually or run      \u001B[0m\n",
+       "\u001B[2;36m             \u001B[0m\u001B[32m'tidy3d config migrate --delete-legacy'\u001B[0m\u001B[31m to clean up.               \u001B[0m\n"
+      ],
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">14:54:13 CET </span><span style=\"color: #800000; text-decoration-color: #800000\">WARNING: Using canonical configuration directory at                </span>\n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'/home/marco/.config/tidy3d'</span><span style=\"color: #800000; text-decoration-color: #800000\">. Found legacy directory at            </span>\n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'~/.tidy3d'</span><span style=\"color: #800000; text-decoration-color: #800000\">, which will be ignored. Remove it manually or run      </span>\n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'tidy3d config migrate --delete-legacy'</span><span style=\"color: #800000; text-decoration-color: #800000\"> to clean up.               </span>\n",
+       "</pre>\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
+    }
+   ],
+   "execution_count": 1
   },
   {
    "cell_type": "markdown",
@@ -46,10 +74,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
    "id": "ecbe3b79-1ed7-44bb-8ee0-51d1fbae4c8e",
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-10-29T13:54:14.775406Z",
+     "start_time": "2025-10-29T13:54:14.773570Z"
+    }
+   },
    "source": [
     "lda0 = 1.55  # wavelength of interest\n",
     "\n",
@@ -58,7 +89,9 @@
     "\n",
     "LN = td.material_library[\"LiNbO3\"][\"Zelmon1997\"](1)\n",
     "SiO2 = td.material_library[\"SiO2\"][\"Palik_Lossless\"]"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": 2
   },
   {
    "cell_type": "markdown",
@@ -70,10 +103,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
    "id": "b12e18b8-ceae-4cc3-b7a4-f30585113a42",
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-10-29T13:54:15.246442Z",
+     "start_time": "2025-10-29T13:54:14.818267Z"
+    }
+   },
    "source": [
     "w_LN_range = np.arange(0.5, 4.1, 0.1)  # waveguide width range\n",
     "n_mode = 10  # number of modes to solve for\n",
@@ -95,244 +131,1550 @@
     "    )\n",
     "    # add the mode solver to the dictionary\n",
     "    mode_solvers[f\"width={w_LN:.2f}\"] = strip_waveguide.mode_solver"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": 3
   },
   {
    "cell_type": "markdown",
    "id": "c3d0b7e6-8766-4e39-bb63-4c8d11d86ead",
    "metadata": {},
-   "source": [
-    "Once the list of mode solvers is created, we simply use the `run_async` method to run the entire batch of tasks in parallel. Alternatively, one can create a [Batch](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.web.api.container.Batch.html) object first and run it with the [run()](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.web.api.container.Batch.html#tidy3d.web.api.container.Batch.run) method. [Batch](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.web.api.container.Batch.html) provides a better management of the simulation files since one can save the batch information to file and load the batch at a later time."
-   ]
+   "source": "Once the list of mode solvers is created, we simply use the `run` method to run the entire batch of tasks in parallel. Alternatively, one can create a [Batch](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.web.api.container.Batch.html) object first and run it with the [run()](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.web.api.container.Batch.html#tidy3d.web.api.container.Batch.run) method. [Batch](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.web.api.container.Batch.html) provides a better management of the simulation files since one can save the batch information to file and load the batch at a later time."
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
    "id": "e85256cc-7781-4b0e-a0ce-bee8fcb2f4eb",
-   "metadata": {},
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:00:24.941356Z",
+     "start_time": "2025-10-29T13:54:15.249843Z"
+    }
+   },
+   "source": [
+    "# run mode solvers in parallel\n",
+    "batch_results = web.run(\n",
+    "    mode_solvers,  # dictionary of mode solvers\n",
+    "    path=\"data\",  # path to store the result files\n",
+    ")\n",
+    "\n",
+    "# alternative way to run the mode solvers in parallel is shown below\n",
+    "# batch = web.Batch(simulations=mode_solvers)\n",
+    "# batch_results = batch.run(path_dir=\"data\")"
+   ],
    "outputs": [
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "cbe7ee306ea346149782c97b555ccde1",
-       "version_major": 2,
-       "version_minor": 0
-      },
       "text/plain": [
        "Output()"
-      ]
+      ],
+      "application/vnd.jupyter.widget-view+json": {
+       "version_major": 2,
+       "version_minor": 0,
+       "model_id": "93d7d60c00874d5380087d79e106b10f"
+      }
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
+      "text/plain": [],
       "text/html": [
        "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
-      ],
-      "text/plain": []
+      ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
+      "text/plain": [
+       "\u001B[2;36m14:54:38 CET\u001B[0m\u001B[2;36m \u001B[0mStarted working on Batch containing \u001B[1;36m36\u001B[0m tasks.                      \n"
+      ],
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">19:23:48 CEST </span>Started working on Batch containing <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">36</span> tasks.                     \n",
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">14:54:38 CET </span>Started working on Batch containing <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">36</span> tasks.                      \n",
        "</pre>\n"
-      ],
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
+    },
+    {
+     "data": {
       "text/plain": [
-       "\u001b[2;36m19:23:48 CEST\u001b[0m\u001b[2;36m \u001b[0mStarted working on Batch containing \u001b[1;36m36\u001b[0m tasks.                     \n"
+       "\u001B[2;36m14:55:39 CET\u001B[0m\u001B[2;36m \u001B[0mMaximum FlexCredit cost: \u001B[1;36m0.144\u001B[0m for the whole batch.                \n"
+      ],
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">14:55:39 CET </span>Maximum FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.144</span> for the whole batch.                \n",
+       "</pre>\n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
+      "text/plain": [
+       "\u001B[2;36m            \u001B[0m\u001B[2;36m \u001B[0mUse \u001B[32m'Batch.real_cost\u001B[0m\u001B[32m(\u001B[0m\u001B[32m)\u001B[0m\u001B[32m'\u001B[0m to get the billed FlexCredit cost after    \n",
+       "\u001B[2;36m             \u001B[0mcompletion.                                                        \n"
+      ],
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">19:24:20 CEST </span>Maximum FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.144</span> for the whole batch.               \n",
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>Use <span style=\"color: #008000; text-decoration-color: #008000\">'Batch.real_cost()'</span> to get the billed FlexCredit cost after    \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>completion.                                                        \n",
        "</pre>\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
+    },
+    {
+     "data": {
+      "text/plain": [
+       "Output()"
       ],
+      "application/vnd.jupyter.widget-view+json": {
+       "version_major": 2,
+       "version_minor": 0,
+       "model_id": "46d7eded2de241ac93c64b797d1755ed"
+      }
+     },
+     "metadata": {},
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
+    },
+    {
+     "data": {
       "text/plain": [
-       "\u001b[2;36m19:24:20 CEST\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.144\u001b[0m for the whole batch.               \n"
+       "\u001B[2;36m14:58:43 CET\u001B[0m\u001B[2;36m \u001B[0mBatch complete.                                                    \n"
+      ],
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">14:58:43 CET </span>Batch complete.                                                    \n",
+       "</pre>\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
+    },
+    {
+     "data": {
+      "text/plain": [],
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
+      "text/plain": [
+       "\u001B[2;36m14:59:09 CET\u001B[0m\u001B[2;36m \u001B[0mLoading simulation from                                            \n",
+       "\u001B[2;36m             \u001B[0mdata/mo-\u001B[93mf5941f2f-7038-4d8a-a4aa-a412179b860f\u001B[0m.hdf5                  \n"
+      ],
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">              </span>Use <span style=\"color: #008000; text-decoration-color: #008000\">'Batch.real_cost()'</span> to get the billed FlexCredit cost after   \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">              </span>the Batch has completed.                                          \n",
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">14:59:09 CET </span>Loading simulation from                                            \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/mo-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">f5941f2f-7038-4d8a-a4aa-a412179b860f</span>.hdf5                  \n",
        "</pre>\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
+    },
+    {
+     "data": {
+      "text/plain": [
+       "\u001B[2;36m14:59:11 CET\u001B[0m\u001B[2;36m \u001B[0mLoading simulation from                                            \n",
+       "\u001B[2;36m             \u001B[0mdata/mo-\u001B[93me2f49727-ad8e-4649-acc5-42cb8d1761cc\u001B[0m.hdf5                  \n"
       ],
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">14:59:11 CET </span>Loading simulation from                                            \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/mo-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">e2f49727-ad8e-4649-acc5-42cb8d1761cc</span>.hdf5                  \n",
+       "</pre>\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
+    },
+    {
+     "data": {
       "text/plain": [
-       "\u001b[2;36m             \u001b[0m\u001b[2;36m \u001b[0mUse \u001b[32m'Batch.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed FlexCredit cost after   \n",
-       "\u001b[2;36m              \u001b[0mthe Batch has completed.                                          \n"
+       "\u001B[2;36m14:59:13 CET\u001B[0m\u001B[2;36m \u001B[0mLoading simulation from                                            \n",
+       "\u001B[2;36m             \u001B[0mdata/mo-\u001B[93m0a1edfd9-722d-47f2-a505-58b424333ee8\u001B[0m.hdf5                  \n"
+      ],
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">14:59:13 CET </span>Loading simulation from                                            \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/mo-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">0a1edfd9-722d-47f2-a505-58b424333ee8</span>.hdf5                  \n",
+       "</pre>\n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "3cfc0db8761a46d8834b125b3390d805",
-       "version_major": 2,
-       "version_minor": 0
-      },
       "text/plain": [
-       "Output()"
+       "\u001B[2;36m14:59:14 CET\u001B[0m\u001B[2;36m \u001B[0mLoading simulation from                                            \n",
+       "\u001B[2;36m             \u001B[0mdata/mo-\u001B[93m302ba81d-18ca-41dc-a9de-70eca9fd36b4\u001B[0m.hdf5                  \n"
+      ],
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">14:59:14 CET </span>Loading simulation from                                            \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/mo-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">302ba81d-18ca-41dc-a9de-70eca9fd36b4</span>.hdf5                  \n",
+       "</pre>\n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
+      "text/plain": [
+       "\u001B[2;36m14:59:15 CET\u001B[0m\u001B[2;36m \u001B[0mLoading simulation from                                            \n",
+       "\u001B[2;36m             \u001B[0mdata/mo-\u001B[93mef58dc67-5428-4151-9869-f6c91a9f9e03\u001B[0m.hdf5                  \n"
+      ],
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">19:24:57 CEST </span>Batch complete.                                                   \n",
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">14:59:15 CET </span>Loading simulation from                                            \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/mo-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">ef58dc67-5428-4151-9869-f6c91a9f9e03</span>.hdf5                  \n",
        "</pre>\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
+    },
+    {
+     "data": {
+      "text/plain": [
+       "\u001B[2;36m14:59:16 CET\u001B[0m\u001B[2;36m \u001B[0mLoading simulation from                                            \n",
+       "\u001B[2;36m             \u001B[0mdata/mo-\u001B[93m96a4cc32-721d-43c9-a989-78a82f62a31a\u001B[0m.hdf5                  \n"
       ],
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">14:59:16 CET </span>Loading simulation from                                            \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/mo-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">96a4cc32-721d-43c9-a989-78a82f62a31a</span>.hdf5                  \n",
+       "</pre>\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
+    },
+    {
+     "data": {
       "text/plain": [
-       "\u001b[2;36m19:24:57 CEST\u001b[0m\u001b[2;36m \u001b[0mBatch complete.                                                   \n"
+       "\u001B[2;36m14:59:17 CET\u001B[0m\u001B[2;36m \u001B[0mLoading simulation from                                            \n",
+       "\u001B[2;36m             \u001B[0mdata/mo-\u001B[93m0e735b90-0faf-46d4-877e-653f67588e8e\u001B[0m.hdf5                  \n"
+      ],
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">14:59:17 CET </span>Loading simulation from                                            \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/mo-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">0e735b90-0faf-46d4-877e-653f67588e8e</span>.hdf5                  \n",
+       "</pre>\n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
+      "text/plain": [
+       "\u001B[2;36m14:59:18 CET\u001B[0m\u001B[2;36m \u001B[0mLoading simulation from                                            \n",
+       "\u001B[2;36m             \u001B[0mdata/mo-\u001B[93m86eb2efe-a123-4453-a4bb-a07345cdd29c\u001B[0m.hdf5                  \n"
+      ],
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">14:59:18 CET </span>Loading simulation from                                            \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/mo-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">86eb2efe-a123-4453-a4bb-a07345cdd29c</span>.hdf5                  \n",
+       "</pre>\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
+    },
+    {
+     "data": {
+      "text/plain": [
+       "\u001B[2;36m14:59:19 CET\u001B[0m\u001B[2;36m \u001B[0mLoading simulation from                                            \n",
+       "\u001B[2;36m             \u001B[0mdata/mo-\u001B[93mfadd8037-5ec9-4375-a60c-7bca9b2141cd\u001B[0m.hdf5                  \n"
       ],
-      "text/plain": []
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">14:59:19 CET </span>Loading simulation from                                            \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/mo-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">fadd8037-5ec9-4375-a60c-7bca9b2141cd</span>.hdf5                  \n",
+       "</pre>\n"
+      ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "ae062edaa16546bb9aee80ecb3d5e665",
-       "version_major": 2,
-       "version_minor": 0
-      },
       "text/plain": [
-       "Output()"
+       "\u001B[2;36m            \u001B[0m\u001B[2;36m \u001B[0mLoading simulation from                                            \n",
+       "\u001B[2;36m             \u001B[0mdata/mo-\u001B[93m6623f9b7-c9d7-4dce-b540-9ed3f6bce20e\u001B[0m.hdf5                  \n"
+      ],
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>Loading simulation from                                            \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/mo-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">6623f9b7-c9d7-4dce-b540-9ed3f6bce20e</span>.hdf5                  \n",
+       "</pre>\n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
+      "text/plain": [
+       "\u001B[2;36m14:59:20 CET\u001B[0m\u001B[2;36m \u001B[0mLoading simulation from                                            \n",
+       "\u001B[2;36m             \u001B[0mdata/mo-\u001B[93m8152d9ed-5a9a-40bc-a122-08460f257f75\u001B[0m.hdf5                  \n"
+      ],
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">14:59:20 CET </span>Loading simulation from                                            \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/mo-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">8152d9ed-5a9a-40bc-a122-08460f257f75</span>.hdf5                  \n",
+       "</pre>\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
+    },
+    {
+     "data": {
+      "text/plain": [
+       "\u001B[2;36m14:59:21 CET\u001B[0m\u001B[2;36m \u001B[0mLoading simulation from                                            \n",
+       "\u001B[2;36m             \u001B[0mdata/mo-\u001B[93md4a9b954-748c-497b-b204-12cd678f82d3\u001B[0m.hdf5                  \n"
       ],
-      "text/plain": []
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">14:59:21 CET </span>Loading simulation from                                            \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/mo-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">d4a9b954-748c-497b-b204-12cd678f82d3</span>.hdf5                  \n",
+       "</pre>\n"
+      ]
      },
      "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "# run mode solvers in parallel\n",
-    "batch_results = web.run_async(\n",
-    "    simulations=mode_solvers,  # dictionary of mode solvers\n",
-    "    path_dir=\"data\",  # path to store the result files\n",
-    ")\n",
-    "\n",
-    "# alternative way to run the mode solvers in parallel is shown below\n",
-    "# batch = web.Batch(simulations=mode_solvers)\n",
-    "# batch_results = batch.run(path_dir=\"data\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "d74b557b-f06f-4825-aa46-8be0aa373321",
-   "metadata": {},
-   "source": [
-    "After the batch of tasks is finished, we are ready to extract the results. We can plot all the mode profiles to inspect each mode at each waveguide width. As a demonstration, we plot all 10 modes with the widest waveguide.  "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "id": "6574c95a-5ee2-410f-8eaa-7f90e78accb9",
-   "metadata": {},
-   "outputs": [
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
+    },
     {
      "data": {
-      "image/png": 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",
       "text/plain": [
-       "<Figure size 700x1000 with 20 Axes>"
+       "\u001B[2;36m14:59:22 CET\u001B[0m\u001B[2;36m \u001B[0mLoading simulation from                                            \n",
+       "\u001B[2;36m             \u001B[0mdata/mo-\u001B[93m5c164adb-5022-461a-83af-9df8a6a605d7\u001B[0m.hdf5                  \n"
+      ],
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">14:59:22 CET </span>Loading simulation from                                            \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/mo-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">5c164adb-5022-461a-83af-9df8a6a605d7</span>.hdf5                  \n",
+       "</pre>\n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "# plot all mode profiles of the widest waveguide\n",
-    "fig, ax = plt.subplots(5, 2, figsize=(7, 10), tight_layout=True)\n",
-    "for i in range(n_mode):\n",
-    "    mode_solvers[f\"width={w_LN_range[-1]:.2f}\"].plot_field(\n",
-    "        \"E\", \"abs\", mode_index=i, ax=ax[i % 5][i // 5]\n",
-    "    )\n",
-    "    ax[i % 5][i // 5].set_title(f\"mode_index={i}\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "77da6faa-2150-4f60-93cb-cd4f0e20040a",
-   "metadata": {},
-   "source": [
-    "From the mode profiles, we can distinguish fundamental modes and higher order modes. To be more quantitative, we can extract other mode information. For example, we can extract the effective indices and polarization fractions of the modes. "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "id": "6856c85e-63b3-4c95-a6e8-79215262edbc",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# extract the effective index and polarization fraction\n",
-    "n_eff = np.array([result.n_eff[0] for _, result in batch_results.items()]).T\n",
-    "te_fraction = np.array([result.pol_fraction.te.data[0] for _, result in batch_results.items()]).T"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "dfe06f92-c460-4ab4-9d8e-5ee81692bfcc",
-   "metadata": {},
-   "source": [
-    "Once we extract the information, we can plot them to visualize the mode dispersion. Here we plot the effective indices first as curves and then as scatterers with color, where the color indicates the polarization. Red corresponds to quasi-TE modes and blue corresponds to quasi-TM modes. We can see at a few places mode hybridization occurs. For example, at around 1.5 μm waveguide width, the TM0 and TE1 modes hybridize. This hybridization is often utilized to make mode converters for polarization control, as demonstrated in the [polarization splitter rotator](https://www.flexcompute.com/tidy3d/examples/notebooks/BilevelPSR/) example. "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "id": "a163e5e3-4aed-4014-b2fa-48487a3d1283",
-   "metadata": {},
-   "outputs": [
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
+    },
     {
      "data": {
-      "image/png": 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",
       "text/plain": [
-       "<Figure size 1000x500 with 2 Axes>"
+       "\u001B[2;36m14:59:23 CET\u001B[0m\u001B[2;36m \u001B[0mLoading simulation from                                            \n",
+       "\u001B[2;36m             \u001B[0mdata/mo-\u001B[93mf82170f9-3e54-4608-aee3-99b268862d95\u001B[0m.hdf5                  \n"
+      ],
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">14:59:23 CET </span>Loading simulation from                                            \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/mo-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">f82170f9-3e54-4608-aee3-99b268862d95</span>.hdf5                  \n",
+       "</pre>\n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "# plot each mode dispersion curve and polarization as colored scatterers\n",
-    "plt.figure(figsize=(10, 5))\n",
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
+    },
+    {
+     "data": {
+      "text/plain": [
+       "\u001B[2;36m14:59:24 CET\u001B[0m\u001B[2;36m \u001B[0mLoading simulation from                                            \n",
+       "\u001B[2;36m             \u001B[0mdata/mo-\u001B[93mb932bc9c-0630-4c6e-951a-3971ed43d548\u001B[0m.hdf5                  \n"
+      ],
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">14:59:24 CET </span>Loading simulation from                                            \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/mo-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">b932bc9c-0630-4c6e-951a-3971ed43d548</span>.hdf5                  \n",
+       "</pre>\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
+    },
+    {
+     "data": {
+      "text/plain": [
+       "\u001B[2;36m14:59:25 CET\u001B[0m\u001B[2;36m \u001B[0mLoading simulation from                                            \n",
+       "\u001B[2;36m             \u001B[0mdata/mo-\u001B[93m6dc6fac0-7e05-4fc6-ae1e-1c800bb7586b\u001B[0m.hdf5                  \n"
+      ],
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">14:59:25 CET </span>Loading simulation from                                            \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/mo-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">6dc6fac0-7e05-4fc6-ae1e-1c800bb7586b</span>.hdf5                  \n",
+       "</pre>\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
+    },
+    {
+     "data": {
+      "text/plain": [
+       "\u001B[2;36m14:59:27 CET\u001B[0m\u001B[2;36m \u001B[0mLoading simulation from                                            \n",
+       "\u001B[2;36m             \u001B[0mdata/mo-\u001B[93m05172351-96fe-4630-88f3-86450cfe337d\u001B[0m.hdf5                  \n"
+      ],
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">14:59:27 CET </span>Loading simulation from                                            \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/mo-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">05172351-96fe-4630-88f3-86450cfe337d</span>.hdf5                  \n",
+       "</pre>\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
+    },
+    {
+     "data": {
+      "text/plain": [
+       "\u001B[2;36m14:59:28 CET\u001B[0m\u001B[2;36m \u001B[0mLoading simulation from                                            \n",
+       "\u001B[2;36m             \u001B[0mdata/mo-\u001B[93m9a147b1b-451c-4b80-b156-9c87146cd6fe\u001B[0m.hdf5                  \n"
+      ],
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">14:59:28 CET </span>Loading simulation from                                            \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/mo-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">9a147b1b-451c-4b80-b156-9c87146cd6fe</span>.hdf5                  \n",
+       "</pre>\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
+    },
+    {
+     "data": {
+      "text/plain": [
+       "\u001B[2;36m14:59:30 CET\u001B[0m\u001B[2;36m \u001B[0mLoading simulation from                                            \n",
+       "\u001B[2;36m             \u001B[0mdata/mo-\u001B[93mf84ccf6a-1fdc-4ffe-85b2-1fc0f8943865\u001B[0m.hdf5                  \n"
+      ],
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">14:59:30 CET </span>Loading simulation from                                            \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/mo-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">f84ccf6a-1fdc-4ffe-85b2-1fc0f8943865</span>.hdf5                  \n",
+       "</pre>\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
+    },
+    {
+     "data": {
+      "text/plain": [
+       "\u001B[2;36m14:59:31 CET\u001B[0m\u001B[2;36m \u001B[0mLoading simulation from                                            \n",
+       "\u001B[2;36m             \u001B[0mdata/mo-\u001B[93m43d9d675-5d8c-47e5-b77e-1047fed09fec\u001B[0m.hdf5                  \n"
+      ],
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">14:59:31 CET </span>Loading simulation from                                            \n",
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+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/mo-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">af77c985-0bbf-48dd-b6ab-7cfb808f8033</span>.hdf5                  \n",
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+       "\u001B[2;36m14:59:33 CET\u001B[0m\u001B[2;36m \u001B[0mLoading simulation from                                            \n",
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+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/mo-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">3ab0ab17-60e8-40a9-ae1f-befac91879b3</span>.hdf5                  \n",
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+       "\u001B[2;36m14:59:36 CET\u001B[0m\u001B[2;36m \u001B[0mLoading simulation from                                            \n",
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+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/mo-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">ec3a7886-2638-4602-9bae-238e87906ca1</span>.hdf5                  \n",
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+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/mo-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">5c4297f4-736b-4470-9152-113458afc6e8</span>.hdf5                  \n",
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+       "\u001B[2;36m14:59:38 CET\u001B[0m\u001B[2;36m \u001B[0mLoading simulation from                                            \n",
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+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/mo-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">35e6107b-4fd6-480d-ade1-a0bd849974ae</span>.hdf5                  \n",
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+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/mo-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">ac4f8e3f-0d89-45be-b86f-2f3d85a8b77d</span>.hdf5                  \n",
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+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/mo-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">dfcbe39c-3e51-4246-be1c-442536c3ee55</span>.hdf5                  \n",
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+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/mo-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">c7fbcc71-b1a7-49ab-bad7-288ed11c5dcc</span>.hdf5                  \n",
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+       "\u001B[2;36m14:59:42 CET\u001B[0m\u001B[2;36m \u001B[0mLoading simulation from                                            \n",
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+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/mo-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">5019f2af-be5e-452f-831e-a380b78ab030</span>.hdf5                  \n",
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+       "\u001B[2;36m14:59:44 CET\u001B[0m\u001B[2;36m \u001B[0mLoading simulation from                                            \n",
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+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/mo-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">cf8b04c9-6beb-47f6-9f4c-f074370e28f6</span>.hdf5                  \n",
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+       "\u001B[2;36m14:59:46 CET\u001B[0m\u001B[2;36m \u001B[0mLoading simulation from                                            \n",
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+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/mo-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">12a788e9-b14e-4d36-894a-84de517429e9</span>.hdf5                  \n",
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+       "\u001B[2;36m14:59:47 CET\u001B[0m\u001B[2;36m \u001B[0mLoading simulation from                                            \n",
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+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/mo-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">79306634-3b48-40d8-a8bf-b226a64d7e61</span>.hdf5                  \n",
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+       "\u001B[2;36m14:59:48 CET\u001B[0m\u001B[2;36m \u001B[0mLoading simulation from                                            \n",
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+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/mo-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">e154cd6f-93b9-4237-aaf1-b2df82d343fb</span>.hdf5                  \n",
+       "</pre>\n"
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+       "\u001B[2;36m            \u001B[0m\u001B[2;36m \u001B[0mLoading simulation from                                            \n",
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+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/mo-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">f5941f2f-7038-4d8a-a4aa-a412179b860f</span>.hdf5                  \n",
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+       "\u001B[2;36m14:59:49 CET\u001B[0m\u001B[2;36m \u001B[0mLoading simulation from                                            \n",
+       "\u001B[2;36m             \u001B[0mdata/mo-\u001B[93me2f49727-ad8e-4649-acc5-42cb8d1761cc\u001B[0m.hdf5                  \n"
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+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/mo-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">e2f49727-ad8e-4649-acc5-42cb8d1761cc</span>.hdf5                  \n",
+       "</pre>\n"
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+       "\u001B[2;36m14:59:50 CET\u001B[0m\u001B[2;36m \u001B[0mLoading simulation from                                            \n",
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+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/mo-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">0a1edfd9-722d-47f2-a505-58b424333ee8</span>.hdf5                  \n",
+       "</pre>\n"
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+      "text/plain": [
+       "\u001B[2;36m14:59:51 CET\u001B[0m\u001B[2;36m \u001B[0mLoading simulation from                                            \n",
+       "\u001B[2;36m             \u001B[0mdata/mo-\u001B[93m302ba81d-18ca-41dc-a9de-70eca9fd36b4\u001B[0m.hdf5                  \n"
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+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/mo-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">302ba81d-18ca-41dc-a9de-70eca9fd36b4</span>.hdf5                  \n",
+       "</pre>\n"
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+       "\u001B[2;36m14:59:52 CET\u001B[0m\u001B[2;36m \u001B[0mLoading simulation from                                            \n",
+       "\u001B[2;36m             \u001B[0mdata/mo-\u001B[93mef58dc67-5428-4151-9869-f6c91a9f9e03\u001B[0m.hdf5                  \n"
+      ],
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+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/mo-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">ef58dc67-5428-4151-9869-f6c91a9f9e03</span>.hdf5                  \n",
+       "</pre>\n"
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+      "text/plain": [
+       "\u001B[2;36m14:59:53 CET\u001B[0m\u001B[2;36m \u001B[0mLoading simulation from                                            \n",
+       "\u001B[2;36m             \u001B[0mdata/mo-\u001B[93m96a4cc32-721d-43c9-a989-78a82f62a31a\u001B[0m.hdf5                  \n"
+      ],
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+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/mo-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">96a4cc32-721d-43c9-a989-78a82f62a31a</span>.hdf5                  \n",
+       "</pre>\n"
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+      "text/plain": [
+       "\u001B[2;36m14:59:54 CET\u001B[0m\u001B[2;36m \u001B[0mLoading simulation from                                            \n",
+       "\u001B[2;36m             \u001B[0mdata/mo-\u001B[93m0e735b90-0faf-46d4-877e-653f67588e8e\u001B[0m.hdf5                  \n"
+      ],
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+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/mo-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">0e735b90-0faf-46d4-877e-653f67588e8e</span>.hdf5                  \n",
+       "</pre>\n"
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+     "data": {
+      "text/plain": [
+       "\u001B[2;36m            \u001B[0m\u001B[2;36m \u001B[0mLoading simulation from                                            \n",
+       "\u001B[2;36m             \u001B[0mdata/mo-\u001B[93m86eb2efe-a123-4453-a4bb-a07345cdd29c\u001B[0m.hdf5                  \n"
+      ],
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+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/mo-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">86eb2efe-a123-4453-a4bb-a07345cdd29c</span>.hdf5                  \n",
+       "</pre>\n"
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+     "data": {
+      "text/plain": [
+       "\u001B[2;36m14:59:55 CET\u001B[0m\u001B[2;36m \u001B[0mLoading simulation from                                            \n",
+       "\u001B[2;36m             \u001B[0mdata/mo-\u001B[93mfadd8037-5ec9-4375-a60c-7bca9b2141cd\u001B[0m.hdf5                  \n"
+      ],
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">14:59:55 CET </span>Loading simulation from                                            \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/mo-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">fadd8037-5ec9-4375-a60c-7bca9b2141cd</span>.hdf5                  \n",
+       "</pre>\n"
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+     "data": {
+      "text/plain": [
+       "\u001B[2;36m14:59:56 CET\u001B[0m\u001B[2;36m \u001B[0mLoading simulation from                                            \n",
+       "\u001B[2;36m             \u001B[0mdata/mo-\u001B[93m6623f9b7-c9d7-4dce-b540-9ed3f6bce20e\u001B[0m.hdf5                  \n"
+      ],
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">14:59:56 CET </span>Loading simulation from                                            \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/mo-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">6623f9b7-c9d7-4dce-b540-9ed3f6bce20e</span>.hdf5                  \n",
+       "</pre>\n"
+      ]
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+     "data": {
+      "text/plain": [
+       "\u001B[2;36m14:59:57 CET\u001B[0m\u001B[2;36m \u001B[0mLoading simulation from                                            \n",
+       "\u001B[2;36m             \u001B[0mdata/mo-\u001B[93m8152d9ed-5a9a-40bc-a122-08460f257f75\u001B[0m.hdf5                  \n"
+      ],
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">14:59:57 CET </span>Loading simulation from                                            \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/mo-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">8152d9ed-5a9a-40bc-a122-08460f257f75</span>.hdf5                  \n",
+       "</pre>\n"
+      ]
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+      "text/plain": [
+       "\u001B[2;36m14:59:59 CET\u001B[0m\u001B[2;36m \u001B[0mLoading simulation from                                            \n",
+       "\u001B[2;36m             \u001B[0mdata/mo-\u001B[93md4a9b954-748c-497b-b204-12cd678f82d3\u001B[0m.hdf5                  \n"
+      ],
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">14:59:59 CET </span>Loading simulation from                                            \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/mo-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">d4a9b954-748c-497b-b204-12cd678f82d3</span>.hdf5                  \n",
+       "</pre>\n"
+      ]
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+     "jetTransient": {
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+    {
+     "data": {
+      "text/plain": [
+       "\u001B[2;36m15:00:01 CET\u001B[0m\u001B[2;36m \u001B[0mLoading simulation from                                            \n",
+       "\u001B[2;36m             \u001B[0mdata/mo-\u001B[93m5c164adb-5022-461a-83af-9df8a6a605d7\u001B[0m.hdf5                  \n"
+      ],
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">15:00:01 CET </span>Loading simulation from                                            \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/mo-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">5c164adb-5022-461a-83af-9df8a6a605d7</span>.hdf5                  \n",
+       "</pre>\n"
+      ]
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+    {
+     "data": {
+      "text/plain": [
+       "\u001B[2;36m15:00:02 CET\u001B[0m\u001B[2;36m \u001B[0mLoading simulation from                                            \n",
+       "\u001B[2;36m             \u001B[0mdata/mo-\u001B[93mf82170f9-3e54-4608-aee3-99b268862d95\u001B[0m.hdf5                  \n"
+      ],
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">15:00:02 CET </span>Loading simulation from                                            \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/mo-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">f82170f9-3e54-4608-aee3-99b268862d95</span>.hdf5                  \n",
+       "</pre>\n"
+      ]
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+     "data": {
+      "text/plain": [
+       "\u001B[2;36m15:00:03 CET\u001B[0m\u001B[2;36m \u001B[0mLoading simulation from                                            \n",
+       "\u001B[2;36m             \u001B[0mdata/mo-\u001B[93mb932bc9c-0630-4c6e-951a-3971ed43d548\u001B[0m.hdf5                  \n"
+      ],
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">15:00:03 CET </span>Loading simulation from                                            \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/mo-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">b932bc9c-0630-4c6e-951a-3971ed43d548</span>.hdf5                  \n",
+       "</pre>\n"
+      ]
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+     "data": {
+      "text/plain": [
+       "\u001B[2;36m15:00:04 CET\u001B[0m\u001B[2;36m \u001B[0mLoading simulation from                                            \n",
+       "\u001B[2;36m             \u001B[0mdata/mo-\u001B[93m6dc6fac0-7e05-4fc6-ae1e-1c800bb7586b\u001B[0m.hdf5                  \n"
+      ],
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">15:00:04 CET </span>Loading simulation from                                            \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/mo-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">6dc6fac0-7e05-4fc6-ae1e-1c800bb7586b</span>.hdf5                  \n",
+       "</pre>\n"
+      ]
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+    {
+     "data": {
+      "text/plain": [
+       "\u001B[2;36m15:00:05 CET\u001B[0m\u001B[2;36m \u001B[0mLoading simulation from                                            \n",
+       "\u001B[2;36m             \u001B[0mdata/mo-\u001B[93m05172351-96fe-4630-88f3-86450cfe337d\u001B[0m.hdf5                  \n"
+      ],
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">15:00:05 CET </span>Loading simulation from                                            \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/mo-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">05172351-96fe-4630-88f3-86450cfe337d</span>.hdf5                  \n",
+       "</pre>\n"
+      ]
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+    },
+    {
+     "data": {
+      "text/plain": [
+       "\u001B[2;36m15:00:06 CET\u001B[0m\u001B[2;36m \u001B[0mLoading simulation from                                            \n",
+       "\u001B[2;36m             \u001B[0mdata/mo-\u001B[93m9a147b1b-451c-4b80-b156-9c87146cd6fe\u001B[0m.hdf5                  \n"
+      ],
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">15:00:06 CET </span>Loading simulation from                                            \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/mo-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">9a147b1b-451c-4b80-b156-9c87146cd6fe</span>.hdf5                  \n",
+       "</pre>\n"
+      ]
+     },
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+     "jetTransient": {
+      "display_id": null
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+    },
+    {
+     "data": {
+      "text/plain": [
+       "\u001B[2;36m15:00:07 CET\u001B[0m\u001B[2;36m \u001B[0mLoading simulation from                                            \n",
+       "\u001B[2;36m             \u001B[0mdata/mo-\u001B[93mf84ccf6a-1fdc-4ffe-85b2-1fc0f8943865\u001B[0m.hdf5                  \n"
+      ],
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">15:00:07 CET </span>Loading simulation from                                            \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/mo-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">f84ccf6a-1fdc-4ffe-85b2-1fc0f8943865</span>.hdf5                  \n",
+       "</pre>\n"
+      ]
+     },
+     "metadata": {},
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+     "jetTransient": {
+      "display_id": null
+     }
+    },
+    {
+     "data": {
+      "text/plain": [
+       "\u001B[2;36m15:00:08 CET\u001B[0m\u001B[2;36m \u001B[0mLoading simulation from                                            \n",
+       "\u001B[2;36m             \u001B[0mdata/mo-\u001B[93m43d9d675-5d8c-47e5-b77e-1047fed09fec\u001B[0m.hdf5                  \n"
+      ],
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">15:00:08 CET </span>Loading simulation from                                            \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/mo-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">43d9d675-5d8c-47e5-b77e-1047fed09fec</span>.hdf5                  \n",
+       "</pre>\n"
+      ]
+     },
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+     "jetTransient": {
+      "display_id": null
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+    },
+    {
+     "data": {
+      "text/plain": [
+       "\u001B[2;36m15:00:09 CET\u001B[0m\u001B[2;36m \u001B[0mLoading simulation from                                            \n",
+       "\u001B[2;36m             \u001B[0mdata/mo-\u001B[93maf77c985-0bbf-48dd-b6ab-7cfb808f8033\u001B[0m.hdf5                  \n"
+      ],
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">15:00:09 CET </span>Loading simulation from                                            \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/mo-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">af77c985-0bbf-48dd-b6ab-7cfb808f8033</span>.hdf5                  \n",
+       "</pre>\n"
+      ]
+     },
+     "metadata": {},
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+     "jetTransient": {
+      "display_id": null
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+    },
+    {
+     "data": {
+      "text/plain": [
+       "\u001B[2;36m15:00:10 CET\u001B[0m\u001B[2;36m \u001B[0mLoading simulation from                                            \n",
+       "\u001B[2;36m             \u001B[0mdata/mo-\u001B[93md00729e1-dd46-45a9-921b-e185698efe72\u001B[0m.hdf5                  \n"
+      ],
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">15:00:10 CET </span>Loading simulation from                                            \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/mo-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">d00729e1-dd46-45a9-921b-e185698efe72</span>.hdf5                  \n",
+       "</pre>\n"
+      ]
+     },
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+     "jetTransient": {
+      "display_id": null
+     }
+    },
+    {
+     "data": {
+      "text/plain": [
+       "\u001B[2;36m            \u001B[0m\u001B[2;36m \u001B[0mLoading simulation from                                            \n",
+       "\u001B[2;36m             \u001B[0mdata/mo-\u001B[93m4e30095d-daef-4ae7-b370-4e29c870ad6c\u001B[0m.hdf5                  \n"
+      ],
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+       "\u001B[2;36m            \u001B[0m\u001B[2;36m \u001B[0mLoading simulation from                                            \n",
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+       "\u001B[2;36m15:00:20 CET\u001B[0m\u001B[2;36m \u001B[0mLoading simulation from                                            \n",
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+       "</pre>\n"
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+       "\u001B[2;36m15:00:21 CET\u001B[0m\u001B[2;36m \u001B[0mLoading simulation from                                            \n",
+       "\u001B[2;36m             \u001B[0mdata/mo-\u001B[93m5019f2af-be5e-452f-831e-a380b78ab030\u001B[0m.hdf5                  \n"
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+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/mo-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">5019f2af-be5e-452f-831e-a380b78ab030</span>.hdf5                  \n",
+       "</pre>\n"
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+       "\u001B[2;36m15:00:22 CET\u001B[0m\u001B[2;36m \u001B[0mLoading simulation from                                            \n",
+       "\u001B[2;36m             \u001B[0mdata/mo-\u001B[93mcf8b04c9-6beb-47f6-9f4c-f074370e28f6\u001B[0m.hdf5                  \n"
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+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/mo-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">cf8b04c9-6beb-47f6-9f4c-f074370e28f6</span>.hdf5                  \n",
+       "</pre>\n"
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+       "\u001B[2;36m15:00:23 CET\u001B[0m\u001B[2;36m \u001B[0mLoading simulation from                                            \n",
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+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/mo-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">12a788e9-b14e-4d36-894a-84de517429e9</span>.hdf5                  \n",
+       "</pre>\n"
+      ]
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+     }
+    },
+    {
+     "data": {
+      "text/plain": [
+       "\u001B[2;36m            \u001B[0m\u001B[2;36m \u001B[0mLoading simulation from                                            \n",
+       "\u001B[2;36m             \u001B[0mdata/mo-\u001B[93m79306634-3b48-40d8-a8bf-b226a64d7e61\u001B[0m.hdf5                  \n"
+      ],
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+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>Loading simulation from                                            \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/mo-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">79306634-3b48-40d8-a8bf-b226a64d7e61</span>.hdf5                  \n",
+       "</pre>\n"
+      ]
+     },
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+     }
+    },
+    {
+     "data": {
+      "text/plain": [
+       "\u001B[2;36m15:00:24 CET\u001B[0m\u001B[2;36m \u001B[0mLoading simulation from                                            \n",
+       "\u001B[2;36m             \u001B[0mdata/mo-\u001B[93me154cd6f-93b9-4237-aaf1-b2df82d343fb\u001B[0m.hdf5                  \n"
+      ],
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">15:00:24 CET </span>Loading simulation from                                            \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/mo-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">e154cd6f-93b9-4237-aaf1-b2df82d343fb</span>.hdf5                  \n",
+       "</pre>\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
+    }
+   ],
+   "execution_count": 4
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d74b557b-f06f-4825-aa46-8be0aa373321",
+   "metadata": {},
+   "source": [
+    "After the batch of tasks is finished, we are ready to extract the results. We can plot all the mode profiles to inspect each mode at each waveguide width. As a demonstration, we plot all 10 modes with the widest waveguide.  "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "id": "6574c95a-5ee2-410f-8eaa-7f90e78accb9",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:00:26.430114Z",
+     "start_time": "2025-10-29T14:00:24.959864Z"
+    }
+   },
+   "source": [
+    "# plot all mode profiles of the widest waveguide\n",
+    "fig, ax = plt.subplots(5, 2, figsize=(7, 10), tight_layout=True)\n",
+    "for i in range(n_mode):\n",
+    "    mode_solvers[f\"width={w_LN_range[-1]:.2f}\"].plot_field(\n",
+    "        \"E\", \"abs\", mode_index=i, ax=ax[i % 5][i // 5]\n",
+    "    )\n",
+    "    ax[i % 5][i // 5].set_title(f\"mode_index={i}\")"
+   ],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 700x1000 with 20 Axes>"
+      ],
+      "image/png": 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"
+     },
+     "metadata": {},
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
+    }
+   ],
+   "execution_count": 5
+  },
+  {
+   "cell_type": "markdown",
+   "id": "77da6faa-2150-4f60-93cb-cd4f0e20040a",
+   "metadata": {},
+   "source": [
+    "From the mode profiles, we can distinguish fundamental modes and higher order modes. To be more quantitative, we can extract other mode information. For example, we can extract the effective indices and polarization fractions of the modes. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "id": "6856c85e-63b3-4c95-a6e8-79215262edbc",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:00:27.244580Z",
+     "start_time": "2025-10-29T14:00:26.436307Z"
+    }
+   },
+   "source": [
+    "# extract the effective index and polarization fraction\n",
+    "n_eff = np.array([result.n_eff[0] for _, result in batch_results.items()]).T\n",
+    "te_fraction = np.array([result.pol_fraction.te.data[0] for _, result in batch_results.items()]).T"
+   ],
+   "outputs": [],
+   "execution_count": 6
+  },
+  {
+   "cell_type": "markdown",
+   "id": "dfe06f92-c460-4ab4-9d8e-5ee81692bfcc",
+   "metadata": {},
+   "source": [
+    "Once we extract the information, we can plot them to visualize the mode dispersion. Here we plot the effective indices first as curves and then as scatterers with color, where the color indicates the polarization. Red corresponds to quasi-TE modes and blue corresponds to quasi-TM modes. We can see at a few places mode hybridization occurs. For example, at around 1.5 μm waveguide width, the TM0 and TE1 modes hybridize. This hybridization is often utilized to make mode converters for polarization control, as demonstrated in the [polarization splitter rotator](https://www.flexcompute.com/tidy3d/examples/notebooks/BilevelPSR/) example. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "id": "a163e5e3-4aed-4014-b2fa-48487a3d1283",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:00:27.481767Z",
+     "start_time": "2025-10-29T14:00:27.248130Z"
+    }
+   },
+   "source": [
+    "# plot each mode dispersion curve and polarization as colored scatterers\n",
+    "plt.figure(figsize=(10, 5))\n",
     "for i in range(n_mode):\n",
     "    plt.plot(w_LN_range, n_eff[i], c=\"black\")\n",
     "    plt.scatter(w_LN_range, n_eff[i], c=te_fraction[i], cmap=\"coolwarm\", s=40, vmin=0, vmax=1)\n",
@@ -342,7 +1684,23 @@
     "plt.ylabel(\"Effective index\")\n",
     "plt.colorbar()\n",
     "plt.show()"
-   ]
+   ],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 1000x500 with 2 Axes>"
+      ],
+      "image/png": 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"
+     },
+     "metadata": {},
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
+    }
+   ],
+   "execution_count": 7
   }
  ],
  "metadata": {
diff --git a/FocusedApodGC.ipynb b/FocusedApodGC.ipynb
index 7cd8f258..9b386afa 100644
--- a/FocusedApodGC.ipynb
+++ b/FocusedApodGC.ipynb
@@ -25,15 +25,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
    "id": "85959919-a2e6-48b1-996b-bc0f695c0a64",
    "metadata": {
     "slideshow": {
      "slide_type": ""
     },
-    "tags": []
+    "tags": [],
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:22:59.124790Z",
+     "start_time": "2025-10-29T14:22:59.122724Z"
+    }
    },
-   "outputs": [],
    "source": [
     "# Standard python imports.\n",
     "import gdstk\n",
@@ -44,7 +46,9 @@
     "import tidy3d as td\n",
     "import tidy3d.web as web\n",
     "from tidy3d.plugins import waveguide"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": 22
   },
   {
    "cell_type": "markdown",
@@ -91,10 +95,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
    "id": "d10bb29a-c05f-495f-8863-408e81cb165b",
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:22:59.169714Z",
+     "start_time": "2025-10-29T14:22:59.167359Z"
+    }
+   },
    "source": [
     "# Grating coupler set up.\n",
     "h_dev = 0.220  # Device layer thickness (um).\n",
@@ -126,7 +133,9 @@
     "bw = 0.06  # Simulation wavelength bandwidth (um).\n",
     "n_wl = 61  # Number of wavelength points in monitors.\n",
     "run_time = 2e-12  # Run time parameter for simulation (s)."
-   ]
+   ],
+   "outputs": [],
+   "execution_count": 23
   },
   {
    "cell_type": "markdown",
@@ -138,10 +147,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
    "id": "f56c5263-0fec-4c23-a20a-bd9d69cc39c4",
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:22:59.214528Z",
+     "start_time": "2025-10-29T14:22:59.212032Z"
+    }
+   },
    "source": [
     "# Material definitions.\n",
     "mat_si = td.Medium(permittivity=n_si**2)  # Waveguide material.\n",
@@ -158,7 +170,9 @@
     "freq = td.C_0 / wl\n",
     "freqs = td.C_0 / wl_range\n",
     "freqw = 0.5 * (freqs[0] - freqs[-1])"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": 24
   },
   {
    "cell_type": "markdown",
@@ -170,15 +184,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
    "id": "6c614860-73d4-4a2a-83c0-f081093461ae",
    "metadata": {
     "slideshow": {
      "slide_type": ""
     },
-    "tags": []
+    "tags": [],
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:22:59.263333Z",
+     "start_time": "2025-10-29T14:22:59.257351Z"
+    }
    },
-   "outputs": [],
    "source": [
     "# Function to calculate the values of filling fractions and grating element sizes.\n",
     "def calc_gc_par(\n",
@@ -303,7 +319,9 @@
     "        lib.write_gds(gds_file)\n",
     "\n",
     "    return gc_struct"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": 25
   },
   {
    "cell_type": "markdown",
@@ -323,10 +341,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
    "id": "1256637b",
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:22:59.313738Z",
+     "start_time": "2025-10-29T14:22:59.306325Z"
+    }
+   },
    "source": [
     "# Function to create the simulation.\n",
     "def build_sim(\n",
@@ -523,7 +544,9 @@
     "        run_time=run_time,\n",
     "    )\n",
     "    return sim"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": 26
   },
   {
    "cell_type": "markdown",
@@ -537,26 +560,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
    "id": "39db5fa4-71f0-4af0-85ad-7bb678e6ff9d",
    "metadata": {
     "slideshow": {
      "slide_type": ""
     },
-    "tags": []
-   },
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 1000x400 with 2 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
+    "tags": [],
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:22:59.500914Z",
+     "start_time": "2025-10-29T14:22:59.357076Z"
     }
-   ],
+   },
    "source": [
     "# Definition of wide non-etched and etched waveguides.\n",
     "wg_non_etch, wg_etch = (\n",
@@ -580,33 +594,33 @@
     "ax[1].set_aspect(\"auto\")\n",
     "ax[1].set_title(\"Etched\")\n",
     "plt.show()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "id": "c7207809-6214-4668-8619-c9ddcd48411e",
-   "metadata": {},
+   ],
    "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Non-etched waveguide effective index: 2.854\n",
-      "Etched waveguide effective index: 2.276\n"
-     ]
-    },
     {
      "data": {
-      "image/png": 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",
       "text/plain": [
-       "<Figure size 1000x400 with 4 Axes>"
-      ]
+       "<Figure size 1000x400 with 2 Axes>"
+      ],
+      "image/png": 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"
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     }
    ],
+   "execution_count": 27
+  },
+  {
+   "cell_type": "code",
+   "id": "c7207809-6214-4668-8619-c9ddcd48411e",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:23:11.068214Z",
+     "start_time": "2025-10-29T14:22:59.505655Z"
+    }
+   },
    "source": [
     "n_o = wg_non_etch.n_eff.values[0, 0]\n",
     "n_e = wg_etch.n_eff.values[0, 0]\n",
@@ -622,7 +636,31 @@
     "ax[1].set_aspect(\"auto\")\n",
     "ax[1].set_title(\"Etched\")\n",
     "plt.show()"
-   ]
+   ],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Non-etched waveguide effective index: 2.854\n",
+      "Etched waveguide effective index: 2.276\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 1000x400 with 4 Axes>"
+      ],
+      "image/png": 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"
+     },
+     "metadata": {},
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
+    }
+   ],
+   "execution_count": 28
   },
   {
    "cell_type": "markdown",
@@ -634,21 +672,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
    "id": "5bedec4c-58ab-4845-bcf5-2ff27dde3668",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 1000x300 with 2 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:23:11.217743Z",
+     "start_time": "2025-10-29T14:23:11.072260Z"
     }
-   ],
+   },
    "source": [
     "sim_3d = build_sim(\n",
     "    sim_mode=\"sweep\",\n",
@@ -685,7 +715,23 @@
     "ax2.set_aspect(\"auto\")\n",
     "ax2.set_title(\"2D\")\n",
     "plt.show()"
-   ]
+   ],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 1000x300 with 2 Axes>"
+      ],
+      "image/png": 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"
+     },
+     "metadata": {},
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
+    }
+   ],
+   "execution_count": 29
   },
   {
    "cell_type": "markdown",
@@ -699,9 +745,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
    "id": "78eaadd6",
-   "metadata": {},
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:23:11.223555Z",
+     "start_time": "2025-10-29T14:23:11.221858Z"
+    }
+   },
+   "source": [
+    "etch_d_vals = np.linspace(0.07, 0.14, 8)\n",
+    "R_vals = np.linspace(0.015, 0.035, 6)\n",
+    "src_pos_vals = np.linspace(4.0, 6.0, 5)\n",
+    "print(f\"Number of simulations: {len(etch_d_vals) * len(R_vals) * len(src_pos_vals):d}\")"
+   ],
    "outputs": [
     {
      "name": "stdout",
@@ -711,12 +767,7 @@
      ]
     }
    ],
-   "source": [
-    "etch_d_vals = np.linspace(0.07, 0.14, 8)\n",
-    "R_vals = np.linspace(0.015, 0.035, 6)\n",
-    "src_pos_vals = np.linspace(4.0, 6.0, 5)\n",
-    "print(f\"Number of simulations: {len(etch_d_vals) * len(R_vals) * len(src_pos_vals):d}\")"
-   ]
+   "execution_count": 30
   },
   {
    "cell_type": "markdown",
@@ -728,21 +779,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
    "id": "8d7ffa9b",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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VahQVFSEzM/OGfQMCAlBYWIg9e/Zg/vz5ePbZZ5Gbm2uz79y5c2EwGCxLeXm5S+smIqK2zelrlEFBQbh06RL++OMPdOrUCT4+Plbfnz171ukiUlJSsHHjRuTn56NHjx5Or//444+jvLzcoRt6eI2SiIgAN16jTE9Pb05dVoQQeOqpp5CdnY3c3NwmhSRw7bTt9dchicizOEmf2hKng3LatGku27larcbatWuxceNGBAQEoKqqCsC113r5+/sDAJKSkhAREQGNRgPg2jXH4cOHo1evXjAajfjqq6/w6aefYtmyZS6ri4iaTqfT2Xzsm1ar5WPfqFVyOCgdvVvUmdOZ9eH25xefrlq1CsnJyQCAsrIydOjw/5dSa2tr8be//Q1nzpyBv78/+vXrhzVr1mDKlCkO75eI3EOn0yExMbHBDX8VFRVITExEVlYWw5JaHYevUXbo0KHBnMnrCSEgkUhgMplcVpw78BolkXvUv5rq+iPJ6/HVVORtXH6NcseOHS4pjIjaJr1e32hIAtf+MV1eXg69Xt/gLBKRN3M4KGNjY91ZBxG1cvVvE3JVPyJv0ayHohMR1QsLC3NpPyJvwaAkIpdQqVRQKBSN3ssgkUigVCqhUqlauDKi5mFQEpFLSKVSaLVaAGgQlvWf09PTeSMPtToMSiJymYSEBGRlZSEiIsKqXaFQcGoItVpOP8Ku3smTJ3Hq1CnExMTA39/fMj3E23F6CJH78ck81Bq47RF2v//+O6ZMmYLt27dDIpHgxIkT6NmzJ6ZPn46goCAsXry4WYUTUesnlUo5BYTaDKdPvT7zzDPo2LEjysrK0KlTJ0v7lClTsHXrVpcWR0RE5GlOH1F+8803+Prrr6FQKKza+/Tpg9OnT7usMCIiIm/g9BFlbW2t1ZFkvbNnz0Imk7mkKCIiIm/hdFCqVCp88sknls8SiQRmsxmLFi3CqFGjXFocERGRpzl96nXRokUYPXo09u7di6tXr2LOnDk4cuQIzp49i++++84dNRIREXmM00eUAwYMwPHjx3HPPfdg8uTJqK2tRUJCAg4cOIBevXq5o0YiIiKPafI8ytaK8yiJiAhwPA+cPqLs3bs3Xn31VZw4caJZBRIREbUGTgelWq3G5s2b0bdvX0RFRUGr1aKqqsodtREREXlckx44sGfPHhw7dgwTJ07E+++/D6VSibFjx1rdDUtERNQWuOQaZUFBAWbNmoVDhw7BZDK5oi634TVKIiIC3Pis1+vt3r0ba9euxfr161FTU4P//u//bs7miIiIvI7TQXn8+HF89tlnWLduHUpKSnDvvfdi4cKFSEhIQOfOnd1RIxERkcc4HZT9+vVDVFQU1Go1HnroIXTr1s0ddREREXkFp4OyuLgYffr0cUctREREXsfpu15dGZIajQZRUVEICAhASEgI4uPjUVxcbHedFStWQKVSISgoCEFBQRgzZgx2797tspqIiIiu51BQBgcH47fffgMABAUFITg4uNHFGXl5eVCr1SgoKEBOTg7q6uowduxY1NbWNrpObm4upk6dih07dmDXrl2WqSkVFRVO7ZuIiMgRDk0PWb16NR566CHIZDJkZGRAIpE02nfatGlNLubXX39FSEgI8vLyEBMT49A6JpMJQUFBeO+995CUlHTD/pweQkREgIunh1wffsnJyc0urjEGgwEAnDoyvXTpEurq6hpdx2g0wmg0Wj7X1NQ0r0giImpXnL5GKZVK8csvvzRo//333yGVSptciNlsRlpaGqKjozFgwACH13vuuecQHh6OMWPG2Pxeo9FALpdbFqVS2eQaiYio/XE6KBs7U2s0GuHr69vkQtRqNYqKipCZmenwOgsWLEBmZiays7Ph5+dns8/cuXNhMBgsS3l5eZNrJCKi9sfh6SHvvvsuAEAikeCjjz6yeriAyWRCfn4++vXr16QiUlJSsGnTJuTn50OhUDi0zttvv40FCxbg22+/xaBBgxrtJ5PJIJPJmlQXERGRw0G5ZMkSANeOKJcvX251mtXX1xeRkZFYvny5UzsXQuCpp55CdnY2cnNz0aNHD4fWW7RoEebPn4+vv/4aw4cPd2qfREREznA4KEtKSgAAo0aNgk6nQ1BQULN3rlarsXbtWmzcuBEBAQGW13XJ5XL4+/sDAJKSkhAREQGNRgMAWLhwIV5++WWsXbsWkZGRlnU6d+7MR+gREZHLueTtIU3eeSPTTFatWmW5uzYuLg6RkZHIyMgAAERGRuL06dMN1nnllVfw6quv3nCfnB5CRESAG98e8uCDD+LOO+/Ec889Z9W+aNEi7NmzB1988YXD23Iko3Nzc60+l5aWOrx9IiKi5nL6rtf8/HxMnDixQfuECROQn5/vkqKIiIi8hdNBefHiRZvTQHx8fDiZn4iI2hyng3LgwIFYv359g/bMzEz079/fJUURERF5C6evUb700ktISEjAqVOncO+99wIAtm3bhnXr1jl1fZKIiKg1cDooH3jgAWzYsAFvvfUWsrKy4O/vj0GDBuHbb79FbGysO2okIiLyGI9OD/EETg8hIiLA8Txw+holAJw/fx4fffQR5s2bh7NnzwIA9u/fz3dCEhFRm+P0qddDhw5hzJgxkMvlKC0txeOPP47g4GDodDqUlZXhk08+cUedREREHuH0EeWzzz6L5ORknDhxwuqNHRMnTuQ8SiIianOcDso9e/Zg5syZDdojIiIsz10lIiJqK5wOSplMZvPBAsePH0fXrl1dUhQREZG3cDoo//M//xOvv/466urqAFx7sHlZWRmee+45PPjggy4vkIiIyJOcDsrFixfj4sWLCAkJweXLlxEbG4vevXsjICAA8+fPd0eNREREHuP0Xa9yuRw5OTn47rvvcPDgQVy8eBFDhw7FmDFj3FEfERGRRzkUlMHBwTh+/Di6dOmCxx57DFqtFtHR0YiOjnZ3fURERB7l0KnXq1evWm7gWb16Na5cueLWooiIiLyFQ0eUI0eORHx8PIYNGwYhBJ5++mn4+/vb7Lty5UqXFkhERORJDgXlmjVrsGTJEpw6dQoAYDAYeFRJRETtgtMPRe/Rowf27t2LW265xV01uRUfik5ERICLH4oeHByM3377DQAwatQo+Pr6uqZKIiIiL8ebeYiI2gGTyYTc3FysW7cOubm5MJlMni6p1eDNPEREbZxOp0NqairOnDljaVMoFNBqtUhISPBgZa2DQ0eUa9aswcSJE3Hx4kVIJBIYDAacO3fO5kJERN5Dp9MhMTHRKiQBoKKiAomJidDpdB6qrPXw6M08Go0GOp0Ox44dg7+/P+6++24sXLgQffv2bXSdI0eO4OWXX8a+fftw+vRpLFmyBGlpaQ7vkzfzEFF7YTKZEBkZ2SAk60kkEigUCpSUlEAqlbZwdZ7n0pt5rldSUuKyO17z8vKgVqtRUFCAnJwc1NXVYezYsaitrW10nUuXLqFnz55YsGABQkNDXVIHEVFbpNfrGw1JABBCoLy8HHq9vgWran0cDsqJEyfCYDBYPi9YsADnz5+3fP7999/Rv39/p3a+detWJCcn4/bbb8fgwYORkZGBsrIy7Nu3r9F1oqKi8I9//AMPPfQQZDKZU/sjImpPKisrXdqvvXI4KL/++msYjUbL57feegtnz561fP7jjz9QXFzcrGLqgzg4OLhZ27me0WhETU2N1UJE1B6EhYW5tF975XBQ/vlSppOXNm/IbDYjLS0N0dHRGDBggMu2q9FoIJfLLYtSqXTZtomIvJlKpYJCoYBEIrH5vUQigVKphEqlauHKWhenr1G6i1qtRlFRETIzM1263blz58JgMFiW8vJyl26fiMhbSaVSaLVaAGgQlvWf09PT2+WNPM5wOCglEkmjf9HNlZKSgk2bNmHHjh1QKBQu2WY9mUyGwMBAq4WIqL1ISEhAVlYWIiIirNoVCgWysrI4j9IBDr+4WQiB5ORkyw00V65cwZNPPombbroJAKyuXzqzzaeeegrZ2dnIzc1Fjx49nN4GERHZl5CQgMmTJ0Ov16OyshJhYWFQqVQ8knSQw0E5bdo0q88PP/xwgz5JSUlO7VytVmPt2rXYuHEjAgICUFVVBQCQy+WWJ/8kJSUhIiICGo0GwLXH6R09etTy54qKChQWFqJz587o3bu3U/snImovpFIp4uLiPF1Gq+T0AwdcuvNGTt2uWrUKycnJAIC4uDhERkYiIyMDAFBaWmrzyDM2Nha5ubk33CcfOEBERIDjeeDwEaU7OJLRfw6/yMhIl99xS0RE1BivueuViIjIGzEoiYiI7GBQEhER2cGgJCIisoNBSUREZAeDkoiIyA4GJRERkR0MSiIiIjsYlERERHYwKImIiOxgUBIREdnBoCQiIrKDQUlERGQHg5KIiMgOBiUREZEdDEoiIiI7GJRERER2MCiJiIjsYFASERHZwaAkIiKyg0FJRERkB4OSiIjIDgYlERGRHR4NSo1Gg6ioKAQEBCAkJATx8fEoLi6+4XpffPEF+vXrBz8/PwwcOBBfffVVC1RLRETtkUeDMi8vD2q1GgUFBcjJyUFdXR3Gjh2L2traRtf5/vvvMXXqVEyfPh0HDhxAfHw84uPjUVRU1IKVExFReyERQghPF1Hv119/RUhICPLy8hATE2Ozz5QpU1BbW4tNmzZZ2kaMGIEhQ4Zg+fLlN9xHTU0N5HI5DAYDAgMDXVY7ERG1Lo7mgVddozQYDACA4ODgRvvs2rULY8aMsWobN24cdu3aZbO/0WhETU2N1UJEROQorwlKs9mMtLQ0REdHY8CAAY32q6qqQrdu3azaunXrhqqqKpv9NRoN5HK5ZVEqlS6tm4iI2javCUq1Wo2ioiJkZma6dLtz586FwWCwLOXl5S7dPhERtW0dPV0AAKSkpGDTpk3Iz8+HQqGw2zc0NBTV1dVWbdXV1QgNDbXZXyaTQSaTuaxWIiJqXzx6RCmEQEpKCrKzs7F9+3b06NHjhuuMHDkS27Zts2rLycnByJEj3VUmERG1Yx49olSr1Vi7di02btyIgIAAy3VGuVwOf39/AEBSUhIiIiKg0WgAAKmpqYiNjcXixYsxadIkZGZmYu/evfjwww89Ng4iImq7PHpEuWzZMhgMBsTFxSEsLMyyrF+/3tKnrKwMlZWVls9333031q5diw8//BCDBw9GVlYWNmzYYPcGICIioqbyqnmULYHzKImICGil8yiJiIi8DYOSiIjIDgYlERGRHQxKIiIiOxiUREREdjAoiYiI7GBQEhER2cGgJCIisoNBSUREZAeDkoiIyA4GJRERkR0MSiIiIju84sXNREREjjCZTNDr9aisrERYWBhUKhWkUqlb98mgJCKiVkGn0yE1NRVnzpyxtCkUCmi1WiQkJLhtvzz1SkREXk+n0yExMdEqJAGgoqICiYmJ0Ol0bts3g5KIiLyayWRCamoqbL0+ub4tLS0NJpPJLftnUBIRkVfT6/UNjiSvJ4RAeXk59Hq9W/bPoCQiIq9WWVnp0n7OYlASEZFXCwsLc2k/ZzEoiYjIq6lUKigUCkgkEpvfSyQSKJVKqFQqt+yfQUlERF5NKpVCq9UCQIOwrP+cnp7utvmUDEoiIvJ6CQkJyMrKQkREhFW7QqFAVlaWW+dRSoSt+23bsJqaGsjlchgMBgQGBnq6HCIicoIrn8zjaB549IgyPz8fDzzwAMLDwyGRSLBhw4YbrvP+++/jtttug7+/P/r27YtPPvnE/YUSEZFXkEqliIuLw9SpUxEXF+f2x9cBHn6EXW1tLQYPHozHHnvMocPmZcuWYe7cuVixYgWioqKwe/duzJgxA0FBQXjggQdaoGIiImpvPBqUEyZMwIQJExzu/+mnn2LmzJmYMmUKAKBnz57Ys2cPFi5cyKAkIiK3aFUPRTcajfDz87Nq8/f3x+7du1FXVwcfHx+b6xiNRsvnmpoat9dJRERtR6sKynHjxuGjjz5CfHw8hg4din379uGjjz5CXV0dfvvtN5uTTTUaDV577bUG7QxMIqL2rT4HbnhPq/ASAER2drbdPpcuXRKPPvqo6Nixo5BKpSI8PFzMmTNHABBVVVU217ly5YowGAyW5ejRowIAFy5cuHDhIgCI8vJyu9nTqo4o/f39sXLlSnzwwQeorq5GWFgYPvzwQwQEBKBr164215HJZJDJZJbPnTt3Rnl5OQICAhp9yoMjampqoFQqUV5e3qqnmbSVcQBtZywch/dpK2PhOKwJIXDhwgWEh4fb7deqgrKej48PFAoFACAzMxP3338/OnRwbKZLhw4dLOu6QmBgYKv+D65eWxkH0HbGwnF4n7YyFo7j/8nl8hv28WhQXrx4ESdPnrR8LikpQWFhIYKDg3Hrrbdi7ty5qKiosMyVPH78OHbv3o277roL586dwzvvvIOioiKsXr3aU0MgIqI2zqNBuXfvXowaNcry+dlnnwUATJs2DRkZGaisrERZWZnle5PJhMWLF6O4uBg+Pj4YNWoUvv/+e0RGRrZ06URE1E54NCjj4uLs3m2UkZFh9fm2227DgQMH3FyVY2QyGV555RWr65+tUVsZB9B2xsJxeJ+2MhaOo2na3bNeiYiInMG3hxAREdnBoCQiIrKDQUlERGQHg5KIiMgOBuV13n//fURGRsLPzw933XUXdu/ebbf/F198gX79+sHPzw8DBw7EV199ZfW9RCKxufzjH/9w5zBcPo6LFy8iJSUFCoUC/v7+6N+/P5YvX+7OIQBw/Tiqq6uRnJyM8PBwdOrUCePHj8eJEyfcOQQAzo3jyJEjePDBBxEZGQmJRIL09PRmb9OVXD2WpryT1hVcPQ6NRoOoqCgEBAQgJCQE8fHxKC4uduMIrnH1OJYtW4ZBgwZZJvKPHDkSW7ZsceMI/p87/j+pt2DBAkgkEqSlpTWtuKY8l7UtyszMFL6+vmLlypXiyJEjYsaMGeLmm28W1dXVNvt/9913QiqVikWLFomjR4+KF198Ufj4+IjDhw9b+lRWVlotK1euFBKJRJw6dapVjWPGjBmiV69eYseOHaKkpER88MEHQiqVio0bN7aacZjNZjFixAihUqnE7t27xbFjx8QTTzwhbr31VnHx4kWvGcfu3bvF7Nmzxbp160RoaKhYsmRJs7fpzWP56quvxAsvvCB0Op0Abvy8Z1dwxzjGjRsnVq1aJYqKikRhYaGYOHFiq/xv68svvxSbN28Wx48fF8XFxWLevHnCx8dHFBUVuW0c7hrL9X0jIyPFoEGDRGpqapPqY1D+25133inUarXls8lkEuHh4UKj0djs/5e//EVMmjTJqu2uu+4SM2fObHQfkydPFvfee69rCm6EO8Zx++23i9dff92qz9ChQ8ULL7zgwsqtuXocxcXFAoDV//Amk0l07dpVrFixwg0juMbZcVyve/fuNn8BNGebzeGOsVyvpYLS3eMQQohffvlFABB5eXnNKdWulhiHEEIEBQWJjz76qKllOsRdY7lw4YLo06ePyMnJEbGxsU0OSp56BXD16lXs27cPY8aMsbR16NABY8aMwa5du2yus2vXLqv+wLXXgDXWv7q6Gps3b8b06dNdV/ifuGscd999N7788ktUVFRACIEdO3bg+PHjGDt2bKsZR/07Sa9/n2mHDh0gk8mwc+dOVw8BQNPG4YltevN+Xa2lxmEwGAAAwcHBLtvm9VpiHCaTCZmZmaitrcXIkSNdsk1b3DkWtVqNSZMmNfjd4CwGJYDffvsNJpMJ3bp1s2rv1q0bqqqqbK5TVVXlVP/Vq1cjICAACQkJrinaBneNY+nSpejfvz8UCgV8fX0xfvx4vP/++4iJiXH9IOCecfTr18/y/OBz587h6tWrWLhwIc6cOYPKykqvGYcntunN+3W1lhiH2WxGWloaoqOjMWDAAJds88/cOY7Dhw+jc+fOkMlkePLJJ5GdnY3+/fs3a5v2uGssmZmZ2L9/PzQaTXNLbJ1vD2mNVq5cib/+9a9WRzStxdKlS1FQUIAvv/wS3bt3R35+PtRqNcLDw5v9L7WW4uPjA51Oh+nTpyM4OBhSqRRjxozBhAkTbvzSViInqNVqFBUVue1Mhbv17dsXhYWFMBgMyMrKwrRp05CXl+fWsHS18vJypKamIicnxyW/cxmUALp06QKpVIrq6mqr9urqaoSGhtpcJzQ01OH+er0excXFWL9+veuKtsEd47h8+TLmzZuH7OxsTJo0CQAwaNAgFBYW4u2333ZLULrr5zFs2DDLL4CrV6+ia9euuOuuuzB8+HCXjwFo2jg8sU1v3q+ruXscKSkp2LRpE/Lz8136Or8/c+c4fH190bt3bwDX/p/Zs2cPtFotPvjgg2ZttzHuGMu+ffvwyy+/YOjQoZY2k8mE/Px8vPfeezAajZBKpQ5vj6dece0/jGHDhmHbtm2WNrPZjG3btjV6bn7kyJFW/QEgJyfHZv+PP/4Yw4YNw+DBg11b+J+4Yxx1dXWoq6tr8L5PqVQKs9ns4hFc4+6fh1wuR9euXXHixAns3bsXkydPdu0A/q0p4/DENr15v67mrnEIIZCSkoLs7Gxs374dPXr0cEW5jWrJn4fZbLZc43cHd4xl9OjROHz4MAoLCy3L8OHD8de//hWFhYVOhSQATg+pl5mZKWQymcjIyBBHjx4VTzzxhLj55ptFVVWVEEKIRx55RDz//POW/t99953o2LGjePvtt8WPP/4oXnnllQbTKoQQwmAwiE6dOolly5a12nHExsaK22+/XezYsUP89NNPYtWqVcLPz0/885//bFXj+Pzzz8WOHTvEqVOnxIYNG0T37t1FQkKC28bQlHEYjUZx4MABceDAAREWFiZmz54tDhw4IE6cOOHwNlvTWC5cuGDpA0C888474sCBA+L06dOtahyzZs0Scrlc5ObmWk0Ju3TpUqsax/PPPy/y8vJESUmJOHTokHj++eeFRCIR33zzjdvG4a6x/Flz7nplUF5n6dKl4tZbbxW+vr7izjvvFAUFBZbvYmNjxbRp06z6f/755+I//uM/hK+vr7j99tvF5s2bG2zzgw8+EP7+/uL8+fPuLt/C1eOorKwUycnJIjw8XPj5+Ym+ffuKxYsXC7PZ3KrGodVqhUKhED4+PuLWW28VL774ojAajW4dg7PjKCkpEQAaLLGxsQ5vszWNZceOHTb7/Pln6+3jsPU9ALFq1apWNY7HHntMdO/eXfj6+oquXbuK0aNHuz0k3TWWP2tOUPI1W0RERHbwGiUREZEdDEoiIiI7GJRERER2MCiJiIjsYFASERHZwaAkIiKyg0FJRERkB4OSiIjIDgYlERGRHQxKohYUFxeHtLQ0T5fRJE2t/ffff0dISAhKS0tdXtOfPfTQQ1i8eLHb90PtC4OSqBHJycmQSCQNlvHjxwNo2dC7vhYfHx9069YN9913H1auXOmWt7i4cmzz58/H5MmTERkZ6ZLt2fPiiy9i/vz5MBgMbt8XtR8MSiI7xo8fj8rKSqtl3bp1Hq2ltLQUW7ZswahRo5Camor7778ff/zxh0dqupFLly7h448/xvTp01tkfwMGDECvXr2wZs2aFtkftQ8MSiI7ZDIZQkNDrZagoCAkJycjLy8PWq3WcqRXf2rRbDZj0aJF6N27N2QyGW699VbMnz/fsk2z2Yw5c+YgODgYoaGhePXVV52qJSIiAkOHDsW8efOwceNGbNmyBRkZGZZtazQa9OjRA/7+/hg8eDCysrKsthMXF4eUlBSkpKRALpejS5cueOmll1D/foQbjc2Z2r/66ivIZDKMGDHCqn3nzp3w8fHBlStXLG2lpaWQSCQ4ffq05c//+te/EBMTA39/f0RFRaGsrAx6vR4jRoxAp06dMHr0aJw/f95q2w888AAyMzMd+jslckiT3jlC1A5MmzZNTJ482eZ358+fFyNHjhQzZsywvHvwjz/+EEIIMWfOHBEUFCQyMjLEyZMnhV6vFytWrBBCXHvVT2BgoHj11VfF8ePHxerVqx1635+9WgYPHiwmTJgghBDizTffFP369RNbt24Vp06dEqtWrRIymUzk5uZa+sfGxorOnTuL1NRUcezYMbFmzRrRqVMn8eGHH9odW1Nqf/rpp8X48eMbtC9dulQMHDjQqk2n04mgoCAhhBAbNmwQAMTo0aOFXq8X+/fvF0qlUqhUKjFx4kSxZ88eUVBQIG655RbxzjvvWG1ny5YtwtfXV1y5csXu3ymRozp6OqiJvNmmTZvQuXNnq7Z58+Zh3rx58PX1RadOnRAaGmr57sKFC9BqtXjvvfcwbdo0AECvXr1wzz33WPoMGjQIr7zyCgCgT58+eO+997Bt2zbcd999TaqxX79+OHToEIxGI9566y18++23ljfD9+zZEzt37sQHH3yA2NhYyzpKpRJLliyBRCJB3759cfjwYSxZsgQzZsyAXC63Obam1H769GmEh4c3aD948CDuuOMOq7bCwkIMHjzY8ufg4GCsX78et9xyCwAgNjYWO3fuxJEjR9CpUycAQFRUFKqqqqy2Ex4ejqtXr6Kqqgrdu3d3+O+RqDEMSiI7Ro0ahWXLllm1BQcHN9r/xx9/hNFoxOjRoxvtM2jQIKvPYWFh+OWXX5pcoxACEokEJ0+exKVLlxqE1tWrVxuE0ogRIyCRSCyfR44cicWLF8NkMkEqlbqs9suXL8PPz69Be2FhIf7nf/7Hqu3AgQMYMmQIgGtB+l//9V+WkASAsrIyTJkyxRKS9W2TJ0+22o6/vz+Aa9dHiVyBQUlkx0033YTevXs73L/+l7Q9Pj4+Vp8lEkmz7lz98ccf0aNHD1y8eBEAsHnzZkRERFj1kclkTd7+9ZytvUuXLjh37pxVm8lkQlFRUYPw3r9/Px588EEA14J07ty5Vt8fPHgQzzzzjOXzlStXUFxcbDkKrXf27FkAQNeuXR0cFZF9vJmHqIl8fX1hMpms2vr06QN/f39s27atRWrYvn07Dh8+jAcffBD9+/eHTCZDWVkZevfubbUolUqr9X744QerzwUFBejTp4/laNLW2JrijjvuwNGjR63aiouLceXKFatTsrt27UJFRQWGDBmCmpoalJaWWgVpSUkJDAaDVdvhw4chhMDAgQOttl9UVASFQoEuXbo0u34igEeURHYZjcYG18A6duyILl26IDIyEj/88ANKS0vRuXNnBAcHw8/PD8899xzmzJkDX19fREdH49dff8WRI0eaPUWivhaTyYTq6mps3boVGo0G999/P5KSkiCVSjF79mw888wzMJvNuOeee2AwGPDdd98hMDDQcs0UuHbK8tlnn8XMmTOxf/9+LF261Gqivq2xNcW4ceMwd+5cnDt3DkFBQQCuHS0CwNKlS/H000/j5MmTePrppwFcO0188OBBSKVSDBgwwLKd+muW119zLCwsRK9evRpcQ9br9Rg7dmyT6iWyhUFJZMfWrVsRFhZm1da3b18cO3YMs2fPxrRp09C/f39cvnwZJSUliIyMxEsvvYSOHTvi5Zdfxs8//4ywsDA8+eSTLqulY8eOCAoKwuDBg/Huu+9i2rRp6NDh2smhN954A127doVGo8FPP/2Em2++2TKV5HpJSUm4fPky7rzzTkilUqSmpuKJJ56wfG9rbE0xcOBADB06FJ9//jlmzpwJ4FrAjRs3Dj/99BMGDhyI/v3747XXXsOsWbPw7rvv4q677kLfvn2trm3auvnn4MGDDU67XrlyBRs2bMDWrVubVC+RLRIh/j15iojahbi4OAwZMgTp6ektsr/Nmzfj73//O4qKitChQweMGzcOUVFRePPNN12+r2XLliE7OxvffPONy7dN7RevURKRW02aNAlPPPEEKioqAFw7EvzzdUVX8fHxwdKlS92ybWq/eOqViNyu/rmxVVVVqK6udltQPv74427ZLrVvPPVKRERkB0+9EhER2cGgJCIisoNBSUREZAeDkoiIyA4GJRERkR0MSiIiIjsYlERERHYwKImIiOxgUBIREdnBoCQiIrKDQUlERGTH/wHHPLD3UEYSUwAAAABJRU5ErkJggg==",
-      "text/plain": [
-       "<Figure size 500x300 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:23:59.675620Z",
+     "start_time": "2025-10-29T14:23:11.267061Z"
     }
-   ],
+   },
    "source": [
     "n_e_vals = np.zeros_like(etch_d_vals)\n",
     "for i, ed in enumerate(etch_d_vals):\n",
@@ -761,44 +804,69 @@
     "ax.set_xlabel(r\"Etch Depth ($\\mu m$)\")\n",
     "ax.set_ylabel(\"Effective Index\")\n",
     "plt.show()"
-   ]
+   ],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 500x300 with 1 Axes>"
+      ],
+      "image/png": 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"
+     },
+     "metadata": {},
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
+    }
+   ],
+   "execution_count": 31
   },
   {
    "cell_type": "markdown",
    "id": "352c883f",
    "metadata": {},
-   "source": [
-    "Next, we will build and run the [parameter sweep](https://www.flexcompute.com/tidy3d/examples/notebooks/ParameterScan/) using [web.run_async](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.web.api.asynchronous.run_async.html). Verbosity will be turned off to reduce the amount of output data."
-   ]
+   "source": "Next, we will build and run the [parameter sweep](https://www.flexcompute.com/tidy3d/examples/notebooks/ParameterScan/) using [web.run](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.web.api.run.run.html). Verbosity will be turned off to reduce the amount of output data."
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
    "id": "a37dcbbf",
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "jupyter": {
+     "is_executing": true
+    },
+    "ExecuteTime": {
+     "start_time": "2025-10-29T14:23:59.718030Z"
+    }
+   },
    "source": [
-    "sim_sweep = {\n",
-    "    f\"sim_etch_d:{ed}_R:{r}_src_pos:{sp}\": build_sim(\n",
-    "        sim_mode=\"sweep\",\n",
-    "        sim_dim=\"2D\",\n",
-    "        no=n_o,\n",
-    "        ne=ne,\n",
-    "        nc=n_c,\n",
-    "        src_pos=sp,\n",
-    "        R=r,\n",
-    "        alpha_t=alpha_t,\n",
-    "        tap_l=tap_l,\n",
-    "        tap_e=tap_e,\n",
-    "        etch_d=ed,\n",
-    "    )\n",
+    "sim_sweep = [\n",
+    "    [  # for each etch_d\n",
+    "        [  # for each R\n",
+    "            build_sim(\n",
+    "                sim_mode=\"sweep\",\n",
+    "                sim_dim=\"2D\",\n",
+    "                no=n_o,\n",
+    "                ne=ne,\n",
+    "                nc=n_c,\n",
+    "                src_pos=sp,\n",
+    "                R=r,\n",
+    "                alpha_t=alpha_t,\n",
+    "                tap_l=tap_l,\n",
+    "                tap_e=tap_e,\n",
+    "                etch_d=ed,\n",
+    "            )\n",
+    "            for sp in src_pos_vals\n",
+    "        ]\n",
+    "        for r in R_vals\n",
+    "    ]\n",
     "    for ed, ne in zip(etch_d_vals, n_e_vals)\n",
-    "    for r in R_vals\n",
-    "    for sp in src_pos_vals\n",
-    "}\n",
+    "]\n",
     "\n",
-    "batch_data = web.run_async(simulations=sim_sweep, path_dir=\"data\", verbose=False)"
-   ]
+    "batch_data = web.run(sim_sweep, path=\"data\", verbose=False)"
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "markdown",
@@ -810,10 +878,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
    "id": "390993d9",
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:16:48.566400Z",
+     "start_time": "2025-10-29T14:16:41.736850Z"
+    }
+   },
    "source": [
     "ce_vals = np.ones((R_vals.size, etch_d_vals.size)) * (-1000)\n",
     "src_vals = np.zeros_like(ce_vals)\n",
@@ -821,7 +892,7 @@
     "for k, ed in enumerate(etch_d_vals):\n",
     "    for j, r in enumerate(R_vals):\n",
     "        for i, sp in enumerate(src_pos_vals):\n",
-    "            sim_data = batch_data[f\"sim_etch_d:{ed}_R:{r}_src_pos:{sp}\"]\n",
+    "            sim_data = batch_data[k][j][i]\n",
     "            mode_amps = sim_data[\"mode_monitor\"]\n",
     "            coeffs_f = mode_amps.amps.sel(direction=\"-\")\n",
     "            power = np.abs(coeffs_f.sel(mode_index=0)) ** 2\n",
@@ -829,7 +900,9 @@
     "            if ce_vals[j, k] < power_db:\n",
     "                ce_vals[j, k] = power_db\n",
     "                src_vals[j, k] = sp"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": 12
   },
   {
    "cell_type": "markdown",
@@ -841,30 +914,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
    "id": "5c13f626",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Etch depth: 0.090\n",
-      "R: 0.031\n",
-      "Source position: 5.000\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 500x400 with 2 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:16:48.631080Z",
+     "start_time": "2025-10-29T14:16:48.570069Z"
     }
-   ],
+   },
    "source": [
     "jr, ke = np.where(ce_vals == ce_vals.max())\n",
     "final_etch_d = etch_d_vals[ke][0]\n",
@@ -893,7 +949,32 @@
     "ax.set_ylabel(r\"R ($\\mu m^{-1}$)\")\n",
     "fig.colorbar(pcm, ax=ax, label=\"Coupling Efficiency (dB)\", pad=0.01)\n",
     "plt.show()"
-   ]
+   ],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Etch depth: 0.090\n",
+      "R: 0.031\n",
+      "Source position: 5.000\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 500x400 with 2 Axes>"
+      ],
+      "image/png": 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"
+     },
+     "metadata": {},
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
+    }
+   ],
+   "execution_count": 13
   },
   {
    "cell_type": "markdown",
@@ -907,21 +988,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
    "id": "c9dbb957",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 1000x300 with 2 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:16:48.782336Z",
+     "start_time": "2025-10-29T14:16:48.639736Z"
     }
-   ],
+   },
    "source": [
     "sim_3d = build_sim(\n",
     "    sim_mode=\"visualization\",\n",
@@ -942,18 +1015,39 @@
     "sim_3d.plot(z=h_dev / 2 - etch_d / 2, ax=ax1)\n",
     "sim_3d.plot(y=0, ax=ax2)\n",
     "plt.show()"
-   ]
+   ],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 1000x300 with 2 Axes>"
+      ],
+      "image/png": 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iiSda+V577bUX9t9/fyxcuNCRC/Xqq69i3bp1OO6447p9D8aOHQtFUQr+fQDIeyDwj3/8w7qWvuajjz7CmDFjrJBcgiAIgiB2PCi8kCjInXfeiVdffRUTJkywyqlv3LgR8+fPxzvvvOMoaZ5LdXU1brjhBsycORM/+tGPcNJJJ+Hbb7/F3Llzccghh+Dcc88FACxZsgRXX301zjjjDIwcORLpdBqPP/44RFHEaaedBgCYNWsW3nrrLUyePBlDhgxBS0sL5s6di0GDBnVbOryU48477zw899xzuPzyy7F06VL84Ac/gKZp+Oabb/Dcc8/hX//6Fw4++GAMHz4cN910E26//XYceeSROPXUU6GqKj744APU19dj9uzZAIyN+IMPPog77rgDw4cPR01NjVWUw44sy7jrrrtw0UUXYcKECTj77LOtkvFDhw7F9ddfv6W3zcERRxyB8vJyXHDBBbj22mvBGMPjjz9ecOM/duxYPPvss5g2bRoOOeQQ+Hw+nHjiiQXnvfbaa7Fp0yZMnz4dzzzzjOO1/fbbD/vttx+ALcvpGjRoEK677jrcfffdSKVSOOSQQ7BgwQK8/fbbePLJJx1hdzfccAP+9re/YdWqVVZfsdNPPx2HHXYYLrroInz11VeoqqrC3LlzoWkaZs6c6TjXnDlzcNxxx2H8+PG47LLL0NnZiXvvvRcjR47ssRS/y+XC8ccfj9dee61gU+JFixbhnHPOwVFHHYXly5fjz3/+MzweD1599VUccsghOOGEE3r93hQilUpZffIIgiAIgtiB2S41E4mdgjVr1vDzzz+fV1dXc1VV+Z577smvuuoqnkgkOOfZkvGFyspzbpSIHzVqFJdlmdfW1vIrrriCt7e3W69///33/Oc//zkfNmwYd7lcvKKigv/whz/kr732mjXm9ddf5yeffDKvr6/niqLw+vp6fvbZZ/Ply5d3u/ZSj0smk/yuu+7iY8aM4aqq8vLycj527Fg+c+ZM3tnZ6Rj7yCOP8AMPPNAaN2HCBL548WLr9aamJj558mTu9/s5AKt8fG7JeJNnn33Wmq+iooKfc845fP369Y4xF1xwAfd6vXnXZ5Yb74l3332XH3bYYdztdvP6+no+ffp0/q9//StvPeFwmP/sZz/jZWVlHEC35eMnTJhQtPy7vST6lqJpGr/zzjv5kCFDuKIofMyYMfyJJ57IG2eW01+1apXDvnnzZn7xxRfzyspK7vF4+IQJE4r+ji5evJgfdthh1u/feeedxzdu3FjSOv/+979zxhhfu3atZTNLxt9555184sSJXFVV3tDQwJ9//nl+4403co/Hw2fOnMk5z97D3LYGxe75hAkT+JgxYxy2V155hQPgK1asKGnNBEEQBEFsHxjn/RDvQhAEsYujaRr23ntv/PSnP8Xtt98OAFi9ejUaGhrw6KOP4sILL+z3NUyZMgWMMSt8kSAIgiCIHRPK6SIIgtgCRFHErFmz8Kc//cnq+7Ut+frrr/Hiiy9ago8gCIIgiB0XEl0EQRBbyJlnnonNmzc7en1tK0aPHo10Ol1yPz2CIAiCILYfJLoIgiAIgiAIgiD6EcrpIgiCIAiCIAiC6EfI00UQBEEQBEEQBNGPkOgiCIIgCIIgCILoR6g5ch+i6zo2bNgAv98Pxtj2Xg5BEMROBeccXV1dqK+vhyDQM0GCIAhi14FEVx+yYcMG/PGPf4QkSeCco729HaWmzCmKYm0ydF1HMpnsz6UWRJIkSFL2VyKRSJS8/r6CMQZVVa1/p9NppNPpbboGgO6HCd2PLHQ/svT1/WCMoby8HIwx3HnnnVi3bh0GDRrUF0slCIIgiB0CEl19iN/vhyRJUCUZDAyVFXUQStyTaQyIi8b/uzRA3A7lTTiAaOY3QuKA6tn2awCAhAikM45CTxrYHj5Duh9Z6H4Y0P3I0tf3Q2fGe8thTOT3+7dyhQRBEASxY0Giqw9hjIFzDpbZBjFBACthM8IBcMahZsZyAQBn23QzxQHomTUwGJsgXWTbfHOrMUBgHC6eWZMIiNvhvaD7YUD3I7sGuh8G/XE/jGhsPfvZSeHZBEEQxC4Gia4+pqOjA5VltYDAsF+XCx6d8hIIgiC6Iyro+MwfA3TqYEIQBEHsmpDo6mN0XYcAgIHBowvwaiS6CIIgekIEs8ILCYIgCGJXgxQBQRAEQRAEQRBEP0KiiyAIgiAIgiAIoh8h0UUQBEEQBEEQBNGPkOgiCIIgCIIgCILoR0h0EQRBEARBEARB9CMkugiCIAiCIAiCIPoREl0EQRAEQRAEQRD9CIkugiAIYoeAunQRBEEQuyokuvoJ2jwQBEGUDgeQELf3KgiCIAiif5C29wJ2RXQG6IxkF0EQRKlojENn23sVBEEQBNE/kKerj2GMIS4CtHcgCIIoHQ7ApW3vVRAEQRBE/0Ciq49RVRUCB0ROsosgiB0bHcC6gA+vNwxGo9+7XdcicQaBAgQIgiCIXRQKL+xjOOdQNYCRnCUIYgel1e3C8spyrKwoQ1SRAQCMcwzsimy3NTFQLixBEASx60KiiyAIYjcgIktYUVGO5ZVl2Oxx572+qjyI1NpGyDpJH4IgCILoa0h09TGMMSREwEX7FoIgtjM6gBWVZVhRUY7GgA+cFQ97Toki1gQDGN7eue0WaIM+MgmCIIhdGQqC62MSiQR0ZlTiIgiC2J4wAB8NqMX6oL9bwWWysqKs39dUjDRVLyQIgiB2YUh09TGcc7g0empLEMS2ZbNLxfuDBuDzmkrLxgCM2NxR8hxrg34kxO3ztcAAxKlPF0EQBLGLQqKrHxC4UYmLIAhiW7GqPIjP6qrxeU2V46HPiLb2kufQBQGryoJ9v7gSEKl6IUEQBLELs8OJrrfeegsnnngi6uvrwRjDggULHK9zzjFjxgwMGDAAbrcbEydOxIoVK3qc909/+hOGDh0Kl8uFcePG4T//+Y/j9Xg8jquuugqVlZXw+Xw47bTT0NzcvMXXQZKLIIj+IM0YlleU4eXhQx1eqRFtHQCAkEtFi9dj2csSSVRHoiXP/13F9hFdDIBKfboIgiCIXZQdTnRFIhHsv//++NOf/lTw9d/97nf4wx/+gIceegjLli2D1+vFpEmTEI/Hi8757LPPYtq0abj11lvx8ccfY//998ekSZPQ0tJijbn++uvxwgsvYP78+XjzzTexYcMGnHrqqX1+fQRBEFtDQhKxtGEw1pYFHF6pQDKJ2rBR8n1FTm7W8F6EGDb6fUiI2yfOjx5WEQRBELsqO5zo+vGPf4w77rgDp5xySt5rnHPcd999uPnmm3HyySdjv/32w2OPPYYNGzbkecTs3Hvvvbj00ktx0UUXYe+998ZDDz0Ej8eDRx55BADQ2dmJhx9+GPfeey+OOeYYjB07Fo8++ijee+89/Pvf/+6vSyUIguiWNrcL7w8agI8G1Fg2byqNgaEwAKMyoR3T2/VdRRC6zT5sc+kVCXVBwOqywJYumSAIgiCIAuxwoqs7Vq1ahaamJkycONGyBYNBjBs3Du+//37BY5LJJD766CPHMYIgYOLEidYxH330EVKplGPMqFGjsMceexSdFzAqFYZCIccPQRBEX/HRgBp8VleNL2oqHSLKLI7R6PchImc7f+zZ3gnGOWKyjA1+n2X3pVKWF6wUVpHoIgiCIIg+ZacSXU1NTQCA2tpah722ttZ6LZfW1lZomtbtMU1NTVAUBWVlZSXPCwCzZ89GMBi0fgYPHtzbSyIIgkBKMPK0XhzRgJCiWPaRGc9VTJbRGMiKqIb2Toi6DjCG78qzIYaedBr1XYYXLDc3qzfernVBP1LCTvX1QBAEQRA7NPStuhXccMMN6OzstH7WrVu3vZdEEMROyGa3C0v23APrg35HyODgUBfUdBqAM09L0XXs0dkFIL+3limuVpU5Qwz37EXTY00QsDbo79U1EARBEARRnJ1KdNXV1QFAXlXB5uZm67VcqqqqIIpit8fU1dUhmUyio6Oj5HkBQFVVBAIBxw9BEER3GP206vDGkEGWrSYSQyCeAGCIK7Nyusi5JZZWlwWRtjU4HpYJMWzxedGlyJa9ocMIMYzLUl6IYU0vQgwpr4sgCIIg+o6dSnQ1NDSgrq4Or7/+umULhUJYtmwZDj/88ILHKIqCsWPHOo7RdR2vv/66dczYsWMhy7JjzLfffou1a9cWnZcgCGJLeGePgfisrgbfVpUjJhlVAu1NjDvcLrS5XdZ4s/JgUhKxzuZ9GtIZgqQZvqzvbSGG7rRmhRja7QDQ0FF63unaoB8alRMkCIIgiD5hhxNd4XAYn376KT799FMARvGMTz/9FGvXrgVjDNdddx3uuOMO/POf/8Tnn3+O888/H/X19ZgyZYo1x7HHHosHHnjA+ve0adPwl7/8BX/729/w9ddf44orrkAkEsFFF10EwCjGcfHFF2PatGlYunQpPvroI1x00UU4/PDDcdhhh23LyycIYhfBzNN6aUSDozDFyEyzYs6YIzTQrDwIOEMGB3RF4EmmAADflWftss6xR2coY3eKK9M7tqo8sMUhhglJQpPPW/J4giAIgiCKI/U8ZNvy4Ycf4oc//KH172nTpgEALrjgAsybNw/Tp09HJBLB1KlT0dHRgfHjx2PRokVwubJPhr/77ju0trZa/z7zzDOxadMmzJgxA01NTTjggAOwaNEiR3GNOXPmQBAEnHbaaUgkEpg0aRLmzp27Da6YIIhdkU0eD5bsuQcAQNJ1y8vU0NGJt/WB0AQBKyvKsG9LGwCgLJFAZTSGNo8bKyvKMK6xCQzGk7GGjk58WVOF1WV+pBmDxI0AxD3bO/F9RRlafF6EZRm+lCHOhnaE8PYeRhXDZp8HA8JGc+RgIonyWBztNk9ad6wNBjCwq/SQRIIgCIIgCsM457znYUQphEIhTJ8+HXtVDAATBBza6YFX2+GciQRB9DGbXSqWV5ZjbdCP075eCZFzcABP7jsKYVWBoOu44LOvoWoaAOBfw4ZgVcY79bP/fo1AxpP1SV01lg0aAAA45esVqI3EAAAbfF78c9QwAMCklastAZcSBMw7YG9ogoDxaxqxz6Y2a03/GDUMzT4v9m/ahMPXb7TsywbW4RNb36/uKIvFcdaXy7finSmNiKjjP8EouK5j2uzb0NnZSTmyBEEQxC4FKQKCIIgtwP606r3B9fh0QA02e9xW1T+GbD6WLgiOEEOzCAYAfGcLJbSXdf/eFkpYF47AnfFi2fO0ZF3HoFDh/K2hGWG2uizgWOvQjtJDDDvcLnSoSs8DCYIgCILoFhJdBEEQJZISGFZUlOGlEUPx9h4DLfuIze3W/9tLuw+3iSt7npa9CIY9HyuQTKIqErXsplgSADS0GyJqTTAAzVbFsCGTp7XR70VcFC27Kbo6XSo6XKplr4nE4EqlS77mdVQ6niAIgiC2GhJdBEEQ3cCR9WqFVBWv77kH1gUDWFlRZpVwb2jPiqg1ZQEkM42FK2NxlMXiAIDGgA9RyUijlXWOIZkiGK1ej6Mh8rCMiAqrClo9bsvekPFQJSURG/zZAhdDOkNgnIMz5uitVRZPIJgpQ78mmPWyscwxpUL9ugiCIAhi6yHRRRAEUYDNLhX/HliHJ/YbhXUBo99VZSyOiqiRZ5WUREuQGM2KDSGjCYLV44ohK6I4Y47eV/ZKgt9VZL1dDTa7PSSxvisCJa3l2d1pDbWZQhn2+RmAIRlv15oyp3Aa0ovS8Rv8Pkd/MIIgCIIgeg+JLoIgiAwpISsu/ltbjU8H1CCiKFhRWW7ZRxQJGSwWSujM38qKqz1sIYZ2EVWWqTAIwCq2ARiNkk1htyYvT8uwrwv6HaGHpkeryedFwhZ6OLArDFZiDSVNELDRT6XjCYIgCGJrINFFEMRujcayeVpP7DfaEl72PK1VZUGkMiGDdhG1NpgNJdyjswtypjrh+oAPCdGwV8QTloja4PdZDZFlnWNQqAsAMiXfsx08TG9Xu9uFTlshC1NcRRRn6KEpxlKiiCafx7LXhaOQNQ2cMctbBwCqpqMuXHop+PW2YwmCIAiC6D0kugiC2O3ggCV+0gLDG0MHYV0wgIQkWflPA7oi8CaTxhhRwJpMKGEgmUJtRrCkRQFrMl4qiXMrbE8XBEce1Z62EEO7vcFWSXB1WdarZc+5socMDg51WR6qNbZcq/J4Av5Efv6WyLlV3TC3IMbgzq5u3yM76wOU10UQBEEQWwOJLoIgdhs6VAXLBtbhyX1H4Y2hgwEYXh97jpMZSijAWcJ9ZdHS7lmxZM/TstsdeVo2+5AOm4iy5V3VRGLwZHp32UWX3UO1Nrc4RochooqJq3UBvyMkcXBGjJVCm8dtiVSCIAiCIHoPiS6CIHZpYpJohfo1Bnz4ZEANwqqCdQG/JSTseVrrAj4r/2lYe9a+Nui3Qgnt4mpt0G+FHg4OdVl5WuuCfitUsTIWhy9heM3WB3zWeJemYUCXIaIa/T5rfoZsyKCRj5X9qDbFVYvXKYQGZ0IV290udClynj2qyNjsdln2qmjvSsc3+inEkCAIgiC2FBJdBEHscnAAK8uDeHn4UDy2/974trICgCGWBN3w9+gCs7xRe3R2WZUB7Y2MayIx+DNiSReyoYS+VDbEUBOyoYeyzi2RowkC1gWyjZLNUEJNEBw5UmYooZ5nN+Yx8rGy3itTjCHHXt8VhqBnBJ/N7k+mrNLx9vkZjIIapdJIeV0EQRAEscWQ6CIIYpeAA2jyesBhCIrPa6uwtiwAzhhWVJYBMMqrm6IIyIYMipxjaEd+KCFDaSGD9nysYvahHYXztOyhjfaQwUGhrIham5O/Zeaa2UMJZZ1jQEYI5ha+MEMMc3OzBvYixHADeboIgiAIYosh0UUQxE5NVJKsPK0Fo4djU6aq34i2DmvMJq8HHaoKwFl9cKPPi7BshOINt+VpbfD7EM+EGO6ZE2Johgw22MTSmrJsqfYhndk8rbVBP/TMmLpwts/WmmC25HtZIml5otYGs3lXsq7bRFTWzlA8T8ssmtEY8Fnntds3+ryOkvK98XR1ulREbBUWCYIgCIIoHRJd/URpHXAIgtgSYpJolUBPC8zK0wJgebWGtXc4elGtzPTIGtoRgpjxIIExrCo3vEsDu8K2EMNsI+OaSMzyLNlDBoOJpNUoOSWK2JDpZaXa8rTisoQmn2EXeTa/Ki5LljgEsiGDUUV2lII3xVVUkdFmy8cyi2DEZclhN8VVQpKwyZudZ0DY6MuVFgW02OyBRNLKNSuFjb7+7deVom8kgiAIYheFvuL6AQ5AYyS7CKKvWe/3WXlarw4bgpTAEEimUNeV7Tn1XXkZdBihhPbwue8yIYOKrmMPW7l0M2QwN8TQrDLI4AwNtFcfLBoy2GkPGSyQjwVY+WGGPbseez8te4VBeyjhwFAYyAhKe8igvTiGPRxQ1XRUZQSifTyDkQtWKhv6sUmyxoAkfSMRBEEQuyj0FdcPJETydBFEX8ABNPq9WJ8REG0el5WnlRJFqyeVvZFxVJGxMSMOhttCCdvdLmx2GSGG9jytjT6vFTZnDxm0VxlsaHeKKDN0zy6u7CGDzjwtu+jqssSSvdjFgK6I5X2zi6uKWNwqHW/P03JpGqotEeUsjmGKqNxqg6YAzRVO9V2lN0lu6kdPl8Y4FL3ncQRBEASxM0Kiq49RFAU6AyTOeh5MEERBOID/1NfiyX1H4YW9huE/A+sAGCLKGTJYBsAQUYXsDR0hq1ohkPVqDckJMTS9VINsJd+NUEJDuAyw5WMlpGzIYE0kBnfKEEVhVUF7RtQFE0kEMnlamz1uq4S7O50VSy1et5U3JnFuiZ9mr8cSewzZkMEmnxdpWz6W3W7P0zLnKWZv8Xoc8/RGdG32ZNfc14icQSbRRRAEQeyikOjqYwRBgEszNksEQZROTBLxeU0lWjxuMBiiwczTavF50KEq8KbSjnC4tUE/EqKQF0q4qiwIHUZ+lb1YhCm6FF3PGw8YFQAH2aobmmJM5NxR9dAMDTT6afVst3u1rPkZc3ipTLsuCA5v1MCubAn6Zp/HspvvQ26e1sAi9rpwBIxzaIKAFm92Hn8yaeWslYJ9DX2JSOEBBEEQxC4Mia4+Rtd1CLR5IIiSCSkyXhk+FI/vtzfe3WMgvqquBOAMGQSyOVn2KoO6IFhl2e0hg3FZskIM7SXcN3vc6MwIOXso4Qa/z2pAPDSnhLsVSthdyGABu12k2cXV4M5wQbtdBNpDAweGIgXtdeGIVVLebi+LJ6y8LnvhC0XP5nVttIk6BqAuHEWpNHv7R3QRBEEQxK4Mia4+RhAEqsBFEN3AAWzwefHGkEEIyzJUTcP6gA96phT79+VBpBnLNDLOxptZIYO2BsfmeMBoPmwPMTTtQztCVh4VkPVeDbHZdYFZBSbseVdxWbK8QoNDWXu722WFDA4KZUvE20MD67uyomh9IJsHVhuJWiGM9lLwlbG4JZbsjYh9qZQVqmi3yzq3QhVzRZTpBcvtrTXACj30FLSXQn/lddGzKoIgCGJXhuRBH5NOp5EUjEpcBEE4+b4sgCf3HYV/jhqGb6orsLIiCFXTHV6kpCRiXdAPVXNWGTQLYbhyQgbXBXxWiKFdPKwuMwpbeNJphyfHFF2edBo1kazdLMph2GOW3fReudOaY7wZMqhqumXXBQGNGQEk67p13qQkWiXcRc4xIGysP6wqCGU8b3ax1JaTO2Ve7yaPx+oTBsCWB+bM3zL7ezX7PI5+XXXh7Hi7vTZSuqerxetGf6ReaYyT8CIIgiB2WUh09THpdBqKTiXjCQIw8rS+qK7ECyMboDEGWdetPC0AWFFZDgAYYasyCADfZbxUw2yhgUDWe2UPJdQFAWszgqnBVvI9oihWLyx7yGCTz2sJmiE5oYHmX+0eRUq+FyvhPrjTHkpoK+3eVThkcJBtHrs3yj7entdlikldYI58rAG2/C173y9T7KVEEZttfbzsIrDdZq+MxizvW0+kReexfQWHUfmVIAiCIHZFSHT1A7JuVOIiiN0RU7i8vUc9Ht9vb7wzZCAaA36sDfoxMBS2qv0BhkenQ1UxuLPLqg4IGN6oNGMY0hFyhBhmQwadoYSm98ouroBsYQt7aXfOmCWk7B42I5TQEC72fKxWrwcxyVADdnHV6PdZHh+7iGoMFBZXdru9YmCjTVzZ7XYxVsxeF45a74M9ZLAyGoOsaRl7dn5POg1/wghVtOdmCQCqo73zdvU1EmfQ6WOTIAiC2EUh0dVPUCUuYncim6c1EAtGDQMHoKY1K08LAFZUlEEAMGyz03u1siIIiXOHYEqLRoihousO79JmjxsdqgJ3WrNC5QDDG6UxBn8yhcpoNjTQDBksiyesvChzPGDkUZl9sIBsyGB1JNtkGMh6r2oiUUscJiXR8jpVR6OWyGl3u6y+X9WRqEP8mCGAldEYlHS2ibH5cWEvgmEXS75UCv5EMmPPiiVF11ERi+eNFzJrzR0PALXh7u2l0NIPxTQYAJfW4zCCIAiC2Ckh0UUQxBaTZgxpxvD0Pntl8rQq0ezzotXjzgsZXFMWQFIQMKzdabcXwihozwkxLOTVSomiFY5n9161et0Iy3JeCXezsAWD06tlhgwKQF7emGm3l6w3vVcidxajML1RArJ5VJogWN4lAcCAjMiJKjK6lPy8rlaPy6qoCNjzsQrnaTX5vI6cKFNE5QokM8RwU469N3ld9lDGvoQqvxIEQRC7KiS6CILoFWae1t9HDcfLIxogcQ5/Tp+nFRVlKI8nHF4nTRCwpiyAunDU0Rdqsy3EUNKyro41QT80ZoQGOkMJsw2O7ZheLXsoIQCsCxoCyC664rJkFbawhwy2eD2W0LH362oMZL1RxfK0iuVj2Uu+byyQp5Vrt4p+MGf+limu0qKIVpvoMcVVXJYs8QZkRVTIpVrhkUA2jLDdpTpEXXUvRNdmt8tRuIMgCIIgiO4h0UUQRI+kGUNElrDJ47bytFp8HmzwexGWZYxo63CM/64iCA5gWI636/vyIBiAhvZQjj0AiXOHMEpKEjb6fHmhhM0+D+KiiLJEEsECIYO5oYFmyGB9VxiiLT/MDBkc2BW2SsFzxiwvlb1vVkRRrP5ednuzz4N0Rnw487SyYsysVAg4+2YNsF2T3W6/1iZfATEGp/fK7qGyNy62V1q0j6+Kxo08OcawyZO1+1JpR6hld+iCgLZ+KKZBEARBELsqJLoIgigIB7DR58GbQwbisf33xruD61EZjUHVsoIGjGFlRRANHc6eWhFFQZPPk1d9cG3Qj5QgOKoPAlnvVW4hDDOU0C7GihXCCLlUdKgKBDi9VGYoocS5Q9CYjYndac1qGgxkBVMgmXLkgZmhhOW2vCtNECxBY+RpadZazLyuKltlQHsJ96pozBKBdrFUGcuOt+ddlcfiVn6YfXwgkbTWYy+O4U5rVtEMu+gSOUdlJg9sU05BDPv70BOt/RRiSBAEQRC7IiS6CIJw0KEaXp0vqyuxcNRwfF1diaQkYk1ZAClRyCuE8V1FWV5PLQBYVRZEMJHMCzFcG/SjLhxxeKNafB5EZAlDOrscoYRryowy7rmhhKbosudjAdmcLHvxDaNHliE67NUEm71eq5HxQLuXqkiVwY0+w27PuwKyoYQCgNpIvpdK5Fmvk72Eu8i5ZW93u6wy9iLPhgC22PK3BBhePGPtWRHFkJ0/V0SZ/cZyqw2a8+TmZlX3SnSRp4sgCIIgSoVEF0EQtjytYXhm31H4pK4aQzs6rbA7wBBMq8sCGJ4TMrjJ60FIkfO8V9+XGyGGhQphCHD2wgKMnCxVc4YSdqkqOlwqyuMJ+BLZPDDTezWgK+LoL2WFDOaIMdOrZRddusAsT5J9fLvbZeVA5Yor892wizF7CKAjT6uEkEF7xUBnaKAhflKiiA6Xmh1vy9OyN082xVKrx+1ozG7maW3yeBxFNuzj7fTG09VGni6CIAiCKBkSXQSxm6Ixhu/LAmh3qVg2sC6Tp2UIgu/Ly+BOaw5xAQDflZehNhJ1CCAAWFUexJBOZ0+tsKqg1ePOCxlcGzQEUyE7gDyP2dqgP6/6YFyW0OpxQ+LckTPV6DfKsvtSaZRnQugMuyG67KXagawYs/e7ArLVB+15V1FFRiiT15WbY2ZedV0REWXPu2oqYreHABbLx7IXu7B7tczxmiCg3ZX1QJniKi5LiMiyZTfFVSinmEZvRNdmtwtUbJAgCIIgSoNEF0HsZph5Wn/bfzReHT4UX1ZX5pV3T0oi1gX8eeXd1wf8SIpiwfLuqqY7KvgBhlerMha3ekwBQEKS0OTzYlAo7BBp6wNGr61c0WUWwsgNJSzkvUqLohVKZy940ZQpeGGUfM/3Rim67hAcpt2fTDkEpumlqrDlV9lDBqujWfHW5nZbRTZqixTBcIqrfBGVb4/Z7HYxlrXbvVf2a7KLtIpYHIKeXaeJL5mCahOl3ZESRUe1RIIgdh7eeOMNMMbwxhtvbO+lEP3Af/7zHyiKgjVr1mzzc7e1tcHr9eLll1/e5ufe0SHRRRC7AR2qgg/qa7HZpeKD+rpMnpZR6OG7iiDquiJ5letWVgSxZ3unwwOkCwxrgv68UMJmnxdRSSpYCIOhcE6WousOT1JaFLDR50VFLO4oKb/R70WaMdR3hR1ryYYSOoWe6dWyhwbqgmB5nuzn3OT1WHld9UVLuNtFWrbPVo3De2WMl3VuCR1dYJbQcWmaVWnRHhroTaWta23xZkMAfckU3KmUtUYTbyprt4srTzpbedAurlRNt4pp2KsNipyjPB7Pm4cBqIxmPYQ90UZ5XQSxQzN37lzMmzdvey9ji3jqqadw3333be9lOHj44YcxevRouFwujBgxAn/84x9LPjaRSOBXv/oV6uvr4Xa7MW7cOCxevLjg2Pfeew/jx4+Hx+NBXV0drr32WoTD4YJjC3HTTTfh7LPPxpAhQ0o+pq+orKzEJZdcgltuuWWbn3tHh0QXQeyi6AC+qK7EPzJ5Wh/V1+LbqgqM2NzuGBeTZWz0+/K8WmvKAlA03ZGnBBherdpw1FEIAzAEVq64avMYzYlz87esQhi5Xq1MKKHde6UJApp8XqianiN0DO9VZSzuWItZCCM3NNL0XtntnGXzuuziarPbhWRGjDlDBnsu4V4sNLC43RBpCUlCl2KEADJkvVdttp5YDFnvVW4hi6qieVqGiMrNwaq07M55KmKli67NVDaeIHZoiomuo446CrFYDEcdddS2X1SJ7Gii63//939xySWXYMyYMfjjH/+Iww8/HNdeey3uuuuuko6/8MILce+99+Kcc87B/fffD1EU8ZOf/ATvvPOOY9ynn36KY489FtFoFPfeey8uueQS/PnPf8YZZ5xR0nk+/fRTvPbaa7j88st7fY19xeWXX46PP/4YS5Ys2W5r2BHZ6UTXbbfdBsaY42fUqFHdHjN//nyMGjUKLpcL++67b57Lk3OOGTNmYMCAAXC73Zg4cSJWrFjRn5dBEP2Cmae1aNgQtLld+G9tlUMorKwIoqHdWd4dMLxduVUJU6KI9QFfnldrfcAPnbE8r9aasgB8qTSqIs68oLVBP+pzCl5s9rgRliVHlUFj7vyQQbu9kPeKwem9avF6oDEGl6ahwh4ymPFeVUZjVmggkK0EaBddnDHLM2a32xsKFy+C0bPosnujnCGAnjy7LghotxXTMEVUl6oiYSumURkzxufmWlUWEWmmuMoVTpW9EF32/DGC2FGJRCI9D9rNEAQBLpcLgrDTbQO3C7FYDDfddBMmT56M559/Hpdeeikee+wxnHPOObj99tvR3t7e7fH/+c9/8Mwzz2D27Nm4++67MXXqVCxZsgRDhgzB9OnTHWNvvPFGlJeX44033sDll1+OO+64Aw888AAWLVqEV199tce1Pvroo9hjjz1w2GGHbdU1bw2jR4/GPvvss9N6WfuLnfKvbcyYMdi4caP1k/uUwM57772Hs88+GxdffDE++eQTTJkyBVOmTMEXX3xhjfnd736HP/zhD3jooYewbNkyeL1eTJo0CfF46ZsPgthemP203tpjIB7L5GmtLg9iZWVZXq5WRFHQ7nbliZ1VZUFUR6J5IYaryoJ54iotClgf8GFIjveq0e9DmrE8r9a6oD+v4AVgiLeKWNxxzjaPGzFJzAsZzDYsdm6eCoUSGr2zDFFjF2PNXi80lintHs4PDXSnNUdfLlMwVcTiWcHImGU3y7oDQKdNjJWSd2Uv1W4XY8Xysex2ewl+e8ig6bnKzbUyRVSXqlqhlIbdmKfd5YJdglfEelNMQ+15EEH0IY2Njbj44otRX18PVVXR0NCAK664AslMmO68efPAGMObb76JK6+8EjU1NRg0aJB1/Ny5czFmzBioqor6+npcddVV6OjocJxjxYoVOO2001BXVweXy4VBgwbhrLPOQmdn9gHU4sWLMX78eJSVlcHn82GvvfbCjTfe2OP6SzkukUjg1ltvxfDhw6GqKgYPHozp06cjkUjkzffEE0/g0EMPhcfjQXl5OY466ihrYz506FB8+eWXePPNN62H1EcffTSA4jld8+fPx9ixY+F2u1FVVYVzzz0XjY2NjjEXXnghfD4fGhsbMWXKFPh8PlRXV+OXv/wlNNsDrWIsXLgQkydPtu7hsGHDcPvttzuOPfroo/HSSy9hzZo11tqHDh1adM4JEyZg//33L/jaXnvthUmTJvW4ru5YunQp2tracOWVVzrsV111FSKRCF566aVuj3/++echiiKmTp1q2VwuFy6++GK8//77WLduHQAgFAph8eLFOPfccxEIBKyx559/Pnw+H5577rke17pgwQIcc8wxYIw57Iwx3HbbbXnjhw4digsvvND6t/k39M477+Daa69FdXU1ysrKcNlllyGZTKKjowPnn38+ysvLUV5ejunTp4Pz/LJKxx13HF544YWCr+2uSNt7AVuCJEmoq6sraez999+PH/3oR/if//kfAMDtt9+OxYsX44EHHsBDDz0Ezjnuu+8+3HzzzTj55JMBAI899hhqa2uxYMECnHXWWf12HQSxNXSqCpZXlmNFRRlCrvzN78qKMkxevgof1dc67N+Vl2HP9k6sKct+oMdlCc0+Lxo6OvFlTZVlX10WwFFr1qMqEkOrzTuzNhjA4es3QtB16JmNfFoUsNHvxeBQFz62nbPR74PGgMGdYawLZs/ZGPBhVFs7BnaFsaKy3DF+eHsnymNxtGdExSavG0lBQG0k4jin6b3KDYHc6PNiQDiKunAUX9bAWl+b242aaAx14QjWZ0IczeqDRp+tqPVeNtnyt6qjUWzMCLwWrweDQ2FLpJnjTXtZPAFZ0wzxoyqIiyJcmobKWAyMc3DGHJ4uew6V3RuVJ7ra2jP27Pg2jwv1GWFp91C1eVwIZDah9nDBzW4VtRnxZ1Z3TIsCulQFwUzBkPJY/sauGB0u1XrvCKK/2bBhAw499FB0dHRg6tSpGDVqFBobG/H8888jGo1CsT1suPLKK1FdXY0ZM2ZYnq7bbrsNM2fOxMSJE3HFFVfg22+/xYMPPogPPvgA7777LmRZRjKZxKRJk5BIJHDNNdegrq4OjY2NePHFF9HR0YFgMIgvv/wSJ5xwAvbbbz/MmjULqqpi5cqVePfdd7tdfynH6bqOk046Ce+88w6mTp2K0aNH4/PPP8ecOXOwfPlyLFiwwBo7c+ZM3HbbbTjiiCMwa9YsKIqCZcuWYcmSJTj++ONx33334ZprroHP58NNN90EAKitrc1dlsW8efNw0UUX4ZBDDsHs2bPR3NyM+++/H++++y4++eQTlJWVWWM1TcOkSZMwbtw4/P73v8drr72Ge+65B8OGDcMVV1zR7fswb948+Hw+TJs2DT6fD0uWLMGMGTMQCoVw9913AzBykjo7O7F+/XrMmTMHAODz+YrOed555+HSSy/FF198gX322ceyf/DBB1i+fDluvvlmy9be3l6SOPR4PPB4jO+BTz75BABw8MEHO8aMHTsWgiDgk08+wbnnnlt0rk8++QQjR450CCkAOPTQQwEYIYGDBw/G559/jnQ6nXceRVFwwAEHWOsoRmNjI9auXYuDDjqox+vrCfP3f+bMmfj3v/+NP//5zygrK8N7772HPfbYA3feeSdefvll3H333dhnn31w/vnnO44fO3Ys5syZgy+//NJxT3ZndkrRtWLFCtTX18PlcuHwww/H7NmzscceexQc+/7772PatGkO26RJk6wPrlWrVqGpqQkTJ060Xg8Ggxg3bhzef//9bkVXIpFwPHkKhUJFxxJEXxAXRXxXEcTyynJH2GAhIoqCpCiiIhrDZpunZFV5AGM3NEPQOXSBOexDO0IO0RWXJbR4PRjSGXKIrjVlfhy5thH1XVnxAhiVBg9bvxFKWkMy0+sqKYnY5PFgUIHqgxxGIQy76NqQEV31XWFLdBm5V17sEepCdTRmXbsZSlgRizvOaXivNjlCAw27BzXRmKNUu9kLqyKeQG04aq3F7G1lNB+OWaLL7qWqjsYs0dXqcWNwKGzlXZnjWz1uDOoKQ9Y5yuIJtLtdiCgKYpIId1qzimBEFdlRSdCfTFnizR4CGEgkIOo6NEFwjA/Gs/bNbhcaMh5KfyIJSdORFg27Kbq8qbT1nrW7VEt0KboObzKJSAmVCXXBKdgIoj+54YYb0NTUhGXLljk2pbNmzcp7ml5RUYHXX38dYiYEd9OmTZg9ezaOP/54vPLKK1ZY3ahRo3D11VfjiSeewEUXXYSvvvoKq1atwvz583H66adb882YMcP6/8WLFyOZTOKVV15BVVUVSqWU45566im89tprePPNNzF+/HjLvs8+++Dyyy/He++9hyOOOAIrV67ErFmzcMopp+D55593hAma78WUKVNw8803Wx6r7kilUvjVr36FffbZB2+99RZcmdDh8ePH44QTTsCcOXMwc+ZMa3w8HseZZ55pFUu4/PLLcdBBB+Hhhx/uUXQ99dRTcNs+uy6//HJcfvnlmDt3Lu644w6oqorjjjsOAwcORHt7e49rB4AzzjgD11xzDZ544gn89re/texPPPEEvF4vTj31VMt24IEHllTV79Zbb7U8Qxs3boQoiqipqXGMURQFlZWV2LBhQ7dzbdy4EQMGDMizmzbz+I0bNzrsuWPffvvtbs/zzTffAAAaGhq6HVcKtbW1ePnll8EYw5VXXomVK1fi7rvvxmWXXYYHH3wQADB16lQMHToUjzzySJ7o2nPPPQEAX331FYmuDDvdA8px48Zh3rx5WLRoER588EGsWrUKRx55JLq6ugqOb2pqynuyU1tbi6amJut101ZsTDFmz56NYDBo/QwePHhLL4sgimLP03ps/9F4e8igHgWXyXcVQQzLycmKKApCLjUv3G91WQADuiKOfCfAyMnKDRmMKAraXWpeGfd1QT8EIK90fGPAh/J4wqq8BxgFPDpcqiM0EDCaEAMFvFcF7JogYJPHnVdNsNlnCCZfMuUIXzTD/Wpy8s7MnCx7yGBczha2KNYfq5RS7XbvlTM00ObtyoT0RRXZasxsryRoz9MSYM/Hyno4BQBlmfBIu0gz7MZ4ew4WA6wKhu05eV299XYRRH+j6zoWLFiAE088Mc8LACAvlOrSSy+1BBcAvPbaa0gmk7juuuscAuXSSy9FIBCwwsOCwSAA4F//+heits8DO6bHZ+HChdBz8mO7o5Tj5s+fj9GjR2PUqFFobW21fo455hgARpgbYISQ6bqOGTNm5OVl5b4XpfDhhx+ipaUFV155pSW4AGDy5MkYNWpUwfC53EINRx55JL7//vsez2UXXF1dXWhtbcWRRx6JaDRqiYbeEgwGcfLJJ+Ppp5+2RKemaXj22WcxZcoUeL3Z78wnn3wSixcv7vHHLiJisZjDk2rH5XIh1kNYdiwWg6rmf1aa77V5vPnfYmN7Ok9bWxsAoLy8vNtxpXDxxRc7fpfGjRsHzjkuvvhiyyaKIg4++OCC991cQ2tr61avZVdhpxNdP/7xj3HGGWdgv/32w6RJk/Dyyy+jo6OjpDjXvuaGG25AZ2en9WPG5BLE1sIBNHnz87T0XiY9ryoLYmiO6AIMgZWbq9WlqgipSl4Ri7XBAGoisbxqheuC/ryx7W4XIrKUl5O1PuADQ35O1ga/F4GcXlgdbhdikujIxwKy1QftVQMBFCx4kZAkdKoKGAo3IFZtJdwBw6sFGKF79iIjm6z8rewXnemlMsYXztNyhgDaxZUzBNCy28fbNiRmflVclhCVs4EJZmhge07RjGLFMcoz19qek4Nliqv2HOFUFifRRexYbNq0CaFQqOQn5rlP+k3Pxl577eWwK4qCPffc03q9oaEB06ZNw1//+ldUVVVh0qRJ+NOf/uTI5zrzzDPxgx/8AJdccglqa2tx1lln4bnnnutRgJVy3IoVK/Dll1+iurra8TNy5EgAQEtLCwDgu+++gyAI2HvvvUt6P3qi2PsDGN7AXM+Qy+VCdXW1w1ZeXt5jQQnACLM85ZRTEAwGEQgEUF1dbXmz7O9zbzn//POxdu1ayxv02muvobm5Geedd55j3A9+8ANMnDixxx/TUwMYQjGZLOzRj8fjDiFZCLfbXTAnz6wdYB5v/rfY2J7OY9IXeVS5EWTmA4lcB0MwGCx43801bMlDgF2VnU505VJWVoaRI0di5cqVBV+vq6tDc3Ozw9bc3GzlhJn/7W5MMVRVRSAQcPwQxNbQmemn9fQ+e2HB6OH4qqYSCWnLo4DDqoK0IDgKRACFy7sDhb1arV43YpJUIDzQKIRh914BRnhgrqerxWuUd8/1rm3MxOjnCqwmnxfeVNqx7k1eNzTGUJtTicysPmgXV+Y5AacHLORSLcFUqJqgyLlDGJneq0AiCSWd9QCaAssuukIu1SozX1mkCIZ9vF0YOfOu7PZEt/aUKCKc8cYBWTHWqSqO4hiWSMupNmiKq86tEF2dBZ7IEsT2ptTNaSHuuece/Pe//8WNN96IWCyGa6+9FmPGjMH69eutud966y289tprOO+88/Df//4XZ555Jo477rhuc4VKOU7Xdey7775FvS+5hRy2F3YvYm/o6OjAhAkT8Nlnn2HWrFl44YUXsHjxYqvsem88h7lMmjQJtbW1eOKJJwAYoYV1dXWO9BHAEPBNTU09/tj7Yg0YMACaplmi1ySZTKKtrQ319fXdrm3AgAFW6KAd02Yeb4YVFhvb03kqKysBoCTxa1JMoBW7x4XsheYw19CbENxdnZ1edIXDYXz33XcF418B4PDDD8frr7/usC1evBiHH344AOOpVl1dnWNMKBTCsmXLrDEE0Z/ERRFfVlfgH6OG4elMP61ChTG2lLUFvFrtbpcRXpZTHnxd0I/BnfkNGNcHfHlerY0+L3TGCjYnLssJJTQqCnrye2f5jTDA3FBCs6KgXUgZOUyuolUGq4uEDNbkiDFTBNnH23thFRJMDNkQQCDrvXJpmqORsymMyuMJCLrxJdSpqtbc9ve7rajoyt77clsFVbtgctqz402xpAsCQqqSZw+rCtK2p46mvcOlOjxmvRJdrp5zvwhia6murkYgEHBUHu4NZpPYb7/91mFPJpNYtWpVXhPZfffdFzfffDPeeustvP3222hsbMRDDz1kvS4IAo499ljce++9+Oqrr/Cb3/wGS5YsscL/itHTccOGDcPmzZtx7LHHFvS+mJ6oYcOGQdd1fPXVV92er1QvQ7H3x7T1VZPdN954A21tbZg3bx5+8Ytf4IQTTsDEiRMLhsP11kMiiiJ+9rOf4fnnn0d7ezsWLFiAs88+O08kHHLIIRgwYECPP7///e+tYw444AAARhimnQ8//BC6rluvF+OAAw7A8uXL83L/ly1b5ph/n332gSRJeedJJpP49NNPezyP2UJp1apVBV8vlIqTKyT7CnMNo0eP7pf5d0Z2OtH1y1/+Em+++SZWr16N9957D6eccgpEUcTZZ58NwHAv33DDDdb4X/ziF1i0aBHuuecefPPNN7jtttvw4Ycf4uqrrwZg/FFfd911uOOOO/DPf/4Tn3/+Oc4//3zU19djypQp2+MSid0AjTGsKgvgX1uQp9Vb1gQDeeXdAdOr5fwA3ujzQtXSeWKsMZDvvUqLRmn2XCG1we81emcVyMkqiyccYYoRRUFYkfMKXljeqyKhhHYhFVYVRGQJLs0pxloLeKOAwl4qey8se2jgJkep9sKCqTKaHzIoco5gwhRAzArB86bSUNPG9Xe4sqGBZfEEWOZJYXsRMWYPDbTnXHU4xFhhu11EdRYQaQlJQlzKbkyCBUJbikGeLmJbIAgCpkyZghdeeCFvQwr0HE41ceJEKIqCP/zhD46xDz/8MDo7OzF58mQAxkPXdNoZSr3vvvtCEAQr5Gvz5s1585ub4UJhYSalHPfTn/4UjY2N+Mtf/pI3NhaLWZUYp0yZAkEQMGvWrDzvkP36vF5vXkn8Qhx88MGoqanBQw895LiGV155BV9//bX1/mwtpgCyrzGZTGLu3Ll5Y71eb6/DDc877zy0t7fjsssuQzgcLliEY0tyuo455hhUVFRYBSRMHnzwQXg8Hsf709raim+++caRE3j66adD0zT8+c9/tmyJRAKPPvooxo0bZ4XsBYNBTJw4EU888YRDID3++OMIh8M9NkgeOHAgBg8eXPBvBEBei4BXXnkF8Xi8X8q6f/TRRwgGgxgzZkyfz72zstNVL1y/fj3OPvtstLW1obq6GuPHj8e///1vK7Z47dq1jqTSI444Ak899RRuvvlm3HjjjRgxYgQWLFjgiAufPn06IpEIpk6dio6ODowfPx6LFi1yJJMSxNbCYYiJ5ZVl+K6ibKvCBntDq9cNfyJbxtxkXcCPMZva8FldNi5fFwRs9HkxMBR2bP4b/T4cnVzvKJEOGKGEw3J6gYVcKiKyhAHhCL6vKLPsTZlGxrWRqKNcfbPXgz3bOx3ry4YSFgoZbENNJIqVtoqHmzweeDtDqIk4qwnqAFRNd6zbFGOVOQnJbR43qmJxhxiLyxKikgRPOp2Tj+XM01qbuZ7ckEHzPdzsdqEyFs94FxNo8ktGqXZFRiCZgsQ5/IkkQi4V7RkxxgC40hrUdBoJSXLkTvmSSatSoV2MBRJJqyx9p0sBOrN2cA4wQwCa1+JPZseHVBXutPF+e5MpR2n+7ogoMjTGIFIvFqKfufPOO/Hqq69iwoQJVjn1jRs3Yv78+XjnnXccJc1zqa6uxg033ICZM2fiRz/6EU466SR8++23mDt3Lg455BBrc75kyRJcffXVOOOMMzBy5Eik02k8/vjjEEURp512GgCjWuJbb72FyZMnY8iQIWhpacHcuXMxaNAgR8XBXEo57rzzzsNzzz2Hyy+/HEuXLsUPfvADaJqGb775Bs899xz+9a9/4eCDD8bw4cNx00034fbbb8eRRx6JU089Faqq4oMPPkB9fT1mz54NwCjb/eCDD+KOO+7A8OHDUVNTYxXlsCPLMu666y5cdNFFmDBhAs4++2yrZPzQoUNx/fXXb+ltc3DEEUegvLwcF1xwAa699lowxvD4448X3PSPHTsWzz77LKZNm4ZDDjkEPp8PJ554YrfzH3jggdhnn32sgiSFSqf/4Ac/6PW63W43br/9dlx11VU444wzMGnSJLz99tt44okn8Jvf/AYVFRXW2AceeAAzZ87E0qVLrb5o48aNwxlnnIEbbrgBLS0tGD58OP72t79h9erVePjhhx3n+s1vfoMjjjjC+j1fv3497rnnHhx//PH40Y9+1ONaTz75ZPzjH/8A5zzPW/j111/jJz/5CU466SRs2LAB999/P4LBIN577z08/fTTlgOjL1i8eDFOPPFEyumysdOJrmeeeabb13NVPGCUEu3u6QBjDLNmzcKsWbO2dnkEkUenqmBFRRmWV5b3adhgb9jg92NgKIzV5UGbzYdjvl9rbd5NTK/WF7XZOOywqqBLUVDfFXFcw0afFwdtbLFKnps0+bz5BS+8XnAYBS8cosvnwfD2TtREomgMGOXnzbLnFbG4Y/PfUqCwBWCItKGdIVRFY1hZWWbN0Z4RO1U5pd2BfDFmeq8qcrx8bR4XPKGwo2mwGTIocu7wCtpDACticXxn2e3epTiaMpUY290uBDLVFcsza0lKImIZocdgeKOafU7RJcAoEb/Z43Z4mkSbeLOPlziHL5lCWFUcYYci5/Alk+hSVXSqiiVyBRhCrcPd84Mnzhi6FBllVDae6GcGDhyIZcuW4ZZbbsGTTz6JUCiEgQMH4sc//rHVT6k7brvtNlRXV+OBBx7A9ddfj4qKCkydOhV33nknZNn4/Np///0xadIkvPDCC2hsbITH48H++++PV155BYcddhgA4KSTTsLq1avxyCOPoLW1FVVVVZgwYQJmzpxpFRsoRCnHCYKABQsWYM6cOXjsscfwj3/8Ax6PB3vuuSd+8YtfWAU1AEPENTQ04I9//CNuuukmeDwe7Lfffo7CETNmzMCaNWvwu9/9Dl1dXZgwYUJB0QUYTY89Hg9++9vf4le/+hW8Xi9OOeUU3HXXXd0K2t5QWVmJF198Ef/v//0/3HzzzSgvL8e5556LY489Nq+B8ZVXXolPP/0Ujz76KObMmYMhQ4b0KLoAI+Jp+vTpeQU0tpYrr7wSsizjnnvuwT//+U8MHjwYc+bMwS9+8YuSjn/sscdwyy234PHHH0d7ezv2228/vPjiizjqqKMc4w466CC89tpr+NWvfoXrr78efr8fF198sSWke+LnP/85HnjgAbz77rt5DwGuuOIKrFu3DtOmTUNZWRnuvPNOSJKEadOmYcmSJX0mur755ht88cUXuO+++/pkvl0FxqlVdJ8RCoUwffp07FUxAEwQcGinB15tp4vgJPqAhCjiu3Kjn5a5wd6eDG9rR104ineGDHTYp3y9Eh8MrLXEDmCURz9h+So8esDegO0J1Q9XGdU5lzZkKxfJmoaLPvkSi4cNwSqboNu3eRMOX7cRjxw4Bmmbd+3ML75FVJbwwl7DLFttOIJTvvkOywbW4ZMB2R4oR65ZjzGbNuPvo4ajxZfdUP384y/AwPHwgftY6xvSEcKPV67Ger8PL+6VrTh1zPdrMXJzBz4aUIMPBtY55lB0HYuGDbGE6MBQF05cbsSgP7nvXujKiJnD123A/s2tSAkCHj4o6yH/6RffoiKeQKvbhefHGBshVyqNCz8zciy+Kw9i8TAjD2LPzR04/vu1AIDPaqvw/uB6x9wA8P6gAZbX8aRvvrOaHi8dOgjfVhlPUS/65AuomhFK9K/Me+5NJnHef7Nlll8aMRTrggHUh8I4aXm2jO8LIxvQGPBj1KbNOHrN+jz72A3NOGRDtqDQy8OHWh68npi8/HsMDuXnApZKRNTxn2AUXNcxbfZt6OzspMJEBEFsEffffz+uv/56rF69umgP112dY489FvX19Xj88cctG2PM0XusP7nuuuvw1ltv4aOPPiJPlw1SBATRR9jztP62/2i8NXTQDiG4AKPSYG7BC8DIv8rNyWr1uMFyqvgBhlcrN0/LbNybm5PV4vVAQL5HqtnrMXpk2Z71tHrc0JizFxZgz71y2ts8Lsg6d+QvmV6qQiGDgLM4BpDNmyqlaqDpvZJ13VHa3hwfTCSs64nLEuIZkenwgLkL51d1FMivyrXbS9vbvVqmPaIoSNmaXAfjxhrtHi0gE2LYjb0rpweNv0h55ELkHrul6PTdTBDEVsA5x8MPP4wJEybstoILMEJxn3322ZKaQPc1bW1t+Otf/4o77riDBFcOO1144c6CRr9nuwUchsBYXlmG78rLEJd3zD+puCxBZ8gLA9zg92HsRme7BM4Ymn0eDOiKOHKXmnwe+JNJuFMpxGRnKGFuwQtDSDHUhqPY6PdZ9k1eN0a1taM8nrCEiCYIaHe58gRamyW6nOKv1ePGgHAUldFszlRYVRAXRbjTmuMaNxcJGdzsdqE2EnXYY7LRmNid1lAei1shkO051QTDGdFiCiNZ5/AnU+jK2NvdKgaEowja86syJdztDYztcwA54spWETBoE3ohVUFN5n2y27sUBRWZ402xFM7JtepJdBWzl0KXuvWiiwOIb1kVaoIgdnMikQj++c9/YunSpfj888+xcOHC7b2k7cq4ceOK9hXrbyorKx3l9oks5OnqB1ICoDGK2tyVCSkKPhxQg2f22Qv/GD0cX9ZU7bCCy2Sj34f6nAqEzT4PKiMxR0NgwPBq5Rax6HC7kBDFPIHV4nWjKhqzSqQD2fLueblXnsLl3Vs9bviSKauyH2CWcc+vPpjNvXLaN1vervzy6/5kCrKtf45pzxVjpgiye9HabeXUi1UNLCvgjTLzpQCjQInZT8ufSFrvt8NzZasYFirg0QKclQcDjvGKzZ75os3kWpn4M3aj8AXy7F1qdiwA+JLO/mvdYT/PlpJmHAJ9bBIEsQVs2rQJP/vZzzB//nzceOONOOmkk7b3kggijx17l7gTIkkSkgLg5uTq2tXY0fK0essGvxcDu8KOqn8pUUSH24WaSMxxTc0+D0a15pc3bvG6URuJOgpytHg9kDhHRSyOVm/WM9bqcec1VG7zuKDDDAMsd4wd1daOqmjMyi/TBQGdqoryeNzyGBlzmNUH871X9eEIymNxrAsac0QUBQlRhKppKI8lrNwwM2TQ7o0y7QPCUZTZ+mAlJckqbOH0Utm8UfGEdU5nSfaklRvW6VIRSKYgwBCBnS4VUUVGSmCQdQ5PKg1J05EWnT227GF+9jA+f44HzMTuoepSFavAhWnnjCEiKwhk5vVnxFVENsSYyPPn74lIH4guBkAt3leWIAiiKEOHDu2Xsue7EvT+bH/I09XHSJIERc9uXIidGzNP69U999jh8rR6S5PPi7qcnCzAEFiFSrN7kylHg2PTnttsuMOlIikIeblXm7xu+JMpKDbvlSYI6HCp+d4rT7HKgW7IOncICbOkem4vsWLeK7NyoF1ImR4ts9pfrj23ObBpt3ujOm0eMIfdIYCKeaOydlNIMWQFVkhVrLlVTbc8gPY5fMmU1dsrrNjtRUSa3W7zalnjGUNEtttL93SF+0B0iZyBHlURBEEQuyrk6epjdF2HbCZvEDslRp6WG8sry3foPK3eElVkiJxDSWtI2hrhmn2ygGy/rpQootOloiYSw5qy7IZ6k9eDfVtanRMzhjaPEUr4jc3c6nGDwfBI2fO6Wj3uvKbMm92GkKqMFhdSpgfJ7G/lT6YgaZpVHdEM9yskmOoiUUfIYFhVLA9Tma1svHkOVdPhSqWtex9SFdSHI1aRCvM9Mj1gdrs9NDCQKMVuy8dKJNHudiElikiIIlyZkMhAIolNkuTInRJg9NMKq4rDrmo6lHQaSUlyiCtXWrPaA9jFlSeVtsryhxXFKmHvTqdL79Uly1ZvsS2FAaBnVVuGruvYsGED/H4/Ja4TBEFsQzjn6OrqQn19vaNPcCF2jd3kDoQgCNAZQPngOx8hRcaKynIsryx3hIjtSmzKeKrWB7Ml4lu8Hhy2vqng2OqcRsatHldefyvD7s7L02p3ZUIJo07R1e52YeTmDkfBi4QkISJLKI/neqkMIVUeiztK0pv9rcriCbRmenf16KXKsYdUo0lwWTyBtTljAcN7ZYou8/fBm0o5+pqFVAWedDpPRJkUs/tzQgCLjXdlPIK+ZAqbvIa4sT/T8SeTmR5qTk+TP5lCmyQ5xBWDIdJCLtVxTgZDeIVVxREmyDLX26X2/LegCwLimSIkxLZnw4YN+OMf/whJksA5R3t7e69CiRhjUG33OZ1OI23zUG8rFEWxNi26rm+XQgCSJEGyNa5PJBLbPCyL7kcWuh9Z6H4Y7Cj3Q1VVBAIBMMZw++23Y926dRg0aFC3x5Do6mN0XUdcBDx6z2OJ7U9CFPBdeRlWVJY5hMGuSnMB0RVyqZB0Pa8qYavHlVdmPqIoiEkiKmNxh+hqc7swqrXdMdbITVLzcq/sTYjtlRQ7XK680EWzOmEhITWks8shuqKKjIQowKVpDi9VpxUa6PyC6lQVVMbizhwoJStqgvEkmn1eayxgCJFAxhsFGMKoLhI1QvQ4BxhDUhIRz3ip7OLKHoLnt4XudRUJDYwoMmCJLrMgB0NUluHLhH2aIYDhnJLt3mQKbR53Xq6VLyO67GLMtIdVJc/uTaZLEl2AIQi3RnRpjAIEthS/3w9JkuB2KRAYMLSuHqJQmscrrXF0RnWIAhDwCIgnOSIJDq/K4FG3zR3ROUcoqkPTgaDHOKd9TcI28t5FE7p17S6FOdYkidtmDXQ/stD9MKD7kWVHuh8pDUinsx1w/H5/9weCRFefk0wmIXCjEhexY6IxhnUBP5ZXlmFNWcDyWuwObPK6cUDTpjx7m8eFqmgM64J20eXG/k2t+WPdblRGYw7Pk5F7pcOfSDg26Zvdal7uVbZCYNwh/trdKgZ1heFNJhHJiIiQqkBj+aLLrPqXaw+pKqqjMYeXyjyfPY8KsIuxrF0XBEQyoYvOHCinMDJFl2mXOIc3lbLWHVZkuGJaUXFVTIzZ86iK2SNKVnR5M/a4LCHNGKTMp39RMZY5LpoTMmvac3OzvKnS87qisgzk3OveoDEO6iW/ZZghhQIDBIFBVSQoUs+boGRKR0dUg0sRURkQITAGnxtQoxpCMR2qzOD39G/chs452kIawATUlolQZOOXwKXoaO3SEEsya239SVdUQyLNUOETrWv2uIy1hRMcVX7BWlt/QfcjC90PA7ofWXa0+1EVENEaSkPPVG4uJbSbvuL6AVXbutwGou/hAJq9brwzuB6P7zcai0YMxfcVZbuV4AIygiknDBAwBFZuP6w2txuelLMQBmAItELFKjicTYUBw1OVGzIYUhWkGSsaBmi3c8bQpaj5oitTObCQ9wqAI8eqSzGKUsg6h6eACMqt0lfIbhdMgRIEkynGFE2zStXHZclqYlyKuLILJm+R8XZRFHXkaRUWV6Y91wNm2mNFxpdC7rl6i8gZkjv4n+Ps2bNxyCGHwO/3o6amBlOmTMG3337b7THz5s0DY8zx47K1GwCMnIAZM2ZgwIABcLvdmDhxIlasWNGfl4Jkyti0yWL+ps3vERFwCwjFdHRF+y9k1NzApDSOKr/o2LQpsoAqv4iUZozR+zGEqSuzaQu4BcemTWDGeyOLDK1dGpKp/gthofuRhe6HAd2PLDvi/ZBLeLCVyw7+FbdzwmBsIIjtT0iR8ZHVT2sEvqjd8ftp9SdpUUBaFBz9sICs98pOUhIRleW88MB2l5onrtKiiLAiF/RqqZruEDtgDJ2ufCGVzb3KEVIuBUom/NGyqd17r+xeqrQoIJaJQbfbzRwrf06Vvi7Lnh1bTDA5QwPtdkPUsBy7Gb5nFKnIrzxoF1ER2+9pUbvDA2Yfb9zflCgiaXuw4E2mHesw8WTG54u00uPkcwVbbxE5oOzgYdlvvvkmrrrqKvz73//G4sWLkUqlcPzxxyMSya8KaicQCGDjxo3Wz5o1axyv/+53v8Mf/vAHPPTQQ1i2bBm8Xi8mTZqEeHzLPYfd0d0GxqS/NzLdbShNtsXGstiG0mRbbCzpfmSh+2FA9yPLznI/SmH33X32MyS5th8JUcD35WVYvpvkafWWzW4XKqNxbAj4HLYDmloKjFVRHkvkFcIIJBJ5le06uhNSiYQjf6tTVVCT43EzhVQwV0hlRFAgkbRyzsKKDI0xh9cJyIqdXO+VWfDCn8jmaZkeI5FzR1GP7BxOMRZWFJTHEyWHAJp4kykrHDGsGH2zjOIVRh5VTJasPDK7yMmdwySaU3mwsN05Xsm8p3aPlr3aoOUByxFj7l6Irq31dAEwKr/uwCxatMjx73nz5qGmpgYfffQRjjrqqKLHMcZQV1dX8DXOOe677z7cfPPNOPnkkwEAjz32GGpra7FgwQKcddZZfXcBKG0DY2JuskIx3fHvraU3GxhjYwm0dmloC2l9GkrV04bSxNxYtoU0tHZpqPKjz0Kp6H5kofthQPcjy852P3qCPF3ELoHGgNVBP17dcw88tv/eeHPoIBJcRdjsLhAe6FbhzzQKdtrzwwM7XCoY8kP7ComuTtUIO8ytHNjpUuFNpSBp2V12pIiQClleLZudMSNvKq1B0rJPtbpsAs2OKY78OeF75tXavVrmWG8qlc2Qtdnzil1k8BbwaFnzZIgW8F5xxiwvkci55dHLLeteaA5PkbmLjXdnPJycMcRtbQNMcRWXnMLJ3YuKUDFp93uG19nZCQCoqKjodlw4HMaQIUMwePBgnHzyyfjyyy+t11atWoWmpiZMnDjRsgWDQYwbNw7vv/9+wfkSiQRCoZDjpxR6s4Ex6esnyFuygemPJ/qlbihN+uOJPt2PLHQ/DOh+ZNlZ70d3kOgidlo4gBaPmae1NxaNaNgt87R6S3sB0aUJAmKynCdWCgmphCQhLon5QkpV87xUSUk0xhbwPNmbAQOGEAgrcn6OlVo898qYIz8PypcsPIcvJ+zQFB7eAl4qkXOH6DA9SWaIHuAM33OEACqFvU5OezEvlWG3h+tJmf5qxcYCTtFj91DZ53EXG5+ZOymJ0GxfbL3xdCV2M9Gl6zquu+46/OAHP8A+++xTdNxee+2FRx55BAsXLsQTTzwBXddxxBFHYP369QCApiajXUNtba3juNraWuu1XGbPno1gMGj9DB48uMf1bskGxqSvNjJbs4Hpy41lbzeUJn25saT7kYXuhwHdjyw7+/0oBu1OiZ2Orkye1rNjRuLve1OeVm9pLyCkAMPblZuT1amqeeLKsucWsXApcKWzhSNMQqpawHtVXEj5cwWT5WHKzb3K9zyFFaNJrzeVdnipIpZgcs5h2VNFvFQ2gWXmUuUWlzBFkN1uFzT2OYp5qezjXelsPlbKVvbbFIC5Ysx8v2MFPFq5czvsJYgxVy88XXbP2e7AVVddhS+++ALPPPNMt+MOP/xwnH/++TjggAMwYcIE/P3vf0d1dTX+93//d4vPfcMNN6Czs9P6WbduXbfjt2YDY7K1G5m+2MD0xcZySzeUJn2xsaT7kYXuhwHdjyy7yv0oBIkuYqcgIQr4uqocC/faE0/uNxofDKxDh9vV84FEHiFVQaCgkFIKCilfMgVBd35whlQlr4hFSFWtPlZ2uhQ53/Ok5BerAAzRpGq65dUBst6h3DlMcWQXY1qmSW++l8oQEt4cz405dym5UeZYiXNHIZKoJca6D+kDinujioUGFhqfG8ZnCiO7XbSJMbsYUtOaJUbtoYSqlj1nwjbe1Yu+W7mhibsyV199NV588UUsXbq0x2aYuciyjAMPPBArV64EACvXq7m52TGuubm5aB6Y2ZTT/lOMvtjAmGzpRqYvNzBbs7Hc2g2lydZsLOl+ZKH7YUD3I8uudj9y6fW35KpVq/D2229jzZo1iEajqK6uxoEHHojDDz88rwwuQWwNGgPWB/xYXlmO1btZP63+RBeMCoaypiElZj9YQ6qal78VURTojFlNdbNjFdTmNDI2vUz+RBJtHrdl71IV1Hc5q7tFMmPzvVeGGPOmUkhmNv8JyagcmDvWyr1K5nue3GkN3mTaKrwRKTpWyrPHZQkaY0aBjW4EkBlOZ85hF1FJKds3y+HRKibGinid4pKEQGZt5vi4JDqKYLhTGrrUfNHjSqeREkWHXQCgapoVImoi6xyirluiNWvX8wqmFCMhbl9Pl67rePPNNwt+P02cOLGkELye4JzjmmuuwT/+8Q+88cYbaGho6PUcmqbh888/x09+8hMAQENDA+rq6vD666/jgAMOAACEQiEsW7YMV1xxxVatty83MCa9TVbvjw3MlhQP6KsNpcmWFA+g+5GF7ocB3Y8su+r9sFOy6HryySdx//3348MPP0RtbS3q6+vhdruxefNmfPfdd3C5XDjnnHPwq1/9CkOGDOnTRRK7DxzAJo8byyvLsbKijMIG+4kuVUEgRxx1uhQM6cxPyA8rxli76AorCoa1dzrGmRv2QuLIKJGe3bybY/PD/bIiqN3myYzIcl758mxYX473SpZQGTO9VO7MWGNeVzoNxjl45sPcFFK5BSNikgRfKlVcGKXT6Mj8vylqZF23hItp96VScKeyT9iKebriDu+SU3Tl2nVBQEoQoGS8j6aXKpET3udKm2LMaVfThujKFUmudBoRRXGck8EQabESRFdSEq0qjNuSWCyGe+65Bw8++CA2b96MAw44wPp+WrlyJRYsWIBLL70Uxx9/PGbMmIHDDjtsi8911VVX4amnnsLChQvh9/utnKtgMAi32/hdO//88zFw4EDMnj0bADBr1iwcdthhGD58ODo6OnD33XdjzZo1uOSSSwAYlQ2vu+463HHHHRgxYgQaGhpwyy23oL6+HlOmTOnV+jg3hGEqzZFK6WiPaJBEhoBHgOG07JuS0qoiwKNxdEQ0pDUOr7vwRoZzjvawMabcKwKMIZnuo7LWjCHoFtAe0dDSwVHuE4s2J43ENITjOnwuAaoi9N0aAAQ8AtrDGlo60yj3ipCLbNLofmSh+2FA9yPLzng/UmkOzjl6E8VZ0o72wAMPhKIouPDCC/F///d/eU8ME4kE3n//fTzzzDM4+OCDMXfuXJxxxhmlr4LY7elSZKyoKMPyynIKG9wGhFQlzyMVVpS8MumAkTuVX5gi3wYYYYPeVH7elNmvyi7cIrKcP1bJz7ECDIEVTCQdoiZaJMcqVkCMxSTDsybAEBfmGFO45RaMiMmmYCpcqr1QoQqGrHABDLHjS6UcoXvOkD6toN0e0heTc0IDMyQkEUpSd4wvJK7MsXZcaQ0h5Be+UNMaIgqQFPPnieWUki9GUhTh0nofP781jBw5Eocffjj+8pe/4LjjjoNcYK1r1qzBU089hbPOOgs33XQTLr300i0614MPPggAOProox32Rx99FBdeeCEAYO3atRBsIrW9vR2XXnopmpqaUF5ejrFjx+K9997D3nvvbY2ZPn06IpEIpk6dio6ODowfPx6LFi3qVfQIz3zz6xyIJ3VoOocqC1AkhkSKo682MCaiyOB1CUhqHDxmbJac6wGSaQ6BAT6XCI0DWrLvewL4XCKSaR2hqA5FYsjdV6Y1jpTG4XUJEEWGeD+swZ3ZqEYSOhQNyH1GoetAMq3T/QDdDxO6H1l21vuR1jj0Xi6zJNH129/+FpMmTSr6uqqqOProo3H00UfjN7/5DVavXt27VRC7JUlBwPflQSyvLHf0jCL6n8IFKxR4CwipsCLnea8isgxZ51DSaSRtm/eoLOd7r2x5Uw7Rpch5jZCLea+isgQGQ+yEMyGIlmAq4KXKtafFrHfIncqKrnhRT5chPOwCyO4ZcggjR+l1Q7gAGTEWs+VRMVY0X8o+t12MJYvY45JkVW20xJXoDDs0x+d6tIrZlUz5/oQo5NhLF1FJUdjmouvVV1/F6NGjux0zZMgQ3HDDDfjlL3+JtWvXbvG5eAmPNN944w3Hv+fMmYM5c+Z0ewxjDLNmzcKsWbO2eG0dHR2or6oD5wImHxpE0Lt7FTYhCILYlnRGNLz8QSc4L12oliS6uhNcuVRWVqKysrLk8cTuBeVp7RiEFQXVUWdOVloUoAsMrlTaEdYZVpT8IhaWR8opuiKKlFcZsZhHKipLqAs7c70swZTnvcqKI1N0mblNhbxUQH7lvXjGO1TIk5RbMMIUY/Y5ErbwOae9SEGKjKix51FpgoCUwCDrzmIcidxiFzlz5NqTNmFkiihdEJDOzG0fn+vRMkVUsoi4yvN0ab1IghZFAPne0v6kJ8FlR5ZlDBs2rB9Xs/3gnIOBQeMcQa+ICj+FZhMEQfQnksjAeem5Z1v8qdzS0oKWlhboOVXN9ttvvy2dkthF4QBaPW4sryzDiopyytPaAYgoEoZ25G+OzZA/+z2KyhJqw06BZpYz96ScuVdRWcaArlwhZYT25Xqv4pIERXMWaojJkiGkckRQVoxl59AFAUlRyBsbt7xU+WIskEwVzJkyq/2ZhUUSBTxdnDErfM7udSomjOxCSsmILsAQJrKedoiZYp6u3DlM7MIo1y7raYc9JZQmrorZc1sAdEdK3P4PUeLxOP773/8W/H466aSTttOq+h9VVRGK6fC6yMNFEASxI9Lr3e9HH32ECy64AF9//bUVasEYM56yMQZtG4eWEDsuZp7Wispyx8ac2P4UyqcCMpX/ChSsyPVSAYaYyhVSMUnKC9XTBWaEnaWLhAza8qAMYZM/tpDnCQASogR/MukQbtmxzs8iU0x0J5hM0WXOkRtaZ4bPdSeucs9n2HWH3ZtKQ9J1q6hHdyLKWl+RddvHpwQRgPEeyRnBke/RKmw3x+cKJ1kv3dNlnH/7sWjRIpx//vlobW3Ne213+X6Sxa2v+EUQBEH0Pb0WXT//+c8xcuRIPPzww6itrS1aDYXYPXHkafm9yMvaJHYIYrKUJ5gAQwjlCqy4JBZskhuTpYIhfK605qgQCBQWY6ZwcKWzeVDGHFKeYDKFjarle7UCSWOOqCI45lVz5yhgzxU1YcsuFDxfQpKAZKobYaQXtCsFBBND1gNmF0BOEZW1y7a57cJIdpzTbjfmSYvOqoJSRkSl8zxget45c+fvie3t6brmmmtwxhlnYMaMGaitrd2ua9nWcM4hCUAyrQFaDEhvf68jQRDELoumAzzzUyK9Fl3ff/89/u///g/Dhw/v7aHELooOYF3QjxUV5VhVTnlaOwMpUYRU4Km/IaTyQ/tyQ/iArMBy2gzvlZrWHCGKCUnKF0EZb1IhcZTv0SoipDJiTNE0RGHkmZnCI9dLVUi4JW09rwoJKSVHcJhz270/TmFUOO9K6UYwJSTjfpjrkIsIt6Ln1AvPbT9n2lZi3lxjKieMUOoTT9f2/dtvbm7GtGnTdjvBBRhVhH1yFCldAjpWAcltm1tHED2R1Ol3cldAEUqrZrvLE5UBra5/Rdexxx6Lzz77jETXbo49T2tlRVnJJaWJHQdNEPIa3xbyasUlMS/nqbuxgCFsHKJLFAp6qcyxdhKSiGDCWbgjK4KcY81NfmHBlDvWsOd6bsyqhg5hlJlX5NzxHqWt8/VSGNnWki4gmDhj0DLNlEWj2RLAmHOs3QNmP2eOuDKR9CKiSy/s0SrmAZN6Ibpyj93WnH766XjjjTd22WIZPcEYoIh9X/KZIPqCjamN23sJRB8wRN1jey9hp6XXouuvf/0rLrjgAnzxxRfYZ5998nqi7MqJygQQlmWsqDT6aVGe1s5NUhQdYXlAJkcqEcsbp8OZ82Tac/O/kkU8UklRzCtRX0gwmWNzizdkvVe5nqd8j1TxscXOZwiSYuF7iqYjnlmreT6HiBKFgl6qQuLKft0oMF7SNGMeXTeKlYiF50gL2dBNqcjcuaLLRMxUN9QEZ+ivuZatEV25c25rHnjgAZxxxhl4++23se++++Z9P1177bXbaWXbDoroJgiC2DHpteh6//338e677+KVV17Je213SVTeEkQximDVZw5bZ+v+0DTPdlpR6VCe1q5JXJKg2sLyAENU5PVlYgypAvakKCJQxCMl6/ljiwmmQp4nAYCk6UiLOWJHLyyknILECNXLFQummMidw7QXEylSAbGTP7dRql0qEupXVABx53izx5WUEV2FxBIAaKznuSXb+EIiLVdcmWvRcv6+xV50f9zenq6nn34ar776KlwuF9544w1HzjFjbLcQXQRBEMSOSa9F1zXXXINzzz0Xt9xyy24ZN7+7oMPsp1WG1WVBa/NL7DqkRCHPo5SQhILNcJOiUFA05YXwZbw+eUJKFAragHwRlLVr1u+dJZi0IkLKZtcFBp0xiJxD1HUrx7CQuCpm7y5Mz7A5hUhaECDrmmOsUxhxx9hCc9vFjuWNYoU9Wk7hlp1bt89hE3RagfFGSCMg8pxzFhFjpZAr2LY1N910E2bOnIlf//rXEHbD3NJUSAMTgKb3Ioiy/EbnBLE9WV2z6z2UXxMDFAGoU3af59FiS7jnQbsBIa4gxXVwvfTf616Lrra2Nlx//fUkuLYBDDqqXKsR1/wIpyrA0b/lmDmANrcL31aVU57WbkAh75MhHvI32akC9pTA8kSQmZtUyJtUitix28UCQqXoWJ7veRI1w/NkighTzPVedPW8DlNs2AWQPdROtIsrh9fJPj5fGNnHCoBVFdI5d7Fz2j1jhddiilPHObfC06Vv511HMpnEmWeeuVsKLgAAF8DBwLkMXvptK4isa/BpaSQEEXFB3O73ltj5GdS6a+0bYzrHZRvbEeEcdaKAQ10y9lNl7KtIqJX6d7+2PeE69VoFAA4ZHAzgpX/f9PqdO/XUU7F06dLdNlF5WyILcZQrTWBsA1K6is5kDUKpGqR0d5+eh/K0dk/SAssTDylBLFgivLBoEgvm+xQTWHlCRRAKhgGam367XRcYdOSLK62AQDPPp2p6QeEh5OxGTaHiEEy2DabAnSKl8BzFhWL3c3cvjOzeMnO8lhG22bkLe9eKCsA8zxh3rCU3Lyv3Wrtje2/ML7jgAjz77LO48cYbt+s6dgUkzqFwo8CMT0sjLgiICRJSjO0+j/SJPkVJ71qb9c8SSXTqHCoYGlM65qcSmN+VgJsxnOpxY1rQv72XSOxg9PovYOTIkbjhhhvwzjvv7LaJytsanYuQWBJVrnWoUBsRSZejM1mLSLoM2e47vSMpCFhVHsTyyjI0+n30JbobkioohJhjU26SFgSHh6S7sZrACoigImNZobHZyoE9zZv1MBUWbkKB0LvcOQoJqWIipZBHyzF3AYHW7dx6/vrs4/WcP0uBc2g5czivMTuWFQk7LPSe2O0cO6/o0jQNv/vd7/Cvf/0L++23X97307333rudVrb9EIQk3L71DlssPAi6rhQ5wokGgIHDrWtw6TrSjCGW8X5x+t4gdmM+SyahccAvMLDM95bGOZp0DebDLIKws0XVC30+H9588028+eabjte2ZaLyn/70J9x9991oamrC/vvvjz/+8Y849NBDi46fP38+brnlFqxevRojRozAXXfdhZ/85CfW65xz3HrrrfjLX/6Cjo4O/OAHP8CDDz6IESNG9GpdbkmAwHSAAYoQhuE3YkjlbGTAOVQhAh35TWdNZCGRGcqgQwE4h8A0+OVW+KU2JHU3OlO1CCWrkeZqj2sz8rR8WF5ZTnlahCO0zKSQuAIKCyyN5XvKTHshUcKAvBL1xrx63ligkDgSCgoxIF8YdCek8rxU3Qi0YnYGOBpAZ8+Xv4bcOeyihqHYOTNjWWEB5Jijt+fsYXyucOqd6Cp5aL/w+eef48ADDwQAfPHFF/12nh3x+6fCJUNkOjgHPDwBL8ycLg0Madi/giQke+y/Zm4OzF8H48+RQ+YcsqbDp6eQEIC4KCDNQA/uiN2OD5JxMHAIAocpshg4JAAHugQIAuVV7soI3NwH9GOfrlWrVvX2kD7n2WefxbRp0/DQQw9h3LhxuO+++zBp0iR8++23qKmpyRv/3nvv4eyzz8bs2bNxwgkn4KmnnsKUKVPw8ccfY5999gEA/O53v8Mf/vAH/O1vf0NDQwNuueUWTJo0CV999RVcrtJD7vYs90JlMehMwEDvGpTzJDhnaEvVArY/QEXnqPJ8myvF8mDQoUOGIZkAHQJ0roBBhyJGUSOuQqW6FpF0EKF0JWKaH/ZvVw5gs9uFlRVBrCoLIqYYT34VRFDac05iV0WUYvDwJDy26oUqS0IWIvCgyzlWjMLDRcdYWYxAEqJ5YwUpBhfrggfZvxtJiEIUo/DyEDRbbqIgxqAyyTGHLEaM86ELHmQTVJkUhSyIjrEKM8a6mHPNghSDmE7Aiy6kM5tPNTNWEdKOsZIYzcwRtuwKS0MUowAAD8Iwa4yaawMADw+BZ8L5BCkKUYxDFnRrDhdLWGNV5rLs9jlc6LLeU1HK2t0sc+2MWzbjnF0QIUEVwpZdEpg1t3ktABzXKdrOKYvZNQpiDGKmYamcmUdkmuOciiDk3eNiKELEcWypCAIHmG78bAVLly7dquNLYUf9/hngd0EGh8YBr6bBn3mgx3UdaSkKLiessUrED0UrIfSJAUx0JolntBcELsCjM7h5GrqUQlKJI60knKqeIHZRQhrwrabCKwJMyP6NxDTAIwLjylvg3rWiKYkckroHLDoIDP1YSKMYGzduxOOPP47p06f31ZRFuffee3HppZfioosuAgA89NBDeOmll/DII4/g17/+dd74+++/Hz/60Y/wP//zPwCA22+/HYsXL8YDDzyAhx56CJxz3Hfffbj55ptx8sknAwAee+wx1NbWYsGCBTjrrLNKXlta1yHJItIMiKmAAkDV0thY3wW9LFvxJRAR4NnoRkIQu31CyCFkVHShzYgAcA5ZT8OttEJlbQgpMtb6/Wj0eR1NW11Yj9ElXwWxOzDY1wWNMXhFn2VTZA3VFS04SGxyjB0QbIPLrTrGlrsSqKpsw0Fis2NsVUUzdI8Hspjd1NV6owhWteMgcRM0Mfv7Xl61EXCpOEissGz1njCCVZ0YozZikJj14FZUboTOGA4SN+TNO8zjhygGLHt1eTO8qTT2kzciIhqiJuhKIFjVCkUWHXMMKNuMoBzDUJ8XmlgGAJCgI1hlNPIcra5HrWhsfAd6jbUBwFhxE/SM96ymrAV+TwqiIuMg0QjlcslpBKuM92YPvxfJzNz2OUa618AvegEAdcFWBFVjYzxG2YCQqAAcCFY1Wms9QG5GShQRVI1rAQzv0kHiJuM83i4Eq0IAAFXKXmd9sA1BJQ4AEGxrrKxsgivTU427FBwkroHAOIJV2fdHc7twkLgapVDnMe5Hb2GQIWIwInr/JJ+vWbMGd999Nx544IGtnmtH/f5JaTpUo9oKdFGDDs0SR+C53zEZD624hdXkGMAzXjWAQUwpcKcU6IKGtBJHyhXf8rkJYifg07iAqA5U5HxkRTkwRuWoJsFFFKDXvxY///nPC9rXrFmD//znP/0uupLJJD766CPccMMNlk0QBEycOBHvv/9+wWPef/99TJs2zWGbNGkSFixYAMDw3jU1NWHixInW68FgEOPGjcP7779f9EsvkUggkcg+PQyFjM1OmgEpCEhLKaRZChJLgwlxCEhlD2YCNElEWpS2OiwjASDBOQTO4dcSGNMRxoguAU0eN1YFg0iIu24VHWLLEYQ4wBgUW16gxHRATEBBjrdCikMUuGOsyJLgUv5YLiYgCAIUm0dLZDFwKQEZUYh2T6yYgCByxxyCEAeXEpBYDIrtCRIXE5n1RvPmFQQZiv3jTEqC8xRkFoOS+buTMutlguiYg4nxzBxZuwAOLiUyx8WgZB56iJm1AYCCKHTzWsQEuJQCRN2aQ2KaNVZg2bntc4hCDEpmDibFwSXDKyezKJRMSJg51jwngwhJSFp2zmDNbV6LMbntOqWsndnWCDEBbr7Hmftgv3ZjPM//fSiCKMQcx5YK5xwpjW11TtgPf/hDR28uk40bN2Ljxo1bLbp2lO+fYt89RsEZhiSTkGAaGAck3ahKm3LZGm1HXahKMKTEPtwZckDSJQhJP5S0D11uHWtrU9Apip3oJSPaOrCismyr7CPaOgCgoL0v5vgkJiDFBOgyg/mXqKY1cM4wslrGikpPt/OYtmL23qxlW9hLWb/dVoq9t/OXas99rSdyj+1Pev2J297ufIqpaRq+//57fP3115g7d26fLawYra2t0DQtr2R9bW0tvvnmm4LHNDU1FRzf1NRkvW7aio0pxOzZszFz5kyH7d6Z1yEMFYqQQrxiA2QpgjjX4VEkcCH7JSm4GTrqhMwmoy9j4Q3xxQD4GcMQUXF4vAjCxOVLgwNw2zZeTODQq5MYavMEAYBalkSZIDjGyi4dWlUSQ8WNjrGsMoGgKEKxjVW9GlJyCkPkjY48JV6dgEsQMFSUnWOVFGqVDai05R3yauPvZ6jYmDevX5Iw1H4dlUmkdB0DlA1WZUHJpSNVkwQYc84RTCHl0+CVRGsdTABSNYZnqFrZgLLMOlzeNFKKEbY1RGqyHAhC5nyCIGCouM6wCRypGmPNXjE7t32OclmCJ7NuucyYA4Dj2s11AMBg2fD2SWrmWmCEew3NeCZdvjRSaiZP1HadalkSKb+eWVd2jahKIJXJ2ZIFAUNFxXHtgBFeOFQsLRhZ9Rj3o7ek017orUPhYfGeB3fDAQcc4Pi3+f20cuVKzJs3b6vmBnac759C3z333DCt4NhtBbP+y6GDyggQW06xDXNv7H09R2eKoyXJ0eBmWFFZhtc2JsFyQmkjggBNBEb7hKLz9OX6djR7b+fo7/XsiPRadP3jH/8oaP/Nb36DBQsW4LLLLtvqRe0s3HDDDY4nmKFQCE8/ej8E6JCRBjQBjIkQdAZdksHtRTN0QEiL4H3UT0bg3ErsTwsCIrKMmCQZJaTp248ogK4bBRbSPCt4BM4BTUeaOzfZXOPQITjGMq4VHAtdgy6IDrukpwGNI80VZ3U8TQOH4Bgr6ylA49C4jDQXHWMBFJyXi5JzHZoG6AI0riCd6aFhrheMOcZynQMagy5k52CcA5rx96rpEtKClHnPGEzHUBoyuKm6ND3zhmavRdR1a806y85tn0MXZes9NdZhXqPt2rXs50aay9AhZK/FsiuZOWDNbb9O+9z2NULTAKs4h2Fn4I5z6hDz73ERzPvRazQRMtMgsK0LSZszZ05B+1//+lc88MADOOecc7Zq/h2FQt89z82dA6YzCABkTTC80hwQGEegU4EesRVNCckQNWFrU+gAnikqk/mnzoCYwJBgDFqSoX5dzwWeCGJn4MVQDH/risMnMBykSGhMMPjBoCSzf1dxncMH4JgOH8pC5OLdWYjB1/OgAsS5ghRXUKDLTlH6LLbg7LPPxh133NFX0xWlqqoKoiiiudmZR9Lc3Iy6urqCx9TV1XU73vxvc3MzBgwY4BiT++TUjqqqUFXnl4oAwI0oAAlqWoDKBQACvF0quJLdUIgckDQGqYc9hlETR0BhbxgHy/xwMKS4gpTuQprLkMEgAYjKEkKqgi5FofK+hIOKVAwaY+iUson6oq7DEw+hxV3mGCsnuhBWZMdYr5aCOx5Gi6fcMdYb60SnS8FmKdtPLphKwB2LosVd5hBd/lgHIrKMFsVr2crScbhiMWyWfYgJsmOszhha3MG8eTvhQpvtfJ54J1RNR6saQJIZ4sWjpeCLhZEUBMccUiIMMZlCF1exSTZCQgSuoyxm5F21yz5EMsKoPBWHGosBgHEtmb8pdyIEpDXEJREtLiO3TNY1BGJG2FeXS7Gu0T5Hh+BBp2R8hiiJLrBUOnNOP2KCBICjPNZhrXWTKwhNEODOXAtgZHua96AiFYMSM7xF9uuU410QMnPHbGv0xjuhZLxrUVlCi+oH4xxltnOa9lIIpo370VvSugpwcasb+hbj2GOPxTXXXLPV8+wo3z+FvnsUUQDjRripwLPNRIxmySK4vZolF2FERfR0xfnNsjMTWN9KHIbIiosS4kywlTvseW6C2FkIsDSiPA6uA6/GUtDBUSuI2QdvAKK6hoMUBQG40ENxUGIXwHCviEiy0gV2n4muzz77zCrV258oioKxY8fi9ddfx5QpUwAAuq7j9ddfx9VXX13wmMMPPxyvv/46rrvuOsu2ePFiHH744QCAhoYG1NXV4fXXX7e+5EKhEJYtW4YrrriiV+tL6zoUQQQ4Q0J3I5H5e0zpKiRkwwt1cCR1NSOoCsPAIQuFwm04jFaxDDpEJDU3kroLOs+/ne4E4E4kUc2S6FIVdKoqIoqcPyWx28H1FDRRRBp275UOrssOGwBwLkGD065xDp3nj9W5ZHipbHada9B1yfAO2XO6uAQNUoGxKaShIG37iOJcgg7mXAOMeXPXxnUJuq4jnflQNNYL6LoEXRAKjOWOOUTOoevGudO2a9GRztqhWE5kXZeg6wwaz76fDII1Vi8yh/2cnEvWF7Wxbgkss2aTNBRomb9+a26G7Nw8DV1PZ+yCzS5bc+vc9n7rIvRM0o1pF8Ad5yx0j4th3ufeYhzT16HWWZYsWYIf/vCHWz3Pjvz909gVx+CAG5wxhEUJoql6BA2C6GxNEhMZ0gW+L+zIXIdbtz0VzIStm99YOhiigoi4KCLdi00HQeyMDBBFCAACjEEsEqGkAdigabirI4QDVAXjVAVlfRTNROwa9PrbMTchGDCeyC1cuBCTJ092vN5fjSinTZuGCy64AAcffDAOPfRQ3HfffYhEIlY1qfPPPx8DBw7E7NmzAQC/+MUvMGHCBNxzzz2YPHkynnnmGXz44Yf485//DMDoL3bdddfhjjvuwIgRI6ySvfX19dYXa6mkdI4I3HCxNOKaH1ImLEcQnF96nDHEdH+3GxSRpR2ii1mR8gxpXUVC9yCtq3nNTAshcCAYTyIYTyItMIRcKjpUFQmJ8r12V4yn1Lk2XrDXkvlE22HjhSNXBZ7fX8ok12408M2xZWbNLbjGOAcX8tcAFLqOfLs1b5G/l0Jj89ZhG2S3F5rb/lXrWB8vwc4Kjsjai3go7A2RUWB93RxqrT333ckrfNdP6JxB3MpznXrqqXm25uZmLFu2DD/84Q8dr//973/fonPsqN8/7fEU6gNugDHERdEqLCMIOtw576vOGGI9FdHQ0nBDy/Nqpag5MrEbUicKkBmQAlBs11QpCGjVNDwXjeG5aAwTXSruqijbhqsktjUS9Excf6nje8knn3xS0H7IIYegpaUFLS0tAFCwglRfceaZZ2LTpk2YMWMGmpqacMABB2DRokVWIvLatWsh2J4uHHHEEXjqqadw880348Ybb8SIESOwYMECq0cKAEyfPh2RSARTp05FR0cHxo8fj0WLFvWqRxcAMJ6CDrf1dL0vEKBngggFJHUXkpoHWg9PKbtD0jkqonFURONISCI6XSo6VQVpeiKzW8E4z6sWZ4Yn5Y/Nb5rLwAtuuoxwVyfFfrMEnt9QNyukcs9X2AYUEnP59uICLV+GMIcwym8gnC8IcxaUcyLHOuxDigqjIgKo0Nhic9vXh8L/KPgpnRPjV8pDnb4gDRHgW5fTFQwGC9pGjhy5VfPa2ZG/fwqh6woioT23+HgRhlcrJgiICxJSjFEjZGK3Y4AoQgZDmvOiv/8qY1BFEe26DgHA6V5PwXHEroMIDrEXootx3l9R9LsfoVAIc++9EaqoIg0ZRwc+hU80cjeYoEGWnQ1GUyk/eDd9aRjT4JbC0LmAtK5A0+VuwxG3loQsICLJiMkSPcHcDSiPxRGTJcSlrIBX0hrKEgm05HxZ1Iaj6HQpjrHeZAq+ZBLNPq9j7MBQGO0uFVFbGGsgkYQ/kURjwJmwOqgzjC5VRqcrm58SiCcQSKTQ5Pc4HgQM6gwjKQmOtfkThve2w60grGSLPdR3hSHowAa/1+ql5UmlUBFN5M1RHYlCTevodCnoUo05JF1HXZeRm9Tic1sVQM21cQbHtQzoikDUORKygE0eY25F01ATNv7+Q6qMUOYazTkAoM3jQkyWrPdYzmTkNvs9SAkCBM5RH4pY52kMeMEZgzuVRmXU8IJrArDRb6ylLJ6ALzN3ShTQ7PM4rhGAY40DQ2FLMMZkEW0eN0Rdx4CubF5WTJHQ5i5t8+9PJhGMJXsemENYc+PN0P5I6hJuuu1OdHZ2IhAI9HwgAcD47pk+fTrG1AQAUcAxWIcAel9F0o6s6/BpKcTJq0UQ4JxjcksrOnSO8m4eUMc5R6eu40q/Fz/3b1mBBmLnIAQZSzAY0HRce/vdJX1vUfu2PoYxQBLTYLrRd4dJGdHFdPCcuHrG4wDvXkTFIRtPw0Wjf1J/fu25ALjSxsPmpCgiIYlIiuT92lWRxRQ0QQSz5WMogg5BSsOdU0VOlBJQhJRjrCpoEOQ03Dkl0AQpDkXUwB3zpgE5DbfNhcQ4wOQ4JCkFN8tu1BUxDSanoQocMnOOFUTBsTZFMMbKYhpuZmvJIMXBOOASuOVNUgUNTE7lzSGJCTDGHXNIjIPJicxxOsTMhtNcGxgc12Kezz63zHQwOdN3y3aN1hwAFFEz6tNn3mOWqWygMh0SMyrRMTkbYuwyX89cCwAIArPWIospMNk4v30tkpSwyhvb7YIct1xioiTCzdIQbddujBfhZqVt4GUhe229gTEGWUghvQWfcJzzfo2s2F1JCQLaBao+SBCA8Rk1WBSxSSv+WahxjnZdx5GqgvNzHkYSBFCi6PrRj36E2267DYcddli347q6ujB37lz4fD5cddVVfbLAnQ1NA7gggUGEHq2CnunNJQhpCK42x9h0vHKLks63BXLmJy2wTPgh5X/taijRLmzyepBg2fvqTybBEwk0K85qdcFwO1qDfsRZ9ve1KhGDnkqhWck+2WGcoyLcjjbRh4iQ9TzVxSNgyRSaXWWWTdJ1lIc7EPJ50CZmPSkDYhGo8QSaXeVWSKOoc5SH2xFVZcfaahNRuKJxtAs+hGznq+jaDA6gyV1hiYryRByecBQxxTmHN9oBIa2j0+dBe2Yd7lQagbBRebBFCSKVCRc215YWBMe1lEU2AzoQVRU0K8bTTW86BX/Y8G7br7EuHoEaMz4XNkt+RJjhEfRHOsAynq4WtQxpCJA1DWVho4oiZ0Czu8I4XzIBb9jwgCUlAc2qsRYhFoYSN8RdXJGse+OJdEJIG0IrZnsPK7o2W9cQcSloln1QNQ3BzDkBIOpS0SyXtoGojkfhjva+15auq4Auwc17750ZM2YMZsyYgVNPPRWKUry0/YoVK3DvvfdiyJAh+PWvf93r8xAEsXszRJLwQbLwZxTnHJt0HYNEETeVBSDRgyCiACXt+M844wycdtppCAaDOPHEE3HwwQejvr4eLpcL7e3t+Oqrr/DOO+/g5ZdfxuTJk3H33Xf397p3OnRdQjxa2/PAHQxJ56iMxlEZjSMuiQhR/tcug1ggp0vgvGCJ6EJ2ocDxYiZaWc+pZlZorJkfpeWcToA5R34uVX4OmmnPt+XmXRWbwyyb7Thf0Zyp/PMZ50SeXdCzc+iOsXY7K2g3z2l/F3VWeKxjDvv4Arlo9nlYbu6WOX9OwHmhwirF2NptxpbsU/74xz/iV7/6Fa688kocd9xxRb+fvvzyS1x99dW9rkhLEAQBAAMksWiCRyfncDGGm8r8qBHpATVRmJJE18UXX4xzzz0X8+fPx7PPPos///nP6Ow0noQyxrD33ntj0qRJ+OCDDzB69Oh+XTCx/XClNbjCUdSEo4goEjpdKkLU/2unRdR1aEK+aNJzBDXjPFNIw2kX9cJCDCgkbIqLrjyBpudXUCw2r1jA3t0aSrU7BFMPc5vvD1BYoOXPgSL2fJFmX4ezMmJhUSg4hBts9uz/m/Pkbh4soVdMjJVArpDbFhx77LH48MMP8c477+DZZ5/Fk08+iTVr1iAWi6GqqgoHHnggzj//fJxzzjkoLy/f5usjCGLXYIAoGr1Tc0Ka45wjwTmm+rwYp1JILlGckmPbVFXFueeei3PPPRcA0NnZiVgshsrKSsgy9X3a3fAm0/Am06hjEaP/l0tFhH4PdioKeqp0PU9ImcImV6AJnCMt5guxQmNFnRcUeEABT1dBD5ohQ/IEk3k+m3DLzltEXBW4jly7UFQwFRBotrmKiqiidvs6sv9vCh2ncLON1YvNUfichebJFUiW0MtxdeW+591RSrPd/mL8+PEYP3789lsAQRC7NHWiAClTNt4MZDbzuI5QFVzkpzwuonu2OKEoGAwWLM9L7F7k9v+i/K+dG0nniEv5QipXqACAxHXEmfM+m+KokHDL7dpuCrQ8Dxov4IHTexBSJXi6Cokxu5dKK+Dpyve4If98NgFkn0MsxaNVINRPt70dRYWbbU1Or1vp58z1aFl23WnvjacrV7ARBEHsKtRlysanOIfCmJXHVS8KuLksAJmifoge2DGrOBA7Jbn5X50uFSHK/9ohkXS94H0RuY604PRYSlxHusCXScHwxExoYO5G3Rgr59mAwl6xZE5MvFDE22aJPMEudop724BcYdSTRytfEObOXVQY6Xphe4Hx9nUU8toBOZ64IuGPha7HLizt9qKiK9fThdLJFWwEQRC7CjWCAJUxxDOfnWYe143BAOooj4soARJdfQ0DjEx0DghJ42c3xKUDrmgMtVEgqkjoUhWEZZnyv3YQVF2DJqUhw1lpTkYCEAXItq22ypMFx0pIAIIIu5RSEYdeYKzIEoDAINt8NArigJAEE5KQbflKIkuAS7JjDhWJzN+T7DifhAS4yCGyhNWOXOEpQEiCi3DMYawhDSZK1hwK162/UYFl1yFn1qZLonMOJAx3l8Asu4q0NYd9bslcM5C5RqOUusQSgKCDs8z/A5Bt6+CiYM0t84TNzi27MUfms8W2FjEzt3FOATIEiOZnUQYmGE9rFdu6Dbuxdvs5jUkllBo4LAjGe9x7GKzPTYIgiB0QgTHUiyK+TaWsPK5LfF4c4aI8LqI0SHT1MaIAMDENzjkEz2YIUrTng3ZxfAB8HEDK6P+VFAXyfm1nZFGH7NFRIzg/AtyuJMpkxRFW55I0iB6OGmGzcw5PAkFFgdfmgXHLaYiijhqhw7IxDojeBLyKDNl23z1KGoKooUoM5Y1VJdGxNrechuDTEFQ64LXNIXsT4GCoEbJzqJIGwZeGK3cOdxKCyhGQZbgzc0jgEHyGwKiUsnN4VGNtkiCgRmh3nA8ccNvmlkUdgs8oI2yf2+NKQ5A0a27zPVU8SYBzcJZdt30dxjmN98+laBBYOnNd2XN6XCkIsiGu7Gsx5wYAryxBEkRDI/qyfbf8igxVEBzrBoCAYqzdfk4ACMoyPCX+vbpdSQhK74WTkPYA8TRYTn84giCIHYkhkojPUym06zoOVxX8nPK4iF5AoquP0XSAaxIAEXq0ArpAf5B2pMyPJggIqTK6FBVJiQTYtiaYSEDkHJtt/bEAwN/VgWa5zFH5ripuNPhuldyWTdR1BMIhNMsBaDbvVV0siiQ4Wmx9nRRNhz8cwuaAD1Fbn6+6WBQslUaLrc+XnBkbcqvYLGbPVxOLQk4k0SoFkMycT+Qcga5OJCXBMUdFPAY1lsibwxvuBHSO1qDf6k3mTabgCUegC0ZvLJMBsQikRAoxVbauhWXOBwAhrxsdovF0059Mwh02Hq60Bf1WntuAaARSpqdLsxK0vLyBrg4AQErMrtuTSsMTDgMAYkr2nJXxGJRMT6+wS0Vr5nqUaBhCyhBGXV6X1V/MnBsAOnwedAkKlLQOXzgrKNv9XkSY7Fg3ALQHjftTYTsnAGwO+hBjpX1VuCMhq9dYbzD7dPF+bf9OEASxddSLItKcY4gk4payABSK3iF6Qa9F1wUXXICLL74YRx11VH+sZ+eHA0aoDAN0BRQuUxhRB8rTHOWRbP5Xp6pAIw/YNkHQdMRFESlkwyIkXYcGFUnmFGJiOoWoLCOFrF3S0oCuIC54nPOmk0hIomOsoqeMscxtNRk2x6bgHCtnxiaZ22EXtBSgA3HBDS2zMWe6BugKUpAcYw07z5tDTBsCI8Fc2XXoDNBTSDPBOUc6CegMKa5adlnXM3/TQJK5rPeO6QD0dN7cgmbMoTMgyQyxJHJuzZEWs+vmejJrh2LZmWZcCwCkmMuyC+m4VXEjCcMu2OYGgBRcSEGBzFMOu7F2Gdy2bgBIwIUUJOv9y9qd9607mBZzHFsyugLrc3MrOOaYYzBhwgTceuutDnt7eztOO+00LFmyZKvm39HhTEcaIhhLgbHdM7SdIPqTepmjVhRwY7kHA2QNAHnnd1cYNx7Gclb6g8Zei67Ozk5MnDgRQ4YMwUUXXYQLLrgAAwcO7O00BGFh9v+qDUcRzvT/6qL+X/2KrOkIK3KeLVUgGVjSdaRyxLBRiKNARUNdRzi3EEfG85FbXl7WdcRzqlxKmQ17bvippBs5UPYiGJJViCN/bO4coq2oRSF7ofMZdnuRCtsc9uIVtrm1AnMXsgE5BT2KzcGLjC9QeEPMETtmsY88O8t6Cp327gtslELunNuaN954A59//jk++eQTPPnkk/B6DY9hMpnEm2++uV3X1t+oqoqoIENhGtzeJngECm0niL7mJDcw0s9wiCe8vZdCbGdSugcsOgisF8K716JrwYIF2LRpEx5//HH87W9/w6233oqJEyfi4osvxsknn0w9u4itwpdMw5dMQ2cRhFQFIer/1S8ompZXIVDRNaTEfE+joul5dkUvLNBkXc8TV5KuQ2f55d4N4ZYj/LoRQcWEUb4gzK9eKNlKwPOCwi1nbTx/HVIP4grIEYUFyufbBZBzfcUEXeHxdmFkiSvufNpmrjHfXkSMCd2Lt57IrZK4vXjttddw2WWX4bDDDsMLL7yAoUOHbvWcqVQKN998M15++WV8//33CAaDmDhxIn7729+ivr6+6HG33XYbZs6c6bDttdde+Oabb6x/x+Nx/L//9//wzDPPIJFIYNKkSZg7dy5qa2t7tUbGGNJMhCylsbosAI+s9HwQQRC9pgzAiu29CGK7E025kEiKvQpo26JYrurqakybNg2fffYZli1bhuHDh+O8885DfX09rr/+eqxYQb+OxNYhcKAsnsQeHV0Y0daBmkgU6v9v782j46qufP/vOXeqKlWVZHmQLDwy2RgwpA0YBUho7IcNLEYnDcRhCG4gPMwKkLwQEsCkQ8dpyAs0CcPq3yPQYZnwAospNJCmDTaQ2BAbeIQhblAMBmx5klWlGu9wzu+PW3Xr3hqk0mQN7M9atZB2nbvPvveaUn3vPmdvh9L4Q0U1EaPbDswyG5MSipAVAktzKgWaKgSYBExeJuacSiGmFMZWCKZCVszvm0kJVciKsb0JNCDou1r2y7VXZtaYlMUCgGVZsdIna1CMFX0E+39V86HWyrhVEVGu3S/oShkqv7ipJZaK4q0y01VdpIkqdsnqz3SNdJaryNSpU7F+/XoceeSROPbYY7Fu3bpB+8xkMnjzzTdx8803480338QTTzyBLVu24Kyzzurz2MMPPxw7duzwXq+99lrg/euuuw6///3v8dhjj2H9+vXYvn07zjvvvAHH6kgqXU0QBDEaGVQhjR07duDFF1/Eiy++CEVRcPrpp+Mvf/kL5s2bh9tvvx3XXXfdUMVJfIFRhajo/0X7vwaO2zOr8tppQlRkFXVHQHBWkaXSHAc5VS2zVQom169TUzBVGytZLVFTQ6DVsbzQE2hVhGL52FrCKJDpYr0LOjUg0GqIKF4jo8Vq+SmKq6BYsgvj1ZqZLn/vrlKmr1YWLRjL2FlaCLjZHsBdavfII4/gtttuw9KlS3HDDTcMym9jYyNefPHFgO1Xv/oVjjvuOGzbtg0zZsyoeayqqmhtba36XiKRwAMPPIBHHnkEp5xyCgDgwQcfxGGHHYaNGzfi+OOPrzvGfD4PgysQdRf4JwiCIPYn/RZdlmXhmWeewYMPPoj//M//xPz583HttdfiG9/4BuJxtxLXk08+icsuu4xEFzHkBPd/aUiEdNr/1U8Mx0G+ytJAw3awLxQsoqE7DvI1lhwmjfKMVqVgAlwxltYrxRwAWLw8g1aZgdOEm+GsFGjVBROTroiotoywpvirQzBpvqWI/uqOVfeQyVrCzee7inCr8FNFGNWzd6vW0kWnloj0j68hDPuiXAyOBLJM+N1000047LDDcMkllwz5XIlEAowxNDU19Truww8/RFtbG0KhENrb27F69WpPpG3evBmWZWHx4sXe+Llz52LGjBnYsGFDTdGVz+eRz5cqTCaTSUgpYTMDjHFsl7OgS1oZQBAEMVyYUoElDQhZ/9++fouuqVOnQgiBCy+8EG+88QaOPvroijF///d/3+cfovGKovj7dO2hPl3DSBxAXAAyD+QVxa2aV0UgEEFC3AGPSLSU9+gK59CohxD3fc+OqDaUBokWX48uJoFQJIeYYSDk+1IeUW0g5qCFJ4LzRXJwNA0tPoEVVm3wqI0mPRGYLxzOweYcLb7eWCHFAY9aCOtBHw1GHlyTAR9uv6s8BGdo8fUKi2oWeNSBoamB8zYiOUACcUNHqCBIDEX4enclPIEVM0xwRVT41iNuY2JdVdDC97g+eMlHxBd3VLfAC72o/HOGw3lwwxUME7RuxDkr9NcqNWaeqCYq4pMM3vVu0NxrCgDSF2ODYYKr7h8FRWHetQ1F8uAFoaYo7jVnElAjpTlVJXgvesMfV3/hdgQwZwy6T9fWrVsxefLkgG3ZsmWYO3cuNm3aNCjffnK5HG644QZceOGF3sPGaixcuBAPPfQQ5syZgx07duDHP/4xTjrpJLz77ruIxWLo7OyErusVfy9bWlrQ2dlZ0+/q1asr9opdeeWVhZL7rFBZc+RFMEEQxHjFAocA61erk36LrjvvvBNf//rXESp7Iu6nqakJW7du7a/rcYGUgBQcAIe0QxVPXonhwSi8HM6Q0VRkdK0iq0G4GHYOGUVFVpb+91eFgGMzZBANbAoNWzlkOUdW6oGx0mRIGQ0QvpRPxMohD4msDFeMzaqhwHwhKwdh20j75mNSAiZDXleRlb4y8lYe0lKR1UPI+XxMsBiERMBH2LYhLQ5TUwJxRO0MpCWQV3XvXJRCbACQDkVgy8IyPceEtBQIjsD1iJsZSEfA8vlWhIC0XB95riEr3TLySsEHAOS00rlHrCyk5QqLTCgCqzBns8mKPY2RDjdASuZmDgu+BQeyMlrh21I4stIt2x+yc5CF3l2WVrLHLTduALDguy6+OS2419x/Pn57PXBfXP1FOiFA8kF/Xs6cObOq/fDDD8fhhx9et581a9bgyiuv9H5//vnncdJJJwFwV3v8wz/8A6SUuO+++3r1c9ppp3k/z58/HwsXLsTMmTPxu9/9DitWrKg7nnJuvPFGXH/99d7vyWQSt91224D9EQRBEMNPv0XXRRddNBxxjBuEACALosuMQnJaX78/4QCiWSAK0P6vGkzIJrEv1gDTt+E+apnIOiEkZfCp/cRsAslIGD0+0RUzTdiWhm42ISDQJuYSSOsakrLUu6vBMiHzKrobGpH3zTchl0ROSiRlo2cL2TZkXkFKDSPpF0xmCjJvoruh0YuZSwmW5TBVjqRs8sZqZhYyryOjhAJxTM52QzoCiVAU6cK5hG0bMu9+BO6LTYAsCMhwPg2ZzyOvKoH4WnL7IIVEhhtIyoYKHyk9gmRBoBhmBjLvZoyS4bgnuibmEpC2480pJHMrEeY4JNyHBgm41zVqm5B59/PDH4vfd15XvXvWlE9Cmq7oyjEdyYJIK8YNAFnmxu6fEwCyhXMKOaXzARA4177QrSxkPlvX2HKkMAqfm6PjIdVZZ52FhQsXer8X26IUBdcnn3yCl156qdcsVzWamppw6KGH4qOPPgIAtLa2wjRNdHd3B7JdO3furLkPDHD3rBmGUfN9giAIYvQxqEIaBDGaKe7/mpLOIK1phf5f2hd+/1e1cvGG7SCvVn4cGI5T0UtLr7EnTHccdCnBrIhRyLCUV0XUHQeZiqIdrhipKGVfpWCGN7Z8T5ioPl+pcIdSYbPL9n/pvVRQLI9D8+1j8u9PC9iVyvHCVxVQq7Gfq1iYpNyuBubsvehGpZ1V+PD7KbeX76/rjfJjxzKxWAyxWCxgKwquDz/8EC+//DImTpzYb7+pVAodHR3ew8sFCxZA0zSsXbsWy5YtAwBs2bIF27ZtQ3t7e798c85LmUubYYDFiQmCIIg6sGx3tUh/FmiQ6CLGPUwCUdNC1LQgGJA0dCRCRsWX/i8Cbqn3SsEUsp2KZsm640ACFeNDtoO8WllCnktU2A3bganwgKjhBQFjlvf+Kgq0CtFV6aM0tlLMlduLxTWAMsHkFAt0VBdu1QRapd3x2SsFk7+wSLH8PhCsoqg6tURUDTFWR3VFuw8RpdWwD0Z0lRf4GE9YloWvfe1rePPNN/Hss8/CcRxvz1VzczN03c2eLlq0COeeey5WrlwJAPje976HM888EzNnzsT27duxatUqKIqCCy+8EIBbFXHFihW4/vrr0dzcjHg8jmuuuQbt7e39qlwIuFk021EBMOzuioCVZQ2FYAAD+CCaqUnpfslgDGAD8CMkAyTA+eD+rQzmXAZ7Dl4MgzwXuh8udD98MdD9KB0/Bu6HBINluyvb6oVEF/GFotj/qylnwlI4EoUGzNUyN+ORsF2ZuQLcpX17IuEKW/Xsl40uPVQ21hUf5dfRcCoFmlEcW+a7aPcLJkW4QiWrB8f2mRXz2YtjbV4u3CrnA0pizKyRdbLqsfdStr5ybEm41RxfJVvmH+8XdH7/FRktpXdxpZb3+upH9cJyITee+Pzzz/HMM88AQEXxqJdffhknn3wyAKCjowN79uzx3vvss89w4YUXYu/evZg8eTJOPPFEbNy4MVDs48477wTnHMuWLQs0R+4vzPu3LcGZQEVCn0nYtgLJAFWp8n4fOA6D7TCoioCiDOyLEJMStsNhOxyq6qAf/7wAAEICtq2AMQmV9/8cXGThXDhURfb7XKQEbIdDSjagc/Cg+1GA7kcpBLofHmPgfrh7kPsXGIku4guL5ghMyuQwqdD/qztkIGkY/SqTPdYI2zayZWLHzTyJCnEUqiLQmJQwbIG8UiaYqmSjXLuNtFa+5NDdd1Qp0OwqGa2CAKqyxLHczqSE5ghIFlzqVxpbPbPmF0CKECg+1PKLMd3XmNtUKrNl5UsUq/Usq7kU0SfczJrja2TGlOqZq+J4v283TqXCB1DKvNUaXw/jaXlhObNmzaqryMfHH38c+P3RRx/t85hQKIR77rkH99xzz0DDq4hNCFn1yS7nEo6jwBIMiuLU/UXGcTiEYODcAWMCg7nVnAk4QoFlcSiKU/eTbCEZHEcBgwDnTr+X9fhhhSfots0hhISi1HdCUgKOo0ACUBQbkBKDSfDS/XCh++GLge6Hx2i/H1IGA6rnbwSJLoKAKzBaUxm0jPP9XyHLxr5QcAN+rYxW2LaRMPSysa7IKBdjIduu2iyZC1TYDdvt51VteWF5c+aQXRRowbFGlcyaX0T5Pwu9pYi8b+GmBwSNz+7bi+UvylIts6b5BVqV5YxAL+KqyhJFv10REv6VDkXxVu9yQavG8sKae7r60YJhPIuu0U5PTw9++tOfjnQYBEEQX1h6enrQ2NjY6xgSXUMM5wCYgAQD01NgysCqeREjAwMQAxDLA9ICMqqKjKZWFSVjDSYlQmoaIdWEP/cUkyZEWCLOgj2WIkoKKT2COEt5tihM2BELMR78gt3A00jpGuKs1OMpLG0wIwdNtxH3NQKOKhk4YRnwoQkBrmcgDQ1xVmr6GuM5MMOGqlmBOEJqClCBiO8JXATufEJTEGd2aT6eBTMcsJCOOMt610LT0u7cqoU4Uwo+LDAjD8mAsCIQKoi3SMGHUDjirDSnrqXAVAC66l2/UCEOAOCG7l2TGMuDGZY7p24iztz5w0oGzHB96r5Y9MI5uudrQ2UcOgSYUer9F1IdGIyhoRA34O4jC6sCYQAxXppTMqChcL0iins+RXu0cC9CagaMlfajNfD6hBQXElxP1zW2GswJA3kRqHBJ1E9bWxs+/fRTSCkxY8YMfPrpp/2urDiSJJNJTJ8+neLeT1Dc+5exGPdYjBkYmbillOjp6UFbW1ufY8f+N8lRBmMAmIAtNDA1B6aS6BqrMABRCURNQNgMuUID5rG6/FATEkK3EC5brhCBibymIuwTXaqQYGoeqioDHxJhWBA6EPYJDy4BVcmBazrCPsEUgQ3oNjRFwp+/MlgOpq4EfBhSgGkmuOYE4ggxE0wTUFUJpXDZFSHB1TxshQfOJQwbTLMBTUXYJ7oMngfTJBTV8eJTpQTTCj/7fEeY60NwhpAvpVT0IVUF4UID32IcAMA0FWHmipsQHDDN/dk/p8EtMK1wrCoQLmRRdZ4DK1wgrRCLIgCmlQRs8RoacK8T4IqiYoyhQtyA2xi5eF0M7l4/ABA+u1Y4nwq7kkNRH/vtfaGy0vUcCIwxOAAs+cUrbjMUcM4xbdo0JJNJAEA8Hh9TX5SKUNz7F4p7/zIW4x6LMQP7P+6+MlxFSHQNMY4DZNAAhQEiMwmCD/yLCDG6CBVeY3X/18RcFlkAe0WwYEZjzz5sn9AIW5SyUU25PNRcHjtDwQ+thlQ39oVC2Ofbp9VgWmhK9WC7MQGOKF2P6ekepKUM+NAcgeaebuyLRrDX52NKNoOGTA6deiNMUcp2NPbsQ54xdIabvBZOsbyJxlQKyZCBnXqph9S0TA9E3sLeeAOSwl1CyaREc3IfBIBOvQlWQVE05vKIp9KwOUNnuNRvbFqmB0beQlrXsNMolQyf0NMFIYFEJITdWsQ778ZUDwBgbzyKpOIuxWzJZRDJuIJplxZHThQaI6cSEIVlkZ0h91oxKdHc48YnGLAj3AxIoMEq+bYUjp3hJvce5nNoSLmZrpyqYGfI/aBvy6YQyrliLKOr2GnEvTnVwpxpn70p1eWtcy+eKy/EUpRZfj99ETVNxFOpvgfWQAgDjtChSbvvwQRBEAQxBqFGHkOMYBoEGFQ4fQ8mxiTF/V+HdO3D9EQP4nkTbKA7VvcjEdNGRg1mEgzHgWCsojR42LKQ1SoLbhi2QLZs31XYtmEpvEKAhmwbuTIfxT1a2Sp7wgQLViNUhYAiZMX+McOpvq+stM9LrRgrWHC/VNFeu7JisBBHMeHj3/9lBPZo+cbbNeyF8Q5ncIpZrhp7yGru/6o1p78YR80KiKXG0v5Vg1aNIhpWP4polB87EBQIGJxEF0EQBDE+oUzXkMMQZnlwRnp2vBPo/8WBpG4gEdJHbf+vkG1XCKmIaSGtVX4MRCwbO6ORgC1suX3OysVO2Kr0qzkCqpAVlRLDBdFVXlzDrZRYNtaqNbZQXKOscqFeqFzoFyl9laf3F+Io+ii3Gz4Rla8iolx7ZaVDmzOvAbIaqIpY3UewWqK/omHf4/1izC+uAmXka4mrgt3vu9x/XwxFuXiFDd7HFx3DMLBq1SoYhtH34FEExb1/obj3L2Mx7rEYMzD64ybRNeRIKExi9Oc9iKGEC3dJXlMu7/X/SoSMij5SI0XYqqwuCLjiqrwpsiIENEdUiMdIFXEFuEJqd1mPr3CNjFbYtmGq3BMjgCsYFCGRMyqzX0C1SonFTJdaYTMVJVBxMuRUiivAn+kq+fALnfJMl2dXKjNdlq/MvV+4mTV8mFUybuW+9ToyWkVxxQrNpsvH62Xiqli9sUJc1aiAaPVHdA1BposYPIZh4NZbbx3pMPoNxb1/obj3L2Mx7rEYMzD64ybRNeRw5IUKfZAdxYmxy2js/9VgWRXiCgAiloVdDZGysTbyqhIQRu5YG2m9cnmiImSFGAtbFmzOAkvmALdkfU9ZGfpwUURVLEWsFFe80IvLVILCrbZAq7QXfQBBoVMcW2H3NVH2C7pStqx6hqq/2TKziqArzguU+pCV2yvElZfRKs9cVRddxXtUPr4/ywvLfQ4EKTHAZp4EQRAEMfqhNXBDDIMNCxocSZeWqNz/FRuh/V9R06oQTCHb3c9VntFoqDKWSYmwbSNTZXmiu+SwzF4lK2bYDrhEzSWHmSp2mwf3m/W2PBGo9G1UzYqVxFWuyh6tSnFVuZxRKew3c+2Ve8iA6lkx1391MWYG9nRVirdycVW0GzXEVaW9d5FWubywH3u6hmB5oQ1lwM08CYIgCGK0Q5muIYbBgcZMOFAAbrov4gsPAxC1TURTaQgOpDQDPSGtQiQMB4qUUJGDVHRosDx73Moha0hoyAXGR500doXCAXvEsQFuwlZtaL4iMVEnU+GDS4mQyCIVDvqI2XmAmzC1UJnvDBzVARTLi091BBTkkTa0wNgGO+f60JWAPSwyAHdga4ZnL/oABxzVggZXPDU4bhyWyqH6Sty7PmyYuu75YFJClzmAA5bKPHtE2N7/27aqevawk/XsjlbyE5JZoFAkwr2Ghb5cMus9+hKFGDVHgDETYG5Z+OJ1CQvL8y04A+cmOICwyJXm5AwKy0MBEBLZgL14roYvFv94Q+ZQrLAhOMB5vq6nclxK7zoPHAYJICv1PkcSBEEQxFhkzImuSy+9FP/+7/8esC1ZsgQvvPBCr8fdc889uOOOO9DZ2YmjjjoKv/zlL3Hcccd57+dyOXz3u9/Fo48+inw+jyVLluDee+9FS0tLv+JTOBBSc7CEBh7pAlczfR9EfKHgAJoANDmAkAwm5zCrLOcbKnRHgMUEpvDugD2qWsirCqb4MklcSugRE1HdQNQXTojZkHGJyUoy4COmmwUfvqqDjgCPWggbOnTfksqIZoPHHDTpPh8SiITysDnHFJ4oxSxdH5qmBnw3aBZ4VCDi9y2BcDgPSCCuJREvmLWCD8FZIO6IZoNHHXBVCVyTBsME0yV035yKkFAaXOES1jXvWoW4Ax51hUvU0BEuxNKgW+CFBsRxLYlYsf9XwTcY0KwlC9caUBuKDY0ZJhViLMYNuOJqCnftIbU0p/RdrwbdBueFKo0+e9QwwYu9uJSSPRIywQwZHC8BI5L3SudL37x9oQgJHh3cwyVuR6Dl8rCcUN+DCYIgCGIMMibXwC1duhQ7duzwXr/97W97Hf9//+//xfXXX49Vq1bhzTffxFFHHYUlS5Zg165d3pjrrrsOv//97/HYY49h/fr12L59O84777x+x+YIQDoqFMkhMs0Qqcn0olfNF5KToHc3I7qnEXr3BOQzLdhrT8cuMWPIXnZ6SoVtjzMd6JmI7ZgZsGezrUjlp2KXDI6XqcnYZx0QsHVb0yB7JmFnme98tgV2ZjJ2lPlmyUnoybcFbD1WG0RPpe98pgUiNbkibvRMgpOejB2++JLWARA9k5HLtQbizmVdH+VzitQkiLLz2Wu75yJSk7HHmebZ0/mp3r3aWSU+Jz0ZnTJ4nURqMqzMFOyUlb6z2dZS3GbJdypfsmdzrT57KXazMKd7TlNL99f376nHbPPFMsk3vs2778VY/P732dMgekp+0mXXrLdXj9k2+P8XMs1gQgk01yZc7rnnHsyaNQuhUAgLFy7EG2+80ev4xx57DHPnzkUoFMKRRx6J5557LvC+lBK33HILpk6dinA4jMWLF+PDDz8csnhvvfVWMMYCr7lz5466mF955RWceeaZaGtrA2MMTz311JDM2df9yuVyuPrqqzFx4kREo1EsW7YMO3fuHLK4L7300orrv3Tp0hGNe/Xq1Tj22GMRi8UwZcoUnHPOOdiyZcug/ddzj7q6urB8+XLE43E0NTVhxYoVSNXZU7CeuE8++eSK6/3tb397ROO+7777MH/+fK9BcHt7O55//nnv/dF4reuJezRe6/4yJkWXYRhobW31XhMmTOh1/C9+8Qtcfvnl+Na3voV58+bh/vvvRyQSwa9//WsAQCKRwAMPPIBf/OIXOOWUU7BgwQI8+OCD+NOf/oSNGzf2LzgJuIvJGCB0etGr7lcor2Byj4NZXVm0JiyE8hy2NGAhNOCXLQ2E8gxJtSFgN0wFGaUBJgsH7OE8R0qNBmxCGDBMBUktaNdNDgEDqTLf4TxHhgdtcDQotop02VjNVACho6dsTsPkkFJHSomU+dCQZ+FA3Lrl+sjwSMU5QuhI+3w40oBuqhV2zVK9+5BSGnx214eAjqxvvG5xQOgwfbE40oBa8JP1xaLYmuc7y0txq745c77xfrt/fDEWiGAsAXthvBQ6uK1X2LkvFggdOSVciFEN2P3z9vUqP3bALzCMjlqfo4d6Hhj6+dOf/oQLL7wQK1aswFtvvYVzzjkH55xzDt59911vzO233467774b999/P15//XU0NDRgyZIlyOVyVX0OhMMPPzzwYPS1116rOXakYk6n0zjqqKNwzz33VH1/IHPujwe8fcUNjL4H0+vXr8fVV1+NjRs34sUXX4RlWTj11FORTqcH5b+ee7R8+XK89957ePHFF/Hss8/ilVdewRVXXDFkcQPA5ZdfHrjet99++4jGPW3aNPzsZz/D5s2bsWnTJpxyyik4++yz8d577wEYnde6nriB0Xet+wuTcmxtXb700kvx1FNPQdd1TJgwAaeccgpuu+02TJw4sep40zQRiUTw+OOP45xzzvHsl1xyCbq7u/H000/jpZdewqJFi7Bv3z40NTV5Y2bOnIlrr70W1113XVXf+Xwe+XzpyWwymcRv/u1niGoGJBS0h/6GKKcnt8TAKfb/6g4ZVcu190XUNNGYN/F5LBqwt/WkkFVV7AuXlnMxKXHo3n34eEJjoAhEPJ9HSyqDDycGH25MT/RAMIbP4yXfXErM2bMPO6MRdPl8N+VymNqTwdYJ8UBRixmJJMKWjf+eOMErXlH0kdFUfNIU98Y25vJo60mjK2xgZ7TBs09L9iCWt7A91oBEqNSbY86eLnCJwJwRy8LM7h4AwF8nleacnM5gUiYHS+H4qLnJ8zGr240vo6v4pDHuXae5e/YBABIhHdsL19bve08khN2FqpATs1lMSWUBIHBdDuhJIZ5zl+X5Yz9wXzcM212i+Fk8ih5DB5PAnL1dXpPmbY0xpHUNmuPg4K7SssxtTTGkNQ0NloUZhVj844vXsMinjVGkdD0QIwB8Ho8iWVZlshZtPSk05ga3vDAlDGzIHQgGB9+55RdIJBKIx+N9HzjOWbhwIY499lj86le/AgAIITB9+nRcc801+MEPflAx/vzzz0c6ncazzz7r2Y4//ngcffTRuP/++yGlRFtbG7773e/ie9/7HgD3oWNLSwseeughXHDBBYOO+dZbb8VTTz2Ft99+u67xoyFmxhiefPJJ7zvCQOfs634lEglMnjwZjzzyCL72ta8BAP7617/isMMOw4YNG3D88ccPKm7A/Y7U3d1dkQHrjf0d9+7duzFlyhSsX78eX/nKVwbkv5579MEHH2DevHn485//jGOOOQYA8MILL+D000/HZ599hra2tkHFDbjZl6OPPhp33XVXXT5GIm4AaG5uxh133IGvfe1rY+Jal8e9YsWKMXOte2PMZbqWLl2K3/zmN1i7di3+5V/+BevXr8dpp50Gp0bJ4j179sBxnIq9WS0tLejs7AQAdHZ2Qtf1gOAqH1ON1atXo7Gx0XtNnz59cCdHEGUU+3/N6k7i4K5uTE5n+lWeO5Y3kdSDX56ZlIiaZkXp9gbLgs15RU+rmFlZbp5JiYhlIa0HhWCD6e5FKq9+2GDaEJwFBBeTpcbK/mqBEcv1UdHIudAsubx/WLGJsn98yLbBJSoqKxbH5tVgP69wldLyTJYqHWar9ATrzV6th1i5/2AVRbUwpwxUFyyO1x3HE1zF+Mt9A76KhuV2tXpFw5rj+1G5sPxYYmgwTRObN2/G4sWLPRvnHIsXL8aGDRuqHrNhw4bAeMDd81wcv3XrVnR2dgbGNDY2YuHChTV9DoQPP/wQbW1tOPDAA7F8+XJs27at5tjRErOfgcxZz/3avHkzLMsKjJk7dy5mzJgxpOeybt06TJkyBXPmzMFVV12FvXv31hw7EnEnEu6Doubm5gH7r+cebdiwAU1NTd6XaQBYvHgxOOd4/fXXBx13kTVr1mDSpEk44ogjcOONNyKTydT0sb/jdhwHjz76KNLpNNrb28fMtS6Pu8hovtb1MKoLaaxZswZXXnml9/vzzz8feMJ05JFHYv78+TjooIOwbt06LFq0aL/Gd+ONN+L666/3fi9mughiOPD3/8pqChKGgWTIgFOjAIcrrmx0+rJCgCteTEUNlGIHXIGWqpLdaDAt7Kjig0sgVSboomZ14dZgWUiX9/KyLXAJpMtEVENBGJXbi2LMX7ZecxyoQsLhLFDivCiuqpWyB6qUra8i3PxCJ1uz5HzfpehriqtCNkuyYJn34pyClXpoGU7Jh+Mro+8XUQG7TwiJWna/f7t6efl6GIoeXUQlvT0w/Otf/1r1mM7Ozj4fMBZttcYMloULF+Khhx7CnDlzsGPHDvz4xz/GSSedhHfffRexWGxUxlwtpv7OWc/9GugD3v6wdOlSnHfeeZg9ezY6Ojrwwx/+EKeddho2bNgApcrDlP0dtxAC1157LU444QQcccQRA/Zfzz3q7OzElClTAu+rqorm5uYhiRsAvvGNb2DmzJloa2vDO++8gxtuuAFbtmzBE088MaJx/+Uvf0F7eztyuRyi0SiefPJJzJs3D2+//faovta14gZG77XuD6NadJ111llYuHCh9/sBBxxQMebAAw/EpEmT8NFHH1UVXZMmTYKiKBWbBHfu3InW1lYAQGtrK0zTRHd3d+Afon9MNQzDgGEYNd8niOEibDkIWxm0pDNI6RoShoGUrgWyNw2WhYwezCIB7nLBakvHYqaFT+PBL0URywKXsiJzFTXdqoXlws1twlzeQ8uGImSluDKLIqpMXJkWJAuKK1UI6IWmyI5vzlL2q0xc2dXt4Sp2w3H7hwFBcVUUeUBZtqzgQ7KguCoKN8fXFJr7xJW/oXOorFmyLNyierJl/n5hRi27T6Tl6ugXppc1Yy7/N1MLVQhQH3jCz2mnneb9PH/+fCxcuBAzZ87E7373O6xYsWIEI/tiMJoeTFfj6quvxrvvvtvrPr/RSK24/Xt/jjzySEydOhWLFi1CR0cHDjrooP0dpsecOXPw9ttvI5FI4PHHH8cll1yC9evXj1g89VIr7nnz5o3aa90fRvXywlgshoMPPth7hcPhijGfffYZ9u7di6lTp1b1oes6FixYgLVr13o2IQTWrl3rpSwXLFgATdMCY7Zs2YJt27YF0poEMdpgEojlLUxLpnBoVzem9qS9L/+NORMJo3xpoSuuesoyVBHLcvsklYmUmOlmqMrL2bs+gmLJsB1ojqjIfhXFVfkSxQbLXXLon1OREiHbQVatvuSwYtmiVVu4ufZg5qrY0NhvDxd8SBYUXUVxZfNgA2lviaKiBPahFZcF9pXlqt8+cD/VxBiXMtB0uehf84lO//h6oKWFw0c9DwzLaW1t7fMBY9FWr8/B0tTUhEMPPRQfffRR1fdHY8wDmbO/D3jr9TtY/A+mRzrulStX4tlnn8XLL7+MadOmefaB+K/nHrW2tlYUnbFtG11dXUMSdzWKiYLe/r3vj7h1XcfBBx+MBQsWYPXq1TjqqKPwr//6r6P+WteKuxqj5Vr3h1Gd6SonlUrhxz/+MZYtW4bW1lZ0dHTg+9//Pg4++GAsWbLEG7do0SKce+65WLlyJQDg+uuvxyWXXIJjjjkGxx13HO666y6k02l861vfAuCu8VyxYgWuv/56NDc3Ix6P45prrkF7e3u/N4gqCsAUG1JK8Mge6tNF7Dc4gGYAzTYgBHP7QukGGny9snRHADEbzVp34NgosyAagZayXl7Nah6ZsIoWXtoToAoJI5yHETLQ4vMdZjZ4zEZDKIGIT6M1qiZkXKJZKxV8YBJoMHLIq0pgTsMW4FETXAvOGeUWeNSBbuho8WW6GvU8uCoRDpdiUYSEHnEL2MSMhNdvLCQct28XQyCWmOL6thWGKUrJHi/4hsq9GLkEQmG36hHXFLTwLu+6FntVKb7Yw9zxem5puoaWQv+vmOrOCQC6z96o58EVVwGFjJI9auTAClq2aGe+WPx2RUiv/xcAGAW75kjwqM9emNftiVYqhKFpKlr4HtRDWCmd32DgdgQwZ4AxEnFF/A8Mi4USig8Mi3/bymlvb8fatWtx7bXXerYXX3zRe3g4e/ZstLa2Yu3atTj66KMBuMviX3/9dVx11VXDch6pVAodHR246KKLxkzMA5mznvvlf8C7bNkyAMP/gLc/D6aHK24pJa655ho8+eSTWLduHWbPnh14fyD+67lH7e3t6O7uxubNm7FgwQIAwEsvvQQhRGAV1UDjrkaxgEyt670/4q6GEAL5fH7UXuu+4q7GaL3WvTGmRJeiKHjnnXfw7//+7+ju7kZbWxtOPfVU/OQnPwks8+vo6MCePaUvDeeffz52796NW265BZ2dnTj66KPxwgsvBNZ53nnnneCcY9myZYHmyP1FSkAKDoBD2iGMseKQxDihqHkaTcBUOTKaioymIZLPI6WEkZXBbFRTLoWucAh5WbanKc+Q0CMQsiR04qYJ2+FI8qjXTBcAYvkMcsxABhHPzqWEmksjZWjIytL/o2HLhrQY0qoeiCVk5iAtBT16GKYsZVya8mlIIZEMNUAU1uKpQoDlGRwO9LBSLA2WCWlxWAoPxBI2c5CWipymIitLlRUbC76zvBQjFwI8zyABZHwxhmw3bgBIqway0s2waZYJabnxpvUQcoXrGCnMWbQXr2/cTEM6bmBpo3SuzXmG4kdGyojAkhyKEIDJvEtdtOu248Xit4dtG9Iq3a904VoqthmwZwpxqr7YASCjhZCV9f1pCFml8xsM0gkBktPnZRl9PTC8+OKLccABB2D16tUAgO985zv46le/iv/9v/83zjjjDDz66KPYtGkT/u3f/g2AW+3u2muvxW233YZDDjkEs2fPxs0334y2trZABbzB8L3vfQ9nnnkmZs6cie3bt2PVqlVQFAUXXnjhqIo5lUoFnpBv3boVb7/9NpqbmzFjxoy65hyJB7y9xd3c3DwqH0xfffXVeOSRR/D0008jFot5e2UaGxsRDofr9j937lysXr0a5557bl3/Lg477DAsXboUl19+Oe6//35YloWVK1figgsuqKsqXV9xd3R04JFHHsHpp5+OiRMn4p133sF1112Hr3zlK5g/f/6IxX3jjTfitNNOw4wZM9DT04NHHnkE69atwx/+8IdRe637inu0Xuv+MqZEVzgcxh/+8Ic+x3388ccVtpUrV9Z8OggAoVAI99xzT6+9L+pBCACyILrMKCTX+jqEIIYVLQ80AogzAIhgXzSCHmF4S+MaTAsir2B3dEJARE3JZpCWYXSzeMA+MZ1AQmtEUpaKayhCQEtzdEYjSAYETR4yr2BvOIa0LP2/EM2mIPM6dkebYPsEXUu6Gw4k9iilWHTHAc9yZFUF3azRs0/I5SDzKnoMHUlZKlsfy6Ug8yYSkRCSMlI6n0w3pCPQrZViVIWAkuWQAPYZUfQUxFXMNCHz7sdjVzjuiRAjl4HMu2O6Gho9sdSY7YEsLGncG50ApyAMp2TdOQFgT2wCpGTgUuKAjDunZMBe5toN2wFyrl0wYC9vBmQwFr99gpmDzLvXVDKgizVDSiCUL8UIAHsL8zbk0pC+J4bFOIvXq8g+33n1RXMuAWkNPjslhVH43CTR5aevB4bbtm0D92V+v/zlL+ORRx7BTTfdhB/+8Ic45JBD8NRTTwU2/n//+99HOp3GFVdcge7ubpx44ol44YUXEAqFKuYfCJ999hkuvPBC7N27F5MnT8aJJ56IjRs3YvLkyaMq5k2bNuHv//7vvd+LRbEuueQSPPTQQ3XNORIPeHuL+7777huVD6bvu+8+AG55dT8PPvggLr300rr9b9myxasgCNT372LNmjVYuXIlFi1a5Pm/++67hyRuXdfxX//1X55InT59OpYtW4abbrppROPetWsXLr74YuzYsQONjY2YP38+/vCHP+B//I//AWB0Xuu+4v70009H5bXuL2OuT9doJplM4lc//yH16SJGPYIzJHUd3SEDE3I5OJxjZ0MkMObgrm7sDYcCvbyKfaE+aYoF9lFNyObQmsrgw4lNgeIaByRTiFom/ru52SsWAQCH7t0Hi3NsndDo2QzbwYH7EkgaeqD3V9H33kgIu3wxHpBMIZ43sSMWQbfvA/SQvfugColtjVGkC/vL/P2s/jah0du3FM/ncUDS7Vv13xMnwCksUWxJZdCczUEyYIuvh9jM7iQilg2bs0DfskP37oMiJEyFo6PQ50sVAofs7Qbg7p8qnqu/n1dWU/FxoRdZsZcZgECPsmIPsfLx/v5Yfv8zEkk0mMXS+Bx/m+DGM3tfwivIYXOODye69oO6ur39aIIBWyYFyyH3RrEX2mChPl0EQRDEeGdMZboIghgauJBoyuXRlHMfCnSHdGiO41XdC1s2VCGQLKvOGc+bsDmrKFwRM01ktWA1w2I/sJShBwRX2HKrGe4LVVZEBCoLbkRrFOKIFotr+GIxbLeEvFv9sGQvFtywOQsUivCLE8e3P83fK6wouJiUXnGNbFn1w2KBjmygQEepyEVNe5XqhwCQ0yoLelSMt6v7r1YBkUkZqFyY8xXX8PcFy6v1/0koL8BBEARBEERtSHQRBIGmnImmnImspiJh6AjbNtKaFhAiANCYr2yqrAiJiGVjd0OwumiD5fbhKm/OHCuIq3I/1cQVkxINllv8IquW7GHLBi9klixf6fOGKmIJKImriiqHVYQbL1RQLLeH7FIPLb+fsK+0vN8eqSG6gnafn4C46l28+UvR+8drPgHotxuOCDRXLvrxVz8EghUT+6K8MTNBEARBELUh0UUQhEfYsn2NghW3YXKh/5dhOzBsp6JRcszMg0kgqQezYrG8CcEqM1SxvAmb80CJ86Jwy2pqoA9Xg2WBSVeg+bNltbNiBXtFw+XKkvOaI7wsTyArZvpFVCnGhhriqsEnijIBceUbr1YXVxmfiDKqiCijLJtUtIcrxFLR7lS1h2yrzK4U7MHx5U2je6NcsBEEQRAEURsSXQRBVCVsOZhmpeBwhh5dB4eEpfCKXl6NeTdD5u9lxaRE3LSQLmvYbNgOdEegK1wm0IrZrwqBVmNpoZcVK2XLmJReFintsxebMwPBzFWDVSoe4RdjRbEkWPVmyYIHM0LFnmA2Z17DYX+2zObcuzb+pYg2595yTH+2zD/en+XyN10O+eyClXpr+cWYv3mz3w/gF2PV7fVAmS6CIAiCqB8SXUMM5wCYAMDA9BSYkh3pkAhiUKgAJhSyLUIHpuXTyOgabO6WM29gGXRHdMRZScSEHBuKloMdCSHOSsVk4sIEM0yIcAhxVvp/o1lmwQwHMmwjztKl8SwFZgDMcBBnxT5cAmElA6kCql6yhxwbXM/B4YCuCehlc9oKQ1gVKC6CnCBzYIYNU+WIcuGbMw1mSNgaR6xgZ1KigafBDMDUFMSZa1eFgKa5xS9sTUW80Gcq5Nhghlv8wtZVxJkrbqKFWMrtcZkHMyyfn0KDa7gxAoClKZ7/RuZeL3c89+KJsgyY4f5sK6X4o7xkdzhDRCmOd88VcEWaoQkE5XBtIop7b4YC5oSBvAAg+hxLEARBEGMREl1DDGMA4wJSMjA1B6aS6CLGDwqARpFFY879Ui8YwHQBqUuEfeIqJixAdwBNIuxfFijzkLoE16QnfpgEwiwHx2DQFIlizklzJFQlD0vnMJTSGruQcMA0C5bKEfKtvYsKC0xzYKsKwqzHs0dggmkCtqYizEpf6sMsB6YBjqYiXBAzXAI6zwEccPSSXRMCXHXFktA1hAuiKCTdWEp29+cGaYNpdoU9AjdGABCaz87cGMvHh1keTCuIIl0tzVuI3fXjxskkEOI5wLMrnr14TgDgqArCTIBLQFNy7k0F4CgcYVZfZQwuAdV37GBhjAFMgDESXQRBEMT4hETXEOM4gOQqAAUiMwmCSsYT4xReeAkAiqkhZRjeMsCmxD50Gzo6Q6WmxYbtoDmZwL6wgZ2itC8sns9jQk8aeyMh7Bb+vloZiEwOe6IRdIlSSfgZqSSEaWNXrAEJUUq1xJPdEEJgVzyKHuHmuRQp0ZzYBwFgZ2MMaeHGF7ZsNPckIQF0NsWRFe5HYWMuj6aUm2nbMaEReeGqismFWACgs7lkPyCVgij0uNrR3AizYJ+VSkAU+lft0Ev2eHIfRGF5YdEPkxITkvtQrH/RWZhXERLNyX1e7mdnIU7dcdDck/A6Wu1qjCItdIQtGxN6kt712BN3r0/EsjAhVRKh+6IR7NVCaDAtNPns3eEQdurBtgG1iOVNNKVSdY2tByEMQKiQYH0PJgiCIIgxCIkugiAGTSxvIZa34HCGnKqASyBRVp0wXmjMmygrQ1/sNVWtPD0A9Pj2Z3Hfvq1U2b4tVQjIssIdxcIaggWLXBTtDmeBPWpRs3pp+YC9SrVEm/PAfq6w5Xjji3bdccvZl/sJ27ZXWVDw0v4sfyEO//6sSNn+rGIFxPLiGplicQ2rht0u99OfyoVURIMgCIIg+gPvewhBEER9KEJ65dlbUxlMymShFfpDNebNikIcvFASPq/ygMgJ2TY0RyCnKoECHVHTBJOugPKXs48VBFpaCxbuiOZLVQsDdrOymiHg6/3lsyuiVBTDL+gCBTp0X5VDX/VDv59gVcTqpeX9VQ79oiurlkrg++15lUNUsdu+oht+/0HxFqxo6C/J3xflgo0gCKI3HnjgAZx66qnDPs8LL7yAo48+GkLQUmVi9EGiiyCIYUF3BCanszi4K4HZ+xLQHIFkRfbLFVG1slzJUOV4ABV+Sr2/gj2+omZltkwVwhNR/mqJxd5fQDCLFg1UOSzZ/SIqVaX6IRCslhipUVreX4o+INJqlqL324PxFwn0BfMJpJyqeOLNL5xckVb/nwMSXQRB1Esul8PNN9+MVatWDftcS5cuhaZpWLNmzbDPRRD9hUQXQRDDTlHkNGdzmJbsQSxvgkmJRm/JYQ1x5ev9xaX0MlT+xsq643g9rvziKlJozgwERVQxK1ZhN6uXkI/WyFwF7Jre53i/uCqKNCZlQCwVRZQiJAxfSfaiH80R0BxRMd6/dNFvNxzHE5JAaSmiYTvwFWysaAPQG7oTPJYgCKI3Hn/8ccTjcZxwwgn7Zb5LL70Ud999936ZiyD6A4kugiD2G0y6+7+mJVM4pKsbEdNGXlW8pXCAm7HRHFHR+yvmW1po+xooF0VUpqyxcrywtDCjly1FLIirjK56S/OA0j6vjKbC8dmLGS2/nUvpZXtyquL59zdczqulPlz+pYiWwgNL/4r7uYr74Vx7cD9XsV9Y+ZLAYgas3F7MsEXMsvE1/fRjaaFFWS6C+CKye/dutLa24qc//aln+9Of/gRd17F27dqaxz366KM488wzA7aTTz4Z1157bcB2zjnn4NJLL/V+nzVrFm677TZcfPHFiEajmDlzJp555hns3r0bZ599NqLRKObPn49NmzYF/Jx55pnYtGkTOjo6Bn6yBDEMUCGNoYYBbrk2CXDTfREEUYECABwwBHBwdx49ho6krmOCmQe4iVRIgYacN77RTAPcQrrcbqUA7lTYY3YK4BJpo2TnUiLiZAAOZHx21REwhFtWPevzE7IdKMi7doN79gbLAmMmwICMYXj2Rivv/T+fDdhzJbtessfsrG+8XtWe01WohXL8MTvj2S2Vg3ETWpldcECoFjRYiDqZwGeQpTnQkKuwm5oRuHa9EfXFNnQwABLUbpkgRi+TJ0/Gr3/9a5xzzjk49dRTMWfOHFx00UVYuXIlFi1aVPO41157DRdddNGA5rzzzjvx05/+FDfffDPuvPNOXHTRRfjyl7+Myy67DHfccQduuOEGXHzxxXjvvffc1hMAZsyYgZaWFrz66qs46KCDBjQvQQwHJLqGGIUDTLFhCwYe6QJXMyMdEkGMeozCa5INt8+UCoRDOozCH1EmgZiRBwwgZBgwCokoLiXCIVcAhEIluyoEtEih15XPrjsCSoPljZ9SsIeEAx51MzhGSMeU4r4nZoNHCw2PDR1TChmtiFLdHlUt8Kib6dINDVMKmS6/XdNL9phmghd6kKm6iim8UFpeN8FV165oKqbwLne8YYIX+nYxVcEU3u3addPr5yUUjik8WWnnDBPVSjsY0KiXSs33RdwXw1DB7QhkzkHWCfU9mCCIEeP000/H5ZdfjuXLl+OYY45BQ0MDVq9eXXN8d3c3EokE2traBjzflVdeCQC45ZZbcN999+HYY4/F17/+dQDADTfcgPb2duzcuROtra3ecW1tbfjkk08GNCdBDBckuoYYRwA5OwS3T1czBG/o8xiCICppSAMZXUNS16EJAZHOIq1r2Kk3eL2/mrM5iEwOWV3FTqPUE2xKKguRzyOrqej02aem0xB5C3lVQacR8+wHpFIQlg1T5eg04p59Zk8SwhGwFY4dRhzFplmzkwkIIeFwhu1GIyAKhTuSCQjplqjfoTdCCgYuJWI9Ca8P147mRgjBoAiBeDLp9eHqbIrDZhyqE7TvaowhJxRoZfbdsQakFc21F3qOAUBXQxjdqlFhT4QM7NbCrn+fPaOr2KVH67onipSIJxMY6i1dQhiwHANcDq2YIwhi6Pn5z3+OI444Ao899hg2b94Mo6wQkp9sNgsACIUG9kBl/vz53s8tLS0AgCOPPLLCtmvXroDoCofDyGTooTcxuiDRNcRIKLCkjhCzAaHD+/ZGEES/YAAaskBDtrj/SEdGCcNC6Y93NJsDhI5uLRKwN+SzgNCR8NmZlIjkMoDUkdBKflQhEM5zADqSasizG44DzXI/IpNGyR62bCi2uweqR9c9e4NlgjtuQY20ocFkYQBA3DTBCvaMpiJfsEfMfOEzAjAVjqwSKfjJeXbBGXpU98FN1CzZAaBHi8IBq7An1SgsKJXj1QZY0NFg5QP2VNk17Y2QaQaOHTKEDgYgzGg5NkGMdjo6OrB9+3YIIfDxxx8HRFA5EydOBGMM+/bt69Ov41QuMNZ8+02Lywer2cpLxHd1dWHy5Ml9zkkQ+xMqpDHESKjQYEFhVN6LIIaayeksDurqxqRMFrG8Cd1xGyL7S843mKZXtMJf5bBYiAMIlpz3VzP0+4n67P5S9P4qh8Hqh1ZVezQwvnr1w5p2rXr1w6ymeEU9/HbH19S5vIlypjDHoIpoDGOpeBUOfPVLCIIYhZimiW9+85s4//zz8ZOf/AT/+I//iF27dtUcr+s65s2bh/fff7/ivZ07dwZ+/9vf/jYkMeZyOXR0dOBLX/rSkPgjiKGCRNeQI2Bwqu5FEMNFsf/XtGQKAJD3VT4E3CbMgNuw2F/lsDFXKExRVi0xXhBFphJs0FwsW+9wFhAmRZEmWFAsxfIlMdNTU1z5+39V2pms3reLybKmyzXEWC17TvWJNJ8fwYCcWv+Ch4ayaohDCQkughj9/OhHP0IikcDdd9+NG264AYceeiguu+yyXo9ZsmQJXnvttQr7008/jSeeeAIdHR3453/+Z7z//vv45JNP8Pnnnw8qxo0bN8IwDLS3tw/KD0EMNSS6hhwGR9K3B4LYX4RsB4fu3YcDkinE8qYnihK+rJUipSdCkqGSXRUCEdN9SOLPfmmO42ugXLIbjuOVhE/rmtdoOGTbUAvLW7K+0vVhK1gqPu8rCV/snyVYqfR72LYCPbCKoi5sl3qOuXbd8+8fXxRp/hL1fntlPy8V9X5ccSm9a0IQxBePdevW4a677sLDDz+MeDwOzjkefvhhvPrqq7jvvvtqHrdixQo899xzSCQSAfsZZ5yB22+/HfPmzcMrr7yCe++9F2+88QYefvjhQcX529/+FsuXL0ckEhmUH4IYamhP15AjkZUGwqBsF0HsL5h0M1Nx35LAYC+vvLe00N+IOV5jaWHQXn0pYk+Nhsv+LJd/KWLQHsxmFcWbPyuWUxXvHPx2wUvNjP1LF4GSSCvPSBUzYOX2jN6f/lzDl+UCAEdyqIxEHUGMVk4++WRYZZ8Ds2bNqhBT5cybNw9nnHEG7r33Xtx4442e/YADDsBjjz0WGHvVVVd5P3/88ccVvmRZsZ1Zs2YFbHv27MHjjz9e0buLIEYDlOkaYri0wCFhQ+l7MEEQw8aMRI+3/6sp5/a5ypQtOYznXbup1l5amPYJk+J4yYL7xeJm3yIt5bP794sF94XV2v/ls2v+/WKlL0D+Zsx+u/Rl0qJlosvvqy+iw9wU2QFHXtBzQIIYj9xxxx2IRuurkjoYPv74Y9x7772YPXv2sM9FEP2F/sINMYoChNU0TGGAR/ZQny6CGEFChVexEZimKmhleyEZoAiJhkLvL6GraOFudS1FSERCRTGmoKXQC0sREuGiXeGYrLhPd1UhESrYHc7QrPns4ZJIixoJRAt+inYACIdDMArxFP0AgBEy0MIZFAGEQ6XGxaqhoYUr4BKI+OzQ3HNgEoiGcu45w13WOEVJFHqd5cAKOksyoEnv/Qm1nyY1Dx4dnmqs3I5Ayc9CTtQuPU0QxNhl1qxZuOaaa4Z9nmOOOQbHHHPMsM9DEAOBRNcQIyUAyaEyAWmHKlLhBEGMHLoFTMiVikdIy80MJUIR2NL9OW6anj2ph5CX7th4Pu/Ze1QDWalV2FMhHVmpV/jJ6Cqy0i3LHvPZTZUjjQgggZhVsgsOJLnbXyxqmZBWaeNVIhSBkBwR0wrYU3oIOakibNmQps+uujEZtg2YzGtikfXF1BdcSih5NmwNMKQTggJAY8O7hJEgiNHBunXrRjoEgtjvkOgaYoQAIDkYOKQZheT175kgCGL/UJQaEoXqhE4MOeZ+HE5OdUM6IdicYbcywWu1NznTDWm7Jep3xSZAFCpQTCrYAWB3QyPy0l2mOCmdgLTdmfYaUfQUxNhEn32fFkGyIHwmpJOQhSV8iZCOpHSX4jRlkpCFYh9ZTUE3a3RFWjYFmXczQ4IBu2PNkBJoyKYg86Vlg3saGmFKBVNymYC9S29AUtaXWYrnTcj88C2ZlsIAJIcB2tNFEARBjE9IdBEE8YVGERKz9yXdrJOmedUJE74qhyHbhl4QVildgygUvjBsB0bBnle5V75edxwYhUp//tLymiMCFQCTBbsiZKCvVnGfF5fV7UzKsv5fuleF0L9vy1I4zEJMFfu5+lFEYzhLxRMEQRDEFwESXQRBEAB0W0C3S3uqJFzRIxjzen8BwVL0xcIaQO3qhylD96oT+gtl+PuFxcySH79Ii5qWV3URKFVMjFh2WQn5Uql4f0l4v9gzfGIvpypeWft6aBjmyoUEQRAEMd4h0UUQBFGFSZkcJmZz6NF1RAqiQ/Bghigoxvyl6H1iTK9eor6nRul6N2tVEGk+u795c6yiVLxeMR4oibRapeXrQXccaI7oeyBBEARBEDWhkvEEQRA1KPb/KmaPbM5hOG7GKGzZnhjJaqWslX/JoV+kaY5A2LdUsFhaXilbQlgUY+VLCHtqlKLPaCocXtnnS/RWKl7vR6l4WlpIEARBEIOGMl0EQRB1otvC2//lMF9FQd/SwsayLFcxa+XPfuVUpbTXKm96SwglKzVRbrCswBLCYtYqbAWXEBbFWPl+sWLGjEkZWB5oc+Y1V66H8iwZQRAEQRD9h0TXEMM5ACYAMDA9BaZkRzokgiCGGKPsh4iSg4AGyRgmyDSY4YoiJxJCnLm9tJplBsxwM2BmSEe8UB59ks+e0xTEuPtzs8iBGW4GzOGApgtoABpFHszwZZ9CNuIshagwwYySQHIiBuIsh7Btg+ulfl6mriLO6qsSyKREA0+DDXP7LOaEgbwAQMsYCYIgiPEJia4hhjGAcQEpGZiaA1NJdBHEeKfJyaIpB1icQ1UEoLjL+5gmEYbbKFnneW9Bt9QFwiwPLoEQckBhi5Vj6AgzG0wCEeTACnZLUxBmPQCAKPJgWnG5I4OmSGgAotIE0wqihQHQJMIsh5i0wLSSyBKGjnCd/bAMR4Crw5/pYowBTIAxEl0EQRDE+IRE1xDjOIDkKgAFIjMJguf7PIYgiPGBglKuJqcqSKgNyKkqJqczEBk325TVVGwPxwEBTMjmIFIZAK5I+zQ0AVIwxPImJvSkvGbEO5riyAoVIdtGczLpzbGnIYy9IgxFSDQn9nn2tK6iMxQHJNCY3AdRWI4oGPBZYY56mJpOQeSGX3QJYQBChUR9cREEQRDEWGNUFdJ44okncOqpp2LixIlgjOHtt9+uGJPL5XD11Vdj4sSJiEajWLZsGXbu3NmrXyklbrnlFkydOhXhcBiLFy/Ghx9+GBjT1dWF5cuXIx6Po6mpCStWrEAqlRrK0yMI4gtEyHYwe18SB+3rRlOu9PAlUUfVQr/d5tzbgxUvr05Y8OUvOQ+U9n81WBYU3/6vtK55c9QDFdEgCIIgiKFhVImudDqNE088Ef/yL/9Sc8x1112H3//+93jsscewfv16bN++Heedd16vfm+//XbcfffduP/++/H666+joaEBS5YsQS5X2uewfPlyvPfee3jxxRfx7LPP4pVXXsEVV1wxZOdGEMQXE90WgcIXHG7/L80RgaqFiVD1qoXJUHWR5i/GUS7GipURK0rIG/VXLSwv2EEQBEEQxMAZVcsLL7roIgDAxx9/XPX9RCKBBx54AI888ghOOeUUAMCDDz6Iww47DBs3bsTxxx9fcYyUEnfddRduuukmnH322QCA3/zmN2hpacFTTz2FCy64AB988AFeeOEF/PnPf8YxxxwDAPjlL3+J008/HT//+c/R1tY2DGdLEMQXkSmpDCalM16JeQBwOENacwVR3DQDVQuLmTF/iXrAV3JeSDSYJfGW0VWv8bFfdLmVEesXXeW9wAiCIAiCGDijKtPVF5s3b4ZlWVi8eLFnmzt3LmbMmIENGzZUPWbr1q3o7OwMHNPY2IiFCxd6x2zYsAFNTU2e4AKAxYsXg3OO119/vWY8+XweyWQy8CIIgugLLt1+XkXc/l+ucIrngg2Rc2r1pYVF0eUvRQ+UmjFHLCuQqUprGkQ/lhaS6CIIgiCIoWNMia7Ozk7ouo6mpqaAvaWlBZ2dnTWPKY6pdUxnZyemTJkSeF9VVTQ3N9f0CwCrV69GY2Oj95o+fXp/T4kgCAJGYf/Xgfu6A/uoEqFSrXa/uPI3Y64UY0YNe/1ZLsNxoNtUSZAgCIIghooRW164Zs0aXHnlld7vzz//PE466aSRCmdA3Hjjjbj++uu935PJJH7z//0MgHRf3HRfBEEQdWAIBB6FKYzDkG5RDhWlkvOpUBgaclCEQMTJePaMroLzPDiAuJVCcZ2iZEDOcI+phyYzt58/uxi8z02CIAiCGIeMmOg666yzsHDhQu/3Aw44oM9jWltbYZomuru7A9munTt3orW1teYxxTFTp04NHHP00Ud7Y3bt2hU4zrZtdHV11fQLAIZhwDCCXUMVDjDFhpQSPNIFrmb6PC+CIIhqTAIwyQIEY+DRgiBhQMgwYDAgJBzwaGk/F9c1TOFdUB0BLVLKmNkKxySl/uXPMdUszbcf4HYEyNlgdTZtJgiCIIixxoiJrlgshlgs1q9jFixYAE3TsHbtWixbtgwAsGXLFmzbtg3t7e1Vj5k9ezZaW1uxdu1aT2Qlk0m8/vrruOqqqwAA7e3t6O7uxubNm7FgwQIAwEsvvQQhREAY1oMjAOkU+3Q1Q/CGfh1PEARRjeJiP1vh6OYNyKsKpvf0QBT2hkkGbNcbIQTDlHQGwre8cHcsgh5R3/JC1RGI+3qB7Q+oTxdBEAQx3hlV1Qu7urqwbds2bN++HYArqAA3E9Xa2orGxkasWLEC119/PZqbmxGPx3HNNdegvb09ULlw7ty5WL16Nc4991wwxnDttdfitttuwyGHHILZs2fj5ptvRltbG8455xwAwGGHHYalS5fi8ssvx/333w/LsrBy5UpccMEF/a9cKAF3qQwDhA5aLkMQxFCiCmD6vjxMhUN3FLgtmd1y8HkWdkvO5zOFzx+3IXK3FoOoU9DE81nv2P2G0OF9bhIEQRDEOGRUia5nnnkG3/rWt7zfL7jgAgDAqlWrcOuttwIA7rzzTnDOsWzZMuTzeSxZsgT33ntvwM+WLVuQSCS837///e8jnU7jiiuuQHd3N0488US88MILCIVC3pg1a9Zg5cqVWLRokef/7rvvHsazJQiCGDi6E8xFOZyBS4moaYH73krper+qFpYX4CAIgiAIYvAwKSWlYoaIZDKJX/38h4hqBiQUtIf+hijP930gQRDEECCYu//LXyr+08YoUnX259IdBwd1JfoeOMSkhIENuQPB4OA7t/wCiUQC8Xh8v8dBEARBEMPFqMp0EQRBEAOHS4CXPUdzWP2dQRpz9JCIIAiCIIYDEl0EQRDjmFndSeRVjoRhIBEyYPPaIoyWFhIEQRDE8ECiiyAIYpxj2AJT7CympLNI6yoShoGkoUP69nqFbLtin9j+hha7EwRBEOMVEl1DjKK4fbqEAHhkD/XpIghiVBEDEJOAzAOmoiCvKjAVjgZY4NGR6ZPF7QhgzkB2f1dNJAiCIIj9BImuIUZKwHZU2NAg7RCoTglBEKMVvfByOMChQ45Qoks6IVhCgxDKyARAEARBEMMMia4hxhEMWRaCzgSkGYXk2kiHRBAE0SvFXV4j9YhICgNSKggzKuRBEARBjE/qL2tF1IVkGjgkVIzMMh2CIIixiAoHCqOVAQRBEMT4hETXMBBmefSjFylBEMQXHk6CiyAIghjHkOgiCIIgCIIgCIIYRkh0DQNZaVDpY4IgiH4gJC0PIAiCIMYvJLqGGCYtCDDYoCpcBEEQ9WJDgUPCiyAIghinUPXCIUbhEgbPwYYGpqfAlOxIh0QQBDGqYU4YLOcgK4yRDoUgCIIghgUSXUMMY4Cq2GACYGoOTCXRRRAE0RuMMWjcgg3KdBEEQRDjExJdQ4zjAJKrYFAgMpMgOPWdIQiC6A0hDECoCEtrpEMhCIIgiGGB9nQRBEEQowJqtUEQBEGMV0h0EQRBEARBEARBDCMkugiCIAiCIAiCIIYREl0EQRAEQRAEQRDDCBXSGGIkGBzJIMGQFvpIh0MQBDHqSQsdjmRgVL2QIAiCGKeQ6BpiHB5HWiqQAN42p4FDVowRYLClAgYJlTk1v2ZIALZUIMGgMqeqr4HSH98OOBzJoTABBWLIYuiP73qv2UCg+9F/33Q/StD9cBnM/RBgSEuDJBdBEAQxbiHRNYRIKQHGICEBSDBugTOnYhwHwKSCjBOGDSCiZCq+bEgAWScCAY6IkoVSxc9g4QAyTgSWVGvOkRc6TKFC53lo3ByWGITQkRMGdJ6HUWUORyrIOmFwJqpeq6GIge5HKQa6H6U46H7sn/shpQIIHbLgWcqhE9AEQRAEMRpgkv66DRmfffYZpk+fPtJhEARBjGk+/fRTTJs2baTDIAiCIIghg0TXECKEwPbt2yGlxIwZM/Dpp58iHo+PdFh9kkwmMX36dIp3mKB4h5exFO9YihXY//FKKdHT04O2tjZwTnWeCIIgiPEDLS8cQjjnmDZtGpLJJAAgHo+PiS9WRSje4YXiHV7GUrxjKVZg/8bb2Ni4X+YhCIIgiP0JPUokCIIgCIIgCIIYRkh0EQRBEARBEARBDCMkuoYBwzCwatUqGIYx0qHUBcU7vFC8w8tYincsxQqMvXgJgiAIYrRChTQIgiAIgiAIgiCGEcp0EQRBEARBEARBDCMkugiCIAiCIAiCIIYREl0EQRAEQRAEQRDDCIkugiAIgiAIgiCIYYREVx3cc889mDVrFkKhEBYuXIg33nij1/GPPfYY5s6di1AohCOPPBLPPfdc4H0pJW655RZMnToV4XAYixcvxocffjjoOG+99VYwxgKvuXPnjppYX3nlFZx55ploa2sDYwxPPfXUkMzV1/3J5XK4+uqrMXHiRESjUSxbtgw7d+4cdLyXXnppxfVeunTpiMW7evVqHHvssYjFYpgyZQrOOeccbNmyZdC+67kvXV1dWL58OeLxOJqamrBixQqkUqlBx3vyySdXXONvf/vbIxLvfffdh/nz53uNgtvb2/H8889774+ma1tPvKPp2hIEQRDEuEcSvfLoo49KXdflr3/9a/nee+/Jyy+/XDY1NcmdO3dWHf/HP/5RKooib7/9dvn+++/Lm266SWqaJv/yl794Y372s5/JxsZG+dRTT8n/9//+nzzrrLPk7NmzZTabHVSsq1atkocffrjcsWOH99q9e3fN8fs71ueee07+6Ec/kk888YQEIJ988snA+wOZq5778+1vf1tOnz5drl27Vm7atEkef/zx8stf/vKg473kkkvk0qVLA9e7q6urV5/DGe+SJUvkgw8+KN9991359ttvy9NPP13OmDFDplKpQfmu574sXbpUHnXUUXLjxo3y1VdflQcffLC88MILBx3vV7/6VXn55ZcHrnEikRiReJ955hn5H//xH/K///u/5ZYtW+QPf/hDqWmafPfdd6WUo+va1hPvaLq2BEEQBDHeIdHVB8cdd5y8+uqrvd8dx5FtbW1y9erVVcf/wz/8gzzjjDMCtoULF8orr7xSSimlEEK2trbKO+64w3u/u7tbGoYhf/vb3w4q1lWrVsmjjjqq7vEjGWu5iBnoXH3dn+7ubqlpmnzssce8MR988IEEIDds2DDgeKV0RdfZZ59dt4/9Ga+UUu7atUsCkOvXrx+w73ruy/vvvy8ByD//+c/emOeff14yxuTnn38+4HildIXBd77znbp97M94pZRywoQJ8v/8n/8z6q9tebxSjv5rSxAEQRDjCVpe2AumaWLz5s1YvHixZ+OcY/HixdiwYUPVYzZs2BAYDwBLlizxxm/duhWdnZ2BMY2NjVi4cGFNn/3hww8/RFtbGw488EAsX74c27Ztqzl2pGP1M5C56rk/mzdvhmVZgTFz587FjBkzhuQc1q1bhylTpmDOnDm46qqrsHfv3ppj93e8iUQCANDc3Dxg3/Xclw0bNqCpqQnHHHOMN2bx4sXgnOP1118fcLxF1qxZg0mTJuGII47AjTfeiEwmU9PH/orXcRw8+uijSKfTaG9vH/XXtjzeIqPx2hIEQRDEeEQd6QBGM3v27IHjOGhpaQnYW1pa8Ne//rXqMZ2dnVXHd3Z2eu8XbbXGDJSFCxfioYcewpw5c7Bjxw78+Mc/xkknnYR3330XsVhsVMVaLZb+zlXP/ens7ISu62hqaqrbb70sXboU5513HmbPno2Ojg788Ic/xGmnnYYNGzZAUZQRjVcIgWuvvRYnnHACjjjiiAH7rue+dHZ2YsqUKYH3VVVFc3Nz3TFXixcAvvGNb2DmzJloa2vDO++8gxtuuAFbtmzBE088MSLx/uUvf0F7eztyuRyi0SiefPJJzJs3D2+//faovLa14gVG37UlCIIgiPEMia5xxGmnneb9PH/+fCxcuBAzZ87E7373O6xYsWIEIxufXHDBBd7PRx55JObPn4+DDjoI69atw6JFi0YwMuDqq6/Gu+++i9dee21E46iXWvFeccUV3s9HHnkkpk6dikWLFqGjowMHHXTQ/g4Tc+bMwdtvv41EIoHHH38cl1xyCdavX7/f46iXWvHOmzdv1F1bgiAIghjP0PLCXpg0aRIURamoQLZz5060trZWPaa1tbXX8cX/9sfnQGlqasKhhx6Kjz76aNTHOpC56rk/ra2tME0T3d3ddfsdKAceeCAmTZpU83rvr3hXrlyJZ599Fi+//DKmTZvm2Qfiu5770trail27dgXet20bXV1ddcVcK95qLFy4EAB6/Tc9nPHquo6DDz4YCxYswOrVq3HUUUfhX//1X0ftta0VbzVG+toSBEEQxHiGRFcv6LqOBQsWYO3atZ5NCIG1a9cG9kX4aW9vD4wHgBdffNEbP3v2bLS2tgbGJJNJvP766zV9DpRUKoWOjg5MnTp11Mc6kLnquT8LFiyApmmBMVu2bMG2bduG/Bw+++wz7N27t+b1Hu54pZRYuXIlnnzySbz00kuYPXt24P2B+K7nvrS3t6O7uxubN2/2xrz00ksQQnhf5AcSbzXefvttAKh5jYcz3moIIZDP50fdte0r3mqMtmtLEARBEOOKka7kMdp59NFHpWEY8qGHHpLvv/++vOKKK2RTU5Ps7OyUUkp50UUXyR/84Afe+D/+8Y9SVVX585//XH7wwQdy1apVVcuwNzU1yaefflq+88478uyzzx6SkvHf/e535bp16+TWrVvlH//4R7l48WI5adIkuWvXrlERa09Pj3zrrbfkW2+9JQHIX/ziF/Ktt96Sn3zySd1znXLKKfKXv/yl93tf90dKt5T3jBkz5EsvvSQ3bdok29vbZXt7+6Di7enpkd/73vfkhg0b5NatW+V//dd/yb/7u7+ThxxyiMzlciMS71VXXSUbGxvlunXrAmXAM5lMv3zPmTNHPvHEE97v9dyXpUuXyi996Uvy9ddfl6+99po85JBD+iwT3le8H330kfynf/onuWnTJrl161b59NNPywMPPFB+5StfGZF4f/CDH8j169fLrVu3ynfeeUf+4Ac/kIwx+Z//+Z+j7tr2Fe9ou7YEQRAEMd4h0VUHv/zlL+WMGTOkruvyuOOOkxs3bvTe++pXvyovueSSwPjf/e538tBDD5W6rsvDDz9c/sd//EfgfSGEvPnmm2VLS4s0DEMuWrRIbtmyZdBxnn/++XLq1KlS13V5wAEHyPPPP19+9NFHoybWl19+WQKoeBVjqmeumTNnylWrVgVsvd0fKaXMZrPyf/7P/yknTJggI5GIPPfcc+WOHTsGFW8mk5GnnnqqnDx5stQ0Tc6cOVNefvnlAfG0v+OtFisA+eCDD/bLd/kx9dyXvXv3ygsvvFBGo1EZj8flt771LdnT0zOoeLdt2ya/8pWvyObmZmkYhjz44IPl//pf/6uil9T+iveyyy6TM2fOlLquy8mTJ8tFixZ5gmu0Xdu+4h1t15YgCIIgxjtMSin3T06NIAiCIAiCIAjiiwft6SIIgiAIgiAIghhGSHQRBEEQBEEQBEEMIyS6CIIgCIIgCIIghhESXQRBEARBEARBEMMIiS6CIAiCIAiCIIhhhEQXQRAEQRAEQRDEMEKiiyAIgiAIgiAIYhgh0UUQBEEQBEEQBDGMkOgiiHHGAw88gFNPPXXY53nhhRdw9NFHQwgx7HMRBEEQBEGMZUh0EcQ4IpfL4eabb8aqVauGfa6lS5dC0zSsWbNm2OciCIIgCIIYy5DoIohxxOOPP454PI4TTjhhv8x36aWX4u67794vcxEEQRAEQYxVSHQRxChk9+7daG1txU9/+lPP9qc//Qm6rmPt2rU1j3v00Udx5plnBmwnn3wyrr322oDtnHPOwaWXXur9PmvWLNx22224+OKLEY1GMXPmTDzzzDPYvXs3zj77bESjUcyfPx+bNm0K+DnzzDOxadMmdHR0DPxkCYIgCIIgxjkkughiFDJ58mT8+te/xq233opNmzahp6cHF110EVauXIlFixbVPO61117DMcccM6A577zzTpxwwgl46623cMYZZ+Ciiy7CxRdfjG9+85t48803cdBBB+Hiiy+GlNI7ZsaMGWhpacGrr746oDkJgiAIgiC+CJDoIohRyumnn47LL78cy5cvx7e//W00NDRg9erVNcd3d3cjkUigra1twPNdeeWVOOSQQ3DLLbcgmUzi2GOPxde//nUceuihuOGGG/DBBx9g586dgePa2trwySefDGhOgiAIgiCILwIkughiFPPzn/8ctm3jsccew5o1a2AYRs2x2WwWABAKhQY01/z5872fW1paAABHHnlkhW3Xrl2B48LhMDKZzIDmJAiCIAiC+CJAoosgRjEdHR3Yvn07hBD4+OOPex07ceJEMMawb9++Pv06jlNh0zTN+5kxVtNWXiK+q6sLkydP7nNOgiAIgiCILyokughilGKaJr75zW/i/PPPx09+8hP84z/+Y0WWyY+u65g3bx7ef//9ivfKlwT+7W9/G5IYc7kcOjo68KUvfWlI/BEEQRAEQYxHSHQRxCjlRz/6ERKJBO6++27ccMMNOPTQQ3HZZZf1esySJUvw2muvVdiffvppPPHEE+jo6MA///M/4/3338cnn3yCzz//fFAxbty4EYZhoL29fVB+CIIgCIIgxjMkughiFLJu3TrcddddePjhhxGPx8E5x8MPP4xXX30V9913X83jVqxYgeeeew6JRCJgP+OMM3D77bdj3rx5eOWVV3DvvffijTfewMMPPzyoOH/7299i+fLliEQig/JDEARBEAQxnmHSX/+ZIIgxz9e//nX83d/9HW688UYAbp+uo48+GnfdddeQzrNnzx7MmTMHmzZtwuzZs4fUN0EQBEEQxHiCMl0EMc644447EI1Gh32ejz/+GPfeey8JLoIgCIIgiD6gTBdBjHOGK9NFEARBEARB1AeJLoIgCIIgCIIgiGGElhcSBEEQBEEQBEEMIyS6CIIgCIIgCIIghhESXQRBEARBEARBEMMIiS6CIAiCIAiCIIhhhEQXQRAEQRAEQRDEMEKiiyAIgiAIgiAIYhgh0UUQBEEQBEEQBDGMkOgiCIIgCIIgCIIYRv5//J/Ypl9pzkMAAAAASUVORK5CYII="
+     },
+     "metadata": {},
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
+    }
+   ],
+   "execution_count": 14
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
    "id": "9eba2cb2",
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:19:05.865592Z",
+     "start_time": "2025-10-29T14:16:48.786854Z"
+    }
+   },
    "source": [
     "job = web.Job(simulation=sim_3d, task_name=\"gc_in_coupling_3d\", verbose=False)\n",
     "sim_3d_in = job.run(path=\"data/gc3d_in_data.hdf5\")"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": 15
   },
   {
    "cell_type": "markdown",
@@ -965,21 +1059,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
    "id": "1b3231cf",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 1000x400 with 2 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:19:05.973087Z",
+     "start_time": "2025-10-29T14:19:05.874429Z"
     }
-   ],
+   },
    "source": [
     "# Coupling Efficiency\n",
     "mode_amps = sim_3d_in[\"mode_monitor\"]\n",
@@ -1019,32 +1105,56 @@
     "ax2.set_ylabel(\"Power (W)\")\n",
     "ax2.legend()\n",
     "plt.show()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 17,
-   "id": "8758df00",
-   "metadata": {},
+   ],
    "outputs": [
     {
      "data": {
-      "image/png": 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",
       "text/plain": [
-       "<Figure size 1000x400 with 4 Axes>"
-      ]
+       "<Figure size 1000x400 with 2 Axes>"
+      ],
+      "image/png": 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"
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     }
    ],
+   "execution_count": 16
+  },
+  {
+   "cell_type": "code",
+   "id": "8758df00",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:19:08.402333Z",
+     "start_time": "2025-10-29T14:19:05.980729Z"
+    }
+   },
    "source": [
     "fig, (ax1, ax2) = plt.subplots(1, 2, tight_layout=True, figsize=(10, 4))\n",
     "sim_3d_in.plot_field(\"field_xy\", \"E\", f=freq, val=\"abs\", ax=ax1)\n",
     "sim_3d_in.plot_field(\"field_xz\", \"E\", f=freq, val=\"abs\", ax=ax2)\n",
     "ax2.set_aspect(\"auto\")\n",
     "plt.show()"
-   ]
+   ],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 1000x400 with 4 Axes>"
+      ],
+      "image/png": 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"
+     },
+     "metadata": {},
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
+    }
+   ],
+   "execution_count": 17
   },
   {
    "cell_type": "markdown",
@@ -1058,10 +1168,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
    "id": "743e27b1",
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:21:15.445577Z",
+     "start_time": "2025-10-29T14:19:08.446341Z"
+    }
+   },
    "source": [
     "sim_3d_o = build_sim(\n",
     "    sim_mode=\"out_coupling\",\n",
@@ -1080,7 +1193,9 @@
     "\n",
     "job = web.Job(simulation=sim_3d_o, task_name=\"gc_out_coupling_3d\", verbose=False)\n",
     "sim_3d_out = job.run(path=\"data/gc3d_out_data.hdf5\")"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": 18
   },
   {
    "cell_type": "markdown",
@@ -1092,21 +1207,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
    "id": "d5d42937",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 1000x600 with 5 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:21:17.643754Z",
+     "start_time": "2025-10-29T14:21:15.455551Z"
     }
-   ],
+   },
    "source": [
     "power_back = abs(sim_3d_out[\"flux_back\"].flux)\n",
     "\n",
@@ -1123,7 +1230,23 @@
     "ax3.set_xlabel(r\"Wavelength ($\\mu m$)\")\n",
     "ax3.set_ylabel(\"Power (W)\")\n",
     "plt.show()"
-   ]
+   ],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 1000x600 with 5 Axes>"
+      ],
+      "image/png": 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"
+     },
+     "metadata": {},
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
+    }
+   ],
+   "execution_count": 19
   },
   {
    "cell_type": "markdown",
@@ -1135,32 +1258,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
    "id": "4b930759",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">14:49:07 UTC </span><span style=\"color: #800000; text-decoration-color: #800000\">WARNING: Colocating data that has already been colocated during the</span>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #800000; text-decoration-color: #800000\">solver run. For most accurate results when colocating to custom    </span>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #800000; text-decoration-color: #800000\">coordinates set </span><span style=\"color: #008000; text-decoration-color: #008000\">'Monitor.colocate'</span><span style=\"color: #800000; text-decoration-color: #800000\"> to </span><span style=\"color: #008000; text-decoration-color: #008000\">'False'</span><span style=\"color: #800000; text-decoration-color: #800000\"> to use the raw data  </span>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #800000; text-decoration-color: #800000\">on the Yee grid and avoid double interpolation. Note: the default  </span>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #800000; text-decoration-color: #800000\">value was changed to </span><span style=\"color: #008000; text-decoration-color: #008000\">'True'</span><span style=\"color: #800000; text-decoration-color: #800000\"> in Tidy3D version </span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2.4</span><span style=\"color: #800000; text-decoration-color: #800000\">.</span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0</span><span style=\"color: #800000; text-decoration-color: #800000\">.               </span>\n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m14:49:07 UTC\u001b[0m\u001b[2;36m \u001b[0m\u001b[31mWARNING: Colocating data that has already been colocated during the\u001b[0m\n",
-       "\u001b[2;36m             \u001b[0m\u001b[31msolver run. For most accurate results when colocating to custom    \u001b[0m\n",
-       "\u001b[2;36m             \u001b[0m\u001b[31mcoordinates set \u001b[0m\u001b[32m'Monitor.colocate'\u001b[0m\u001b[31m to \u001b[0m\u001b[32m'False'\u001b[0m\u001b[31m to use the raw data  \u001b[0m\n",
-       "\u001b[2;36m             \u001b[0m\u001b[31mon the Yee grid and avoid double interpolation. Note: the default  \u001b[0m\n",
-       "\u001b[2;36m             \u001b[0m\u001b[31mvalue was changed to \u001b[0m\u001b[32m'True'\u001b[0m\u001b[31m in Tidy3D version \u001b[0m\u001b[1;36m2.4\u001b[0m\u001b[31m.\u001b[0m\u001b[1;36m0\u001b[0m\u001b[31m.               \u001b[0m\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:21:22.030241Z",
+     "start_time": "2025-10-29T14:21:17.648612Z"
     }
-   ],
+   },
    "source": [
     "# Creates a range of angles to probe.\n",
     "num_angles = 1101\n",
@@ -1186,7 +1290,34 @@
     "\n",
     "# Compute the scattered cross section\n",
     "ps = np.abs(far_fields.radar_cross_section.sel(f=freq).values[0, ...])"
-   ]
+   ],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "\u001B[2;36m15:21:17 CET\u001B[0m\u001B[2;36m \u001B[0m\u001B[31mWARNING: Colocating data that has already been colocated during the\u001B[0m\n",
+       "\u001B[2;36m             \u001B[0m\u001B[31msolver run. For most accurate results when colocating to custom    \u001B[0m\n",
+       "\u001B[2;36m             \u001B[0m\u001B[31mcoordinates set \u001B[0m\u001B[32m'Monitor.colocate'\u001B[0m\u001B[31m to \u001B[0m\u001B[32m'False'\u001B[0m\u001B[31m to use the raw data  \u001B[0m\n",
+       "\u001B[2;36m             \u001B[0m\u001B[31mon the Yee grid and avoid double interpolation. Note: the default  \u001B[0m\n",
+       "\u001B[2;36m             \u001B[0m\u001B[31mvalue was changed to \u001B[0m\u001B[32m'True'\u001B[0m\u001B[31m in Tidy3D version \u001B[0m\u001B[1;36m2.4\u001B[0m\u001B[31m.\u001B[0m\u001B[1;36m0\u001B[0m\u001B[31m.               \u001B[0m\n"
+      ],
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">15:21:17 CET </span><span style=\"color: #800000; text-decoration-color: #800000\">WARNING: Colocating data that has already been colocated during the</span>\n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #800000; text-decoration-color: #800000\">solver run. For most accurate results when colocating to custom    </span>\n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #800000; text-decoration-color: #800000\">coordinates set </span><span style=\"color: #008000; text-decoration-color: #008000\">'Monitor.colocate'</span><span style=\"color: #800000; text-decoration-color: #800000\"> to </span><span style=\"color: #008000; text-decoration-color: #008000\">'False'</span><span style=\"color: #800000; text-decoration-color: #800000\"> to use the raw data  </span>\n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #800000; text-decoration-color: #800000\">on the Yee grid and avoid double interpolation. Note: the default  </span>\n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #800000; text-decoration-color: #800000\">value was changed to </span><span style=\"color: #008000; text-decoration-color: #008000\">'True'</span><span style=\"color: #800000; text-decoration-color: #800000\"> in Tidy3D version </span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2.4</span><span style=\"color: #800000; text-decoration-color: #800000\">.</span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0</span><span style=\"color: #800000; text-decoration-color: #800000\">.               </span>\n",
+       "</pre>\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
+    }
+   ],
+   "execution_count": 20
   },
   {
    "cell_type": "markdown",
@@ -1198,21 +1329,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
    "id": "993c361b",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 400x400 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:21:22.108713Z",
+     "start_time": "2025-10-29T14:21:22.048900Z"
     }
-   ],
+   },
    "source": [
     "# plot the angle dependence\n",
     "fig, ax = plt.subplots(subplot_kw={\"projection\": \"polar\"}, figsize=(4, 4))\n",
@@ -1230,7 +1353,23 @@
     "ax.set_title(\"Scattered Cross-section (arb. units)\", va=\"bottom\")\n",
     "plt.legend()\n",
     "plt.show()"
-   ]
+   ],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 400x400 with 1 Axes>"
+      ],
+      "image/png": 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"
+     },
+     "metadata": {},
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
+    }
+   ],
+   "execution_count": 21
   }
  ],
  "metadata": {
@@ -1338,7 +1477,7 @@
         {
          "data": {
           "text/html": "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Processing surface monitor 'near_field'... <span style=\"color: #729c1f; text-decoration-color: #729c1f\">━━━━━━━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">100%</span> <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\n</pre>\n",
-          "text/plain": "Processing surface monitor 'near_field'... \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[36m0:00:00\u001b[0m\n"
+          "text/plain": "Processing surface monitor 'near_field'... \u001B[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━\u001B[0m \u001B[35m100%\u001B[0m \u001B[36m0:00:00\u001B[0m\n"
          },
          "metadata": {},
          "output_type": "display_data"
diff --git a/InverseDesign.ipynb b/InverseDesign.ipynb
index 55827623..4b82eea9 100644
--- a/InverseDesign.ipynb
+++ b/InverseDesign.ipynb
@@ -1109,7 +1109,7 @@
    "source": [
     "Finally, we combine everything into an `InverseDesignMulti` object.\n",
     "\n",
-    "In an analogy to the `InverseDesign` from the previous section, this object will generate a set of `td.SimulationData` objects under the hood and use `td.web.run_async` to run each of them in parallel.\n",
+    "In an analogy to the `InverseDesign` from the previous section, this object will generate a set of `td.SimulationData` objects under the hood and use `td.web.run` to run each of them in parallel.\n",
     "\n",
     "After the simulations are run, the combined post-processing function will be applied to the combined data to give the final value, minus any penalties in the shared `DesignRegion`."
    ]
@@ -1211,7 +1211,7 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m18:46:55 EDT\u001b[0m\u001b[2;36m \u001b[0mStarted working on Batch containing \u001b[1;36m3\u001b[0m tasks.                       \n"
+       "\u001B[2;36m18:46:55 EDT\u001B[0m\u001B[2;36m \u001B[0mStarted working on Batch containing \u001B[1;36m3\u001B[0m tasks.                       \n"
       ]
      },
      "metadata": {},
@@ -1224,7 +1224,7 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m18:47:00 EDT\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.075\u001b[0m for the whole batch.                \n"
+       "\u001B[2;36m18:47:00 EDT\u001B[0m\u001B[2;36m \u001B[0mMaximum FlexCredit cost: \u001B[1;36m0.075\u001B[0m for the whole batch.                \n"
       ]
      },
      "metadata": {},
@@ -1238,8 +1238,8 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mUse \u001b[32m'Batch.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed FlexCredit cost after the\n",
-       "\u001b[2;36m             \u001b[0mBatch has completed.                                               \n"
+       "\u001B[2;36m            \u001B[0m\u001B[2;36m \u001B[0mUse \u001B[32m'Batch.real_cost\u001B[0m\u001B[32m(\u001B[0m\u001B[32m)\u001B[0m\u001B[32m'\u001B[0m to get the billed FlexCredit cost after the\n",
+       "\u001B[2;36m             \u001B[0mBatch has completed.                                               \n"
       ]
      },
      "metadata": {},
@@ -1266,7 +1266,7 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m18:47:27 EDT\u001b[0m\u001b[2;36m \u001b[0mBatch complete.                                                    \n"
+       "\u001B[2;36m18:47:27 EDT\u001B[0m\u001B[2;36m \u001B[0mBatch complete.                                                    \n"
       ]
      },
      "metadata": {},
@@ -1376,7 +1376,7 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m18:49:36 EDT\u001b[0m\u001b[2;36m \u001b[0mStarted working on Batch containing \u001b[1;36m3\u001b[0m tasks.                       \n"
+       "\u001B[2;36m18:49:36 EDT\u001B[0m\u001B[2;36m \u001B[0mStarted working on Batch containing \u001B[1;36m3\u001B[0m tasks.                       \n"
       ]
      },
      "metadata": {},
@@ -1389,7 +1389,7 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m18:49:42 EDT\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.075\u001b[0m for the whole batch.                \n"
+       "\u001B[2;36m18:49:42 EDT\u001B[0m\u001B[2;36m \u001B[0mMaximum FlexCredit cost: \u001B[1;36m0.075\u001B[0m for the whole batch.                \n"
       ]
      },
      "metadata": {},
@@ -1403,8 +1403,8 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mUse \u001b[32m'Batch.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed FlexCredit cost after the\n",
-       "\u001b[2;36m             \u001b[0mBatch has completed.                                               \n"
+       "\u001B[2;36m            \u001B[0m\u001B[2;36m \u001B[0mUse \u001B[32m'Batch.real_cost\u001B[0m\u001B[32m(\u001B[0m\u001B[32m)\u001B[0m\u001B[32m'\u001B[0m to get the billed FlexCredit cost after the\n",
+       "\u001B[2;36m             \u001B[0mBatch has completed.                                               \n"
       ]
      },
      "metadata": {},
@@ -1431,7 +1431,7 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m18:49:55 EDT\u001b[0m\u001b[2;36m \u001b[0mBatch complete.                                                    \n"
+       "\u001B[2;36m18:49:55 EDT\u001B[0m\u001B[2;36m \u001B[0mBatch complete.                                                    \n"
       ]
      },
      "metadata": {},
@@ -1552,7 +1552,7 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m18:50:11 EDT\u001b[0m\u001b[2;36m \u001b[0mStarted working on Batch containing \u001b[1;36m3\u001b[0m tasks.                       \n"
+       "\u001B[2;36m18:50:11 EDT\u001B[0m\u001B[2;36m \u001B[0mStarted working on Batch containing \u001B[1;36m3\u001B[0m tasks.                       \n"
       ]
      },
      "metadata": {},
@@ -1565,7 +1565,7 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m18:50:17 EDT\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.075\u001b[0m for the whole batch.                \n"
+       "\u001B[2;36m18:50:17 EDT\u001B[0m\u001B[2;36m \u001B[0mMaximum FlexCredit cost: \u001B[1;36m0.075\u001B[0m for the whole batch.                \n"
       ]
      },
      "metadata": {},
@@ -1579,8 +1579,8 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mUse \u001b[32m'Batch.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed FlexCredit cost after the\n",
-       "\u001b[2;36m             \u001b[0mBatch has completed.                                               \n"
+       "\u001B[2;36m            \u001B[0m\u001B[2;36m \u001B[0mUse \u001B[32m'Batch.real_cost\u001B[0m\u001B[32m(\u001B[0m\u001B[32m)\u001B[0m\u001B[32m'\u001B[0m to get the billed FlexCredit cost after the\n",
+       "\u001B[2;36m             \u001B[0mBatch has completed.                                               \n"
       ]
      },
      "metadata": {},
@@ -1607,7 +1607,7 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m18:50:41 EDT\u001b[0m\u001b[2;36m \u001b[0mBatch complete.                                                    \n"
+       "\u001B[2;36m18:50:41 EDT\u001B[0m\u001B[2;36m \u001B[0mBatch complete.                                                    \n"
       ]
      },
      "metadata": {},
@@ -1717,7 +1717,7 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m18:53:54 EDT\u001b[0m\u001b[2;36m \u001b[0mStarted working on Batch containing \u001b[1;36m3\u001b[0m tasks.                       \n"
+       "\u001B[2;36m18:53:54 EDT\u001B[0m\u001B[2;36m \u001B[0mStarted working on Batch containing \u001B[1;36m3\u001B[0m tasks.                       \n"
       ]
      },
      "metadata": {},
@@ -1730,7 +1730,7 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m18:54:00 EDT\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.075\u001b[0m for the whole batch.                \n"
+       "\u001B[2;36m18:54:00 EDT\u001B[0m\u001B[2;36m \u001B[0mMaximum FlexCredit cost: \u001B[1;36m0.075\u001B[0m for the whole batch.                \n"
       ]
      },
      "metadata": {},
@@ -1744,8 +1744,8 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mUse \u001b[32m'Batch.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed FlexCredit cost after the\n",
-       "\u001b[2;36m             \u001b[0mBatch has completed.                                               \n"
+       "\u001B[2;36m            \u001B[0m\u001B[2;36m \u001B[0mUse \u001B[32m'Batch.real_cost\u001B[0m\u001B[32m(\u001B[0m\u001B[32m)\u001B[0m\u001B[32m'\u001B[0m to get the billed FlexCredit cost after the\n",
+       "\u001B[2;36m             \u001B[0mBatch has completed.                                               \n"
       ]
      },
      "metadata": {},
@@ -1772,7 +1772,7 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m18:54:20 EDT\u001b[0m\u001b[2;36m \u001b[0mBatch complete.                                                    \n"
+       "\u001B[2;36m18:54:20 EDT\u001B[0m\u001B[2;36m \u001B[0mBatch complete.                                                    \n"
       ]
      },
      "metadata": {},
@@ -1893,7 +1893,7 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m18:54:39 EDT\u001b[0m\u001b[2;36m \u001b[0mStarted working on Batch containing \u001b[1;36m3\u001b[0m tasks.                       \n"
+       "\u001B[2;36m18:54:39 EDT\u001B[0m\u001B[2;36m \u001B[0mStarted working on Batch containing \u001B[1;36m3\u001B[0m tasks.                       \n"
       ]
      },
      "metadata": {},
@@ -1906,7 +1906,7 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m18:54:45 EDT\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.075\u001b[0m for the whole batch.                \n"
+       "\u001B[2;36m18:54:45 EDT\u001B[0m\u001B[2;36m \u001B[0mMaximum FlexCredit cost: \u001B[1;36m0.075\u001B[0m for the whole batch.                \n"
       ]
      },
      "metadata": {},
@@ -1920,8 +1920,8 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mUse \u001b[32m'Batch.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed FlexCredit cost after the\n",
-       "\u001b[2;36m             \u001b[0mBatch has completed.                                               \n"
+       "\u001B[2;36m            \u001B[0m\u001B[2;36m \u001B[0mUse \u001B[32m'Batch.real_cost\u001B[0m\u001B[32m(\u001B[0m\u001B[32m)\u001B[0m\u001B[32m'\u001B[0m to get the billed FlexCredit cost after the\n",
+       "\u001B[2;36m             \u001B[0mBatch has completed.                                               \n"
       ]
      },
      "metadata": {},
@@ -1948,7 +1948,7 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m18:55:11 EDT\u001b[0m\u001b[2;36m \u001b[0mBatch complete.                                                    \n"
+       "\u001B[2;36m18:55:11 EDT\u001B[0m\u001B[2;36m \u001B[0mBatch complete.                                                    \n"
       ]
      },
      "metadata": {},
@@ -2058,7 +2058,7 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m18:57:18 EDT\u001b[0m\u001b[2;36m \u001b[0mStarted working on Batch containing \u001b[1;36m3\u001b[0m tasks.                       \n"
+       "\u001B[2;36m18:57:18 EDT\u001B[0m\u001B[2;36m \u001B[0mStarted working on Batch containing \u001B[1;36m3\u001B[0m tasks.                       \n"
       ]
      },
      "metadata": {},
@@ -2071,7 +2071,7 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m18:57:24 EDT\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.075\u001b[0m for the whole batch.                \n"
+       "\u001B[2;36m18:57:24 EDT\u001B[0m\u001B[2;36m \u001B[0mMaximum FlexCredit cost: \u001B[1;36m0.075\u001B[0m for the whole batch.                \n"
       ]
      },
      "metadata": {},
@@ -2085,8 +2085,8 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mUse \u001b[32m'Batch.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed FlexCredit cost after the\n",
-       "\u001b[2;36m             \u001b[0mBatch has completed.                                               \n"
+       "\u001B[2;36m            \u001B[0m\u001B[2;36m \u001B[0mUse \u001B[32m'Batch.real_cost\u001B[0m\u001B[32m(\u001B[0m\u001B[32m)\u001B[0m\u001B[32m'\u001B[0m to get the billed FlexCredit cost after the\n",
+       "\u001B[2;36m             \u001B[0mBatch has completed.                                               \n"
       ]
      },
      "metadata": {},
@@ -2113,7 +2113,7 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m18:57:36 EDT\u001b[0m\u001b[2;36m \u001b[0mBatch complete.                                                    \n"
+       "\u001B[2;36m18:57:36 EDT\u001B[0m\u001B[2;36m \u001B[0mBatch complete.                                                    \n"
       ]
      },
      "metadata": {},
diff --git a/MIMResonator.ipynb b/MIMResonator.ipynb
index fff0f00e..94899a7b 100644
--- a/MIMResonator.ipynb
+++ b/MIMResonator.ipynb
@@ -24,9 +24,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:02:51.412220Z",
+     "start_time": "2025-10-29T14:02:51.410336Z"
+    }
+   },
    "source": [
     "# Standard python imports.\n",
     "import matplotlib.pylab as plt\n",
@@ -35,7 +38,9 @@
     "# Import regular tidy3d.\n",
     "import tidy3d as td\n",
     "import tidy3d.web as web"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": 22
   },
   {
    "cell_type": "markdown",
@@ -47,9 +52,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:02:51.458518Z",
+     "start_time": "2025-10-29T14:02:51.456525Z"
+    }
+   },
    "source": [
     "# Geometry\n",
     "period = np.asarray([0.36, 0.27, 0.23])  # Resonator period (um).\n",
@@ -58,7 +66,9 @@
     "mgf2_t = 0.22  # MgF2 layer thickness (um).\n",
     "al_t = 0.04  # Al layer thickness (um).\n",
     "znse_t = 0.1  # ZnSe layer thickness (um)."
-   ]
+   ],
+   "outputs": [],
+   "execution_count": 23
   },
   {
    "cell_type": "markdown",
@@ -69,9 +79,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:02:51.503586Z",
+     "start_time": "2025-10-29T14:02:51.501461Z"
+    }
+   },
    "source": [
     "n_sub = 1.45  # Substrate refractive index.\n",
     "n_znse = 2.65  # ZnSe refractive index.\n",
@@ -81,7 +94,9 @@
     "mat_air = td.Medium(permittivity=1)  # Air.\n",
     "mat_al = td.material_library[\"Al\"][\"RakicLorentzDrude1998\"]  # Aluminum.\n",
     "mat_mgf2 = td.material_library[\"MgF2\"][\"Horiba\"]  # MgF2 material."
-   ]
+   ],
+   "outputs": [],
+   "execution_count": 24
   },
   {
    "cell_type": "markdown",
@@ -92,9 +107,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:02:51.548799Z",
+     "start_time": "2025-10-29T14:02:51.546393Z"
+    }
+   },
    "source": [
     "wl_min = 0.400  # Minimum simulation wavelength (um).\n",
     "wl_max = 0.700  # Maximum simulation wavelength (um).\n",
@@ -110,7 +128,9 @@
     "freq_res = td.C_0 / wl_res\n",
     "\n",
     "size_z = 2 * wl_max + mgf2_t + 2 * al_t + znse_t  # Simulation size in the z-direction (um)."
-   ]
+   ],
+   "outputs": [],
+   "execution_count": 25
   },
   {
    "cell_type": "markdown",
@@ -121,9 +141,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:02:51.597647Z",
+     "start_time": "2025-10-29T14:02:51.591997Z"
+    }
+   },
    "source": [
     "def build_sim(\n",
     "    p: float = 0.360,\n",
@@ -232,7 +255,9 @@
     "        medium=mat_air,\n",
     "    )\n",
     "    return sim"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": 26
   },
   {
    "cell_type": "markdown",
@@ -244,14 +269,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
-   "metadata": {},
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:02:51.834717Z",
+     "start_time": "2025-10-29T14:02:51.641440Z"
+    }
+   },
+   "source": "sim = [build_sim(p=period[s], w=width[s]) for s in range(len(period))]",
    "outputs": [],
-   "source": [
-    "sim = {}\n",
-    "for s in range(len(period)):\n",
-    "    sim[f\"MIM_color_filter_{s}\"] = build_sim(p=period[s], w=width[s])"
-   ]
+   "execution_count": 27
   },
   {
    "cell_type": "markdown",
@@ -262,62 +288,56 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
-   "metadata": {},
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:02:51.920303Z",
+     "start_time": "2025-10-29T14:02:51.839315Z"
+    }
+   },
+   "source": [
+    "fig, ax = plt.subplots(1, 1, figsize=(3, 5), tight_layout=True)\n",
+    "sim[0].plot(y=0, ax=ax)\n",
+    "ax.set_aspect(\"auto\")\n",
+    "plt.show()"
+   ],
    "outputs": [
     {
      "data": {
-      "image/png": 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",
       "text/plain": [
        "<Figure size 300x500 with 1 Axes>"
-      ]
+      ],
+      "image/png": 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"
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     }
    ],
-   "source": [
-    "fig, ax = plt.subplots(1, 1, figsize=(3, 5), tight_layout=True)\n",
-    "sim[\"MIM_color_filter_0\"].plot(y=0, ax=ax)\n",
-    "ax.set_aspect(\"auto\")\n",
-    "plt.show()"
-   ]
+   "execution_count": 28
   },
   {
    "cell_type": "markdown",
    "metadata": {},
-   "source": [
-    "Now, we can run all the simulations in parallel using [run_async](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.web.api.asynchronous.run_async.html). This function submits a set of `Simulation` objects to the server, starts running, monitors progress, downloads, and loads results as a `BatchData` object."
-   ]
+   "source": "Now, we can run all the simulations in parallel using [run](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.web.api.run.run.html). This function submits one or many `Simulation` objects to the server, starts running, monitors progress, downloads, and loads results as a `BatchData` object."
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
-   "metadata": {},
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:03:19.519164Z",
+     "start_time": "2025-10-29T14:02:51.925852Z"
+    }
+   },
+   "source": "sim_data = web.run(sim, path=\"data\", verbose=False)",
    "outputs": [],
-   "source": [
-    "batch_data = web.run_async(simulations=sim, path_dir=\"data\", verbose=False)"
-   ]
+   "execution_count": 29
   },
   {
    "cell_type": "markdown",
    "metadata": {},
-   "source": [
-    "## Simulation Results\n",
-    "After running the simulation, we download the results from the server. "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "sim_data = []\n",
-    "# Get the results.\n",
-    "for _, sim_res in batch_data.items():\n",
-    "    sim_data.append(sim_res)"
-   ]
+   "source": "## Simulation Results"
   },
   {
    "cell_type": "markdown",
@@ -328,20 +348,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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kCadPn+bs2bMsXLiQM2fO4KjlIKkJrFghd70qVcq8a6NfJm9eOVQG2rSmb3KTv5BVXXqg4SB9OrSlLWUoQzTRfMu3WoejmNrChVCtmpxlWbQo7NsHISHpLxOo08njbNkCy5bJ7emuXYNatWDIEPnhYCuEnYmMjBSAiIyMfO53jx8/FqdOnRKPHz/WILLXd/PmTdGvXz9RsGBB4ezsLDJnziyCgoLEt99+K2JjY1O9j7U+5/r1hQAhvvpK60hS2rdPxuXsLMStW+Z97LFirEAgKovK5n3g17RKrBIIhLtwF+EiXOtwFFOZO1cInU7+gbRuLUQqn8EZFh0tRI8e8tggRMWKQoSb/r30snxiLCpJJ2OtCet1WONzvnNHCEdH+bd47pzW0TyvUiUZ24gR5nvMRJEoCovCAoGYK+aa74GNIFEkiiARJBCIAWKA1uEopjB7dlKC7tVLiIQE0zzOsmVCeHvLx/H3F+LwYdM8zr/MkaRVd7didf78U67aKFsWihTROprnffSRPJ81y3y9bgc4wAUu4I477/KueR7USHToGI3crWQa07jJTY0jUoxq9Wro2VO2cfv1kxO/HEyUet55R3ahFy0qu78rV04q7G+lVJJWrI5+VrcWFcbSomVL8PWVG3+sXm2ex1zEIgCa01yzJYOvox71qEIVnvDEMJlMsQEnTkCHDjJBf/CBnLFt6qUYRYvKJVp168KjR3I95G+/mfYxTUjzJD116lQKFCiAm5sbwcHB7N+//6W3f/jwIX379iVXrly4urpStGhR1q5da6ZoFa09fJg0gfNdC20wurgkFVfRb6FpSgkksIQlAHSgg+kf0AR06PiKrwCYyUyuclXjiJTXdu8eNGsmq4jVrCmXUplrrWTWrLIF3akTPHsGHTvKFrwV0jRJL1myhIEDBzJy5EgOHTpEQEAA9evX5/bt26nePj4+nrp163LlyhWWLVvG2bNnmTVrFnny5DFz5IpW1q+Xf3NvvgmFC2sdzYv17Ck/jzZtkss7TWkb2wgnnGxkox71TPtgJlSDGtSiFk95ytd8rXU4yutITIT27eHyZShYUK5zdjbzfubOzrJOb79+siXft69syVsbk412p0FQUJDo27ev4eeEhASRO3duERISkurtp02bJgoVKiTi4+Mz/Jhq4lhK1vac27eXc0IGD9Y6kldr1EjG+tlnpn2c7qK7QCA+FB+a9oHMYJfYJRAIR+EoLogLWoejZNSPP8o3f6ZMQhw/rm0siYlCfPFF0szvqVONdmibnjgWHx/PwYMHqVOnjuE6BwcH6tSpw549e1K9z6pVq6hYsSJ9+/bF19eXkiVLMnbsWBISEswVtqKhp09l/QOQvWiWrte/O0T+/LOst2AKT3jCcpYD1tvVnVwlKtGQhiSQYJhMpliZM2fg88/l5QkTZIESLel08PXXcrs6kC3qWbO0jSkdNEvSd+/eJSEhAV9f3xTX+/r6Eh4enup9Ll26xLJly0hISGDt2rUMHz6c7777jq+/fnHXWFxcHFFRUSlOinXasUNuquHjA0FBWkfzao0agb+/HJpbvtw0j7GOdUQSSV7yUoUqpnkQM9Mn54Us5AxnNI5GSZdnz6BzZ/mttG5dWR3MEuh0smjKwIHy5w8/lEVQrIDmE8fSIzExER8fH2bOnEn58uVp27YtQ4cOZfpLZueEhITg5eVlOPn7+5sxYsWYVsndF2nSRNtdptLK0VGOTYPpJpDpJ4y1ox0O1vXn/EKBBNKMZiSSSAghWoejpMeECXDggKwg9vPP2hfVT06nk/H16iU7vjt2hK1btY7qlTT7q86RIweOjo5ERESkuD4iIgI/P79U75MrVy6KFi2aosRliRIlCA8PJz4+PtX7DBkyhMjISMPp2rVrxnsSitkIkZSkraGrW69HD5msd+6Uq1GM6QlPDGVA22Ch69EyaBjDAPiVX7nEJY2jUdLk+nVZQxtkXdy8eTUNJ1U6nZxl3qoVxMfLDT6OHNE6qpfSLEm7uLhQvnx5QkNDDdclJiYSGhpKxYoVU71P5cqVuXDhAomJiYbrzp07R65cuXBxSX0zAVdXV7JkyZLipFifkyflRFFXV0g2jcHi5c6dtG3ljBnGPfZGNhJDDP74E0igcQ+usbd5m/rUJ4EEvuEbrcNR0mLQILkuuXJl2eVtqRwd4ddf5eYc0dHQtKksamChNO0fGzhwILNmzWL+/PmcPn2a3r17ExsbS7du3QDo3LkzQ4YMMdy+d+/e3L9/n48//phz587x119/MXbsWPr27avVU7AYXbt2RafTGU7Zs2enQYMGHDt2TOvQjEJfFKROHfCwsm2H9RPIfvnFuLvp6SeMtaJVujZjsRb61vRc5nKd6xpHo7zUtm2wZIlsqU6ebFnd3Klxc5OlC4sXlz0ALVrIrS8tkKZJum3btkyYMIERI0ZQpkwZjhw5wvr16w2TycLCwriV7BuOv78/GzZs4MCBA5QuXZqPPvqIjz/+mMGDB2v1FCxKgwYNuHXrFrdu3SI0NBQnJyeaNGmidVhGsW6dPG/cWNs4MqJWLbmmOyrKeIWP4olnFbL//x3eMc5BLUwVqlCd6sQTzwQmaB2O8iLPniXVwu3VS9brtQbe3vLbf7ZssH+/HJsSQuuonmeyxV0WylbXSXfp0kU0b948xXU7duwQgLh9+/YL72cNz/nhw6QNNS5e1DqajPn2Wxl/uXLGOd4GsUEgED7CRzwTz4xzUAu0SWwSCEQmkUntkGWp5syRb+5s2YS4e1fraNJv61YhnJwytK2eTa+TVkwrJiaGhQsXUrhwYbJnz651OK8lNFRuqFG0KBQqpHU0GdO1qywXeugQHD78+sfTd3W3pCWOWMFU9wyqTW2CCeYxj/me77UOR/mvuDj48kt5edgwsMbPmho1kkqGDh9uuvWSGaSS9CsIIccRtTilt+dlzZo1ZM6cmcyZM+Pp6cmqVatYsmQJDqbaccZM1q+X5w0aaBvH68iRI2kC2c8/v96xEkhgBSsA2+3q1tOhM4xNT2Uq97mvcURKCjNmyN2m8uSxnDXRGdGzJ3zyibz83nvy27SFsO5PbzN49AgyZ9bm9OhR+mKtWbMmR44c4ciRI+zfv5/69evTsGFDrl613s0KhLCNJA3Qvbs8//XX16tAtotd3OY2WclKDWoYJTZL1pjGBBBADDFMZrLW4Sh6MTEwZoy8PGKEnIxlzb79Vn7IPH4s13m+YA8Jc1NJ2oZ4eHhQuHBhChcuzNtvv83s2bOJjY1llhWVwPuv06flF3VXV6heXetoXk+dOrIC2YMHsGJFxo+jnzDWmMY4Y+ZNCzSgQ8dQhgLwAz8QhaoaaBF+/FEmsjfegH9X5Fg1JydYvFjO+L5xA9q1k5PiNKaS9Cu4u8svjFqc3N1fL3adToeDgwOPLXRpQVroW9HVq7/+66E1R0c5Ng2v1+W9GrkerTnNXz8oK9GKVhSnOA94wDSmaR2OEh0tq3cBjBpl/h2uTMXLC/74Q3Zlbt0KQ4dqHZFK0q+i08l1uVqc0rvUMC4ujvDwcMLDwzl9+jT9+/cnJiaGpk2bmubFMQNb6erW0zc4Nm+GjIxCnOUs5ziHM85WvS1lejniyBd8AcB3fMcj0jkWpBjXzJmyS6hoUdnitCUlSiR9i/7mG80nkqkkbUPWr19Prly5yJUrF8HBwRw4cIClS5dSo0YNrUPLkNhY2L5dXraVJF2wINSuLcfa581L//31reia1CQL9lU9rz3tKUhB7nCHWVjvEI7Vi4uDiRPl5c8/t45C+unVujV8+qm83K2b3NlLIypJ24h58+YhhDCcoqKi2L9/P++8Y72zf3fskOV1/f3lMJGt0E8gmzsXklW4TRP9eHRTrLd3JKOccGIIsgLhN3xDHHEaR2SnFiyAmzfljO733tM6GtMZN06Os0VHy1rfMTGahKGStGKx9GXd69a1/CqD6dGypSx2dPVq0nNMi3vcYxe7APtM0gCd6Uxe8nKTm8xnvtbh2J+EBNkFDLKl+YI9E2yCk5MsdZo7t5zBqlFFMpWkFYu1ebM8t6YNNdIiUybo0EFeTs8EsrWsJZFEAgggP/lNE5yFc8WVz/gMgBBCeMpTjSOyM3/8AefPy1Ka+n1YbZmvLyxdKhP277/LGe1mppK0YpHu3EnaQa5WLU1DMYkePeT5n3/C/TTW57Dnru7k3ud9fPDhClf4DSMVQ1fSRj8W3a+fnAFtDypVgu++k5c/+0zul21GKkkrFmnLFnleurT8MmtrypaFgAA5B2fRolffPp54NrABUEnaHXcGMhCQrelE0jmwr2TM/v2wd6/s4u7TR+tozKt/fzku/fQptGkDDx+a7aFVklYskq12devpdEmt6TlzXn37PewhmmhyktPm9o7OiN70xhtvznCGP/hD63Dsg76rt1072/zm/DI6nfxDLVgQrlyRsz/NND6tknQqhCVuV2Yilvpc9ROqbDVJgxyXdnGR3fqv2nRjHXKvzvrUx0H92ZKFLHyE3B5xLGMRWOb72GbcuiXHZCFpW0p74+0tXwMXFzlONdk8JWrVX3syzv9WzXmU3qLZVkz/XJ0tqGLQpUtw+bIsYlS1qtbRmE727HKmN7y6Nb0eWdWlIQ1NHJX1+IiP8MCDwxw2fIlRTGTGDNnVW6kSlC+vdTTaCQxMGp8eNAgOHjT5Q+qEpTalTCQqKgovLy8iIyPJkuX5YhC3bt3i4cOH+Pj44O7ujs6W1v4kI4Tg0aNH3L59G29vb3LlyqV1SAYzZ8KHH0K1aknFTGzVxo1Qv778kn7rVup7FNzkJnnIgw4dEUSQk5xmj9NSfcZnTGAClajETnaiwzb/XjUVFwf58sk63UuWyDFZeyaELHayfDlR+fLhFRb2wnxiDE4mOaoV8/PzA+C2heyAYmre3t6G52wp9OPRtWtrG4c51KkjP//CwmQPWvv2z99mIxsBCCRQJej/GMhAJjOZ3exmO9vtYlcws1u+XCboPHmSun7smX58+vBh2e1nYipJ/4dOpyNXrlz4+Pjw9Kltr8F0dnbG0cJK+iUmyrr2YB9J2sFBVh0cNUqumU4tSeu7chtgI7VRjSgXuehBD37iJ8YwRiVpU5g5U5737Gk7G2m8Li8vOT5dsaIcBjAh1d2tWJQTJ6BUKbnj1cOH9vGZcOUKFCoke9EuX4YCBZJ+94xn+ODDAx6wm91UpKJWYVqsq1ylMIV5xjP2sY8ggrQOyXacPStr8jo4yBJ5efNqHZFFiTp8GK9y5UyaT9TEMcWi6MegK1e2jwQNMinrew3+u+nGAQ7wgAdkJStv87a5Q7MK+clPJzoBMIYxGkdjY/R70TdurBJ0at54w+QPoZK0YlG2bZPnVrpxV4Yl33QjISHpev2s7rrUxUmNTr3QYAajQ8cqVnGc41qHYxvi4pK+NX7wgaah2DOVpBWLIURSS7p6dW1jMTf9phthYSk33VDj0WlTjGK0pjUg100rRvDnn3DvnmxB28pesVZIJWnFYpw+LWt2Z8oEb9tZz66bG3TsKC/rN924wx3+4R9AJem0+IIvAPid3znPeY2jsQH6CWM9esgNJhRNqCStWAx9K7pSJdveAe9Fkm+6ce8ebGITAkEAAeTCctaxW6oAAmhCExJJZBzjtA7Hul26JJdZ6HRJYzGKJlSSViyGvY5H65UtC2XKQHy83HRDPx6tWtFpN5ShAPzCL4QRpnE0VuyXX+S5fiG/ohmVpBWLYM/j0cklbbohWCdUkk6vClSgFrV4xjO+5Vutw7FOiYkwf7683LWrpqEoKkkrFuLsWYiIkGOzQXa8zLVDB3B1haNHddw9nBdPPKlEJa3Dsir61vRsZhNBhMbRWKEdO+Ti/SxZoEULraOxeypJKxZB34quWFEmKXuVLVuyyotzelCb2rhghwP0r6EmNalABZ7whAlM0Doc66NfdtWmjawqpGhKJWnFIujHo+25q1tP3+XNrx2p9bixprFYIx06hjMcgJ/4idvYRx1+o4iJgaVL5WXV1W0RVJJWNJd8PNpeJ40lV67WQyhwGSK9SVjeQutwrFJDGhJIII94pFrT6fHHHxAbC4ULy2UWiuZUklY0d/683KbR1RWCg7WORntbHUKhh9xgesXsHBpHY5106BjJSACmMpU73NE4IiuxYIE879JFLr9SNKeStKI5fSu6QoXU91O2N5vYBF3noXNIZPt2OHdO64isU2MaU57yPOIR3/Gd1uFYvvBw2LJFXu7QQdtYFAOLSNJTp06lQIECuLm5ERwczP79+19423nz5qHT6VKc3NQnu1VT49EpbWYz5L1B+Yay9aevQKakT/LW9BSmcJe7Gkdk4ZYulcuvgoPltmyKRdA8SS9ZsoSBAwcycuRIDh06REBAAPXr1+f27RdP9siSJQu3bt0ynK5evWrGiBVjUuPRKV3mMhe5iBNODHxfbn03b57Jt6y1WU1oQjnKEUusak2/yqJF8ly1oi2K5kl64sSJ9OzZk27duvHmm28yffp03N3d+fklzQedToefn5/h5Ovra8aIFWO6eBFu3JBlQCtU0Doa7W1mMyCLcrzbOBO+vnL9+F9/aRyYlfpva/oe9zSOyEJdvgx798p9o9u00ToaJRlNk3R8fDwHDx6kTp06huscHByoU6cOe/bseeH9YmJiyJ8/P/7+/jRv3pyTJ0+aI1zFBPSt6OBgubGGvdMn6TrUwdk5aRXM7NnaxWTtmtKUspQlhhgmMlHrcCzT4sXyvGZN8PPTNhYlBU2T9N27d0lISHiuJezr60t4eHiq9ylWrBg///wzK1euZOHChSQmJlKpUiWuX7+e6u3j4uKIiopKcVIshxqPTpJIIqHIfSrrIL+46tdMr1sHL3iLK6+gQ8cIRgDwIz+q1nRqfvtNnrdvr20cynM07+5Or4oVK9K5c2fKlClD9erV+eOPP8iZMyczZsxI9fYhISF4eXkZTv7+/maOWHkRNR6d0hGOcI97eOJJELI2apEi8gtMYiLMnatxgFasOc0pQxliiOF7vtc6HMty4gQcPw7OztCqldbRKP+haZLOkSMHjo6ORESkrK8bERGBXxq7XJydnSlbtiwXLlxI9fdDhgwhMjLScLp27dprx60Yx+XLcO2a/GyoWFHraLSn7+quQQ2ccTZc//778nzOHJmslfRL3pr+gR/Uuunk9K3ohg0ha1ZtY1Geo2mSdnFxoXz58oSGhhquS0xMJDQ0lIpp/NROSEjg+PHj5MqV+n67rq6uZMmSJcVJsQz6VnRQkCoRDCnHo5N75x3w9oarVyHZn4qSTi1oQXnKE0MMIYRoHY5lECJpPFp1dVskzbu7Bw4cyKxZs5g/fz6nT5+md+/exMbG0q1bNwA6d+7MkCFDDLcfPXo0Gzdu5NKlSxw6dIhOnTpx9epV3tc3NxSrocajkzzhCTvYATyfpDNlgk6d5GU1gSzjdOgYy1hA1vS+hupVY/9+uHQJPDygaVOto1FSoXmSbtu2LRMmTGDEiBGUKVOGI0eOsH79esNksrCwMG7dumW4/YMHD+jZsyclSpSgUaNGREVFsXv3bt58802tnoKSQWo8OskudvGEJ+QmNyUo8dzv9d9B//wT7qie2gyrS12qU5044hjNaK3D0Z6+q7t5c5moFYujE0IIrYMwp6ioKLy8vIiMjFRd3xq6cgUKFgQnJ3j4UH0+DGEI4xhHZzozn/mp3iYoCA4cgG++gc8+M3OANmQ3u6lMZRxx5BSnKEpRrUPSRkIC5M0ry4GuXg1NmmgdkdUxRz7RvCWt2Cd9K/rtt1WChhePRyfXq5c8nzFDTSB7HZWoRBOakECCYTKZXdq2TSborFmhXj2to1FeQCVpRRNqPDrJPe5xkIPAy5N027bg5SWrtKkJZK9nDGMAWMISDnNY42g0ou/qfvddWfJPsUgqSSuaUOPRSbayFYHgLd4iF6mvUgDZ49C5s7w8bZqZgrNRpSlNe+Rs5mEM0zgaDcTHw/Ll8rKa1W3RVJJWzC4sTK6RdnRU+8pD2rq69T78UJ6vWiVrnisZN5rROOLIWtayk51ah2NeW7fKySC+vlCtmtbRKC+hkrRidvpWdGAgeHpqG4sl2MQmQM48fpW33oKqVeWcnzlzTB2ZbStMYXog664OYQgCO5pD+8cf8rxlS/ltWbFYKkkrZqfGo5Nc+vefE05UI20tGv0Eslmz4NkzEwZnB0YwAjfc2MlO1rBG63DMIyEBVqyQl1UZUIunkrRidmo8Ool+Q40KVMCTtHUrvPMO5MghN9xYu9aU0dm+POThEz4BYBCDeIodbNy9ezfcvi3L2Kk/QounkrRiVtevy9nJDg5QubLW0WgvPV3deq6u0L27vDx9uimisi9DGIIPPpzjHNOwgxl5+q7upk1l4XzFoqkkrZiVvhVdvjzYey2Z1LamTKsPPpDn69fLSXhKxmUhC1/xFQBf8iX3ua9xRCYkhCxbB6qr20qoJK2YlRqPTnKEI9znPp548jZvp+u+b7wh608IATNnmihAO9Kd7pSkJA94YEjYNunwYblTi7u7KmBiJVSSVsxKjUcnedHWlGmln0A2Z45c9qpknBNOfMd3AExhCuc4p3FEJqLv6m7YUG09ZyVUklbM5uZNOH9ejkdXqaJ1NNrLyHh0ck2aQO7ccsMN/WevknH1qEcjGvGMZ/yP/2kdjmno3yiqq9tqqCStmI2+FV22rCxvac8e8/iFW1OmlbMz9OwpL0+ZYqzI7NsEJuCIIytYwVa2ah2OcZ0+LU/OztC4sdbRKGmkkrRiNmo8OsludhNHHLnJTXGKZ/g4H34odxLbtQsOHTJigHaqBCXohRxHGMhAEkjQOCIj0k8Yq11bfUu2IipJK2ajxqOTJO/q1qHL8HFy5YI2beTlyZONEZnyJV/ihRdHOPLCbUOtkurqtkoZStILFiygcuXK5M6dm6tXrwIwadIkVq5cadTgFNtx6xacPQs6nSxrae/SU6/7VT76SJ4vWiRrVCivJwc5GM5wAP7H/7jHPY0jMoKwMDh4UP4BNm+udTRKOqQ7SU+bNo2BAwfSqFEjHj58SEKC7A7y9vZm0qRJxo5PsRF//y3Py5SRhY7s2T3ucQjZN12b2q99vOBgCAqSM7xnzXrtwynAR3zEW7zFXe4yhCFah/P69F3dVauCj4+2sSjpku4kPXnyZGbNmsXQoUNxTFaYPTAwkOPHjxs1OMV2qPHoJFvYgkBQkpIv3ZoyPfr3l+c//QRP7aCypak542yoPjaLWexhj8YRvSbV1W210p2kL1++TNmyZZ+73tXVldjYWKMEpdgeNR6dxJhd3XqtW8tdB2/eVMuxjKUqVelKVwB605tnWOluJhERsEOuJKBlS21jUdIt3Um6YMGCHDly5Lnr169fT4kSJYwRk2JjIiLkyg81Hi2ZIkm7uiYVN/nxR6Md1u59wzdkJStHOcoUrHSd26pVsjRd+fKQL5/W0SjplO4kPXDgQPr27cuSJUsQQrB//37GjBnDkCFD+Pzzz00Ro2Ll9OPRpUtDtmzaxqK1jGxNmVYffiiXwO7eLecIKa8vJzkZz3gAhjOcG9zQOKIMUF3dVi3dSfr9999n/PjxDBs2jEePHtGhQwemTZvGDz/8QLt27UwRo2Ll1Hh0En0ruiIV07w1ZVqp5Vim0YMeVKQiMcQwgAFah5M+kZEQKjdxUUnaOmVoCVbHjh05f/48MTExhIeHc/36dXr06GHs2BQbocajk5iiqzs5/XKs335Ty7GMxQEHpjENRxxZylI2sEHrkNLur7/kTMISJaB4xovmKNrJ0MSx8+fPA+Du7o7Pv9P5z58/z5UrV4wanGL97tyBkyflZXsfj36drSnTKihILsmKj1e7YxlTAAF8hPwG1Ic+xGIlk2RVV7fVS3eS7tq1K7t3737u+n379tG1a1djxKTYEP14dKlSkCOHtrFo7TCHDVtTBhFkssdJvhwrLs5kD2N3RjGKvOTlEpcYxjCtw3m1R49g3Tp5WSVpq5XuJH348GEqV6783PUVKlRIdda3Yt/UeHQSfVd3TWrihJPJHqd1a8iTR1Z5W7TIZA9jdzzxZBayWswP/MAudmkc0Sts3CgTdf78clcbxSqlO0nrdDqio6Ofuz4yMtJQfUxR9PTj0SpJm348Ws/FBT7+WF6eMEGuvlGMowEN6EY3BIJudOMxj7UO6cX0Xd0tW8r1j4pVSneSrlatGiEhISkSckJCAiEhIVRRmwQrydy9C/oidNWMu9rI6iTfmjKj+0enxwcfgKcnnDqV1OOpGMdEJpKb3JznvKHGt8WJj4fVq+Vl1dVt1dKdpMePH8+WLVsoVqwY3bp1o1u3bhQrVoy///6bb7/91hQxKlZKPx795puqXPBOdhJHHHnIQzGKmfzxvLxkogZQf5bG5Y03M5Gz8r7ne/ayV+OIUrFtGzx8KP/wKlXSOhrlNaQ7Sb/55pscO3aMNm3acPv2baKjo+ncuTNnzpyhZMmSpohRsVJbt8rzmjW1jcMSbGQj8PpbU6bHxx/Lvaa3bYN//jHLQ9qNxjSmM51JJJFudOMJT7QOKSX9hhotWkCyPRYU65Oh2Su5c+dm7Nixxo5FsTFbtsjzWrW0jcMS6PePrkc9sz2mvz+0bw8LFsjW9JIlZntou/A937ORjZzhDF/yJeMYp3VIUkJCUpJWXd1WTydE+qeVPHz4kP3793P79m0SExNT/K5z585GC84UoqKi8PLyIjIykixZsmgdjs2KiAA/Pzlf5c4dyJ5d64i0E0EEfvgZLvtgvr7/o0fl9qAODnDhAhQsaLaHtgurWEVzmuOAA7vYRQUqaB0S7NoFVarIMY/bt+VMQsUkzJFP0t2SXr16NR07diQmJoYsWbKgSzZrUKfTWXySVsxD39UdEGDfCRqSZnWXpaxZEzTI179ePbka5/vv1eYbxtaMZnSkI7/yK53oxGEOG73ca7rpZ3U3aaIStA1I95j0p59+Svfu3YmJieHhw4c8ePDAcLp//36Ggpg6dSoFChTAzc2N4OBg9u/fn6b7LV68GJ1OR4sWLTL0uIrpqK7uJPqubnPM6k7NZ5/J8zlz4N49TUKwaVOYQj7ycZGLfMzH2gYjhKoyZmPSnaRv3LjBRx99hLu7u1ECWLJkCQMHDmTkyJEcOnSIgIAA6tevz+1XFB6+cuUKgwYNoqq915q0UPqWtL0naYEwTBoz53h0crVryy7vR49g2jRNQrBp3nizkIU44MBc5rKMZdoFc+QIXLkCmTJB/fraxaEYTbqTdP369fnHiFNFJ06cSM+ePenWrRtvvvkm06dPx93dnZ9//vmF90lISKBjx46MGjWKQoUKGS0WxTjCwuT4p6Ojqtd9ilPc4hZuuFGZ5yv1mYNOB4MGycuTJ8MTC5uIbAuqUpXBDAbgAz7gOte1CUTfim7QADw8tIlBMap0j0k3btyYzz77jFOnTlGqVCmcnZ1T/L5Zs2ZpPlZ8fDwHDx5kyJAhhuscHByoU6cOe/bseeH9Ro8ejY+PDz169GDHjh0vfYy4uDjikhUwjoqKSnN8SsboW9GBgWDvc/P0rejqVMcNN83iaNMGvvhCfoGaOxd699YsFJv1JV+ykY38wz90oQub2IRDxjYazDg1q9vmpDtJ9+zZE5CJ8r90Ol26SoPevXuXhIQEfH19U1zv6+vLmTNnUr3Pzp07mTNnTprrhIeEhDBq1Kg0x6S8PtXVnUTr8Wg9Z2c5Nt2/P4wbBz16qDlFxuaMM4tYRBnKsIUtTGQigxhkvgDOnpVbzjk5yUljik1I99e8xMTEF55MXbs7Ojqa9957j1mzZpEjjVsqDRkyhMjISMPp2rVrJo3R3gmRNGnM3ouYxBHHNrYB2o1HJ9ejh1wWFxYm104rxleEIvyInEL/BV9wmMPme3B9K7pWLfD2Nt/jKiZl5r6YlHLkyIGjoyMREREpro+IiMDPz++521+8eJErV67QtGlTnJyccHJy4pdffmHVqlU4OTlx8eLF5+7j6upKlixZUpwU07l4Ea5dky23VDZLsyu72c1jHuOHHyXRvhpfpkxJY9Njx8KzZ9rGY6u6051WtOIpT2lHO6J5fkMik1Czum1ShiqOxcbGsn37dsLCwoiPj0/xu48++ijNx3FxcaF8+fKEhoYallElJiYSGhpKv379nrt98eLFOa7fseFfw4YNIzo6mh9++AF/f//0PxnFqPRd3RUqgJEWAFgt/Xh0HeqYrRToq/TqJbu7L12C336D997TOiLbo0PHTGZygAOc4xwf8iG/8qtp3wNhYXDggJwl2Ly56R5HMbt0J+nDhw/TqFEjHj16RGxsLNmyZePu3bu4u7vj4+OTriQNMHDgQLp06UJgYCBBQUFMmjSJ2NhYunXrBsgKZnny5CEkJAQ3N7fn6oN7/9uto+qGWwa1PjqJFqVAX8XDAwYOlJPIxoyBDh1UaWdTyE52lrCEalTjN36jOtX5kA9N94ArVsjzypXlmIZiM9Ld3T1gwACaNm3KgwcPyJQpE3v37uXq1auUL1+eCRMmpDuAtm3bMmHCBEaMGEGZMmU4cuQI69evN0wmCwsL49atW+k+rmJ+QqhJY3p3ucshDgGm3z86vfr2haxZ5TyjZRou6bV1FalICCEAfMzHph2fVl3dtkukk5eXlzhz5ozh8qlTp4QQQuzdu1cUK1YsvYczu8jISAGIyMhIrUOxOSdPCgFCuLkJ8eSJ1tFoa7FYLBCIUqKU1qGk6ssv5f9VyZJCJCRoHY3tShSJoqloKhCIwqKwiBQm+Ny5fVsIBwf5H3r5svGPr7yQOfJJulvSzs7OODjIu/n4+BAWFgaAl5eXmjlt5/Rd3VWqgKurtrFozVKWXr3IRx+BpyecOAGrVmkdje3SoWMe88hHPi5wgZ70RJDuPY1ebtUqSEyEcuWgQAHjHlvRXLqTdNmyZTlw4AAA1atXZ8SIEfz666988sknalzYzqmubskSSoG+Stascs00wFdfyaEKxTSykY0lLMEJJ37nd6Zh5Nqs+q7uli2Ne1zFIqQ7SY8dO5ZcuXIBMGbMGLJmzUrv3r25c+cOM2bMMHqAinVITExK0va+Pvoc57jGNVxwoSqWWxd1wAA5A//QIVi3TutobFsFKjCe8QAMYAD72GecA0dGwma5y5oaj7ZN6U7SgYGB1Pz3U9jHx4f169cTFRXFwYMHKVOmjLHjU6zE0aPw4IHsQg0M1Doabelb0VWpijuWuw4tR46k8qAjR6rWtKkNYAAtaUk88bzDO0QQ8eo7vcratRAfD8WKQYkSr388xeKkO0nXqlWLhw8fPnd9VFQUtey9n9OO6VvR1arJqoT2bB2yWWqpXd3Jff65XJb1zz9Jq3gU09CPTxenODe4QWta85Snr3fQ5LO6dZaxFl8xrnQn6W3btj1XwATgyZMnr9zsQrFdoaHy3N67uh/zmK3IbywNaahxNK/m4wOffCIvDx8OJq7sa/eykIUVrMATT3awg0/5NOMHe/xYtqRBdXXbsDS3eY4dO2a4fOrUKcLDww0/JyQksH79evLkyWPc6BSrEBcH27bJy3UtczKz2WxnO094Ql7yWkQp0LQYNAimTpV7M/z2G3TqpHVEtq0YxVjIQprTnMlMpjzl6UKX9B9o0ya5Sbi/P5Qvb/xAFYuQ5iRdpkwZdDodOp0u1W7tTJkyMXnyZKMGp1iH3bvlZ4WvL5QqpXU02tJ3dTekocWUAn0Vb2/43/9gyBA5Nt22ray9rphOM5oxkpGMYhQf8iElKUl50plok8/qVl3dNivN3d2XL1/m4sWLCCHYv38/ly9fNpxu3LhBVFQU3bt3N2WsioXasEGe16unPivWIrsfraGrO7n+/eWXrEuX4OeftY7GPoxgBE1oQhxxtKIVd7iT9js/fZq0wF11ddu0NCfp/PnzU6BAAbZu3UqZMmXInz+/4aRfkvX333+bLFDFcm2Uk5mpX1/bOLR24d9/TjhRm9pah5MuHh4wdKi8PHq0HO5UTMsBBxaykKIUJYwwWtGKOOLSduft2+Vyipw5ZfUgxWZlaHb3/fv3n7v+4cOHhqVZiv24fRsO/1uSuI5llag2O31XdxWqkAXr2xL1gw8gXz64eRN++knraOyDF16sYAVeeLGTnfSiV9oqkum7ups3Vzuk2Lh0J2khBLpU+jTv3buHh4eHUYJSrMcmWf2SMmVkd6k9Sz4ebY1cXeHLL+XlkBCIitI0HLtRghL8zu844sg85vEt3778DomJ8Oef8rLq6rZ5aZ441urfN4NOp6Nr1664JivOnJCQwLFjx6hUqZLxI1Qsmurqlqxt6dWLvPcejB8vd8iaNAlGjNA6IvtQj3pMYhL96c9gBlOUorSgReo33rsXwsMhSxZVg9cOpLkl7eXlhZeXF0IIPD09DT97eXnh5+fHBx98wMKFC00Zq2JhhEhK0vUsv26HSemXXuUhj9UsvUqNk5MckwaYMEEOZyjm0Y9+9KEPAkEnOnGEI6nfUN+KbtJE7WRjB9Lckp47dy4ABQoUYNCgQaprW+H4cfmF3t1d7jVvz6xx6dWLvPuuXHZ78CCMGiXXUCvm8QM/cI5zbGYzzWjGfvbjh1/SDYRQG2rYmXSPSY8cOVIlaAVIakXXqKG+0Fv7eHRyDg7w3Xfy8owZcPq0tvHYEyecWMpSilGMa1yjGc2IJTbpBseOyXVybm7QoIF2gSpmk6aWdLly5QgNDSVr1qyULVs21YljeocOHTJacIplU13d0gUucJ7zOOFEHWxjinv16nLi8MqV8NlnsGaN1hHZD2+8WcMaKlCBAxygDW1YyUqccEpqRdevD5kzaxuoYhZpStLNmzc3TBRr0aKFKeNRrMSjR6BfFm/vSdral169yDffwF9/yVNoKNS2rqXfVq0whVnNampRi7WspTe9mclMdMk31FDsgk4I+9qgLioqCi8vLyIjI8mSxXY+UM1twwbZ2+bvD1ev2nelsUY0Yh3rGM94PudzrcMxqo8+gsmTISBAjlGrJbnmtZKVtKIViSTy5Z1+jPSZImf3RURAtmxah2f3zJFP0j0mnVxMTAxRUVEpTop9SN7Vbc8J2laWXr3IyJGytvfRo/DLL1pHY3+a05ypyJl7X+acwpzuyKpBKkHbjXQn6cuXL9O4cWM8PDzw8vIia9asZM2aFW9vb7JmzWqKGBULlLxetz2zlaVXL5I9OwwbJi8PHQqxsS+/vWJ8vejFUGTN1g9nwNpPimockWJOaV6CpdepUyeEEPz888/4+vq+dBKZYptu3JDbGup0qhSoLS29epF+/WSZ0EuX5NrpkSO1jsj+fHWhC9d3jmF+V2hdbzabaUdFKmodlmIG6U7SR48e5eDBgxQrVswU8ShWQF8K9O237bvXTSCsdter9HB1hXHjoE0bOZmsZ0/InVvrqOyLbvkfzBoG4W9lZ8Pb92hEI7axjQACtA5NMbF0d3e//fbbXLt2zRSxKFZCdXVLZzjDBS7gggt1qat1OCb17rtQqZKc1f+5bc2Nsw7LluH8DJYfG0FlKvOQh9SjHuc4p3VkiomluyU9e/ZsevXqxY0bNyhZsiTO/9kdvnTp0kYLTrE8iYlJLWl7r9e9kpUA1KIWnnhqHI1p6XTwww8QFAS//ip3zKpWTeuo7MSVK/DPP+DggEeTtqyhMzWpyRGOUIc67GQn+cindZSKiaQ7Sd+5c4eLFy/SrVs3w3U6nc6wO1ZCQoJRA1Qsyz//wL17srZ/cLDW0WhrFasAOQPXHgQGyuQ8Y4Ycpz50SK4GUkxs+XJ5Xq0a+PriDWxgA9WoxlnOUpe6/M3f+GLn29DZqHR3d3fv3p2yZcuyZ88eLl26xOXLl1OcK7ZNX3mqXj34TyeKXYkggr3sBaApTTWOxnzGjJHzEI4fV3tOm82yZfL83XcNV/ngwyY2kY98nOMc9anPAx5oFKBiSun+Hnz16lVWrVpF4cKFTRGPYuH++kueN26sbRxaW8MaBIJAAslDHq3DMZvs2WHsWOjVC4YPh7Zt1T7iJnXtmtyaUqd7bkMNf/zZzGaqUpWjHKUBDdjABrzx1iZWxSTS3ZKuVasWR48eNUUsioW7dUt2cQI0tN3JzGmiH49uRjONIzG/99+Xu2RFRcH//qd1NDZOXwa0cuVUp9QXoQgb2Uh2srOf/dSnPpFEmjlIxZTS3ZJu2rQpAwYM4Pjx45QqVeq5iWPNmtnfh5a9WCtXGxEUZN+tp0c8YhNy9py9jEcn5+got6+sUAHmz5fj1JUqaR2VjUqlq/u/SlOaUEKpRS32s5961GMjG/HCy0xBKqaU7trdDg4vbnxbw8QxVbs741q2hBUr5B7DI0ZoHY12VrKSFrQgP/m5zGWbLWLyKj16wM8/Q9mycOCAquttdDdvQt68cg/psDBZKP8ljnKUWtTiPvcJIkglajOwyNrdiYmJLzxZeoJWMi4uLmnplb2PRyef1W2vCRpkgRNvbzh8WM74Vozszz9lgq5Q4ZUJGiCAALawhWxkU13fNuS1NtjQe/jw4Wvdf+rUqRQoUAA3NzeCg4PZv3//C2/7xx9/EBgYiLe3Nx4eHpQpU4YFCxa81uMrr/b337Jus5+fbDnZqwQSWM1qwD7Ho5PLmRO+/lpe/uILOWdBMaI0dHX/VwABhBJKNrKxj33Uox73uW+iABVzSHeSHj9+PEuWLDH83Lp1a7Jly0aePHkyNKFsyZIlDBw4kJEjR3Lo0CECAgKoX78+t2/fTvX22bJlY+jQoezZs4djx47RrVs3unXrxgZ9GSzFJPSzuhs1gpeMeNi8fezjDnfwxptqqGoevXrJ9dORkXJbS8VIIiKSNmx/55103bUMZQyJej/7qUlNIogwQZCKWYh0KlCggNi1a5cQQoiNGzcKb29vsWHDBtGjRw9Rt27d9B5OBAUFib59+xp+TkhIELlz5xYhISFpPkbZsmXFsGHD0nTbyMhIAYjIyMh0x2qvEhOFKFRICBBi+XKto9HW5+JzgUB0EB20DsViHDkihKOjfH+sXKl1NDZi6lT5ggYGZvgQx8Vx4Sf8BAJRRBQRV8VVIwaoCGGefJLuNlF4eDj+/46PrFmzhjZt2lCvXj0+//xzDhw4kK5jxcfHc/DgQeok20rJwcGBOnXqsGfPnlfeXwhBaGgoZ8+epZqqUWgyJ0/KHZBcXVW9bv14tL13dScXEACDBsnLffrIpVnKa1q8WJ63a5fhQ5SkJDvYQX7yc57zVKEK5zlvpAAVc0l3ks6aNathg43169cbEqwQIt0Tx+7evUtCQgK+/1nP4+vrS3h4+AvvFxkZSebMmXFxcaFx48ZMnjyZunVT3+AgLi6OqKioFCclfVbKJcHUqQOZM2sbi5bOcY4znMEZZxrQQOtwLMqIEVCokNzGVL//tJJB167Bjh3yctu2r3WowhRmBzsoSlGucY2qVOUYx4wQpGIu6U7SrVq1okOHDtStW5d79+7R8N+qFocPHzZbFTJPT0+OHDnCgQMHGDNmDAMHDmTbtm2p3jYkJAQvLy/DyT8NsySVlFaskOfN7W9JcAr6VnQNaqilLf/h7g7Tp8vLU6bIIllKBv3+uzyvWlUuwXpN/vizgx2UoQwRRFCDGuxm92sfVzGPdCfp77//nn79+vHmm2+yadMmMv/btLp16xZ9+vRJ17Fy5MiBo6MjEREpJzVERETg5+f34qAdHChcuDBlypTh008/5d133yUkJCTV2w4ZMoTIyEjDSW2zmT43bshNNXQ6aGo/JapTpa8yZo8FTNKibl3o3FmuGurZE54+1ToiK2WEru7/8sGHrWylIhV5wANqU5sVrDDa8RXTSXeSdnZ2ZtCgQfzwww+UTbYWZ8CAAbz//vvpOpaLiwvly5cnNDTUcF1iYiKhoaFUrFgxzcdJTEwkLi4u1d+5urqSJUuWFCcl7VbJxiMVKsjlV/bqDncMrQ972lAjvb77DnLkgBMn4NtvtY7GCl24IL8VOzqma+lVWnjjzSY20YQmPOEJ7/AO05hm1MdQjC9DG82dP3+erVu3cvv2bRITE1P8bkQ6S1ENHDiQLl26EBgYSFBQEJMmTSI2NtawFWbnzp3JkyePoaUcEhJCYGAgb7zxBnFxcaxdu5YFCxYwbZp6s5mCfjxadXWvIpFEylJW7d37EjlywPffw3vvwejR0KoVFC+udVRWRL+8tXZt8PEx+uE98OBP/qQPfZjFLPrQh2tcYwxj7LowjyVLd5KeNWsWvXv3JkeOHPj5+aHTJf3H6nS6dCfptm3bcufOHUaMGEF4eDhlypRh/fr1hslkYWFhKUqRxsbG0qdPH65fv06mTJkoXrw4CxcupO1rTrBQnhcVBVu2yMv2nqSXIQtLvItxWze2qGNHWLgQNmyArl1h506173Sa/fabPDdiV/d/OeHEDGbgjz8jGEEIIdzgBrOYhQsuJntcJWPSXbs7f/789OnTh/9Z6fY3qnZ32v3+u5xcWrQonD2rdTTaecADfPDhGc84y1mKUlTrkCzetWtQsqT8ojdunNotK01OnIBSpcDFRRYz8fY2+UP+zM98wAckkEBtarOUpWQlq8kf11ZYZO3uBw8e0Lp1a1PEolgY/S55LVpoGobmVrOaZzyjFKVUgk4jf3/44Qd5ecQImX+UV9BPGGvY0CwJGqA73VnNajzwIJRQKlCBc5wzy2MraZPuJN26dWs2btxoilgUC/L4MaxZIy8bef6K1VFd3RnTpQs0aQLx8bLbW832fgkhTDKrOy0a0pDd7CYf+TjHOYIJJpTQV99RMYt0jxQVLlyY4cOHs3fv3lT3k/5IFfC1CRs2yA018uWTtZntVRRRbEDWhX+H9NVQtnc6HcycCW+9BQcPym7v4cO1jspC/fMPXLwoF5xrsNaxNKXZz35a0pI97KE+9ZnCFHrRy+yxKCmlO0nPnDmTzJkzs337drZv357idzqdTiVpG6HfgOedd+SHrb1awxriiac4xXmTN7UOx+rkyiWLm3TsKGd7N20KZcpoHZUF0reimzUDDw9NQvDFly1s4X3e51d+pTe9OclJJjIRZ5xffQDFJNKdpC9fvmyKOBQLEhcHq+VujKqrO1lXt1qikjHt28svfX/+KbvADxyQc6OUfyUmJi29MnNX93+54cYCFvAmbzKUoUxhCsc4xhKW4IcdF0rQkB1vOqi8yObNclZu7tyyiIm9iiaadawDVFf369DpZMnQHDng2DH48kutI7Iwu3bJ0n5eXtBA+5rwOnR8wRf8yZ944snf/E15yrOHV296pBhfhlYvXr9+nVWrVhEWFkZ8fHyK302cONEogSna0Xd1t2pl33tHr2QlT3hCMYoRQIDW4Vg1Hx+ZqN99V45N16sHNWpoHZWFWLRInrdsKbeasxAtaGEYpz7DGapTnR/5kQ/5UPUqmVG6k3RoaCjNmjWjUKFCnDlzhpIlS3LlyhWEEJQrV84UMSpm9PRpUpUxe+/qXowcJ2xHO/WhZATvvAM9esCcOdCpk2xVZ8umdVQai4tL6uru0EHbWFJRnOLsZz/d6MZyltOb3uxnP1OZSiYyaR2eXUh3O2nIkCEMGjSI48eP4+bmxvLly7l27RrVq1dX66dtwObN8OCBbPlUqaJ1NNq5z33DrO62qGp2xvLDD7I4zo0b8P77cuWRXfvrL/kHlycP1KqldTSp8sSTpSxlHONwwIG5zKUCFTiLHVc4MqN0J+nTp0/TuXNnAJycnHj8+DGZM2dm9OjRjB8/3ugBKualn2TaurWs8W+v/uAPnvGMAAIoQQmtw7EZHh6y8qWzs5xINmuW1hFpbP58ed6pk0X/wenQ8T/+xwY2kJOcHOMY5SnPAhZoHZrNS3eS9vDwMIxD58qVi4sXLxp+d/fuXeNFppjd48fygxPkjFx7lryrWzGucuVAv7PsJ5/A6dOahqOdO3dg7Vp5+d+Gj6WrQx2OcpSa1CSWWDrTmW50I5ZYrUOzWelO0hUqVGDnzp0ANGrUiE8//ZQxY8bQvXt3KtjzVGAbsG4dREfLko7p2CnU5oQTzla2Aqqr21QGDJD7Tz9+LL8QvmCnWdu2eDE8eyarBb1pPWvwc5GLTWxiFKNwwIF5zONt3uY4x7UOzSalO0lPnDiR4OBgAEaNGkXt2rVZsmQJBQoUYM6cOUYPUDGf5FUJ7XlW9zKWkUgiwQRTkIJah2OTHBxkT2+OHHD0qJ1uwPHLL/LcSlrRyTniyAhGsIUt5CY3pznN27zNJCaRSOKrD6CkWbp2wUpISGDXrl2ULl0abzMVgDc2tQtW6qKj5WSxJ09kCUd7nqhfgQrsYx/f8z2f8InW4di0v/6S9b1B7rpmN3NPT52S9VKdnODmTciZU+uIMuwOd+hGN/7iLwBqU5t5zCMveTWOzPQsbhcsR0dH6tWrx4MHD0wSjKKdVatkgi5aFMqW1Toa7ZznPPvYhwMOajzaDBo3hs8+k5e7dbOj8Wl9K7pRI6tO0AA5yclqVjONaWQiE6GEUprS/M7vWodmE9LdqVmyZEkuXbpkilgUDSXfa96ea3UvZCEA9ainyiCaydixULOm3NClZUtZ7c6mJSTAQvk+o0sXbWMxEh06etGLwxwmkEAe8IC2tKUznXmAatS9jnQn6a+//ppBgwaxZs0abt26RVRUVIqTYn1u35a7XoF9z+oWCEOSfo/3NI7Gfjg5yfkQefLA2bPQvbuNr5/eulUuFM+aVXYl2JBiFGM3uxnGMBxwYAELeIu3WM1qrUOzWmlO0qNHjyY2NpZGjRpx9OhRmjVrRt68ecmaNStZs2bF29ubrFmzmjJWxUR++01OMg0KguLFtY5GO7vZzSUukZnMtKCF1uHYFR8fWY7W2RmWL4fvvtM6IhPSr41u186iyoAaizPOfMVX7GAHRSnKLW7RjGa8x3vc577W4VmdNE8cc3R05NatW5x+xaBR9erVjRKYqaiJY88rXx4OHZJbCvbtq3U02ulFL2Ywgy50YR7ztA7HLk2bBn36yNnfmzfLbnCbEh0Nfn7w6BHs2WPzO9g85jEjGMFEJpJIIr74Mp3pNvMl2Bz5JM1J2sHBgfDwcHx8fEwSiLmoJJ3SiRNQqpRswdy8KZfE2KM44shFLh7wgE1sog51tA7JLgkBXbvKeVU5c8I//0C+fFpHZUTz58snWLQonDljNxNA9rGPbnTjNLKR9y7vMolJ5CGPxpG9Houb3a2zkzeUPVnwb1W/xo3tN0ED/MVfPOABuclNTWyt+WY9dDrZmi5TRhbkatLExiaSJV8bbUefp8EEc4hDDGEIjjiyjGWUoAQ/8iPPeKZ1eBYtXUm6aNGiZMuW7aUnxXokn2RqhfUUjOpnfgagM51xxHJrKNsDd3e5E5uvLxw/LiczPrOFz/FLl2DLFnm5UydtY9GAG26MZSwHOUgFKhBNNB/zMcEEc4ADWodnsdK1VeWoUaPw8vIyVSyKmYWGyi7ubNnkck17dZObrGMdAN3opnE0Csgu7tWroXp1Wd56wAD48Ucrb3zOni3P69WD/Pm1jUVDAQSwi13MZjb/438c4hDBBNOHPoxhDF6oHJOCSCOdTiciIiLSenOLFRkZKQARGRmpdSiaa9dOCBCid2+tI9HWODFOIBCVRWWtQ1H+Y9ky+R4FIUJCtI7mNcTHC+HrK5/I8uVaR2MxwkW4eE+8J/j3n5/wE7+J30SiSNQ6tDQxRz5Jc3e3Go+2LffuwR9/yMs9emgbi5YEwtDV3Z3uGkej/Nc778D338vLQ4YkNUatzqpVEBEh+/CbNtU6Govhiy+/8AuhhFKUooQTTnvaU5vaHOWo1uFZhDQnaWHT1QXsz8KFEB8vS4CWL691NNrZzW7OcQ4PPGiNvRSOti6ffCITNMCHHyZ9ubQqM2fK8+7d5VIKJYVa1OIYxxjNaFxxZStbKUtZetKTCCK0Dk9TaU7SiYmJVr/8SpGESGqRvP++trFoTd+KbkMbPPHUOBrlRcaMkT0+iYnQtq2cWGY1Ll2CjRvl5Z49tY3FgrniynCGc4YztKUtAsFsZlOEIoxjHE94onWImrDjDQnt1759cn10pkzQoYPW0WgnmmiWsARQXd2WTqeDGTOSZnq3bi0nllmF5BPGCqqtT1+lAAVYzGJ2spO3eZtoohnCEEpQgqUsRWBfvboqSdsh/WdG69ZgpTuOGsWv/EossRSjGJWprHU4yis4Osplxm3bwtOncrx6+XKto3qFp0/hZ9lbw4cfahuLlalMZfayl1/4hTzk4QpXaEMbqlGN/ezXOjyzUUnazkRHy80MwL67ugWC6UwHZDlQHWpipDVwcpLzKdq0kfmvTRsLn0ymJoy9FgcceI/3OMtZRjKSTGRiJzsJJphWtOIUp7QO0eRUkrYzCxfKLQGLFYMqVbSORjv72c9RjuKKK52x80ouVsbJCRYtkl8yExPlMO/48Ra6c5aaMGYUHnjwJV9yjnN0oQsOOPAnf1KKUnSlK1e4onWIJqOStB0RAqZOlZf79LHywhCvSd+KbktbsqEq5VkbR0eZ/wYPlj8PHgwffCBXLFgMNWHM6PKSl3nM4zjHaUlLEklkPvMpSlE+4iObnAmukrQd+ftvOHkSPDxsZq/5DHnAAxYj+/x70UvjaJSM0ukgJAR++EHumjV7tpybde+e1pH9S00YM5k3eZM/+IN97KM2tXnKUyYzmTd4g2EM4yEPtQ7RaCwiSU+dOpUCBQrg5uZGcHAw+/e/eFLArFmzqFq1qmEf6zp16rz09kqSKVPkeadOYM/VXRewgCc8oRSlqIBtbxVoDz76SM709vSE7dvluv9//tE4KDVhzCyCCGLzv//e5m1iiWUMYyhAAYYznHtYyje2jNM8SS9ZsoSBAwcycuRIDh06REBAAPXr1+f27dup3n7btm20b9+erVu3smfPHvz9/alXrx43btwwc+TW5cYN+PNPedme94xOJJGpyD5/NWHMdjRqBLt3wxtvwNWrULky/PSThuPUK1eqCWNmVJva7GMff/AHb/ImkUTyNV9TgAL8j/9xm9TziVUwWcHRNAoKChJ9+/Y1/JyQkCBy584tQtJYqPfZs2fC09NTzJ8/P023t9fa3SNGyLLBVatqHYm21ol1AoHIIrKIKBGldTiKkT14IESLFkn1vlu2FOLOHQ0CqVZNBjB0qAYPbt8SRIJYJpaJABFgqAmeSWQSn4hPxA1xw6iPZVG1u00hPj6egwcPUqdOHcN1Dg4O1KlThz179qTpGI8ePeLp06cv3CYzLi6OqKioFCd7ExcnC0GAfbeiAX7kR0AWL1EVxmyPt7csG/rdd3Iy9Z9/QqlSsG6dGYM4ckROAHFygt69zfjACshlW+/wDoc5zCpW8TZv85jHTGIShShEX/pylatah5lmmibpu3fvkpCQgK+vb4rrfX19CQ8PT9Mx/ve//5E7d+4UiT65kJAQvLy8DCd/f//Xjtva/Pab7HnLnRtattQ6Gu2c5SzrWIcOHX2x828rNkyng4EDZWW9EiUgPFx2h3fuDHfumCGAyZPl+TvvQJ48ZnhAJTU6dDSlKfvYx3rWU5nKxBHHT/zEG7xBRzpymMNah/lKmo9Jv45x48axePFi/vzzT9zc3FK9zZAhQ4iMjDScrl27ZuYotSUETJwoL3/0Ebi4aBuPlqYgZ841pjGFKaxxNIqplS0LBw/Cxx/LxL1ggUza8+ebcKz67l349Vd5+aOPTPQgSnro0FGf+uxgB1vZSm1qk0ACi1hEOcpRhzqsZ73FlhvVNEnnyJEDR0dHIiJSrm2LiIjAz8/vpfedMGEC48aNY+PGjZQuXfqFt3N1dSVLliwpTvYkNBSOH5fLrj74QOtotBNJJPOYB8BHqA9Pe5EpE0yaBHv2yG7ve/ega1eoUwfOnzfBA86eLceXypeHihVN8ABKRunQUYMabGYzBzlIBzrgiCOhhNKQhpSmNPOZTzyWtNhe4yTt4uJC+fLlCQ0NNVyXmJhIaGgoFV/yBv/mm2/46quvWL9+PYGBgeYI1WrpW9Hdu0PWrNrGoqU5zCGGGEpQgjqkPjSi2K7gYNmqHjcO3NxgyxaZtEeMgJgYIz3I06dySjnIVrQ9VwuycOUox6/8ykUuMoABZCYzJzhBV7pSkIKMZ7zlLN8y2ZS0NFq8eLFwdXUV8+bNE6dOnRIffPCB8Pb2FuHh4UIIId577z0xePBgw+3HjRsnXFxcxLJly8StW7cMp+jo6DQ9nj3N7j55Uk4w1emEuHBB62i0Ey/ihb/wFwjETDFT63AUjV24IETdukkzwHPnFmL+fCESEl7zwIsWyQP6+Ajx+LFRYlXM44F4IMaJcSKXyGWYEe4m3ER30V0cEodeeD9z5BPNk7QQQkyePFnky5dPuLi4iKCgILF3717D76pXry66dOli+Dl//vwCeO40cuTIND2WPSXp7t3lZ0arVlpHoq0FYoFAIHyFr3gs1IenIkRiohDLlwtRsGBSsg4MFGLnztc4YLly8kCjRxs1VsV84kScmCfmiXKinCFZIxCVRWWxWCwW8SI+xe3NkU90QlhkWXqTiYqKwsvLi8jISJsenw4Lk4Udnj2TRR7sdXhMIChDGY5xjK/5mqEM1TokxYI8eSLLio4ZI3eIA3j3Xflz0aLpONC2bVCzphwEDwuDHDlMEa5iJgLBXvYymcksZSnPeAZALnLRi158wAf44WeWfGLVs7uVF5swQSbomjXtN0EDbGITxziGO+70Rq1ZVVJyc4P//Q/OnZO7aul0sGwZvPmmnGh5/XoaDzRhgjzv1k0laBugQ0dFKrKIRYQRxkhG4ocft7jFSEbijz9taMN2tps+FtWStj23b0P+/LKVsHkz1K6tdUTaqUc9NrGJ/vQ3FDJRlBc5dgyGDoU1a+TPbm7Qv7/cZesF9ZLg1Cl46y2Z4c+dg8JqeZ8tiieeZSxjMpPZy155ZRTghWpJK+nz/fcyQQcFQa1aWkejnX/4h01swgEHBjBA63AUK1C6tNysY+dOud/6kyfw7bdQqBCMHSv3Yn/Od9/J8xYtVIK2YS640IEO7GEPhzlML3rhgYfJH1e1pG3Mw4eQL58cX1u5Epo10zoi7bSgBStZSSc6sYAFWoejWBkhZDnRIUNkCxvkfhnDhsmucTc34No1Ofnj6VPYtQsqVdI0ZsW8bkTdIK9XXtWSVtLu++9lgi5ZEpo00Toa7RzjGCtZiQ6dmiymZIhOJ8uJHj4si4gVKiTL6/bvLxvMU6fCk/E/yARdvbpK0HbIHPX/VZK2IffuySQNMHIkONjx/+4YxgDQmtYUp7jG0SjWzMEBOnSA06dlrZK8eeXWr/36QeGpA5hKH558NlzrMBUbZccf47bn229lK7pMGWjVSutotHOGMyxlKQDDGKZxNIqtcHGRm1pduPBvsvZ8yA3y0I+pFP6wlmxZP9E6SsXWqCRtIyIikjbfGT1ataIFgha0oBSltA5HsTGurtC7/UMuUISf6E3e7I+4cUMnW9aF5d/ho0daR6nYCjv+KLct48fLD4agIPseiz7FKX5F7kKkWtGKyUyZgmv0XXq/tYML19xSdIN/9BEUKCBngz98qHWgirVTSdoGhIUl1fUfPdq+6/qPYAQCQStaUZ7yWoej2KKHD5OWXQ0dimsmhxTd4AUKyH2rhw6V9QoGD5Y9XYqSESpJ24Dhw+XueNWrQ716WkejnUMcYjnL0aFjNKO1DkexVT/8IBP1m29CmzaGq11d5Zj1uXNy7+q33oKoKNnLlT8/9OkDly9rF7ZinVSStnJHjsgPBJCVCe25Fa3v3u5IR97iLY2jUWzSw4cpl1A4Oj53E2dn6NRJrq1euVJukxkXB9OmQZEi8neHD5s3bMV6qSRt5T7/XBZdaN8e7Hlr7Z3sZB3rcMKJL/lS63AUW/X99xAZKQsRvPvuS2/q4CCLCe3ZI/evrlsXEhLkmuty5WRd/TVrIDHRTLErVkklaSu2YQNs2iSXhowZo3U02hEIPuMzALrTnTd4Q+OIFJt07x5MmiQvf/llmpdQ6HQyIW/cCP/8I9dcOzrKjbOaNpW95jNmqBnhSupUkrZST5/CwIHycr9+ULCgtvFoaRnL2MtePPBQrWjFdEJC5CBzQAC0bJmhQ5QvL1vSly/DZ5+BlxecPQu9eslyvsOHQ3i4keNWrJpK0lZq6lS5+U6OHLKWsL2KI47BDAbgcz4nF7k0jkixSWFhMGWKvDxu3GsXIvD3h2++kaW/f/hBfsm+dw++/lom644d5T7w9rWzgpIalaStUESEnLMC8st91qzaxqOln/iJS1wiF7n4lE+1DkexVSNHytlfNWpA/fpGO6ynp1xXff683Me6UiXZS7ZoEVSuLMeu58xRXeH2TCVpKzR4sOx1CwyE7t21jkY797jHV3wFwFd8ZZZt4xQ7dPIk/PKLvDxunEmWUDg6wjvvyI20Dh6Uf9dubnL1xvvvy0Ipn34q12Ir9kUlaSuzZw/MmycvT5li3+U/hzGMBzygFKXoSletw1Fs1ZAhcgp2q1ZyPZWJ6VvP168n7WX94AFMnCiXcDVsCH/+KVvciu1T+0lbkadP5R/wiRPQtSvMnat1RNo5xCECCUQg2M52qlFN65AUWxQaCnXqyKbuiRNQ3Pw7qiUmwvr18kv5+vVJ49S+vvJzoEcPmbwV8zNHPrHjdpj1mTBBfk7kyCG/YdurRBLpRz8Egg50UAlaMY2EBBgwQF7u21eTBA2yt6xRI1i7Vo5dDx4sE3REhKxmVrSoHCr/9Vd4/FiTEBUTUi1pK3H+PJQqJeeuLFggqxbZq/nMpytd8cCDs5wlD3m0DkmxRTNnwocfypmZFy5AtmxaR2Tw9Cn89RfMmiVb1/qCKFmzypnhXbvKXjd7rkBoDqolrQCye6tXL5mg69aVf4T26h73DIVLRjBCJWjFNCIjk9Y2fvmlRSVokKVHW7SQifrKFRg1Si7devBAdosHBsqiaOPHy7FtxXqpJG0FZsyQZQUzZZL1f+352/EgBnGHO7zFW3zCJ1qHo9iq0aPlVlbFisldMyyYvz+MGAGXLslWdbt2cmb4qVOyazxfPvnlfsECiInROlolvVR3t4W7eFEWOIqNlUUPPvpI64i0s4Ut1KY2OnTsYhcVqah1SIotOnZM9hUnJMC6ddCggdYRpVtkpFx3/csv8PffSdd7eMhJ6h06QO3askWuZJw58olK0hYsIUHW/N2xQ04MCQ213yVXj3lMKUpxkYv0oQ9Tmap1SIotSkyEqlVlua9334WlS7WO6LVdvgwLF8qEnXyddfbs8im2ayefciobeimvoJK0CVhTkv7uOxg0CDJnll/u7bk+9+d8zrd8Sx7ycIpTZMGy/+8UKzV3rqwk4uEBZ87IKiI2QgjYu1dWM/v9d7h9O+l3uXPLrbHbtYOgIPseUksPlaRNwFqS9KFDUKGCnMU5YwZ88IHWEWlnN7upQhUEgpWspBnNtA5JsUV378plVvfuyfWOn9pumdlnz+QuXIsXw/LlcptsvQIFZPWzVq3kZ5C99t6lhUrSJmANSTo6Wu6Wc/683Gxn+XL7/WYbSyxlKMMFLtCFLsxjntYhKbbqvfdkv3DJkvJbsp0M2MbHy200f/sNVq6U81/0/PzkLPJWreSQm528JGmmkrQJWEOS7tJFjh/5+8vavRa2+sOs+tOfKUwhL3k5znG88dY6JMUWrV0LjRvLZuOePbLP1w49eiTnyv35J6xeLfcI0PP2hmbNZMOhXj1wd9csTIuhkrQJWHqSnj9fFiJwcJDdUVWrah2RdjawgQY0MFyuRz2NI1JsUlSUbD1fuyY3af/uO60jsgjx8XLp559/wooVKcew3d1lDfEWLeR59uxaRaktlaRNwJKT9OHDcqu6J09kcYIRI7SOSDvhhBNAALe5rWZzK6bVp48sQFCoEBw/rpqIqUhIkBPe//hDnsLCkn7n4AAVK8qOiCZN5Pcdexmes4uKY1OnTqVAgQK4ubkRHBzM/v37X3jbkydP8s4771CgQAF0Oh2TJk0yX6Amdv++nKzx5Ims06svdmSPEkmkM525zW1KUYoJTNA6JMVWbdwoEzTIGpsqQafK0VH26n3/vaxwdvAgfPGFLFWcmCi32PziCyhdGvLnl/Vf/vpL7YNtDJom6SVLljBw4EBGjhzJoUOHCAgIoH79+txO3q+SzKNHjyhUqBDjxo3Dz8/PzNGaTkKCLPV5+bL8Mr9woX3PqJzABDaxiUxkYjGLyUQmrUNSbNH9+9Ctm7zcrx/UqqVtPFZCp5O1XsaMkUtDr16Fn36SLWk3NzlqMH26bFVnzy6vnzZNJnclA4SGgoKCRN++fQ0/JyQkiNy5c4uQkJBX3jd//vzi+++/T/djRkZGCkBERkam+76mMnCgECBEpkxCHDmidTTa2i62C0fhKBCImWKm1uEotqxdO/mHV6yYELGxWkdjE2JjhVizRojevYXIl0++vMlPRYoI0bevECtXCmFBH8EZZo584qTVl4P4+HgOHjzIkCFDDNc5ODhQp04d9uzZo1VYZjdrltzMHWQdhYAAbePR0k1u0oY2JJBABzrwPu9rHZJiqxYtkouEHR1lUWvVzW0U7u6y5dy4sUzLJ07Ibu+//pKT5s+fl6epU8HJSa7DrldPngIDVdWz1GiWpO/evUtCQgK+vr4prvf19eXMmTNGe5y4uDji4uIMP0clX1Ogsa1b5ZwVkBPF2rbVNh4tPeUpbWhDBBGUpCQzmYkOO5l9opjX+fNyC0qA4cPh7be1jcdG6XRyzLpUKbnRR2SkXLGycaM8XbgAO3fK04gRcolX7doyYdeuLYf+7GUC2stolqTNJSQkhFGjRmkdxnOOH5frDZ89g/bt5WeFPRvAAHaxiyxk4Q/+wAMPrUNSbFFcnPw2HBMD1arB0KFaR2Q3vLygeXN5AjkHZ9MmmbBDQ2XVs+XL5QlknYiaNeWpRg1ZCc0eaTY9KUeOHDg6OhIREZHi+oiICKNOChsyZAiRkZGG07Vr14x27Iy6elVurBMZCVWqwJw59v2Nceq//3ToWMACilBE65AUWzVokFzrmD277PJ2svl2isUqWFCWO162TO4KumeP7FGsUkVWNrt2TRZ16tZN3rZgQVlWfcEC+9ojW7Mk7eLiQvny5QkNDTVcl5iYSGhoKBUrGm8LQldXV7JkyZLipKW7d6F+fbh5U64nXLVK7hNtrzaxiY/5GIAQQlRdbsV0liyBKVPk5V9+gTx5tI1HMdCPT48YIXf9e/BAtrCHDJHXOzrK2eFz50LnzrKVXaSITPILFshWua1W/ND0a+TAgQPp0qULgYGBBAUFMWnSJGJjY+n277KIzp07kydPHkJCQgA52ezUqVOGyzdu3ODIkSNkzpyZwoULa/Y80urBAznecvasfJOtWwdZs2odlXZOcpLWtCaBBDrTmc/5XOuQFFt17JhshgF8/rksRqBYLA8PqFtXnkDuZ7Brl5zHs3WrXKd94YI8zZolb5M7t2yFV6ki13SXKmUjE9FMNm88jSZPnizy5csnXFxcRFBQkNi7d6/hd9WrVxddunQx/Hz58mUBPHeqXr16mh9PqyVYkZFCBAXJZQg5cwpx+rRZH97ihIkwkVfkFQhEZVFZPBFPtA5JsVX37glRsKD846tbV4hnz7SOSHlNDx8KsXq1EIMGCVGhghDOzs8v9/L0FKJ+fSG++kqIrVtNs8rOHPlElQU1g+ho+cV95065Wca2bfJbnr16wAOqUIVTnKIEJdjBDrJjp8V/FdN69kz+8W3aJAc1//nHvnessVGPHsGBA0mzxXfvTrk5CMgu9fLlZUu7UiXZjZ479+s9rqrdbQLmTtIPHsgC9Pv2ydmNW7bIaj32KpZY6lOfXewiN7nZwx7ykU/rsBRbJIRc4zh9ulzAu3u3fRcisCMJCXKNtj5p79gBN248f7u8eWWyrlABgoNlEk/PHCGVpE3AnEn6zh05Bq3fbnLDBrlg31495jFNaMIWtuCFFzvYQSnsuEtBMa3vv5e7Wul0cisn/dofxe4IITcF0SfsvXvlMtjExJS3c3KS9ceTJ+4iRV68+kYlaRMwV5IOC5PLrE6fBh8f2LzZvru444mnJS1Zy1oyk5lNbKICFbQOS7FVK1ZAq1by0/m772SyVpRkYmLkBLS9e5NO4eHP3y5bNrm9eIUKsu5NYKD8TAeVpE3CpC/qs2dw4QLH1l6n4egK3IzMTF73e2wuP5hi8cflwMnTp/J2jo5yMWCmTPJ//L+nIkWgRAmwsO00M+IJT2hDG1azmkxkYh3rqE51rcNSbNXff8surLg4WVls2jT7LkSgpIkQcm323r1yeHLvXpnEkxWsNMiXTybsUqWi+PJLlaSNymhJ+ulT2L9fno4dk6eTJwmNq0wr/iAKL97iBOtpQF5SGQxJK39/ePNNeQoIkDMeChe2mg+dRzyiJS3ZyEbccGMlK6lHPa3DUmzV0aOyklhUFDRrJstXqYIlSgbFx8uPdn3i/ucfuYQ2KWtGASpJG1WGk7S+WnxoqOy73r5d9pckM4MP6MtUEnCiao7TrGzzK1kLZZX9JVmzQubMsvXs5CRnNjx9Ko9x5w7cvp10unVLvhNu3Uo9Fh8fmawrVZJTFQMD5XEtTDTRNKMZ29iGO+6sZjW1UNsBKiZy/rxcIBsRIRP1+vX2XSlIMYmoKNnCPnAAdu+OYuVKlaSNKl1JOjFRzghdskR+I/9v0syeHapU4Vnpcnx6sAM/rpUFVTp2hNmz5d6qr+X+fTmofeoUnDwp3xX//CO/3iXn4SE/lGrXlqfSpTXfkDqCCBrRiEMcwhNP1rGOylTWNCbFhl24IAs837ghe5y2b5fLKRTFhNSYtAm88kUVQibCJUvkKXmR2EyZkpJhnToQEED4bQfatpXDYCA3Qh8yxIS90U+eyK9xu3fLEjw7dshknlz27LIqvT5pm7l7/AIXqE99LnGJnORkLWsJxI6ntSumdfGiTNDXr8thoa1bk2b2KIoJqSRtAi98UaOiYOFC+Okn2WrV8/SEFi2gXTuZ8FxdDb/auRPatJENbE9PmD9f7mxlVomJchxuyxbZFf/33xAbm/I2/v5JCbtWrddfwf8SO9lJK1pxhzsUohAb2EBhLL9kq2Klzp6VX5ivX5cTLbduhf9sf6sopqKStAk896IePy5nfy5YkDTGnCkTNG0qE3PDhs/1WyckwNixcseWhAT55f2PP6BYMQ2e0H/Fx8tu8dBQedqzR459J1e8OFSsKNeElSwpKzHlzfva/fPzmc8HfEA88ZSjHH/xF34Yb0czRUnh8GG5W82dOzJBb9kCRtxBT1FeRSVpEzC8qMuWkWXyZDl2pVesmKxQ1Lmz3IE8FdeuwXvvJd2tY0dZ0ChzZtPHniGxsbJbXJ+0Dx168XYx2bLJcTxPT3BxSbrdf89B9ih4eYG3N8/y+DKk/TEmBG4DoJVoyS+6BWpPaMV0duyAJk1kD1i5cnKSWM6cWkel2BmVpE3A8KICWUCuV27ZUibnGjVeOHabmCh3W/nsM1mLO3Nm2TP+3ntmDN4YHjyQ3zCOHJG9CKdOyQ2uHz/O0OEifKDdYthWU/489GsYHeKGQ5lysmu9Vi3Zan/tWXSK8q8lS6BLF7mAtWpVWL1aTRJTNKGStAkYXlR3d7L06gUDBsiu3pe4dAnef18Od4HMOb/8Iudj2QQh5OSz8HD5DSQqShZc0Uv+xUWnk7ePi2OH637aV/mJG56RZH7sxNwv8/Hu5FvPJ3xXV7lcrHZtOb7/5ptWs85bsSBCwDffwODB8ufmzWHRIlmXW1E0oJK0CRhe1MuXyVKgwEtvm5Ag94j/4gtZLMzdXY5F9+tnI/uUZtAznvE1X/MVX5FIIsUpzh/8QQlKyBftwgU5+1w/me2/S9eKF4fWreHdd+W4uErYyqs8eQK9e8O8efLnjz6CiRPt+w9R0ZxK0iaQ1hd13z74+GN5DnJF0+zZUKiQmQK1UBe4QFe6sotdAHShC5OZjCeeqd9BCDh3TibstWth48aU67yLFIH27eU8gDfeMMMzUKzOzZtySGr/frn+f+JE+cepKBpTSdoEXvWiXr8u1zkvXCh/9vSEb7+Fnj01rw+iqUQS+Ymf+B//4xGP8MST6UynAx3Sd6DISFizBpYulZN9khfGrVYNunaVLWzPFyR9xb5s2SJnZ4aHy6p9v/8ul1wpigVQSdoEXvSiPnokk/H48UlDql27yuIkJlxWbBVOcII+9GEHOwCoSU3mMIeCFHy9A0dHw6pVcoB/06ak2ePu7jJR9+olt55R3eH259kzGD0avv5avi9KlZI7W9l7V5ZiUVSSNoH/vqhxcTB3rvws0G8KXqUKTJokNwC3Z9FEM4pRTGISCSTgjjvjGU8f+uCAkbsVrl+Xa9XnzZPd43oBAXIssmNHC17nphjVxYty9vYuOaRCz57yD1JNEFMsjErSJqB/USMiIlm6NAvjxiVV/ixQQLam33nHvhtvAsEylvEJn3CTmwC0pCWTmEQ+8pn4wYXccmbmTFi8WE4YAtn93amTnDBUvLhpY1C0IYRc5zhwoFzf7+kJM2bIOQuKYoFUkjYB/Yvq5xdJeLh8UXPnlqs6evZUy3kPcYj/8T82sxmAN3iDyUymIQ3NH8z9+7LW6vTpKVvXTZrAp59C9er2/W3Klly8KPd+Dg2VP1evLntVXrECQ1G0ZI4kbbdTocLD5fLoqVPl50P//vadoE9zmta0pjzl2cxmXHHlS77kBCe0SdAgK6ANGABnzsjtQZs3l0l5zRo53T4wEH777fmyp4r1iI+XE0FKlpQJ2s0NvvtOThhTCVpR7LclPXFiJH36ZEm+X4ZdusIVRjGKX/iFRBLRoaMjHRnFKAphgZN0zp2D77+XrSx9V3iBAjBsmFzGZYH7aisvsH69XEql7yWpXVt2b6uleIqVUN3dJmCOF9UanOIUE5nIL/zCU2RLtAUt+IqvKElJjaNLgzt35MYoU6bIyyBn/g4fLseunZy0jU95sYMH5f/TunXyZx8fWUmsc2c1fKFYFdXdrRiVQLCVrTSmMW/xFnOYw1OeUpva7GUvf/KndSRokJspjBgBV67AhAny50uXoFs3uSPSggWy+pliOU6cgFat5DDFunXyi9TAgbIl3aWLStCKkgqVpO3AIx7xC78QSCC1qMVa1qJDR0taspOdbGYzwQRrHWbGuLvLSWSXL8vWWI4csixp585Qpgz89deLd/1SzOPcOejQAUqXhj//lMm4Uye5uct336nNMRTlJVR3tw07xCFmM5tFLCKSSAAykYludOMTPqEIRTSO0ARiYmQX+DffyB2/QM4UHj8egq30i4g1EkLutjZpkixYo/+YefdduRH7m29qGp6iGIMakzYBW0/SEUSwlKX8zM8c5rDh+gIU4H3e50M+JAc5NIzQTB48gJAQ+PHHpNKj774rd0gpYoNfTizFkydyxv2kSXDsWNL1TZvKCmJlymgVmaIYnUrSJmCLSTqccJaznKUs5W/+RiD/S11woRWt6EEPalHL+FXCrMG1a3Lsev582ZpzcpIL4keOBF9fraOzDULA0aNyHsCCBUkT+dzd5VizKkCj2CiVpE3AFpK0QHCKU6xnPatYxQ52GBIzwNu8TUc60olOZCe7hpFakOPH5c4pf/0lf/bwgEGD5Hi22swjY65fl/s5L1ggJ4Xp5csn93N9/325KYai2CiVpE3AWpP0Ax6whS2s//ffda6n+H0wwbSmNe/yLvnJr1GUVmD7dvj8c7ntIcjlPyNGwAcfqDXWaXH2rCwms3o1/P130lizq6vs0n7vPWjUSC2BU+yCStImYA1JWiAII4ydyf6d5GSK1rIbbtSgBg1oQEtamr6mti0RApYvhy++gPPn5XWFC8stz1q3VkuBknv8GHbvlj0Qa9YkvV56VavKxNy6NXh7axKiomhFJWkTsLQkLRBc5jJHkv07xCFucOO52xanOA3+/VeNamQikwYR25CnT2H2bDnbOCJCXleqlCxF2r69fdaJjY2FPXtkj8P27bBvnyzdqefsDDVqyFZzs2aQX/XaKPZLJWkT0CJJCwT3uMclLnGBC5znvOH8DGcMy6OSc8KJcpSjyr//KlEJX9REJ5OIiYGJE+UWaDEx8jofHznpqWtX210u9PixnIF96FDS6dgxuZdzcrlyQf36cmOTevXUGL6i/MtukvTUqVP59ttvCQ8PJyAggMmTJxMUFPTC2y9dupThw4dz5coVihQpwvjx42nUqFGaHkv/ooZHhhObJZYoonjCE+KIM5zHE5/qfXU83w36lKdEE00MMYbzSCIJJ5xb//6LIMJQejM1LrhQkpKUSfavPOVxR+2fa1YPHsiW9Y8/Ju1fCnJj8aZNZZIqWxYcrGyW/MOHciz57Fm5WYn+dO5c6lXZ/P3l2nL9qXBhNQSgKKmwiyS9ZMkSOnfuzPTp0wkODmbSpEksXbqUs2fP4uPj89ztd+/eTbVq1QgJCaFJkyYsWrSI8ePHc+jQIUqWfHVJS/2LSiRg5t7u3OSmCEUoTGHDeVGKUpziOKMmLVmMp0/lGOy8efI8ecsya1aoWFGeAgLgrbfkBh9aJO4nT+Ryp+SnW7fg6lUIC0s6f/jwxcfw8ZFfQsqVSzrlz6+SsqKkgV0k6eDgYN5++22mTJkCQGJiIv7+/vTv35/Bgwc/d/u2bdsSGxvLmjVrDNdVqFCBMmXKMH369Fc+XvIk7ZbFDW+8yUQmXHHF7d9/zjg/12pOPmkrOUcc8fz3X2YyGy774kuuZP988cUFl/S8NIoluH1bTphaswY2bUrqDk/OxQX8/GS3sP7k5ye7hT085MndXZ67usqZz/qTo6M8RnQ0REU9f/7fyw8eJCXk1GJ5kdy55VrlYsXkefHi8gtG7twqIStKBpkjSWu6TiI+Pp6DBw8yZMgQw3UODg7UqVOHPXv2pHqfPXv2MHDgwBTX1a9fnxUrVqR6+7i4OOL0FaeQLyrAVa7ij3+qXdiKYuDjA927y9PTp7Jox+7dckLViROy2zg+XrZYw8LMH5+Tk9xcRH/y9ZUt4fz55Xpl/XnmzOaPTVGU16Zpkr579y4JCQn4/qfyk6+vL2fOnEn1PuHh4anePjw8PNXbh4SEMGrUqOeu98ZbJWglfZyd5Q5OgYFJ1z17BjduyG7m5KeICNnSjY2FR4/keWysTOjPnslTQoI8F0K2urNkef78v9d5eyclZB8fuTmFagkris2y+YoDQ4YMSdHyjoqKwt/fX8OIFJvi5JTUclUURTEyTZN0jhw5cHR0JEK/RvVfERER+Pn5pXofPz+/dN3e1dUVV1dX4wSsKIqiKGak6VoSFxcXypcvT2hoqOG6xMREQkNDqVixYqr3qVixYorbA2zatOmFt1cURVEUa6V5d/fAgQPp0qULgYGBBAUFMWnSJGJjY+nWrRsAnTt3Jk+ePISEhADw8ccfU716db777jsaN27M4sWL+eeff5g5c6aWT0NRFEVRjE7zJN22bVvu3LnDiBEjCA8Pp0yZMqxfv94wOSwsLAyHZGtQK1WqxKJFixg2bBhffPEFRYoUYcWKFWlaI60oiqIo1kTzddLmZmm1uxVFURTrZI58YmX1DRVFURTFfqgkrSiKoigWSiVpRVEURbFQKkkriqIoioVSSVpRFEVRLJRK0oqiKIpioVSSVhRFURQLpXkxE3PTLwvXb1mpKIqiKBmhzyOmLDdid0n63r17AGonLEVRFMUo7t27h5eXl0mObXdJOlu2bIAsN2qqF9Wa6LfuvHbtmt1XYFOvRRL1WiRRr0US9VqkFBkZSb58+Qx5xRTsLknr64B7eXmpN1kyWbJkUa/Hv9RrkUS9FknUa5FEvRYpJd9fwujHNtmRFUVRFEV5LSpJK4qiKIqFsrsk7erqysiRI3F1ddU6FIugXo8k6rVIol6LJOq1SKJei5TM8XrY3VaViqIoimIt7K4lrSiKoijWQiVpRVEURbFQKkkriqIoioWyiSQ9depUChQogJubG8HBwezfvz9N91u8eDE6nY4WLVqkuF4IwYgRI8iVKxeZMmWiTp06nD9/3gSRG5+xX4uuXbui0+lSnBo0aGCCyI0vPa/FvHnznnuebm5uKW5jze8LMP7rYS/vDYCHDx/St29fcuXKhaurK0WLFmXt2rWvdUxLYezX4ssvv3zufVG8eHFTPw2jSM9rUaNGjeeep06no3HjxobbGOUzQ1i5xYsXCxcXF/Hzzz+LkydPip49ewpvb28RERHx0vtdvnxZ5MmTR1StWlU0b948xe/GjRsnvLy8xIoVK8TRo0dFs2bNRMGCBcXjx49N+Exenyleiy5duogGDRqIW7duGU7379834bMwjvS+FnPnzhVZsmRJ8TzDw8NT3MZa3xdCmOb1sJf3RlxcnAgMDBSNGjUSO3fuFJcvXxbbtm0TR44cyfAxLYUpXouRI0eKt956K8X74s6dO+Z6ShmW3tfi3r17KZ7jiRMnhKOjo5g7d67hNsb4zLD6JB0UFCT69u1r+DkhIUHkzp1bhISEvPA+z549E5UqVRKzZ88WXbp0SZGYEhMThZ+fn/j2228N1z18+FC4urqK3377zSTPwViM/VoIIVK9zhqk97WYO3eu8PLyeuHxrPl9IYTxXw8h7Oe9MW3aNFGoUCERHx9vtGNaClO8FiNHjhQBAQHGDtXkXvf/8Pvvvxeenp4iJiZGCGG8zwyr7u6Oj4/n4MGD1KlTx3Cdg4MDderUYc+ePS+83+jRo/Hx8aFHjx7P/e7y5cuEh4enOKaXlxfBwcEvPabWTPFa6G3btg0fHx+KFStG7969DZuUWKqMvhYxMTHkz58ff39/mjdvzsmTJw2/s9b3BZjm9dCzh/fGqlWrqFixIn379sXX15eSJUsyduxYEhISMnxMS2CK10Lv/Pnz5M6dm0KFCtGxY0fCwsJM+lxelzH+D+fMmUO7du3w8PAAjPeZYdVJ+u7duyQkJODr65viel9fX8LDw1O9z86dO5kzZw6zZs1K9ff6+6XnmJbAFK8FQIMGDfjll18IDQ1l/PjxbN++nYYNGz73R2lJMvJaFCtWjJ9//pmVK1eycOFCEhMTqVSpEtevXwes930Bpnk9wH7eG5cuXWLZsmUkJCSwdu1ahg8fznfffcfXX3+d4WNaAlO8FgDBwcHMmzeP9evXM23aNC5fvkzVqlWJjo426fN5Ha/7f7h//35OnDjB+++/b7jOWJ8ZdrXBRnR0NO+99x6zZs0iR44cWoejqbS+Fu3atTNcLlWqFKVLl+aNN95g27Zt1K5d2xyhmkXFihWpWLGi4edKlSpRokQJZsyYwVdffaVhZNpIy+thL++NxMREfHx8mDlzJo6OjpQvX54bN27w7bffMnLkSK3DM6u0vBYNGzY03L506dIEBweTP39+fv/995f22FmzOXPmUKpUKYKCgox+bKtO0jly5MDR0ZGIiIgU10dERODn5/fc7S9evMiVK1do2rSp4brExEQAnJycOHv2rOF+ERER5MqVK8Uxy5QpY4JnYRymeC3eeOON5+5XqFAhcuTIwYULFyz2gzi9r0VqnJ2dKVu2LBcuXACw2vcFmOb1SI2tvjdy5cqFs7Mzjo6OhutKlChBeHg48fHxRnl9tWCK18LFxeW5+3h7e1O0aNGXvne09jr/h7GxsSxevJjRo0enuN5YnxlW3d3t4uJC+fLlCQ0NNVyXmJhIaGhoilaAXvHixTl+/DhHjhwxnJo1a0bNmjU5cuQI/v7+FCxYED8/vxTHjIqKYt++fake01KY4rVIzfXr17l3716KN52lSe9rkZqEhASOHz9ueJ7W+r4A07weqbHV90blypW5cOGC4UsswLlz58iVKxcuLi5GeX21YIrXIjUxMTFcvHjR5t4XekuXLiUuLo5OnTqluN5onxlpnmJmoRYvXixcXV3FvHnzxKlTp8QHH3wgvL29DctF3nvvPTF48OAX3j+1Garjxo0T3t7eYuXKleLYsWOiefPmVrHUxtivRXR0tBg0aJDYs2ePuHz5sti8ebMoV66cKFKkiHjy5Impn85rSe9rMWrUKLFhwwZx8eJFcfDgQdGuXTvh5uYmTp48abiNtb4vhDD+62FP742wsDDh6ekp+vXrJ86ePSvWrFkjfHx8xNdff53mY1oqU7wWn376qdi2bZu4fPmy2LVrl6hTp47IkSOHuH37ttmfX3pk9POzSpUqom3btqke0xifGVafpIUQYvLkySJfvnzCxcVFBAUFib179xp+V716ddGlS5cX3je1JJ2YmCiGDx8ufH19haurq6hdu7Y4e/asiaI3LmO+Fo8ePRL16tUTOXPmFM7OziJ//vyiZ8+eFv/Bo5ee1+KTTz4x3NbX11c0atRIHDp0KMXxrPl9IYRxXw97em8IIcTu3btFcHCwcHV1FYUKFRJjxowRz549S/MxLZmxX4u2bduKXLlyCRcXF5EnTx7Rtm1bceHCBXM9ndeS3tfizJkzAhAbN25M9XjG+MxQu2ApiqIoioWy6jFpRVEURbFlKkkriqIoioVSSVpRFEVRLJRK0oqiKIpioVSSVhRFURQLpZK0oiiKolgolaQVRVEUxUKpJK0oiqIoFkolaUWxAV9++aVFbfSh0+lYsWJFuu+n3+TG1Nsa3r17Fx8fnxRbbyqKJVJJWlHSaPr06Xh6evLs2TPDdTExMTg7O1OjRo0Ut922bRs6nY6LFy+aOUrzMvaXgyFDhtC/f388PT2NdszU5MiRg86dO9vdVpOK9VFJWlHSqGbNmsTExPDPP/8YrtuxYwd+fn7s27ePJ0+eGK7funUr+fLlS3W7TyV1YWFhrFmzhq5du5rl8bp168avv/7K/fv3zfJ4ipIRKkkrShoVK1aMXLlysW3bNsN127Zto3nz5hQsWJC9e/emuL5mzZoALFiwgMDAQDw9PfHz86NDhw7cvn0bkNvh5c2bl2nTpqV4rMOHD+Pg4MDVq1cBePjwIe+//z45c+YkS5Ys1KpVi6NHj7403tmzZ1OiRAnc3NwoXrw4P/30k+F3V65cQafT8ccff1CzZk3c3d0JCAhgz549KY4xa9Ys/P39cXd3p2XLlkycOBFvb28A5s2bx6hRozh69Cg6nQ6dTse8efMM97179y4tW7bE3d2dIkWKsGrVqpfG+/vvvxMQEECePHkM182bNw9vb282bNhAiRIlyJw5Mw0aNODWrVuG23Tt2pUWLVowduxYfH198fb2ZvTo0Tx79ozPPvuMbNmykTdvXubOnZvi8d566y1y587Nn3/++dK4FEVLKkkrSjrUrFmTrVu3Gn7eunUrNWrUoHr16obrHz9+zL59+wxJ+unTp3z11VccPXqUFStWcOXKFUNr0cHBgfbt27No0aIUj/Prr79SuXJl8ufPD0Dr1q25ffs269at4+DBg5QrV47atWu/sBX466+/MmLECMaMGcPp06cZO3Ysw4cPZ/78+SluN3ToUAYNGsSRI0coWrQo7du3N3Tn79q1i169evHxxx9z5MgR6taty5gxYwz3bdu2LZ9++ilvvfUWt27d4tatW7Rt29bw+1GjRtGmTRuOHTtGo0aN6Nix40tbrTt27CAwMPC56x89esSECRNYsGABf//9N2FhYQwaNCjFbbZs2cLNmzf5+++/mThxIiNHjqRJkyZkzZqVffv20atXLz788MPnxqCDgoLYsWPHC2NSFM2lcycvRbFrs2bNEh4eHuLp06ciKipKODk5idu3b4tFixaJatWqCSGECA0NFYC4evVqqsc4cOCAAER0dLQQQojDhw8LnU5nuH1CQoLIkyePmDZtmhBCiB07dogsWbI8t0/zG2+8IWbMmCGEEGLkyJEiICAgxe8WLVqU4vZfffWVqFixohBCiMuXLwtAzJ492/D7kydPCkCcPn1aCCG3HGzcuHGKY3Ts2FF4eXkZfv7v4+oBYtiwYYafY2JiBCDWrVuX6msihBABAQFi9OjRKa6bO3euAFJsdTh16lTh6+tr+LlLly4if/78IiEhwXBdsWLFRNWqVQ0/P3v2THh4eIjffvstxfEHDBggatSo8cKYFEVrqiWtKOlQo0YNYmNjOXDgADt27KBo0aLkzJmT6tWrG8alt23bRqFChciXLx8ABw8epGnTpuTLlw9PT0+qV68OyDFYgDJlylCiRAlDa3r79u3cvn2b1q1bA3D06FFiYmLInj07mTNnNpwuX76c6sS02NhYLl68SI8ePVLc/uuvv37u9qVLlzZczpUrF4ChK/7s2bMEBQWluP1/f36Z5Mf28PAgS5YshmOn5vHjx7i5uT13vbu7e4qx/Vy5cj13nLfeegsHh6SPM19fX0qVKmX42dHRkezZsz93v0yZMvHo0aM0PydFMTcnrQNQFGtSuHBh8ubNy9atW3nw4IEh4ebOnRt/f392797N1q1bqVWrFiATZv369alfvz6//vorOXPmJCwsjPr16xMfH284bseOHVm0aBGDBw9m0aJFNGjQgOzZswNyBvl/x8L19OPDycXExAByPDk4ODjF7xwdHVP87OzsbLis0+kAOU5uDMmPrT/+y46dI0cOHjx4kKbjCCFeeZu0PP79+/fJmTPni5+EomhMJWlFSaeaNWuybds2Hjx4wGeffWa4vlq1aqxbt479+/fTu3dvAM6cOcO9e/cYN24c/v7+AClmh+t16NCBYcOGcfDgQZYtW8b06dMNvytXrhzh4eE4OTlRoECBV8bn6+tL7ty5uXTpEh07dszw8yxWrBgHDhxIcd1/f3ZxcSEhISHDj5Fc2bJlOXXqlFGOlVYnTpx4bvmcolgS1d2tKOlUs2ZNdu7cyZEjRwwtaYDq1aszY8YM4uPjDZPG8uXLh4uLC5MnT+bSpUusWrWKr7766rljFihQgEqVKtGjRw8SEhJo1qyZ4Xd16tShYsWKtGjRgo0bN3LlyhV2797N0KFDU034ICdthYSE8OOPP3Lu3DmOHz/O3LlzmThxYpqfZ//+/Vm7di0TJ07k/PnzzJgxg3Xr1hla3Pq4L1++zJEjR7h79y5xcXFpPv5/1a9fnz179hgt6b/Ko0ePOHjwIPXq1TPL4ylKRqgkrSjpVLNmTR4/fkzhwoXx9fU1XF+9enWio6MNS7UAcubMybx581i6dClvvvkm48aNY8KECaket2PHjhw9epSWLVuSKVMmw/U6nY61a9dSrVo1unXrRtGiRWnXrh1Xr15N8fjJvf/++8yePZu5c+dSqlQpqlevzrx58yhYsGCan2flypWZPn06EydOJCAggPXr1zNgwIAU48bvvPMODRo0oGbNmuTMmZPffvstzcf/r4YNG+Lk5MTmzZszfIz0WLlyJfny5aNq1apmeTxFyQid+O/gjqIoygv07NmTM2fOmGzZ0tSpU1m1ahUbNmwwyfGTq1ChAh999BEdOnQw+WMpSkapMWlFUV5owoQJ1K1bFw8PD9atW8f8+fNTFEUxtg8//JCHDx8SHR1t0tKgd+/epVWrVrRv395kj6EoxqBa0oqivFCbNm3Ytm0b0dHRFCpUiP79+9OrVy+tw1IUu6GStKIoiqJYKDVxTFEURVEslErSiqIoimKhVJJWFEVRFAulkrSiKIqiWCiVpBVFURTFQqkkrSiKoigWSiVpRVEURbFQKkkriqIoioVSSVpRFEVRLNT/AUYtWPLa9dFaAAAAAElFTkSuQmCC",
-      "text/plain": [
-       "<Figure size 500x400 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:03:19.678399Z",
+     "start_time": "2025-10-29T14:03:19.523112Z"
     }
-   ],
+   },
    "source": [
     "fig, ax = plt.subplots(1, 1, figsize=(5, 4), tight_layout=True)\n",
     "\n",
@@ -354,7 +366,23 @@
     "ax.legend()\n",
     "\n",
     "plt.show()"
-   ]
+   ],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 500x400 with 1 Axes>"
+      ],
+      "image/png": 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"
+     },
+     "metadata": {},
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
+    }
+   ],
+   "execution_count": 30
   },
   {
    "cell_type": "markdown",
@@ -365,20 +393,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 1000x400 with 6 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:03:20.248411Z",
+     "start_time": "2025-10-29T14:03:19.727707Z"
     }
-   ],
+   },
    "source": [
     "fig, (ax1, ax2, ax3) = plt.subplots(1, 3, figsize=(10, 4), tight_layout=True)\n",
     "\n",
@@ -395,7 +415,23 @@
     "ax3.set_aspect(\"auto\")\n",
     "\n",
     "plt.show()"
-   ]
+   ],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 1000x400 with 6 Axes>"
+      ],
+      "image/png": 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"
+     },
+     "metadata": {},
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
+    }
+   ],
+   "execution_count": 31
   }
  ],
  "metadata": {
diff --git a/ParameterScan.ipynb b/ParameterScan.ipynb
index 57908cc3..192e9f94 100644
--- a/ParameterScan.ipynb
+++ b/ParameterScan.ipynb
@@ -18,7 +18,7 @@
     "\n",
     "This example will also provide a walkthrough of Tidy3D's [Job](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.web.api.container.Job.html) and [Batch](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.web.api.container.Batch.html) features for managing both individual simulations and sets of simulations.\n",
     "\n",
-    "> Note: as of version `1.8`, the [tidy3d.web.run_async](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.web.api.asynchronous.run_async.html) function handles the same functionality as the batch, with a simpler syntax. As such, it could be a good alternative for parameter scan depending on how your script is set up.\n",
+    "> Note: as of version `2.10`, the [tidy3d.web.run](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.web.api.run.run.html) unifies the submission of a single simulation as well as any nested combination of lists, tuples, and dictionaries of them, handling the same functionality as the batch, with a simpler syntax. As such, it could be a good alternative for parameter scan depending on how your script is set up.\n",
     "\n",
     "Additionally, we will show how to do this problem using `tidy3d.plugins.design`, which provides convenience methods for defining and running parameter scans, which has a full tutorial [here](https://www.flexcompute.com/tidy3d/examples/notebooks/Design/).\n",
     "\n",
@@ -383,8 +383,8 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m12:13:44 -03\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'CouplerVerify'\u001b[0m with task_id                          \n",
-       "\u001b[2;36m             \u001b[0m\u001b[32m'fdve-d5f43711-3a72-4261-a06c-b6575e0f33fe'\u001b[0m and task_type \u001b[32m'FDTD'\u001b[0m.  \n"
+       "\u001B[2;36m12:13:44 -03\u001B[0m\u001B[2;36m \u001B[0mCreated task \u001B[32m'CouplerVerify'\u001B[0m with task_id                          \n",
+       "\u001B[2;36m             \u001B[0m\u001B[32m'fdve-d5f43711-3a72-4261-a06c-b6575e0f33fe'\u001B[0m and task_type \u001B[32m'FDTD'\u001B[0m.  \n"
       ]
      },
      "metadata": {},
@@ -399,9 +399,9 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mView task using web UI at                                          \n",
-       "\u001b[2;36m             \u001b[0m\u001b]8;id=145950;https://tidy3d.simulation.cloud/workbench?taskId=fdve-d5f43711-3a72-4261-a06c-b6575e0f33fe\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=624063;https://tidy3d.simulation.cloud/workbench?taskId=fdve-d5f43711-3a72-4261-a06c-b6575e0f33fe\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=145950;https://tidy3d.simulation.cloud/workbench?taskId=fdve-d5f43711-3a72-4261-a06c-b6575e0f33fe\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=4405;https://tidy3d.simulation.cloud/workbench?taskId=fdve-d5f43711-3a72-4261-a06c-b6575e0f33fe\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=145950;https://tidy3d.simulation.cloud/workbench?taskId=fdve-d5f43711-3a72-4261-a06c-b6575e0f33fe\u001b\\\u001b[32m-d5f43711-3a7\u001b[0m\u001b]8;;\u001b\\\n",
-       "\u001b[2;36m             \u001b[0m\u001b]8;id=145950;https://tidy3d.simulation.cloud/workbench?taskId=fdve-d5f43711-3a72-4261-a06c-b6575e0f33fe\u001b\\\u001b[32m2-4261-a06c-b6575e0f33fe'\u001b[0m\u001b]8;;\u001b\\.                                         \n"
+       "\u001B[2;36m            \u001B[0m\u001B[2;36m \u001B[0mView task using web UI at                                          \n",
+       "\u001B[2;36m             \u001B[0m\u001B]8;id=145950;https://tidy3d.simulation.cloud/workbench?taskId=fdve-d5f43711-3a72-4261-a06c-b6575e0f33fe\u001B\\\u001B[32m'https://tidy3d.simulation.cloud/workbench?\u001B[0m\u001B]8;;\u001B\\\u001B]8;id=624063;https://tidy3d.simulation.cloud/workbench?taskId=fdve-d5f43711-3a72-4261-a06c-b6575e0f33fe\u001B\\\u001B[32mtaskId\u001B[0m\u001B]8;;\u001B\\\u001B]8;id=145950;https://tidy3d.simulation.cloud/workbench?taskId=fdve-d5f43711-3a72-4261-a06c-b6575e0f33fe\u001B\\\u001B[32m=\u001B[0m\u001B]8;;\u001B\\\u001B]8;id=4405;https://tidy3d.simulation.cloud/workbench?taskId=fdve-d5f43711-3a72-4261-a06c-b6575e0f33fe\u001B\\\u001B[32mfdve\u001B[0m\u001B]8;;\u001B\\\u001B]8;id=145950;https://tidy3d.simulation.cloud/workbench?taskId=fdve-d5f43711-3a72-4261-a06c-b6575e0f33fe\u001B\\\u001B[32m-d5f43711-3a7\u001B[0m\u001B]8;;\u001B\\\n",
+       "\u001B[2;36m             \u001B[0m\u001B]8;id=145950;https://tidy3d.simulation.cloud/workbench?taskId=fdve-d5f43711-3a72-4261-a06c-b6575e0f33fe\u001B\\\u001B[32m2-4261-a06c-b6575e0f33fe'\u001B[0m\u001B]8;;\u001B\\.                                         \n"
       ]
      },
      "metadata": {},
@@ -414,7 +414,7 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mTask folder: \u001b]8;id=856254;https://tidy3d.simulation.cloud/folders/folder-dc5128c7-562b-4bcf-a539-9356f1d308ca\u001b\\\u001b[32m'default'\u001b[0m\u001b]8;;\u001b\\.                                            \n"
+       "\u001B[2;36m            \u001B[0m\u001B[2;36m \u001B[0mTask folder: \u001B]8;id=856254;https://tidy3d.simulation.cloud/folders/folder-dc5128c7-562b-4bcf-a539-9356f1d308ca\u001B\\\u001B[32m'default'\u001B[0m\u001B]8;;\u001B\\.                                            \n"
       ]
      },
      "metadata": {},
@@ -453,9 +453,9 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m12:13:48 -03\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.588\u001b[0m. Minimum cost depends on task       \n",
-       "\u001b[2;36m             \u001b[0mexecution details. Use \u001b[32m'web.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed  \n",
-       "\u001b[2;36m             \u001b[0mFlexCredit cost after a simulation run.                            \n"
+       "\u001B[2;36m12:13:48 -03\u001B[0m\u001B[2;36m \u001B[0mMaximum FlexCredit cost: \u001B[1;36m0.588\u001B[0m. Minimum cost depends on task       \n",
+       "\u001B[2;36m             \u001B[0mexecution details. Use \u001B[32m'web.real_cost\u001B[0m\u001B[32m(\u001B[0m\u001B[32mtask_id\u001B[0m\u001B[32m)\u001B[0m\u001B[32m'\u001B[0m to get the billed  \n",
+       "\u001B[2;36m             \u001B[0mFlexCredit cost after a simulation run.                            \n"
       ]
      },
      "metadata": {},
@@ -468,7 +468,7 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m12:13:49 -03\u001b[0m\u001b[2;36m \u001b[0mstatus = queued                                                    \n"
+       "\u001B[2;36m12:13:49 -03\u001B[0m\u001B[2;36m \u001B[0mstatus = queued                                                    \n"
       ]
      },
      "metadata": {},
@@ -484,10 +484,10 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mTo cancel the simulation, use \u001b[32m'web.abort\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m or              \n",
-       "\u001b[2;36m             \u001b[0m\u001b[32m'web.delete\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m or abort/delete the task in the web UI.      \n",
-       "\u001b[2;36m             \u001b[0mTerminating the Python script will not stop the job running on the \n",
-       "\u001b[2;36m             \u001b[0mcloud.                                                             \n"
+       "\u001B[2;36m            \u001B[0m\u001B[2;36m \u001B[0mTo cancel the simulation, use \u001B[32m'web.abort\u001B[0m\u001B[32m(\u001B[0m\u001B[32mtask_id\u001B[0m\u001B[32m)\u001B[0m\u001B[32m'\u001B[0m or              \n",
+       "\u001B[2;36m             \u001B[0m\u001B[32m'web.delete\u001B[0m\u001B[32m(\u001B[0m\u001B[32mtask_id\u001B[0m\u001B[32m)\u001B[0m\u001B[32m'\u001B[0m or abort/delete the task in the web UI.      \n",
+       "\u001B[2;36m             \u001B[0mTerminating the Python script will not stop the job running on the \n",
+       "\u001B[2;36m             \u001B[0mcloud.                                                             \n"
       ]
      },
      "metadata": {},
@@ -514,7 +514,7 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m12:14:10 -03\u001b[0m\u001b[2;36m \u001b[0mstatus = preprocess                                                \n"
+       "\u001B[2;36m12:14:10 -03\u001B[0m\u001B[2;36m \u001B[0mstatus = preprocess                                                \n"
       ]
      },
      "metadata": {},
@@ -537,7 +537,7 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m12:14:14 -03\u001b[0m\u001b[2;36m \u001b[0mstarting up solver                                                 \n"
+       "\u001B[2;36m12:14:14 -03\u001B[0m\u001B[2;36m \u001B[0mstarting up solver                                                 \n"
       ]
      },
      "metadata": {},
@@ -550,7 +550,7 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mrunning solver                                                     \n"
+       "\u001B[2;36m            \u001B[0m\u001B[2;36m \u001B[0mrunning solver                                                     \n"
       ]
      },
      "metadata": {},
@@ -577,7 +577,7 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m12:14:41 -03\u001b[0m\u001b[2;36m \u001b[0mearly shutoff detected at \u001b[1;36m52\u001b[0m%, exiting.                            \n"
+       "\u001B[2;36m12:14:41 -03\u001B[0m\u001B[2;36m \u001B[0mearly shutoff detected at \u001B[1;36m52\u001B[0m%, exiting.                            \n"
       ]
      },
      "metadata": {},
@@ -600,7 +600,7 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mstatus = postprocess                                               \n"
+       "\u001B[2;36m            \u001B[0m\u001B[2;36m \u001B[0mstatus = postprocess                                               \n"
       ]
      },
      "metadata": {},
@@ -627,7 +627,7 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m12:14:44 -03\u001b[0m\u001b[2;36m \u001b[0mstatus = success                                                   \n"
+       "\u001B[2;36m12:14:44 -03\u001B[0m\u001B[2;36m \u001B[0mstatus = success                                                   \n"
       ]
      },
      "metadata": {},
@@ -652,9 +652,9 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m12:14:46 -03\u001b[0m\u001b[2;36m \u001b[0mView simulation result at                                          \n",
-       "\u001b[2;36m             \u001b[0m\u001b]8;id=743781;https://tidy3d.simulation.cloud/workbench?taskId=fdve-d5f43711-3a72-4261-a06c-b6575e0f33fe\u001b\\\u001b[4;34m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=348474;https://tidy3d.simulation.cloud/workbench?taskId=fdve-d5f43711-3a72-4261-a06c-b6575e0f33fe\u001b\\\u001b[4;34mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=743781;https://tidy3d.simulation.cloud/workbench?taskId=fdve-d5f43711-3a72-4261-a06c-b6575e0f33fe\u001b\\\u001b[4;34m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=31302;https://tidy3d.simulation.cloud/workbench?taskId=fdve-d5f43711-3a72-4261-a06c-b6575e0f33fe\u001b\\\u001b[4;34mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=743781;https://tidy3d.simulation.cloud/workbench?taskId=fdve-d5f43711-3a72-4261-a06c-b6575e0f33fe\u001b\\\u001b[4;34m-d5f43711-3a7\u001b[0m\u001b]8;;\u001b\\\n",
-       "\u001b[2;36m             \u001b[0m\u001b]8;id=743781;https://tidy3d.simulation.cloud/workbench?taskId=fdve-d5f43711-3a72-4261-a06c-b6575e0f33fe\u001b\\\u001b[4;34m2-4261-a06c-b6575e0f33fe'\u001b[0m\u001b]8;;\u001b\\\u001b[4;34m.\u001b[0m                                         \n"
+       "\u001B[2;36m12:14:46 -03\u001B[0m\u001B[2;36m \u001B[0mView simulation result at                                          \n",
+       "\u001B[2;36m             \u001B[0m\u001B]8;id=743781;https://tidy3d.simulation.cloud/workbench?taskId=fdve-d5f43711-3a72-4261-a06c-b6575e0f33fe\u001B\\\u001B[4;34m'https://tidy3d.simulation.cloud/workbench?\u001B[0m\u001B]8;;\u001B\\\u001B]8;id=348474;https://tidy3d.simulation.cloud/workbench?taskId=fdve-d5f43711-3a72-4261-a06c-b6575e0f33fe\u001B\\\u001B[4;34mtaskId\u001B[0m\u001B]8;;\u001B\\\u001B]8;id=743781;https://tidy3d.simulation.cloud/workbench?taskId=fdve-d5f43711-3a72-4261-a06c-b6575e0f33fe\u001B\\\u001B[4;34m=\u001B[0m\u001B]8;;\u001B\\\u001B]8;id=31302;https://tidy3d.simulation.cloud/workbench?taskId=fdve-d5f43711-3a72-4261-a06c-b6575e0f33fe\u001B\\\u001B[4;34mfdve\u001B[0m\u001B]8;;\u001B\\\u001B]8;id=743781;https://tidy3d.simulation.cloud/workbench?taskId=fdve-d5f43711-3a72-4261-a06c-b6575e0f33fe\u001B\\\u001B[4;34m-d5f43711-3a7\u001B[0m\u001B]8;;\u001B\\\n",
+       "\u001B[2;36m             \u001B[0m\u001B]8;id=743781;https://tidy3d.simulation.cloud/workbench?taskId=fdve-d5f43711-3a72-4261-a06c-b6575e0f33fe\u001B\\\u001B[4;34m2-4261-a06c-b6575e0f33fe'\u001B[0m\u001B]8;;\u001B\\\u001B[4;34m.\u001B[0m                                         \n"
       ]
      },
      "metadata": {},
@@ -691,7 +691,7 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m12:15:01 -03\u001b[0m\u001b[2;36m \u001b[0mloading simulation from data/sim_data.hdf5                         \n"
+       "\u001B[2;36m12:15:01 -03\u001B[0m\u001B[2;36m \u001B[0mloading simulation from data/sim_data.hdf5                         \n"
       ]
      },
      "metadata": {},
@@ -906,7 +906,7 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m12:15:13 -03\u001b[0m\u001b[2;36m \u001b[0mStarted working on Batch containing \u001b[1;36m11\u001b[0m tasks.                      \n"
+       "\u001B[2;36m12:15:13 -03\u001B[0m\u001B[2;36m \u001B[0mStarted working on Batch containing \u001B[1;36m11\u001B[0m tasks.                      \n"
       ]
      },
      "metadata": {},
@@ -919,7 +919,7 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m12:15:26 -03\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m6.251\u001b[0m for the whole batch.                \n"
+       "\u001B[2;36m12:15:26 -03\u001B[0m\u001B[2;36m \u001B[0mMaximum FlexCredit cost: \u001B[1;36m6.251\u001B[0m for the whole batch.                \n"
       ]
      },
      "metadata": {},
@@ -933,8 +933,8 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mUse \u001b[32m'Batch.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed FlexCredit cost after the\n",
-       "\u001b[2;36m             \u001b[0mBatch has completed.                                               \n"
+       "\u001B[2;36m            \u001B[0m\u001B[2;36m \u001B[0mUse \u001B[32m'Batch.real_cost\u001B[0m\u001B[32m(\u001B[0m\u001B[32m)\u001B[0m\u001B[32m'\u001B[0m to get the billed FlexCredit cost after the\n",
+       "\u001B[2;36m             \u001B[0mBatch has completed.                                               \n"
       ]
      },
      "metadata": {},
@@ -961,7 +961,7 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m12:16:44 -03\u001b[0m\u001b[2;36m \u001b[0mBatch complete.                                                    \n"
+       "\u001B[2;36m12:16:44 -03\u001B[0m\u001B[2;36m \u001B[0mBatch complete.                                                    \n"
       ]
      },
      "metadata": {},
@@ -1245,7 +1245,7 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m12:17:02 -03\u001b[0m\u001b[2;36m \u001b[0mRunning \u001b[1;36m9\u001b[0m Simulations                                              \n"
+       "\u001B[2;36m12:17:02 -03\u001B[0m\u001B[2;36m \u001B[0mRunning \u001B[1;36m9\u001B[0m Simulations                                              \n"
       ]
      },
      "metadata": {},
@@ -1834,7 +1834,7 @@
         {
          "data": {
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           "text/html": "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">solver progress (field decay = 2.31e-05) <span style=\"color: #729c1f; text-decoration-color: #729c1f\">━━━━━━━━━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">100%</span> <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\n</pre>\n",
-          "text/plain": "solver progress (field decay = 2.31e-05) \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[36m0:00:00\u001b[0m\n"
+          "text/plain": "solver progress (field decay = 2.31e-05) \u001B[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━\u001B[0m \u001B[35m100%\u001B[0m \u001B[36m0:00:00\u001B[0m\n"
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           "text/html": "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">l=5.00: status = success  <span style=\"color: #729c1f; text-decoration-color: #729c1f\">━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">100%</span> <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\nl=5.70: status = success  <span style=\"color: #729c1f; text-decoration-color: #729c1f\">━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">100%</span> <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\nl=6.40: status = success  <span style=\"color: #729c1f; text-decoration-color: #729c1f\">━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">100%</span> <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\nl=7.10: status = success  <span style=\"color: #729c1f; text-decoration-color: #729c1f\">━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">100%</span> <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\nl=7.80: status = success  <span style=\"color: #729c1f; text-decoration-color: #729c1f\">━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">100%</span> <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\nl=8.50: status = success  <span style=\"color: #729c1f; text-decoration-color: #729c1f\">━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">100%</span> <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\nl=9.20: status = success  <span style=\"color: #729c1f; text-decoration-color: #729c1f\">━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">100%</span> <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\nl=9.90: status = success  <span style=\"color: #729c1f; text-decoration-color: #729c1f\">━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">100%</span> <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\nl=10.60: status = success <span style=\"color: #729c1f; text-decoration-color: #729c1f\">━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">100%</span> <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\nl=11.30: status = success <span style=\"color: #729c1f; text-decoration-color: #729c1f\">━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">100%</span> <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\nl=12.00: status = success <span style=\"color: #729c1f; text-decoration-color: #729c1f\">━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">100%</span> <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\n</pre>\n",
-          "text/plain": "l=5.00: status = success  \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[36m0:00:00\u001b[0m\nl=5.70: status = success  \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[36m0:00:00\u001b[0m\nl=6.40: status = success  \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[36m0:00:00\u001b[0m\nl=7.10: status = success  \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[36m0:00:00\u001b[0m\nl=7.80: status = success  \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[36m0:00:00\u001b[0m\nl=8.50: status = success  \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[36m0:00:00\u001b[0m\nl=9.20: status = success  \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[36m0:00:00\u001b[0m\nl=9.90: status = success  \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[36m0:00:00\u001b[0m\nl=10.60: status = success \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[36m0:00:00\u001b[0m\nl=11.30: status = success \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[36m0:00:00\u001b[0m\nl=12.00: status = success \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[36m0:00:00\u001b[0m\n"
+          "text/plain": "l=5.00: status = success  \u001B[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001B[0m \u001B[35m100%\u001B[0m \u001B[36m0:00:00\u001B[0m\nl=5.70: status = success  \u001B[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001B[0m \u001B[35m100%\u001B[0m \u001B[36m0:00:00\u001B[0m\nl=6.40: status = success  \u001B[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001B[0m \u001B[35m100%\u001B[0m \u001B[36m0:00:00\u001B[0m\nl=7.10: status = success  \u001B[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001B[0m \u001B[35m100%\u001B[0m \u001B[36m0:00:00\u001B[0m\nl=7.80: status = success  \u001B[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001B[0m \u001B[35m100%\u001B[0m \u001B[36m0:00:00\u001B[0m\nl=8.50: status = success  \u001B[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001B[0m \u001B[35m100%\u001B[0m \u001B[36m0:00:00\u001B[0m\nl=9.20: status = success  \u001B[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001B[0m \u001B[35m100%\u001B[0m \u001B[36m0:00:00\u001B[0m\nl=9.90: status = success  \u001B[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001B[0m \u001B[35m100%\u001B[0m \u001B[36m0:00:00\u001B[0m\nl=10.60: status = success \u001B[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001B[0m \u001B[35m100%\u001B[0m \u001B[36m0:00:00\u001B[0m\nl=11.30: status = success \u001B[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001B[0m \u001B[35m100%\u001B[0m \u001B[36m0:00:00\u001B[0m\nl=12.00: status = success \u001B[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001B[0m \u001B[35m100%\u001B[0m \u001B[36m0:00:00\u001B[0m\n"
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           "text/html": "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800000; text-decoration-color: #800000; font-weight: bold\">↑</span> <span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">simulation.hdf5.gz</span> <span style=\"color: #729c1f; text-decoration-color: #729c1f\">━━━━━━━━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">100.0%</span> • <span style=\"color: #008000; text-decoration-color: #008000\">3.1/3.1 kB</span> • <span style=\"color: #800000; text-decoration-color: #800000\">?</span> • <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\n</pre>\n",
-          "text/plain": "\u001b[1;31m↑\u001b[0m \u001b[1;34msimulation.hdf5.gz\u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100.0%\u001b[0m • \u001b[32m3.1/3.1 kB\u001b[0m • \u001b[31m?\u001b[0m • \u001b[36m0:00:00\u001b[0m\n"
+          "text/plain": "\u001B[1;31m↑\u001B[0m \u001B[1;34msimulation.hdf5.gz\u001B[0m \u001B[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━\u001B[0m \u001B[35m100.0%\u001B[0m • \u001B[32m3.1/3.1 kB\u001B[0m • \u001B[31m?\u001B[0m • \u001B[36m0:00:00\u001B[0m\n"
          },
          "metadata": {},
          "output_type": "display_data"
@@ -3590,7 +3590,7 @@
         {
          "data": {
           "text/html": "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008000; text-decoration-color: #008000; font-weight: bold\">↓</span> <span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">monitor_data.hdf5</span> <span style=\"color: #729c1f; text-decoration-color: #729c1f\">━━━━━━━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">100.0%</span> • <span style=\"color: #008000; text-decoration-color: #008000\">82.2/82.2 kB</span> • <span style=\"color: #800000; text-decoration-color: #800000\">?</span> • <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\n</pre>\n",
-          "text/plain": "\u001b[1;32m↓\u001b[0m \u001b[1;34mmonitor_data.hdf5\u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100.0%\u001b[0m • \u001b[32m82.2/82.2 kB\u001b[0m • \u001b[31m?\u001b[0m • \u001b[36m0:00:00\u001b[0m\n"
+          "text/plain": "\u001B[1;32m↓\u001B[0m \u001B[1;34mmonitor_data.hdf5\u001B[0m \u001B[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━\u001B[0m \u001B[35m100.0%\u001B[0m • \u001B[32m82.2/82.2 kB\u001B[0m • \u001B[31m?\u001B[0m • \u001B[36m0:00:00\u001B[0m\n"
          },
          "metadata": {},
          "output_type": "display_data"
@@ -3672,7 +3672,7 @@
         {
          "data": {
           "text/html": "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800000; text-decoration-color: #800000; font-weight: bold\">↑</span> <span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">simulation.hdf5.gz</span> <span style=\"color: #729c1f; text-decoration-color: #729c1f\">━━━━━━━━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">100.0%</span> • <span style=\"color: #008000; text-decoration-color: #008000\">3.1/3.1 kB</span> • <span style=\"color: #800000; text-decoration-color: #800000\">?</span> • <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\n</pre>\n",
-          "text/plain": "\u001b[1;31m↑\u001b[0m \u001b[1;34msimulation.hdf5.gz\u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100.0%\u001b[0m • \u001b[32m3.1/3.1 kB\u001b[0m • \u001b[31m?\u001b[0m • \u001b[36m0:00:00\u001b[0m\n"
+          "text/plain": "\u001B[1;31m↑\u001B[0m \u001B[1;34msimulation.hdf5.gz\u001B[0m \u001B[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━\u001B[0m \u001B[35m100.0%\u001B[0m • \u001B[32m3.1/3.1 kB\u001B[0m • \u001B[31m?\u001B[0m • \u001B[36m0:00:00\u001B[0m\n"
          },
          "metadata": {},
          "output_type": "display_data"
@@ -4072,7 +4072,7 @@
         {
          "data": {
           "text/html": "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008000; text-decoration-color: #008000; font-weight: bold\">↓</span> <span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">monitor_data.hdf5</span> <span style=\"color: #729c1f; text-decoration-color: #729c1f\">━━━━━━━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">100.0%</span> • <span style=\"color: #008000; text-decoration-color: #008000\">82.4/82.4 kB</span> • <span style=\"color: #800000; text-decoration-color: #800000\">?</span> • <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\n</pre>\n",
-          "text/plain": "\u001b[1;32m↓\u001b[0m \u001b[1;34mmonitor_data.hdf5\u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100.0%\u001b[0m • \u001b[32m82.4/82.4 kB\u001b[0m • \u001b[31m?\u001b[0m • \u001b[36m0:00:00\u001b[0m\n"
+          "text/plain": "\u001B[1;32m↓\u001B[0m \u001B[1;34mmonitor_data.hdf5\u001B[0m \u001B[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━\u001B[0m \u001B[35m100.0%\u001B[0m • \u001B[32m82.4/82.4 kB\u001B[0m • \u001B[31m?\u001B[0m • \u001B[36m0:00:00\u001B[0m\n"
          },
          "metadata": {},
          "output_type": "display_data"
@@ -4101,7 +4101,7 @@
         {
          "data": {
           "text/html": "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800000; text-decoration-color: #800000; font-weight: bold\">↑</span> <span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">simulation.hdf5.gz</span> <span style=\"color: #729c1f; text-decoration-color: #729c1f\">━━━━━━━━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">100.0%</span> • <span style=\"color: #008000; text-decoration-color: #008000\">3.1/3.1 kB</span> • <span style=\"color: #800000; text-decoration-color: #800000\">?</span> • <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\n</pre>\n",
-          "text/plain": "\u001b[1;31m↑\u001b[0m \u001b[1;34msimulation.hdf5.gz\u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100.0%\u001b[0m • \u001b[32m3.1/3.1 kB\u001b[0m • \u001b[31m?\u001b[0m • \u001b[36m0:00:00\u001b[0m\n"
+          "text/plain": "\u001B[1;31m↑\u001B[0m \u001B[1;34msimulation.hdf5.gz\u001B[0m \u001B[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━\u001B[0m \u001B[35m100.0%\u001B[0m • \u001B[32m3.1/3.1 kB\u001B[0m • \u001B[31m?\u001B[0m • \u001B[36m0:00:00\u001B[0m\n"
          },
          "metadata": {},
          "output_type": "display_data"
diff --git a/Primer.ipynb b/Primer.ipynb
index fd0dfa85..b208d25a 100644
--- a/Primer.ipynb
+++ b/Primer.ipynb
@@ -14,18 +14,45 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
    "id": "1382cd8c",
    "metadata": {
-    "tags": []
+    "tags": [],
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:07:19.820546Z",
+     "start_time": "2025-10-29T14:07:18.557940Z"
+    }
    },
-   "outputs": [],
    "source": [
     "# First, let's import the main packages we'll need\n",
     "import matplotlib.pylab as plt\n",
     "import numpy as np\n",
     "import tidy3d as td"
-   ]
+   ],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "\u001B[2;36m15:07:18 CET\u001B[0m\u001B[2;36m \u001B[0m\u001B[31mWARNING: Using canonical configuration directory at                \u001B[0m\n",
+       "\u001B[2;36m             \u001B[0m\u001B[32m'/home/marco/.config/tidy3d'\u001B[0m\u001B[31m. Found legacy directory at            \u001B[0m\n",
+       "\u001B[2;36m             \u001B[0m\u001B[32m'~/.tidy3d'\u001B[0m\u001B[31m, which will be ignored. Remove it manually or run      \u001B[0m\n",
+       "\u001B[2;36m             \u001B[0m\u001B[32m'tidy3d config migrate --delete-legacy'\u001B[0m\u001B[31m to clean up.               \u001B[0m\n"
+      ],
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">15:07:18 CET </span><span style=\"color: #800000; text-decoration-color: #800000\">WARNING: Using canonical configuration directory at                </span>\n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'/home/marco/.config/tidy3d'</span><span style=\"color: #800000; text-decoration-color: #800000\">. Found legacy directory at            </span>\n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'~/.tidy3d'</span><span style=\"color: #800000; text-decoration-color: #800000\">, which will be ignored. Remove it manually or run      </span>\n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'tidy3d config migrate --delete-legacy'</span><span style=\"color: #800000; text-decoration-color: #800000\"> to clean up.               </span>\n",
+       "</pre>\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
+    }
+   ],
+   "execution_count": 1
   },
   {
    "cell_type": "markdown",
@@ -75,10 +102,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
    "id": "19eab659",
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:07:19.828544Z",
+     "start_time": "2025-10-29T14:07:19.826785Z"
+    }
+   },
    "source": [
     "# wrong way\n",
     "try:\n",
@@ -88,7 +118,9 @@
     "\n",
     "# correct way\n",
     "m = td.Medium(permittivity=2.0)"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": 2
   },
   {
    "cell_type": "markdown",
@@ -104,22 +136,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
    "id": "20e27567",
    "metadata": {
-    "tags": []
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "attrs={} type='Box' center=(1.0, 2.0, 3.0) size=(2.0, 2.0, 3.0)\n",
-      "attrs={} type='Box' center=(1.0, 2.0, 3.0) size=(2.0, 2.0, 3.0)\n",
-      "True\n"
-     ]
+    "tags": [],
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:07:19.875881Z",
+     "start_time": "2025-10-29T14:07:19.873575Z"
     }
-   ],
+   },
    "source": [
     "my_box = td.Box(center=(1, 2, 3), size=(2, 2, 3))\n",
     "\n",
@@ -131,7 +155,19 @@
     "print(my_box)\n",
     "print(your_box)\n",
     "print(my_box == your_box)"
-   ]
+   ],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "attrs={} type='Box' center=(1.0, 2.0, 3.0) size=(2.0, 2.0, 3.0)\n",
+      "attrs={} type='Box' center=(1.0, 2.0, 3.0) size=(2.0, 2.0, 3.0)\n",
+      "True\n"
+     ]
+    }
+   ],
+   "execution_count": 3
   },
   {
    "cell_type": "markdown",
@@ -143,9 +179,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
    "id": "5c05d911-dfd0-4d5f-ba60-54eb59d2a041",
-   "metadata": {},
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:07:19.923343Z",
+     "start_time": "2025-10-29T14:07:19.921866Z"
+    }
+   },
+   "source": [
+    "print(my_box.json())\n",
+    "print(my_box.dict())"
+   ],
    "outputs": [
     {
      "name": "stdout",
@@ -156,10 +200,7 @@
      ]
     }
    ],
-   "source": [
-    "print(my_box.json())\n",
-    "print(my_box.dict())"
-   ]
+   "execution_count": 4
   },
   {
    "cell_type": "markdown",
@@ -175,14 +216,75 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
    "id": "b34de32a",
    "metadata": {
-    "tags": []
+    "tags": [],
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:07:19.984331Z",
+     "start_time": "2025-10-29T14:07:19.969485Z"
+    }
    },
+   "source": [
+    "monitor = td.FieldMonitor(size=(2, 2, 0), freqs=[200e12], name=\"monitor\")\n",
+    "\n",
+    "monitor.help()"
+   ],
    "outputs": [
     {
      "data": {
+      "text/plain": [
+       "\u001B[34m╭─\u001B[0m\u001B[34m───────────────────────────\u001B[0m\u001B[34m \u001B[0m\u001B[1;34m<\u001B[0m\u001B[1;95mclass\u001B[0m\u001B[39m \u001B[0m\u001B[32m'tidy3d.components.monitor.FieldMonitor'\u001B[0m\u001B[1;34m>\u001B[0m\u001B[34m \u001B[0m\u001B[34m───────────────────────────\u001B[0m\u001B[34m─╮\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[36m:class:`Monitor` that records electromagnetic fields in the frequency domain.\u001B[0m                            \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                                                                                          \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m╭──────────────────────────────────────────────────────────────────────────────────────────────────────╮\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[1;35mFieldMonitor\u001B[0m\u001B[1m(\u001B[0m                                                                                        \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   \u001B[0m\u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                                                        \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   \u001B[0m\u001B[33mtype\u001B[0m=\u001B[32m'FieldMonitor'\u001B[0m,                                                                             \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   \u001B[0m\u001B[33mcenter\u001B[0m=\u001B[1m(\u001B[0m\u001B[1;36m0.0\u001B[0m, \u001B[1;36m0.0\u001B[0m, \u001B[1;36m0.0\u001B[0m\u001B[1m)\u001B[0m,                                                                          \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   \u001B[0m\u001B[33msize\u001B[0m=\u001B[1m(\u001B[0m\u001B[1;36m2.0\u001B[0m, \u001B[1;36m2.0\u001B[0m, \u001B[1;36m0.0\u001B[0m\u001B[1m)\u001B[0m,                                                                            \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   \u001B[0m\u001B[33mname\u001B[0m=\u001B[32m'monitor'\u001B[0m,                                                                                  \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   \u001B[0m\u001B[33minterval_space\u001B[0m=\u001B[1m(\u001B[0m\u001B[1;36m1\u001B[0m, \u001B[1;36m1\u001B[0m, \u001B[1;36m1\u001B[0m\u001B[1m)\u001B[0m,                                                                        \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   \u001B[0m\u001B[33mcolocate\u001B[0m=\u001B[3;92mTrue\u001B[0m,                                                                                   \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   \u001B[0m\u001B[33mfreqs\u001B[0m=\u001B[1m(\u001B[0m\u001B[1;36m200000000000000.0\u001B[0m,\u001B[1m)\u001B[0m,                                                                      \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   \u001B[0m\u001B[33mapodization\u001B[0m=\u001B[1;35mApodizationSpec\u001B[0m\u001B[1m(\u001B[0m                                                                     \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   \u001B[0m\u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                                                    \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   \u001B[0m\u001B[33mstart\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                                                  \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   \u001B[0m\u001B[33mend\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                                                    \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   \u001B[0m\u001B[33mwidth\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                                                  \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   \u001B[0m\u001B[33mtype\u001B[0m=\u001B[32m'ApodizationSpec'\u001B[0m                                                                       \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   \u001B[0m\u001B[1m)\u001B[0m,                                                                                               \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   \u001B[0m\u001B[33mfields\u001B[0m=\u001B[1m(\u001B[0m\u001B[32m'Ex'\u001B[0m, \u001B[32m'Ey'\u001B[0m, \u001B[32m'Ez'\u001B[0m, \u001B[32m'Hx'\u001B[0m, \u001B[32m'Hy'\u001B[0m, \u001B[32m'Hz'\u001B[0m\u001B[1m)\u001B[0m                                                      \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[1m)\u001B[0m                                                                                                    \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m╰──────────────────────────────────────────────────────────────────────────────────────────────────────╯\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                                                                                          \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m     \u001B[3;33mapodization\u001B[0m = \u001B[1;35mApodizationSpec\u001B[0m\u001B[1m(\u001B[0m\u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m, \u001B[33mstart\u001B[0m=\u001B[3;35mNone\u001B[0m, \u001B[33mend\u001B[0m=\u001B[3;35mNone\u001B[0m, \u001B[33mwidth\u001B[0m=\u001B[3;35mNone\u001B[0m, \u001B[33mtype\u001B[0m=\u001B[32m'ApodizationSpec'\u001B[0m\u001B[1m)\u001B[0m    \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m           \u001B[3;33mattrs\u001B[0m = \u001B[1m{\u001B[0m\u001B[1m}\u001B[0m                                                                                     \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m    \u001B[3;33mbounding_box\u001B[0m = \u001B[1;35mBox\u001B[0m\u001B[1m(\u001B[0m\u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m, \u001B[33mtype\u001B[0m=\u001B[32m'Box'\u001B[0m, \u001B[33mcenter\u001B[0m=\u001B[1m(\u001B[0m\u001B[1;36m0.0\u001B[0m, \u001B[1;36m0.0\u001B[0m, \u001B[1;36m0.0\u001B[0m\u001B[1m)\u001B[0m, \u001B[33msize\u001B[0m=\u001B[1m(\u001B[0m\u001B[1;36m2.0\u001B[0m, \u001B[1;36m2.0\u001B[0m, \u001B[1;36m0.0\u001B[0m\u001B[1m)\u001B[0m\u001B[1m)\u001B[0m                \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m          \u001B[3;33mbounds\u001B[0m = \u001B[1m(\u001B[0m\u001B[1m(\u001B[0m\u001B[1;36m-1.0\u001B[0m, \u001B[1;36m-1.0\u001B[0m, \u001B[1;36m0.0\u001B[0m\u001B[1m)\u001B[0m, \u001B[1m(\u001B[0m\u001B[1;36m1.0\u001B[0m, \u001B[1;36m1.0\u001B[0m, \u001B[1;36m0.0\u001B[0m\u001B[1m)\u001B[0m\u001B[1m)\u001B[0m                                                   \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m          \u001B[3;33mcenter\u001B[0m = \u001B[1m(\u001B[0m\u001B[1;36m0.0\u001B[0m, \u001B[1;36m0.0\u001B[0m, \u001B[1;36m0.0\u001B[0m\u001B[1m)\u001B[0m                                                                        \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m        \u001B[3;33mcolocate\u001B[0m = \u001B[3;92mTrue\u001B[0m                                                                                   \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m          \u001B[3;33mfields\u001B[0m = \u001B[1m(\u001B[0m\u001B[32m'Ex'\u001B[0m, \u001B[32m'Ey'\u001B[0m, \u001B[32m'Ez'\u001B[0m, \u001B[32m'Hx'\u001B[0m, \u001B[32m'Hy'\u001B[0m, \u001B[32m'Hz'\u001B[0m\u001B[1m)\u001B[0m                                                   \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m           \u001B[3;33mfreqs\u001B[0m = \u001B[1m(\u001B[0m\u001B[1;36m200000000000000.0\u001B[0m,\u001B[1m)\u001B[0m                                                                   \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[3;33mfrequency_range\u001B[0m = \u001B[1m(\u001B[0m\u001B[1;36m200000000000000.0\u001B[0m, \u001B[1;36m200000000000000.0\u001B[0m\u001B[1m)\u001B[0m                                                 \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m        \u001B[3;33mgeometry\u001B[0m = \u001B[1;35mBox\u001B[0m\u001B[1m(\u001B[0m\u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m, \u001B[33mtype\u001B[0m=\u001B[32m'Box'\u001B[0m, \u001B[33mcenter\u001B[0m=\u001B[1m(\u001B[0m\u001B[1;36m0.0\u001B[0m, \u001B[1;36m0.0\u001B[0m, \u001B[1;36m0.0\u001B[0m\u001B[1m)\u001B[0m, \u001B[33msize\u001B[0m=\u001B[1m(\u001B[0m\u001B[1;36m2.0\u001B[0m, \u001B[1;36m2.0\u001B[0m, \u001B[1;36m0.0\u001B[0m\u001B[1m)\u001B[0m\u001B[1m)\u001B[0m                \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m  \u001B[3;33minterval_space\u001B[0m = \u001B[1m(\u001B[0m\u001B[1;36m1\u001B[0m, \u001B[1;36m1\u001B[0m, \u001B[1;36m1\u001B[0m\u001B[1m)\u001B[0m                                                                              \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m            \u001B[3;33mname\u001B[0m = \u001B[32m'monitor'\u001B[0m                                                                              \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m     \u001B[3;33mplot_params\u001B[0m = \u001B[1;35mPlotParams\u001B[0m\u001B[1m(\u001B[0m                                                                            \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                       \u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                                          \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                       \u001B[33malpha\u001B[0m=\u001B[1;36m0\u001B[0m\u001B[1;36m.4\u001B[0m,                                                                         \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                       \u001B[33mzorder\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                                       \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                       \u001B[33mtype\u001B[0m=\u001B[32m'PlotParams'\u001B[0m,                                                                 \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                       \u001B[33medgecolor\u001B[0m=\u001B[32m'orange'\u001B[0m,                                                                \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                       \u001B[33mfacecolor\u001B[0m=\u001B[32m'orange'\u001B[0m,                                                                \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                       \u001B[33mfill\u001B[0m=\u001B[3;92mTrue\u001B[0m,                                                                         \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                       \u001B[33mhatch\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                                        \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                       \u001B[33mlinewidth\u001B[0m=\u001B[1;36m3\u001B[0m\u001B[1;36m.0\u001B[0m                                                                      \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                   \u001B[1m)\u001B[0m                                                                                      \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m            \u001B[3;33msize\u001B[0m = \u001B[1m(\u001B[0m\u001B[1;36m2.0\u001B[0m, \u001B[1;36m2.0\u001B[0m, \u001B[1;36m0.0\u001B[0m\u001B[1m)\u001B[0m                                                                        \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m            \u001B[3;33mtype\u001B[0m = \u001B[32m'FieldMonitor'\u001B[0m                                                                         \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m       \u001B[3;33mzero_dims\u001B[0m = \u001B[1m[\u001B[0m\u001B[1;36m2\u001B[0m\u001B[1m]\u001B[0m                                                                                    \u001B[34m│\u001B[0m\n",
+       "\u001B[34m╰──────────────────────────────────────────────────────────────────────────────────────────────────────────╯\u001B[0m\n"
+      ],
       "text/html": [
        "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #000080; text-decoration-color: #000080\">╭──────────────────────────── </span><span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">&lt;</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff; font-weight: bold\">class</span><span style=\"color: #000000; text-decoration-color: #000000\"> </span><span style=\"color: #008000; text-decoration-color: #008000\">'tidy3d.components.monitor.FieldMonitor'</span><span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">&gt;</span><span style=\"color: #000080; text-decoration-color: #000080\"> ────────────────────────────╮</span>\n",
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">:class:`Monitor` that records electromagnetic fields in the frequency domain.</span>                            <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
@@ -236,70 +338,16 @@
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>       <span style=\"color: #808000; text-decoration-color: #808000; font-style: italic\">zero_dims</span> = <span style=\"font-weight: bold\">[</span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span><span style=\"font-weight: bold\">]</span>                                                                                    <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
        "<span style=\"color: #000080; text-decoration-color: #000080\">╰──────────────────────────────────────────────────────────────────────────────────────────────────────────╯</span>\n",
        "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[34m╭─\u001b[0m\u001b[34m───────────────────────────\u001b[0m\u001b[34m \u001b[0m\u001b[1;34m<\u001b[0m\u001b[1;95mclass\u001b[0m\u001b[39m \u001b[0m\u001b[32m'tidy3d.components.monitor.FieldMonitor'\u001b[0m\u001b[1;34m>\u001b[0m\u001b[34m \u001b[0m\u001b[34m───────────────────────────\u001b[0m\u001b[34m─╮\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[36m:class:`Monitor` that records electromagnetic fields in the frequency domain.\u001b[0m                            \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                                                                                          \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m╭──────────────────────────────────────────────────────────────────────────────────────────────────────╮\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[1;35mFieldMonitor\u001b[0m\u001b[1m(\u001b[0m                                                                                        \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   \u001b[0m\u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                                                        \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   \u001b[0m\u001b[33mtype\u001b[0m=\u001b[32m'FieldMonitor'\u001b[0m,                                                                             \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   \u001b[0m\u001b[33mcenter\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m\u001b[1m)\u001b[0m,                                                                          \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   \u001b[0m\u001b[33msize\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m2.0\u001b[0m, \u001b[1;36m2.0\u001b[0m, \u001b[1;36m0.0\u001b[0m\u001b[1m)\u001b[0m,                                                                            \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   \u001b[0m\u001b[33mname\u001b[0m=\u001b[32m'monitor'\u001b[0m,                                                                                  \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   \u001b[0m\u001b[33minterval_space\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m1\u001b[0m, \u001b[1;36m1\u001b[0m, \u001b[1;36m1\u001b[0m\u001b[1m)\u001b[0m,                                                                        \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   \u001b[0m\u001b[33mcolocate\u001b[0m=\u001b[3;92mTrue\u001b[0m,                                                                                   \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   \u001b[0m\u001b[33mfreqs\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m200000000000000.0\u001b[0m,\u001b[1m)\u001b[0m,                                                                      \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   \u001b[0m\u001b[33mapodization\u001b[0m=\u001b[1;35mApodizationSpec\u001b[0m\u001b[1m(\u001b[0m                                                                     \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   \u001b[0m\u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                                                    \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   \u001b[0m\u001b[33mstart\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                                                  \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   \u001b[0m\u001b[33mend\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                                                    \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   \u001b[0m\u001b[33mwidth\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                                                  \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   \u001b[0m\u001b[33mtype\u001b[0m=\u001b[32m'ApodizationSpec'\u001b[0m                                                                       \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   \u001b[0m\u001b[1m)\u001b[0m,                                                                                               \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   \u001b[0m\u001b[33mfields\u001b[0m=\u001b[1m(\u001b[0m\u001b[32m'Ex'\u001b[0m, \u001b[32m'Ey'\u001b[0m, \u001b[32m'Ez'\u001b[0m, \u001b[32m'Hx'\u001b[0m, \u001b[32m'Hy'\u001b[0m, \u001b[32m'Hz'\u001b[0m\u001b[1m)\u001b[0m                                                      \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[1m)\u001b[0m                                                                                                    \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m╰──────────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                                                                                          \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m     \u001b[3;33mapodization\u001b[0m = \u001b[1;35mApodizationSpec\u001b[0m\u001b[1m(\u001b[0m\u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m, \u001b[33mstart\u001b[0m=\u001b[3;35mNone\u001b[0m, \u001b[33mend\u001b[0m=\u001b[3;35mNone\u001b[0m, \u001b[33mwidth\u001b[0m=\u001b[3;35mNone\u001b[0m, \u001b[33mtype\u001b[0m=\u001b[32m'ApodizationSpec'\u001b[0m\u001b[1m)\u001b[0m    \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m           \u001b[3;33mattrs\u001b[0m = \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m                                                                                     \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m    \u001b[3;33mbounding_box\u001b[0m = \u001b[1;35mBox\u001b[0m\u001b[1m(\u001b[0m\u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m, \u001b[33mtype\u001b[0m=\u001b[32m'Box'\u001b[0m, \u001b[33mcenter\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m\u001b[1m)\u001b[0m, \u001b[33msize\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m2.0\u001b[0m, \u001b[1;36m2.0\u001b[0m, \u001b[1;36m0.0\u001b[0m\u001b[1m)\u001b[0m\u001b[1m)\u001b[0m                \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m          \u001b[3;33mbounds\u001b[0m = \u001b[1m(\u001b[0m\u001b[1m(\u001b[0m\u001b[1;36m-1.0\u001b[0m, \u001b[1;36m-1.0\u001b[0m, \u001b[1;36m0.0\u001b[0m\u001b[1m)\u001b[0m, \u001b[1m(\u001b[0m\u001b[1;36m1.0\u001b[0m, \u001b[1;36m1.0\u001b[0m, \u001b[1;36m0.0\u001b[0m\u001b[1m)\u001b[0m\u001b[1m)\u001b[0m                                                   \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m          \u001b[3;33mcenter\u001b[0m = \u001b[1m(\u001b[0m\u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m\u001b[1m)\u001b[0m                                                                        \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m        \u001b[3;33mcolocate\u001b[0m = \u001b[3;92mTrue\u001b[0m                                                                                   \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m          \u001b[3;33mfields\u001b[0m = \u001b[1m(\u001b[0m\u001b[32m'Ex'\u001b[0m, \u001b[32m'Ey'\u001b[0m, \u001b[32m'Ez'\u001b[0m, \u001b[32m'Hx'\u001b[0m, \u001b[32m'Hy'\u001b[0m, \u001b[32m'Hz'\u001b[0m\u001b[1m)\u001b[0m                                                   \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m           \u001b[3;33mfreqs\u001b[0m = \u001b[1m(\u001b[0m\u001b[1;36m200000000000000.0\u001b[0m,\u001b[1m)\u001b[0m                                                                   \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[3;33mfrequency_range\u001b[0m = \u001b[1m(\u001b[0m\u001b[1;36m200000000000000.0\u001b[0m, \u001b[1;36m200000000000000.0\u001b[0m\u001b[1m)\u001b[0m                                                 \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m        \u001b[3;33mgeometry\u001b[0m = \u001b[1;35mBox\u001b[0m\u001b[1m(\u001b[0m\u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m, \u001b[33mtype\u001b[0m=\u001b[32m'Box'\u001b[0m, \u001b[33mcenter\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m\u001b[1m)\u001b[0m, \u001b[33msize\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m2.0\u001b[0m, \u001b[1;36m2.0\u001b[0m, \u001b[1;36m0.0\u001b[0m\u001b[1m)\u001b[0m\u001b[1m)\u001b[0m                \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m  \u001b[3;33minterval_space\u001b[0m = \u001b[1m(\u001b[0m\u001b[1;36m1\u001b[0m, \u001b[1;36m1\u001b[0m, \u001b[1;36m1\u001b[0m\u001b[1m)\u001b[0m                                                                              \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m            \u001b[3;33mname\u001b[0m = \u001b[32m'monitor'\u001b[0m                                                                              \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m     \u001b[3;33mplot_params\u001b[0m = \u001b[1;35mPlotParams\u001b[0m\u001b[1m(\u001b[0m                                                                            \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                       \u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                                          \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                       \u001b[33malpha\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.4\u001b[0m,                                                                         \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                       \u001b[33mzorder\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                                       \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                       \u001b[33mtype\u001b[0m=\u001b[32m'PlotParams'\u001b[0m,                                                                 \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                       \u001b[33medgecolor\u001b[0m=\u001b[32m'orange'\u001b[0m,                                                                \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                       \u001b[33mfacecolor\u001b[0m=\u001b[32m'orange'\u001b[0m,                                                                \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                       \u001b[33mfill\u001b[0m=\u001b[3;92mTrue\u001b[0m,                                                                         \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                       \u001b[33mhatch\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                                        \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                       \u001b[33mlinewidth\u001b[0m=\u001b[1;36m3\u001b[0m\u001b[1;36m.0\u001b[0m                                                                      \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                   \u001b[1m)\u001b[0m                                                                                      \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m            \u001b[3;33msize\u001b[0m = \u001b[1m(\u001b[0m\u001b[1;36m2.0\u001b[0m, \u001b[1;36m2.0\u001b[0m, \u001b[1;36m0.0\u001b[0m\u001b[1m)\u001b[0m                                                                        \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m            \u001b[3;33mtype\u001b[0m = \u001b[32m'FieldMonitor'\u001b[0m                                                                         \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m       \u001b[3;33mzero_dims\u001b[0m = \u001b[1m[\u001b[0m\u001b[1;36m2\u001b[0m\u001b[1m]\u001b[0m                                                                                    \u001b[34m│\u001b[0m\n",
-       "\u001b[34m╰──────────────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     }
    ],
-   "source": [
-    "monitor = td.FieldMonitor(size=(2, 2, 0), freqs=[200e12], name=\"monitor\")\n",
-    "\n",
-    "monitor.help()"
-   ]
+   "execution_count": 5
   },
   {
    "cell_type": "markdown",
@@ -311,13 +359,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
    "id": "c21b0749-9ab2-489e-b4a4-d977f3ff9dd1",
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:07:20.029009Z",
+     "start_time": "2025-10-29T14:07:20.027682Z"
+    }
+   },
    "source": [
     "# help(td.FieldMonitor) # commented out for brevity\n"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": 6
   },
   {
    "cell_type": "markdown",
@@ -386,15 +439,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
    "id": "a197e0c0",
    "metadata": {
-    "tags": []
+    "tags": [],
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:07:20.073403Z",
+     "start_time": "2025-10-29T14:07:20.072013Z"
+    }
    },
-   "outputs": [],
    "source": [
     "pec_medium = td.PEC"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": 7
   },
   {
    "cell_type": "markdown",
@@ -407,17 +464,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
    "id": "6bde0e4e",
    "metadata": {
-    "tags": []
+    "tags": [],
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:07:20.118107Z",
+     "start_time": "2025-10-29T14:07:20.116464Z"
+    }
    },
-   "outputs": [],
    "source": [
     "lossless_dielectric = td.Medium(permittivity=4.0)\n",
     "lossy_dielectric = td.Medium(permittivity=4.0, conductivity=1.0)\n",
     "lossy_dielectric_from_nk = td.Medium.from_nk(n=2.0, k=0.1, freq=150e12)"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": 8
   },
   {
    "cell_type": "markdown",
@@ -433,17 +494,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
    "id": "e7a92005",
    "metadata": {
-    "tags": []
+    "tags": [],
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:07:20.162943Z",
+     "start_time": "2025-10-29T14:07:20.161365Z"
+    }
    },
-   "outputs": [],
    "source": [
     "anisotropic_medium = td.AnisotropicMedium(\n",
     "    xx=lossless_dielectric, yy=lossy_dielectric, zz=lossy_dielectric_from_nk\n",
     ")"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": 9
   },
   {
    "cell_type": "markdown",
@@ -463,20 +528,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
    "id": "43618ec5",
    "metadata": {
-    "tags": []
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "variants for silver include:  ['Rakic1998BB', 'JohnsonChristy1972', 'RakicLorentzDrude1998', 'Yang2015Drude']\n"
-     ]
+    "tags": [],
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:07:20.207333Z",
+     "start_time": "2025-10-29T14:07:20.205458Z"
     }
-   ],
+   },
    "source": [
     "# material library\n",
     "silver = td.material_library[\"Ag\"]\n",
@@ -487,7 +546,17 @@
     "# models\n",
     "lorentz_model = td.Lorentz(eps_inf=2.0, coeffs=[(1, 2, 3), (4, 5, 6)])\n",
     "sellmeier_model = td.Sellmeier(coeffs=[(1, 2), (3, 4)])"
-   ]
+   ],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "variants for silver include:  ['Rakic1998BB', 'JohnsonChristy1972', 'RakicLorentzDrude1998', 'Yang2015Drude']\n"
+     ]
+    }
+   ],
+   "execution_count": 10
   },
   {
    "cell_type": "markdown",
@@ -503,11 +572,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
    "id": "789f0ac9",
    "metadata": {
-    "tags": []
+    "tags": [],
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:07:20.354676Z",
+     "start_time": "2025-10-29T14:07:20.253324Z"
+    }
    },
+   "source": [
+    "freqs_hz = 1e12 * np.linspace(50, 200, 1001)\n",
+    "print(f\"complex relative permittivity at freqs_hz = \\n\\t {lossy_dielectric.eps_model(freqs_hz)}\\n\")\n",
+    "\n",
+    "ax = lossy_dielectric_from_nk.plot(freqs_hz)"
+   ],
    "outputs": [
     {
      "name": "stdout",
@@ -521,21 +599,19 @@
     },
     {
      "data": {
-      "image/png": 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hnOvOx44dU9OmTbV69WpdddVVZdYZOnSoMjMz9dlnn7nLLrvsMnXr1k1JSUkyDEORkZF66KGH9PDDD0uS0tPTFRYWpoULF+r2228/az8cDoeCg4OVnp6uoKCgcx3OOXE6nTrtDnpZxUKfK/gVvc8qVi9bp7JPKzs3Rzl5OcrOy3W95uYoJy9X2Xmu15y8HGXlFr3PzstVTm6Oe3tdYrFY3CGxKPSdOUgWbrdaLLJYrLJaLAVB0iqrxSqLxSKr1VVuKwiP1hL1XPtZZbWWLCuq67GvtfDV6tGW1WKRtaAvhccsu561aLvVKossBf23FIRbz3WrxSKLLO7jy6KCfayyWOQud9WRLAXjtsgiq7VoX4vkPp4sxY5RxvFU7HiWwuNZrbIU/JxU5vFVrI+ex7OUOJ6lnPEVbZe7n4X/NizF/p0UrhXtU/42ALgQeJNzzuseu/T0dElSo0aNyq2zfv16JSQkeJTFx8dr8eLFkqTk5GSlpKQoLi7OvT04OFgxMTFav359mcEuOztb2dlFZ8ocjuo/Q1bIarWqnj1A9ewB1XpcwzAKAl9REMzOzXaHxNy8POXm5ykv3/Va/H3xsrLKS7/mKyc/t8z9Xe/zlZefp3xnfsHiLFjylO90Kq+wLD9f+Ubh9oK6+fnKN5zKy8+X03CecbyFxwQqW2HIKx50C8tLbnO9lyugemxT6XrFwmjhtgoF0uL7FNumMvrmuV95/XaPtNxtpfutYuG3nH1KHL/oKKXntnQdS/FK57xv8XzuWV6R43q7bzl9K2/f8vrp8UfFue/rMZaK9rVCxz77vtX6M/ByLs40R2W1c6bCsvYv64/Cv113h0KDys9C1emcg53T6dSECRN0+eWXuy+pliUlJUVhYWEeZWFhYUpJSXFvLywrr05JiYmJeuqpp86166ZgsVhc9+L5+qmByr4MfqExDEPOgpCXbxQEQWe+8pz5chaEwcL3eR4hMr/MIOl05stZ0KbTWfjqdL0azmLbiq07C1+L7VuyXkFbhmEov0Q9w3CF2qL6JcqMMvYtr54zX4YhGSrax5Drvz1DhlS4rWDdMORRzyh8bxiu9lXsvWFIKnpvFGz3WC9jn6LjSXKPpXQfjWJ9KquPKhxLOX2siX97ktzzCgDeuOPyGy78YDdu3Dht375da9eurcz+VMjEiRM9zgI6HA5FRUVVez9QuSwWi2wW16VU1G3lhk0Z7vBYWE/FQllhkCzeRvFtRe+LB8jytxlSiTaKte16U+62svfz7J9UzrHcY1WZ7Uue7ZXcr/xt7okrNU/F59RzW+k+F99W2L/iPzv3+/LKi4XniuyritQv8QeBZz3v9i/ekme73u1betu5H9tzPs5jLksd28v9vZ7Lso9V8f3L7ve5/CzKbqd0X85Yr5w/PIMDG5RztOp3TsFu/Pjx+uyzz7RmzRo1a9bsjHXDw8OVmprqUZaamqrw8HD39sKyiIgIjzrdunUrs0273S673X4uXQdwASh+uZCYDwAV59UHrxmGofHjx+ujjz7SihUrFB0dfdZ9YmNjtXz5co+yZcuWKTY2VpIUHR2t8PBwjzoOh0MbNmxw1wEAAMDZeXXGbty4cXrrrbf08ccfq0GDBu574IKDgxUQ4Hp4YPjw4brooouUmJgoSXrggQfUp08fzZgxQwMHDtQ777yjTZs2ad68eZJcf5lPmDBB06ZNU9u2bd0fdxIZGakhQ4ZU4lABAADMzatgN3fuXElS3759Pcpfe+01jRw5UpK0f/9+j29g6N27t9566y09+eSTeuKJJ9S2bVstXrzY44GLRx99VJmZmbrnnnuUlpamK664QkuWLKlVn2EHAABQ253X59jVFjX5OXYAAABVyZucw5ebAgAAmATBDgAAwCQIdgAAACZBsAMAADAJgh0AAIBJEOwAAABMgmAHAABgEgQ7AAAAkyDYAQAAmATBDgAAwCQIdgAAACZBsAMAADAJgh0AAIBJEOwAAABMgmAHAABgEgQ7AAAAkyDYAQAAmATBDgAAwCQIdgAAACZBsAMAADAJgh0AAIBJEOwAAABMgmAHAABgEgQ7AAAAkyDYAQAAmATBDgAAwCQIdgAAACZBsAMAADAJgh0AAIBJEOwAAABMgmAHAABgEgQ7AAAAkyDYAQAAmATBDgAAwCS8DnZr1qzRoEGDFBkZKYvFosWLF5+x/siRI2WxWEotnTp1cteZOnVqqe0dOnTwejAAAAB1mdfBLjMzU127dtWcOXMqVP/FF1/UkSNH3MuBAwfUqFEj3XrrrR71OnXq5FFv7dq13nYNAACgTvPxdocBAwZowIABFa4fHBys4OBg9/rixYt14sQJjRo1yrMjPj4KDw/3tjsAAAAoUO332M2fP19xcXFq0aKFR/muXbsUGRmpVq1a6Y477tD+/fvLbSM7O1sOh8NjAQAAqOuqNdgdPnxYX375pcaMGeNRHhMTo4ULF2rJkiWaO3eukpOTdeWVV+rkyZNltpOYmOg+ExgcHKyoqKjq6D4AAECtZjEMwzjnnS0WffTRRxoyZEiF6icmJmrGjBk6fPiw/Pz8yq2XlpamFi1aaObMmRo9enSp7dnZ2crOznavOxwORUVFKT09XUFBQV6PAwAAoLZyOBwKDg6uUM7x+h67c2UYhhYsWKC77rrrjKFOkkJCQtSuXTvt3r27zO12u112u70qugkAAHDBqrZLsatXr9bu3bvLPANXUkZGhvbs2aOIiIhq6BkAAIA5eB3sMjIytG3bNm3btk2SlJycrG3btrkfdpg4caKGDx9ear/58+crJiZGl1xySaltDz/8sFavXq29e/dq3bp1uvHGG2Wz2TRs2DBvuwcAAFBneX0pdtOmTbr66qvd6wkJCZKkESNGaOHChTpy5EipJ1rT09P1wQcf6MUXXyyzzYMHD2rYsGH6/fffFRoaqiuuuELfffedQkNDve0eAABAnXVeD0/UFt7cVAgAAHAh8Sbn8F2xAAAAJkGwAwAAMAmCHQAAgEkQ7AAAAEyCYAcAAGASBDsAAACTINgBAACYBMEOAADAJAh2AAAAJkGwAwAAMAmCHQAAgEkQ7AAAAEyCYAcAAGASBDsAAACTINgBAACYBMEOAADAJAh2AAAAJkGwAwAAMAmCHQAAgEkQ7AAAAEyCYAcAAGASBDsAAACTINgBAACYBMEOAADAJAh2AAAAJkGwAwAAMAmCHQAAgEkQ7AAAAEyCYAcAAGASBDsAAACTINgBAACYBMEOAADAJAh2AAAAJkGwAwAAMAmvg92aNWs0aNAgRUZGymKxaPHixWesv2rVKlksllJLSkqKR705c+aoZcuW8vf3V0xMjDZu3Oht1wAAAOo0r4NdZmamunbtqjlz5ni1344dO3TkyBH30rRpU/e2d999VwkJCZoyZYq2bNmirl27Kj4+XkePHvW2ewAAAHWWj7c7DBgwQAMGDPD6QE2bNlVISEiZ22bOnKmxY8dq1KhRkqSkpCR9/vnnWrBggR5//HGvjwUAAFAXVds9dt26dVNERISuu+46ffvtt+7ynJwcbd68WXFxcUWdsloVFxen9evXl9lWdna2HA6HxwIAAFDXVXmwi4iIUFJSkj744AN98MEHioqKUt++fbVlyxZJ0vHjx5Wfn6+wsDCP/cLCwkrdh1coMTFRwcHB7iUqKqqqhwEAAFDreX0p1lvt27dX+/bt3eu9e/fWnj179MILL+g///nPObU5ceJEJSQkuNcdDgfhDgAA1HlVHuzK0qtXL61du1aS1KRJE9lsNqWmpnrUSU1NVXh4eJn72+122e32Ku8nAADAhaRGPsdu27ZtioiIkCT5+fmpR48eWr58uXu70+nU8uXLFRsbWxPdAwAAuCB5fcYuIyNDu3fvdq8nJydr27ZtatSokZo3b66JEyfq0KFDev311yVJs2bNUnR0tDp16qSsrCy9+uqrWrFihb766it3GwkJCRoxYoR69uypXr16adasWcrMzHQ/JQsAAICz8zrYbdq0SVdffbV7vfBetxEjRmjhwoU6cuSI9u/f796ek5Ojhx56SIcOHVJgYKC6dOmir7/+2qONoUOH6tixY5o8ebJSUlLUrVs3LVmypNQDFQAAACifxTAMo6Y7cb4cDoeCg4OVnp6uoKCgmu4OAABApfEm5/BdsQAAACZBsAMAADAJgh0AAIBJEOwAAABMgmAHAABgEgQ7AAAAkyDYAQAAmATBDgAAwCQIdgAAACZBsAMAADAJgh0AAIBJEOwAAABMgmAHAABgEgQ7AAAAkyDYAQAAmATBDgAAwCQIdgAAACZBsAMAADAJgh0AAIBJEOwAAABMgmAHAABgEgQ7AAAAkyDYAQAAmATBDgAAwCQIdgAAACZBsAMAADAJgh0AAIBJEOwAAABMgmAHAABgEgQ7AAAAkyDYAQAAmATBDgAAwCQIdgAAACZBsAMAADAJr4PdmjVrNGjQIEVGRspisWjx4sVnrP/hhx/quuuuU2hoqIKCghQbG6ulS5d61Jk6daosFovH0qFDB2+7BgAAUKd5HewyMzPVtWtXzZkzp0L116xZo+uuu05ffPGFNm/erKuvvlqDBg3S1q1bPep16tRJR44ccS9r1671tmsAAAB1mo+3OwwYMEADBgyocP1Zs2Z5rP/jH//Qxx9/rE8//VTdu3cv6oiPj8LDw73tDgAAAApU+z12TqdTJ0+eVKNGjTzKd+3apcjISLVq1Up33HGH9u/fX24b2dnZcjgcHgsAAEBdV+3B7vnnn1dGRoZuu+02d1lMTIwWLlyoJUuWaO7cuUpOTtaVV16pkydPltlGYmKigoOD3UtUVFR1dR8AAKDWshiGYZzzzhaLPvroIw0ZMqRC9d966y2NHTtWH3/8seLi4sqtl5aWphYtWmjmzJkaPXp0qe3Z2dnKzs52rzscDkVFRSk9PV1BQUFejwMAAKC2cjgcCg4OrlDO8foeu3P1zjvvaMyYMXr//ffPGOokKSQkRO3atdPu3bvL3G6322W326uimwAAABesarkU+/bbb2vUqFF6++23NXDgwLPWz8jI0J49exQREVENvQMAADAHr8/YZWRkeJxJS05O1rZt29SoUSM1b95cEydO1KFDh/T6669Lcl1+HTFihF588UXFxMQoJSVFkhQQEKDg4GBJ0sMPP6xBgwapRYsWOnz4sKZMmSKbzaZhw4ZVxhgBAADqBK/P2G3atEndu3d3f1RJQkKCunfvrsmTJ0uSjhw54vFE67x585SXl6dx48YpIiLCvTzwwAPuOgcPHtSwYcPUvn173XbbbWrcuLG+++47hYaGnu/4AAAA6ozzeniitvDmpkIAAIALiTc5h++KBQAAMAmCHQAAgEkQ7AAAAEyCYAcAAGASBDsAAACTINgBAACYRLV9pRgAAMC5MAxDeXl5ys/Pr+muVAmbzSYfHx9ZLJbzbotgBwAAaq2cnBwdOXJEp06dqumuVKnAwEBFRETIz8/vvNoh2AEAgFrJ6XQqOTlZNptNkZGR8vPzq5SzWrWJYRjKycnRsWPHlJycrLZt28pqPfc75Qh2AACgVsrJyZHT6VRUVJQCAwNrujtVJiAgQL6+vtq3b59ycnLk7+9/zm3x8AQAAKjVzucM1oWissZo/pkCAACoIwh2AAAAJkGwAwAAMAmCHQAAgEnwVCwAAEAl69u3r7p06SJ/f3+9+uqr8vPz07333qupU6dW6XEJdgAA4IJhGIZO5WTVyLED/fy9+hy9RYsWKSEhQRs2bND69es1cuRIXX755bruuuuqrI8EOwAAcME4lZOl1g9cXSPH3vPiStWzB1S4fpcuXTRlyhRJUtu2bTV79mwtX768SoMd99gBAABUgS5dunisR0RE6OjRo1V6TM7YAQCAC0agn7/2vLiyxo7tDV9fX491i8Uip9NZmV0qhWAHAAAuGBaLxavLoXUNl2IBAABMgmAHAABgElyKBQAAqGSrVq0qVbZ48eIqPy5n7AAAAEyCYAcAAGASBDsAAACTINgBAACYBMEOAADAJAh2AAAAJkGwAwAAMAmCHQAAgEkQ7AAAAEyCYAcAAFDJ+vbtqwkTJlT7cb0OdmvWrNGgQYMUGRkpi8VSoa/HWLVqlf70pz/JbrerTZs2WrhwYak6c+bMUcuWLeXv76+YmBht3LjR264BAADUaV4Hu8zMTHXt2lVz5sypUP3k5GQNHDhQV199tbZt26YJEyZozJgxWrp0qbvOu+++q4SEBE2ZMkVbtmxR165dFR8fr6NHj3rbPQAAgDrL62A3YMAATZs2TTfeeGOF6iclJSk6OlozZszQxRdfrPHjx+uWW27RCy+84K4zc+ZMjR07VqNGjVLHjh2VlJSkwMBALViwwNvuAQAA1Dqff/65goOD9eabb1bpcXyqtHVJ69evV1xcnEdZfHy8+7pzTk6ONm/erIkTJ7q3W61WxcXFaf369WW2mZ2drezsbPe6w+Go/I4DAIDaxzCk3FM1c2zfQMli8Xq3t956S/fee6/eeust/fnPf66CjhWp8mCXkpKisLAwj7KwsDA5HA6dPn1aJ06cUH5+fpl1fv311zLbTExM1FNPPVVlfQYAALVU7inp6YiaOfbkI5JfPa92mTNnjv7+97/r008/VZ8+faqoY0WqPNhVhYkTJyohIcG97nA4FBUVVYM9AgAA8PR///d/Onr0qL799ltdeuml1XLMKg924eHhSk1N9ShLTU1VUFCQAgICZLPZZLPZyqwTHh5eZpt2u112u73K+gwAAGop30DXmbOaOrYXunfvri1btmjBggXq2bOnLOdwGddbVf45drGxsVq+fLlH2bJlyxQbGytJ8vPzU48ePTzqOJ1OLV++3F0HAABAkuseN796NbN4Gcxat26tlStX6uOPP9Z9991XRRPiyeszdhkZGdq9e7d7PTk5Wdu2bVOjRo3UvHlzTZw4UYcOHdLrr78uSbr33ns1e/ZsPfroo7r77ru1YsUKvffee/r888/dbSQkJGjEiBHq2bOnevXqpVmzZikzM1OjRo2qhCECAADUjHbt2mnlypXq27evfHx8NGvWrCo9ntfBbtOmTbr66qvd64X3uo0YMUILFy7UkSNHtH//fvf26Ohoff7553rwwQf14osvqlmzZnr11VcVHx/vrjN06FAdO3ZMkydPVkpKirp166YlS5aUeqACAADgQtO+fXutWLFCffv2lc1m04wZM6rsWBbDMIwqa72aOBwOBQcHKz09XUFBQTXdHQAAUAmysrKUnJys6Oho+fv713R3qtSZxupNzuG7YgEAAEyCYAcAAGASBDsAAACTINgBAACYBMEOAADAJAh2AACgVjPBB3icVWWNkWAHAABqJV9fX0nSqVOnargnVa9wjIVjPldV/l2xAAAA58JmsykkJERHjx6VJAUGBlbL961WJ8MwdOrUKR09elQhISGy2Wzn1R7BDgAA1Frh4eGS5A53ZhUSEuIe6/kg2AEAgFrLYrEoIiJCTZs2VW5ubk13p0r4+vqe95m6QgQ7AABQ69lstkoLP2bGwxMAAAAmQbADAAAwCYIdAACASRDsAAAATIJgBwAAYBIEOwAAAJMg2AEAAJgEwQ4AAMAkCHYAAAAmQbADAAAwCYIdAACASRDsAAAATIJgBwAAYBIEOwAAAJMg2AEAAJgEwQ4AAMAkCHYAAAAmQbADAAAwCYIdAACASRDsAAAATIJgBwAAYBIEOwAAAJM4p2A3Z84ctWzZUv7+/oqJidHGjRvLrdu3b19ZLJZSy8CBA911Ro4cWWp7//79z6VrAAAAdZaPtzu8++67SkhIUFJSkmJiYjRr1izFx8drx44datq0aan6H374oXJyctzrv//+u7p27apbb73Vo17//v312muvudftdru3XQMAAKjTvD5jN3PmTI0dO1ajRo1Sx44dlZSUpMDAQC1YsKDM+o0aNVJ4eLh7WbZsmQIDA0sFO7vd7lGvYcOG5zYiAACAOsqrYJeTk6PNmzcrLi6uqAGrVXFxcVq/fn2F2pg/f75uv/121atXz6N81apVatq0qdq3b6+//vWv+v33373pGgAAQJ3n1aXY48ePKz8/X2FhYR7lYWFh+vXXX8+6/8aNG7V9+3bNnz/fo7x///666aabFB0drT179uiJJ57QgAEDtH79etlstlLtZGdnKzs7273ucDi8GQYAAIApeX2P3fmYP3++OnfurF69enmU33777e73nTt3VpcuXdS6dWutWrVK1157bal2EhMT9dRTT1V5fwEAAC4kXl2KbdKkiWw2m1JTUz3KU1NTFR4efsZ9MzMz9c4772j06NFnPU6rVq3UpEkT7d69u8ztEydOVHp6uns5cOBAxQcBAABgUl4FOz8/P/Xo0UPLly93lzmdTi1fvlyxsbFn3Pf9999Xdna27rzzzrMe5+DBg/r9998VERFR5na73a6goCCPBQAAoK7z+qnYhIQEvfLKK1q0aJF++eUX/fWvf1VmZqZGjRolSRo+fLgmTpxYar/58+dryJAhaty4sUd5RkaGHnnkEX333Xfau3evli9frsGDB6tNmzaKj48/x2EBAADUPV7fYzd06FAdO3ZMkydPVkpKirp166YlS5a4H6jYv3+/rFbPvLhjxw6tXbtWX331Van2bDabfvjhBy1atEhpaWmKjIxUv3799Mwzz/BZdgAAAF6wGIZh1HQnzpfD4VBwcLDS09O5LAsAAEzFm5zDd8UCAACYBMEOAADAJAh2AAAAJkGwAwAAMAmCHQAAgEkQ7AAAAEyCYAcAAGASBDsAAACTINgBAACYBMEOAADAJAh2AAAAJkGwAwAAMAmCHQAAgEkQ7AAAAEyCYAcAAGASBDsAAACTINgBAACYBMEOAADAJAh2AAAAJkGwAwAAMAmCHQAAgEkQ7AAAAEyCYAcAAGASBDsAAACTINgBAACYBMEOAADAJAh2AAAAJkGwAwAAMAmCHQAAgEkQ7AAAAEyCYAcAAGASBDsAAACTINgBAACYBMEOAADAJM4p2M2ZM0ctW7aUv7+/YmJitHHjxnLrLly4UBaLxWPx9/f3qGMYhiZPnqyIiAgFBAQoLi5Ou3btOpeuAQAA1FleB7t3331XCQkJmjJlirZs2aKuXbsqPj5eR48eLXefoKAgHTlyxL3s27fPY/tzzz2nl156SUlJSdqwYYPq1aun+Ph4ZWVleT8iAACAOsrrYDdz5kyNHTtWo0aNUseOHZWUlKTAwEAtWLCg3H0sFovCw8PdS1hYmHubYRiaNWuWnnzySQ0ePFhdunTR66+/rsOHD2vx4sXnNCgAAIC6yKtgl5OTo82bNysuLq6oAatVcXFxWr9+fbn7ZWRkqEWLFoqKitLgwYP1008/ubclJycrJSXFo83g4GDFxMScsU0AAAB48irYHT9+XPn5+R5n3CQpLCxMKSkpZe7Tvn17LViwQB9//LHeeOMNOZ1O9e7dWwcPHpQk937etJmdnS2Hw+GxAAAA1HVV/lRsbGyshg8frm7duqlPnz768MMPFRoaqn//+9/n3GZiYqKCg4PdS1RUVCX2GAAA4MLkVbBr0qSJbDabUlNTPcpTU1MVHh5eoTZ8fX3VvXt37d69W5Lc+3nT5sSJE5Wenu5eDhw44M0wAAAATMmrYOfn56cePXpo+fLl7jKn06nly5crNja2Qm3k5+frxx9/VEREhCQpOjpa4eHhHm06HA5t2LCh3DbtdruCgoI8FgAAgLrOx9sdEhISNGLECPXs2VO9evXSrFmzlJmZqVGjRkmShg8frosuukiJiYmSpKefflqXXXaZ2rRpo7S0NP3zn//Uvn37NGbMGEmuJ2YnTJigadOmqW3btoqOjtakSZMUGRmpIUOGVN5IAQAATM7rYDd06FAdO3ZMkydPVkpKirp166YlS5a4H37Yv3+/rNaiE4EnTpzQ2LFjlZKSooYNG6pHjx5at26dOnbs6K7z6KOPKjMzU/fcc4/S0tJ0xRVXaMmSJaU+yBgAAADlsxiGYdR0J86Xw+FQcHCw0tPTuSwLAABMxZucw3fFAgAAmATBDgAAwCQIdgAAACZBsAMAADAJgh0AAIBJEOwAAABMgmAHAABgEgQ7AAAAkyDYAQAAmATBDgAAwCQIdgAAACZBsAMAADAJgh0AAIBJEOwAAABMgmAHAABgEgQ7AAAAkyDYAQAAmATBDgAAwCQIdgAAACZBsAMAADAJgh0AAIBJEOwAAABMgmAHAABgEgQ7AAAAkyDYAQAAmATBDgAAwCQIdgAAACZBsAMAADAJgh0AAIBJ+NR0By4oa1+WktdI7fq5loYtarpHAAAAbgQ7b/z0sXRgo7RjqWs9tH1RyGsRK/n41Wz/AABAnWYxDMOo6U6cL4fDoeDgYKWnpysoKKjqDpT6syvU7fxK2v+d5Mwv2uZXX2pztSvktblGComqun4AAIA6w5ucQ7A7V6fTpD0rpR1fSbuWSRlHPbc3bi217utaoq+UAhtVT78AAICpEOyqm9MpHfnedSZv51fSoS2eZ/MsFimiW0HQ6+O6bOsbUP39BAAAFxxvcs45PRU7Z84ctWzZUv7+/oqJidHGjRvLrfvKK6/oyiuvVMOGDdWwYUPFxcWVqj9y5EhZLBaPpX///ufStZphtUoXdZeufkz6n+XSE3ulO96RYu+VmnaQDEM6vFX65gVp4RBpWpT0Sry07Glp5zIpy1HTIwAAACbg9cMT7777rhISEpSUlKSYmBjNmjVL8fHx2rFjh5o2bVqq/qpVqzRs2DD17t1b/v7+mj59uvr166effvpJF110kbte//799dprr7nX7Xb7OQ6pFvAPli6+3rVIkuOI9Ntqac8qac9qyXFI2rfetUiSxSpFdJFa9pZa9Ha91mtSY90HAAAXJq8vxcbExOjSSy/V7NmzJUlOp1NRUVG677779Pjjj591//z8fDVs2FCzZ8/W8OHDJbnO2KWlpWnx4sXej0C14FKsNwxD+n2PK9Tt/Vbau046sbd0vdB2rpAXdalradLOdWYQAADUKd7kHK/O2OXk5Gjz5s2aOHGiu8xqtSouLk7r16+vUBunTp1Sbm6uGjXyfJhg1apVatq0qRo2bKhrrrlG06ZNU+PGjb3p3oXBYpGatHEtPe5ylTkOuwLe3m9dgS/1Z+nYTteyaaGrjj1IatZDiurpCnrNLpXqmXB+AADAOfMq2B0/flz5+fkKCwvzKA8LC9Ovv/5aoTYee+wxRUZGKi4uzl3Wv39/3XTTTYqOjtaePXv0xBNPaMCAAVq/fr1sNlupNrKzs5Wdne1edzgu8HvUgiKlLre4Fkk69bu0b4PrI1UObHI9jJHtcD2Fu2dl0X6NoqVmBUHvou5SeGfJL7BmxgAAAGpctX5A8bPPPqt33nlHq1atkr+/v7v89ttvd7/v3LmzunTpotatW2vVqlW69tprS7WTmJiop556qlr6XCMCG3veo5efJx39WTrwX1fQO/hf19m8P5Jdyw/vu+pZrK4PTY7sKkV2cy0RnSV7g5oaCQAAqEZeBbsmTZrIZrMpNTXVozw1NVXh4eFn3Pf555/Xs88+q6+//lpdunQ5Y91WrVqpSZMm2r17d5nBbuLEiUpISHCvOxwORUWZ+AOBbT6uhysiuki9RrvKTp+QDm5xhb2Dm6TD21yfpXf0F9ey7R1XPYvF9Zl67qDXVYrsIgU0rKHBAACAquJVsPPz81OPHj20fPlyDRkyRJLr4Ynly5dr/Pjx5e733HPP6X//93+1dOlS9ezZ86zHOXjwoH7//XdFRESUud1ut1/YT81WhoCGUttrXYvkeijjZIor4B3+vujVcUg6vtu1/PB/RfsHRUrhnaSwTlJYRyn8EtcDGnwtGgAAFyyvL8UmJCRoxIgR6tmzp3r16qVZs2YpMzNTo0aNkiQNHz5cF110kRITEyVJ06dP1+TJk/XWW2+pZcuWSklJkSTVr19f9evXV0ZGhp566indfPPNCg8P1549e/Too4+qTZs2io+Pr8ShmpzFIgVFuJYOA4rKM465Pjy5MOwd2ial7XM9sOE47PocvUJWH6lJ29KBL7iZq30AAFCreR3shg4dqmPHjmny5MlKSUlRt27dtGTJEvcDFfv375e12MdyzJ07Vzk5Obrllls82pkyZYqmTp0qm82mH374QYsWLVJaWpoiIyPVr18/PfPMM5yVqwz1Q6W2ca6lUJbDdbk2ZbuU+pOU8rPrNSu96FKuip3dszdwBb7Q9q6laXvXx7E0jHZdJgYAALUCXykGF8OQ0g8VBL2fXK+pP0vHdkjOvLL3sfm57t8LbS+FFgt+TdrydC4AAJWkyj7HDiZmsUghzVxL+2KXwPNypD9+cwW8oztcr8d2Ssd3Srmni53hK9FWUDNX6GvSWmrUyvW+cWupUUvJhzOxAABUBc7Y4dw4nVL6wYKgVxD2Ct+f+qP8/SwWKTiqIOgVD3ytCH0AAJTBm5xDsEPlyzzu+tq047tdr3/8Jv3+m+t99sny97NYpaCLpIbNpYYtii0tXa8NIvhaNQBAncOlWNSsek1cS/MYz3LDKAp97uW3ovc5GVL6Adey99vS7dr8Ci4XFwt7jYqFv8DGPL0LAKjTCHaoPhaL6ynd+qFSi8s8txmGlHnM9U0aJ/ZJJ/YXvO6TTux1XfbNzykIgr+V3b5vgBR8ketSb/BFJd43c73a61f5MAEAqCkEO9QOFotUv6lrKXmmT3J9rZrjsCvope13hT138NsnnTziepij8MOYyxMQUhDympUd/IIiuM8PAHDBItjhwmDzKbj3rnnZ2/OyXR/Xkn6o4HJuGe+z0qXTaa4lZXv5xwps5LqfLyhcahBZ8Frw4c8Nwl2v9ZryGX4AgFqH/zPBHHzsBU/Ztiq/TpajRNg7KKUddL13FLzmZbue6j31h+uz/MpjsbjCXVCx4FcY+hqEu848NgiT6oVKNt/KHy8AAGUg2KHu8A9yLWEXl73dMKTTJ1zfues44lpOFiyOlKLXjBTJmS9lpLqWw2c5bkDDosvM9UMLXsM81+sVvOcyMADgPBDsgEIWi+sybGAj1/fklseZ73q692Rh+Espei0syzjqehjEme8Ki6dPuD7j72z8Q6QGhUGvWPALbOx60rjwtV5jV2C02ipt+ACACx/BDvCW1ea6zNogTIrsVn49p9MV6DKOFltSpYxjBcHvaNH7jKOur27LSnMtx3aevR8WiyvclQx9gY1dwa/wtfg230A+EgYATIxgB1QVq7UgWDUu//JvocLLwBnHCsJfYRA85jrzd+p311nCwtfTaa59Cu8HPL6rYn3y8S8WABsVBMOGrtfCJbCM91wiBoALAsEOqA2KXwZu2v7s9fPzpNN/SJnFAl/J8JdZWPa7dOq468GQvCzJcci1eMM3sOIh0L0ES371OUMIANWIYAdciGw+RQ9kVIRhSDmZJc76Fdz7d+pE0ftS62mS4ZRyT7kWbwOh1SbZgyT/4KIlINhVFlBYFuS6t9C/+HqxetxHCAAVRrAD6gKLxfWtG/b6UqOWFd/P6ZSyHWWHvpIB0KP8Dyk/1/PhkXNlb1A69HkExBDXmUF7A8m/gavMXrBe+J5LyQDqCIIdgPJZra7gFBAiKbri+xmG65tAsh3S6fSCh0LSXZ8lmJVeUJZesL1wW7HtWemu/SUp+6RrST947uOw+RUEvWKLf8GrX7H39voFYbCMdf8GrgDJGUQAtRjBDkDls1gkv0DX0iD83NrIyzlz8DudVhQcczKkrIIAmHOy6H3uKVdb+TlF9yGeL796BWcIC1796hWV+dUru9xe8N63nO18iwmASsJvEwC1k4+f5NPE9QTvucrPc4W+wrN+xZesEiGw1FK4n8P1mp/rajMn07VkVM4wJbkuFfudIRD61S8IysXq+AYUvfoGSn4BruDoG+Cq6xvoes8ZRqBOIdgBMC+bT7FLyecpL7sgEBYEvZxTrtCYe8oVAgsDX07B++xi70stGa59nHlFbRd+nV1l87EXhLzC8Fcs9LkD4BmCoV/Bq289z/0Ly30CXJfsAdQKBDsAqAgfu2s5nzOIJeXllB/+3GGxRGjMLnifd9oVLnNPue5HLP4+95TrPkepKDSezwMsZ+PjL/n6u0Kej70gCBas+/oXBED/onqF674BZ9lWTps+dj5GBygHwQ4AaoqPn+RT8PmFlckwXJ9ZmHuqIPCdLva+MAhmlig/U50y6udlFR0vL6tgPa1yx1Eei6UoDFY0ENrsBfX9Srz6ux6u8S149fEvCvEe9QrKbHbJ5kuwRK1FsAMAs7FYis6GBTaummM4ncXOGp4uCJLFXt3vs4qVZbn2cb9ml1gv1kbhvsXbNJyuYxc+dV345HR1KwyWNnuxEGj3DITusFjGtpL1C+uUrG/zcwVLm19RoPQp/t4uWX25FA4PBDsAgPes1qIHPaqDYbgeYMk77bq0XDIoegTCkiEyy3XZOy/L9YR0bpaUn130bSyF29x1sgtCZ0H9vKyih2cK+1KTwbIkm29B+Cu2FAZCn4IQWDwM2vw835cKj2XU8ahXvN0SxyhZx+rD2c1qRrADANR+FkvBZVG/mjm+01ksDGaXHQQ9wmJ2GUuxoOiuX0awzCvYlp8j5eUWe5/jei186KZQfm5B8Myskak5q8KQaPUtCICFQdTH9Wr19XzvU1i3oI77fYn9rT7F2vItdozCtovX8/M8rrVEH8pq8wINpQQ7AADOxmqVrAWXt2ua0+kKePnZBaEupyAM5ha8FguBZ6rjrldenTJCZfH3HnVyiwJp4YM7hQr3uxCVDItlBkJf6bbXvPtWnypEsAMA4EJitUrWgodGaiNnvmd4LAyN+XkFZxyLr+cWnYUsWddZYj+PumW1WbA4c13h06PNXM86ZR235JlQqahu4Yedlzvm3DNvr0YEOwAAUHmsNtfnHCqwpnvincL7OMsKlM4SgdAjeOZKQZE13Xs3gh0AAEDhfZzyk1RNDwVVAZ6RBgAAMAmCHQAAgEkQ7AAAAEyCYAcAAGASBDsAAACTINgBAACYxDkFuzlz5qhly5by9/dXTEyMNm7ceMb677//vjp06CB/f3917txZX3zxhcd2wzA0efJkRUREKCAgQHFxcdq1a9e5dA0AAKDO8jrYvfvuu0pISNCUKVO0ZcsWde3aVfHx8Tp69GiZ9detW6dhw4Zp9OjR2rp1q4YMGaIhQ4Zo+/bt7jrPPfecXnrpJSUlJWnDhg2qV6+e4uPjlZWVde4jAwAAqGMshlHyS93OLCYmRpdeeqlmz54tSXI6nYqKitJ9992nxx9/vFT9oUOHKjMzU5999pm77LLLLlO3bt2UlJQkwzAUGRmphx56SA8//LAkKT09XWFhYVq4cKFuv/32s/bJ4XAoODhY6enpCgoK8mY4AAAAtZo3OcerM3Y5OTnavHmz4uLiihqwWhUXF6f169eXuc/69es96ktSfHy8u35ycrJSUlI86gQHBysmJqbcNgEAAFCaV18pdvz4ceXn5yssLMyjPCwsTL/++muZ+6SkpJRZPyUlxb29sKy8OiVlZ2crOzvbve5wOLwZBgAAgCldkE/FJiYmKjg42L1ERUXVdJcAAABqnFfBrkmTJrLZbEpNTfUoT01NVXh4eJn7hIeHn7F+4as3bU6cOFHp6enu5cCBA94MAwAAwJS8CnZ+fn7q0aOHli9f7i5zOp1avny5YmNjy9wnNjbWo74kLVu2zF0/Ojpa4eHhHnUcDoc2bNhQbpt2u11BQUEeCwAAQF3n1T12kpSQkKARI0aoZ8+e6tWrl2bNmqXMzEyNGjVKkjR8+HBddNFFSkxMlCQ98MAD6tOnj2bMmKGBAwfqnXfe0aZNmzRv3jxJksVi0YQJEzRt2jS1bdtW0dHRmjRpkiIjIzVkyJAK9anwwV7utQMAAGZTmG8q9EEmxjl4+eWXjebNmxt+fn5Gr169jO+++869rU+fPsaIESM86r/33ntGu3btDD8/P6NTp07G559/7rHd6XQakyZNMsLCwgy73W5ce+21xo4dOyrcnwMHDhiSWFhYWFhYWFhMuxw4cOCsmcjrz7GrjZxOpw4fPqwGDRrIYrHUdHeqhcPhUFRUlA4cOMCl6ALMSWnMSWnMSWnMSWnMSWnMSWnVNSeGYejkyZOKjIyU1Xrmu+i8vhRbG1mtVjVr1qymu1EjuMewNOakNOakNOakNOakNOakNOaktOqYk+Dg4ArVuyA/7gQAAAClEewAAABMgmB3gbLb7ZoyZYrsdntNd6XWYE5KY05KY05KY05KY05KY05Kq41zYoqHJwAAAMAZOwAAANMg2AEAAJgEwQ4AAMAkCHa13KFDh3TnnXeqcePGCggIUOfOnbVp0yb3dsMwNHnyZEVERCggIEBxcXHatWtXDfa4auXn52vSpEmKjo5WQECAWrdurWeeecbja1bMPidr1qzRoEGDFBkZKYvFosWLF3tsr8j4//jjD91xxx0KCgpSSEiIRo8erYyMjGocReU605zk5ubqscceU+fOnVWvXj1FRkZq+PDhOnz4sEcbdWlOSrr33ntlsVg0a9Ysj/K6OCe//PKLbrjhBgUHB6tevXq69NJLtX//fvf2rKwsjRs3To0bN1b9+vV18803KzU1tRpHUbnONicZGRkaP368mjVrpoCAAHXs2FFJSUkedcw2J4mJibr00kvVoEEDNW3aVEOGDNGOHTs86lRkzPv379fAgQMVGBiopk2b6pFHHlFeXl6V959gV4udOHFCl19+uXx9ffXll1/q559/1owZM9SwYUN3neeee04vvfSSkpKStGHDBtWrV0/x8fHKysqqwZ5XnenTp2vu3LmaPXu2fvnlF02fPl3PPfecXn75ZXcds89JZmamunbtqjlz5pS5vSLjv+OOO/TTTz9p2bJl+uyzz7RmzRrdc8891TWESnemOTl16pS2bNmiSZMmacuWLfrwww+1Y8cO3XDDDR716tKcFPfRRx/pu+++U2RkZKltdW1O9uzZoyuuuEIdOnTQqlWr9MMPP2jSpEny9/d313nwwQf16aef6v3339fq1at1+PBh3XTTTdU1hEp3tjlJSEjQkiVL9MYbb+iXX37RhAkTNH78eH3yySfuOmabk9WrV2vcuHH67rvvtGzZMuXm5qpfv37KzMx01znbmPPz8zVw4EDl5ORo3bp1WrRokRYuXKjJkydX/QAq/IWsqHaPPfaYccUVV5S73el0GuHh4cY///lPd1laWppht9uNt99+uzq6WO0GDhxo3H333R5lN910k3HHHXcYhlH35kSS8dFHH7nXKzL+n3/+2ZBk/Pe//3XX+fLLLw2LxWIcOnSo2vpeVUrOSVk2btxoSDL27dtnGEbdnZODBw8aF110kbF9+3ajRYsWxgsvvODeVhfnZOjQocadd95Z7j5paWmGr6+v8f7777vLfvnlF0OSsX79+qrqarUpa046depkPP300x5lf/rTn4y///3vhmGYf04MwzCOHj1qSDJWr15tGEbFxvzFF18YVqvVSElJcdeZO3euERQUZGRnZ1dpfzljV4t98skn6tmzp2699VY1bdpU3bt31yuvvOLenpycrJSUFMXFxbnLgoODFRMTo/Xr19dEl6tc7969tXz5cu3cuVOS9P3332vt2rUaMGCApLo5J8VVZPzr169XSEiIevbs6a4TFxcnq9WqDRs2VHufa0J6erosFotCQkIk1c05cTqduuuuu/TII4+oU6dOpbbXtTlxOp36/PPP1a5dO8XHx6tp06aKiYnxuDS5efNm5ebmevz31aFDBzVv3ty0v1969+6tTz75RIcOHZJhGFq5cqV27typfv36Saobc5Keni5JatSokaSKjXn9+vXq3LmzwsLC3HXi4+PlcDj0008/VWl/CXa12G+//aa5c+eqbdu2Wrp0qf7617/q/vvv16JFiyRJKSkpkuTxD6dwvXCb2Tz++OO6/fbb1aFDB/n6+qp79+6aMGGC7rjjDkl1c06Kq8j4U1JS1LRpU4/tPj4+atSoUZ2Yo6ysLD322GMaNmyY+7sd6+KcTJ8+XT4+Prr//vvL3F7X5uTo0aPKyMjQs88+q/79++urr77SjTfeqJtuukmrV6+W5JoTPz8/9x8Ehcz8++Xll19Wx44d1axZM/n5+al///6aM2eOrrrqKknmnxOn06kJEybo8ssv1yWXXCKpYmNOSUkp8/dw4baq5FOlreO8OJ1O9ezZU//4xz8kSd27d9f27duVlJSkESNG1HDvasZ7772nN998U2+99ZY6deqkbdu2acKECYqMjKyzc4KKy83N1W233SbDMDR37tya7k6N2bx5s1588UVt2bJFFoulprtTKzidTknS4MGD9eCDD0qSunXrpnXr1ikpKUl9+vSpye7VmJdfflnfffedPvnkE7Vo0UJr1qzRuHHjFBkZ6XHGyqzGjRun7du3a+3atTXdlQrjjF0tFhERoY4dO3qUXXzxxe4ntMLDwyWp1JM4qamp7m1m88gjj7jP2nXu3Fl33XWXHnzwQSUmJkqqm3NSXEXGHx4erqNHj3psz8vL0x9//GHqOSoMdfv27dOyZcvcZ+ukujcn33zzjY4eParmzZvLx8dHPj4+2rdvnx566CG1bNlSUt2bkyZNmsjHx+esv3NzcnKUlpbmUcesv19Onz6tJ554QjNnztSgQYPUpUsXjR8/XkOHDtXzzz8vydxzMn78eH322WdauXKlmjVr5i6vyJjDw8PL/D1cuK0qEexqscsvv7zUI9Y7d+5UixYtJEnR0dEKDw/X8uXL3dsdDoc2bNig2NjYau1rdTl16pSsVs9/tjabzf3Xdl2ck+IqMv7Y2FilpaVp8+bN7jorVqyQ0+lUTExMtfe5OhSGul27dunrr79W48aNPbbXtTm566679MMPP2jbtm3uJTIyUo888oiWLl0qqe7NiZ+fny699NIz/s7t0aOHfH19Pf772rFjh/bv32/K3y+5ubnKzc094+9cM86JYRgaP368PvroI61YsULR0dEe2ysy5tjYWP34448efxwV/kFZ8o+HqhgAaqmNGzcaPj4+xv/+7/8au3btMt58800jMDDQeOONN9x1nn32WSMkJMT4+OOPjR9++MEYPHiwER0dbZw+fboGe151RowYYVx00UXGZ599ZiQnJxsffvih0aRJE+PRRx911zH7nJw8edLYunWrsXXrVkOSMXPmTGPr1q3uJzwrMv7+/fsb3bt3NzZs2GCsXbvWaNu2rTFs2LCaGtJ5O9Oc5OTkGDfccIPRrFkzY9u2bcaRI0fcS/Gn0+rSnJSl5FOxhlH35uTDDz80fH19jXnz5hm7du0yXn75ZcNmsxnffPONu417773XaN68ubFixQpj06ZNRmxsrBEbG1tTQzpvZ5uTPn36GJ06dTJWrlxp/Pbbb8Zrr71m+Pv7G//617/cbZhtTv76178awcHBxqpVqzx+X5w6dcpd52xjzsvLMy655BKjX79+xrZt24wlS5YYoaGhxsSJE6u8/wS7Wu7TTz81LrnkEsNutxsdOnQw5s2b57Hd6XQakyZNMsLCwgy73W5ce+21xo4dO2qot1XP4XAYDzzwgNG8eXPD39/faNWqlfH3v//d43/QZp+TlStXGpJKLSNGjDAMo2Lj//33341hw4YZ9evXN4KCgoxRo0YZJ0+erIHRVI4zzUlycnKZ2yQZK1eudLdRl+akLGUFu7o4J/PnzzfatGlj+Pv7G127djUWL17s0cbp06eNv/3tb0bDhg2NwMBA48YbbzSOHDlSzSOpPGebkyNHjhgjR440IiMjDX9/f6N9+/bGjBkzDKfT6W7DbHNS3u+L1157zV2nImPeu3evMWDAACMgIMBo0qSJ8dBDDxm5ublV3n9LwSAAAABwgeMeOwAAAJMg2AEAAJgEwQ4AAMAkCHYAAAAmQbADAAAwCYIdAACASRDsAAAATIJgBwAAYBIEOwBVyjAM3XPPPWrUqJEsFou2bdtW012qtXJyctSmTRutW7eu2o992WWX6YMPPqj24wKoXAQ7AFVqyZIlWrhwoT777DMdOXJEl1xySU13qdZKSkpSdHS0evfurYULF8pisZxx2bt3r6ZOnapu3bqVamvv3r1eBeknn3xSjz/+uPvL3QFcmAh2AKrUnj17FBERod69eys8PFw+Pj6l6uTk5NRAz2oXwzA0e/ZsjR49WpI0dOhQHTlyxL3ExsZq7NixHmVRUVGVdvwBAwbo5MmT+vLLLyutTQDVj2AHoMqMHDlS9913n/bv3y+LxaKWLVtKkvr27avx48drwoQJatKkieLj4yVJ27dv14ABA1S/fn2FhYXprrvu0vHjx93tZWZmavjw4apfv74iIiI0Y8YM9e3bVxMmTHDXsVgsWrx4sUc/QkJCtHDhQvf6gQMHdNtttykkJESNGjXS4MGDtXfvXo9+DxkyRM8//7wiIiLUuHFjjRs3Trm5ue462dnZeuyxxxQVFSW73a42bdpo/vz5MgxDbdq00fPPP+/Rh23btslisWj37t1lztXmzZu1Z88eDRw4UJIUEBCg8PBw9+Ln56fAwECPMpvNVtEfhUaOHFnmWb9Vq1ZJkmw2m66//nq98847FW4TQO1DsANQZV588UU9/fTTatasmY4cOaL//ve/7m2LFi2Sn5+fvv32WyUlJSktLU3XXHONunfvrk2bNmnJkiVKTU3Vbbfd5t7nkUce0erVq/Xxxx/rq6++0qpVq7Rlyxav+pSbm6v4+Hg1aNBA33zzjb799lvVr19f/fv39zhzuHLlSu3Zs0crV67UokWLtHDhQo9wOHz4cL399tt66aWX9Msvv+jf//636tevL4vForvvvluvvfaax3Ffe+01XXXVVWrTpk2Z/frmm2/Url07NWjQwKvxVNSLL77ocbbvgQceUNOmTdWhQwd3nV69eumbb76pkuMDqB6lr4kAQCUJDg5WgwYNZLPZFB4e7rGtbdu2eu6559zr06ZNU/fu3fWPf/zDXbZgwQJFRUVp586dioyM1Pz58/XGG2/o2muvleQKh82aNfOqT++++66cTqdeffVVWSwWSa7QFRISolWrVqlfv36SpIYNG2r27Nmy2Wzq0KGDBg4cqOXLl2vs2LHauXOn3nvvPS1btkxxcXGSpFatWrmPMXLkSE2ePFkbN25Ur169lJubq7feeqvUWbzi9u3bp8jISK/GUujHH39U/fr1PcoMw/BYDw4OVnBwsCTpww8/1L///W99/fXXHj+XyMhIHThwQE6nU1Yrf/cDFyKCHYAa0aNHD4/177//XitXriwVUCTXfXqnT59WTk6OYmJi3OWNGjVS+/btvTru999/r927d5c6M5aVlaU9e/a41zt16uRxqTMiIkI//vijJNdlVZvNpj59+pR5jMjISA0cOFALFixQr1699Omnnyo7O1u33npruf06ffq0/P39vRpLofbt2+uTTz7xKDt06JD69u1bqu7WrVt11113afbs2br88ss9tgUEBMjpdCo7O1sBAQHn1BcANYtgB6BG1KtXz2M9IyNDgwYN0vTp00vVjYiIKPfetJIsFkups1XF743LyMhQjx499Oabb5baNzQ01P3e19e3VLuFT4xWJPSMGTNGd911l1544QW99tprGjp0qAIDA8ut36RJE3dw9Jafn1+pS7xlPaSSkpKiG264QWPGjHE/pFHcH3/8oXr16hHqgAsYwQ5ArfCnP/1JH3zwgVq2bFlmKGndurV8fX21YcMGNW/eXJJ04sQJ7dy50+PMWWhoqI4cOeJe37Vrl06dOuVxnHfffVdNmzZVUFDQOfW1c+fOcjqdWr16tftSbEnXX3+96tWrp7lz52rJkiVas2bNGdvs3r275s6dK8Mw3JeIK1NWVpYGDx6sDh06aObMmWXW2b59u7p3717pxwZQfbiJAkCtMG7cOP3xxx8aNmyY/vvf/2rPnj1aunSpRo0apfz8fNWvX1+jR4/WI488ohUrVmj79u0aOXJkqXvBrrnmGs2ePVtbt27Vpk2bdO+993qcfbvjjjvUpEkTDR48WN98842Sk5O1atUq3X///Tp48GCF+tqyZUuNGDFCd999txYvXuxu47333nPXsdlsGjlypCZOnKi2bdsqNjb2jG1effXVysjI0E8//eTFrFXc//zP/+jAgQN66aWXdOzYMaWkpCglJcXjgZFvvvnGfY8hgAsTwQ5ArRAZGalvv/1W+fn56tevnzp37qwJEyYoJCTEHd7++c9/6sorr9SgQYMUFxenK664otS9ejNmzFBUVJSuvPJK/eUvf9HDDz/scQk0MDBQa9asUfPmzXXTTTfp4osv1ujRo5WVleXVGby5c+fqlltu0d/+9jd16NBBY8eOVWZmpked0aNHKycnR6NGjTpre40bN9aNN95Y5iXiyrB69WodOXJEHTt2VEREhHsp/JaLQ4cOad26dRXqK4Day2KUvBkFAC4gffv2Vbdu3TRr1qya7kop33zzja699lodOHBAYWFhZ63/ww8/6LrrrtOePXvKfIikKj322GM6ceKE5s2bV63HBVC5OGMHAJUsOztbBw8e1NSpU3XrrbdWKNRJUpcuXTR9+nQlJydXcQ9La9q0qZ555plqPy6AykWwA4BK9vbbb6tFixZKS0vz+Ky+ihg5cqQ6d+5cRT0r30MPPVThAAqg9uJSLAAAgElwxg4AAMAkCHYAAAAmQbADAAAwCYIdAACASRDsAAAATIJgBwAAYBIEOwAAAJMg2AEAAJgEwQ4AAMAk/h+cpKiiEAN3nAAAAABJRU5ErkJggg==",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
-      ]
+      ],
+      "image/png": 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"
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     }
    ],
-   "source": [
-    "freqs_hz = 1e12 * np.linspace(50, 200, 1001)\n",
-    "print(f\"complex relative permittivity at freqs_hz = \\n\\t {lossy_dielectric.eps_model(freqs_hz)}\\n\")\n",
-    "\n",
-    "ax = lossy_dielectric_from_nk.plot(freqs_hz)"
-   ]
+   "execution_count": 11
   },
   {
    "cell_type": "markdown",
@@ -569,11 +645,40 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
    "id": "15b8d749",
    "metadata": {
-    "tags": []
+    "tags": [],
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:07:20.434169Z",
+     "start_time": "2025-10-29T14:07:20.360363Z"
+    }
    },
+   "source": [
+    "s1 = td.Sphere(radius=1, center=(0, 0, 0))\n",
+    "s2 = td.Box(center=(1, 1, 1), size=(1, 1, 1))\n",
+    "\n",
+    "# do two geometric objects intersect?\n",
+    "print(s1.intersects(s2))\n",
+    "\n",
+    "# does the object intersect a plane?\n",
+    "print(s1.intersects_plane(z=10))\n",
+    "\n",
+    "# get polygons that intersect sphere at plane x=0\n",
+    "print(s1.intersects_plane(x=0))\n",
+    "\n",
+    "# get bounds (rmin, rmax) of geometry\n",
+    "print(s1.bounds)\n",
+    "\n",
+    "# get td.Box() for bounding box of geometry\n",
+    "print(s1.bounding_box.help())\n",
+    "\n",
+    "# evaluate whether point(s) are inside of geometry\n",
+    "print(s1.inside(x=0, y=1, z=1))\n",
+    "print(s1.inside(x=np.linspace(-1, 1, 5), y=np.zeros(5), z=np.ones(5)))\n",
+    "\n",
+    "# plot the geometry at a cross sectional plane\n",
+    "ax = s1.plot(y=0)"
+   ],
    "outputs": [
     {
      "name": "stdout",
@@ -587,10 +692,40 @@
     },
     {
      "data": {
+      "text/plain": [
+       "\u001B[34m╭─\u001B[0m\u001B[34m───────────────────\u001B[0m\u001B[34m \u001B[0m\u001B[1;34m<\u001B[0m\u001B[1;95mclass\u001B[0m\u001B[39m \u001B[0m\u001B[32m'tidy3d.components.geometry.base.Box'\u001B[0m\u001B[1;34m>\u001B[0m\u001B[34m \u001B[0m\u001B[34m────────────────────\u001B[0m\u001B[34m─╮\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[36mRectangular prism.\u001B[0m                                                                     \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[36m   Also base class for :class:`.Simulation`, :class:`Monitor`, and :class:`Source`.\u001B[0m    \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                                                                        \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m╭────────────────────────────────────────────────────────────────────────────────────╮\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[1;35mBox\u001B[0m\u001B[1m(\u001B[0m\u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m, \u001B[33mtype\u001B[0m=\u001B[32m'Box'\u001B[0m, \u001B[33mcenter\u001B[0m=\u001B[1m(\u001B[0m\u001B[1;36m0.0\u001B[0m, \u001B[1;36m0.0\u001B[0m, \u001B[1;36m0.0\u001B[0m\u001B[1m)\u001B[0m, \u001B[33msize\u001B[0m=\u001B[1m(\u001B[0m\u001B[1;36m2.0\u001B[0m, \u001B[1;36m2.0\u001B[0m, \u001B[1;36m2.0\u001B[0m\u001B[1m)\u001B[0m\u001B[1m)\u001B[0m            \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m╰────────────────────────────────────────────────────────────────────────────────────╯\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                                                                        \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m        \u001B[3;33mattrs\u001B[0m = \u001B[1m{\u001B[0m\u001B[1m}\u001B[0m                                                                      \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[3;33mbounding_box\u001B[0m = \u001B[1;35mBox\u001B[0m\u001B[1m(\u001B[0m\u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m, \u001B[33mtype\u001B[0m=\u001B[32m'Box'\u001B[0m, \u001B[33mcenter\u001B[0m=\u001B[1m(\u001B[0m\u001B[1;36m0.0\u001B[0m, \u001B[1;36m0.0\u001B[0m, \u001B[1;36m0.0\u001B[0m\u001B[1m)\u001B[0m, \u001B[33msize\u001B[0m=\u001B[1m(\u001B[0m\u001B[1;36m2.0\u001B[0m, \u001B[1;36m2.0\u001B[0m, \u001B[1;36m2.0\u001B[0m\u001B[1m)\u001B[0m\u001B[1m)\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m       \u001B[3;33mbounds\u001B[0m = \u001B[1m(\u001B[0m\u001B[1m(\u001B[0m\u001B[1;36m-1.0\u001B[0m, \u001B[1;36m-1.0\u001B[0m, \u001B[1;36m-1.0\u001B[0m\u001B[1m)\u001B[0m, \u001B[1m(\u001B[0m\u001B[1;36m1.0\u001B[0m, \u001B[1;36m1.0\u001B[0m, \u001B[1;36m1.0\u001B[0m\u001B[1m)\u001B[0m\u001B[1m)\u001B[0m                                   \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m       \u001B[3;33mcenter\u001B[0m = \u001B[1m(\u001B[0m\u001B[1;36m0.0\u001B[0m, \u001B[1;36m0.0\u001B[0m, \u001B[1;36m0.0\u001B[0m\u001B[1m)\u001B[0m                                                         \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m     \u001B[3;33mgeometry\u001B[0m = \u001B[1;35mBox\u001B[0m\u001B[1m(\u001B[0m\u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m, \u001B[33mtype\u001B[0m=\u001B[32m'Box'\u001B[0m, \u001B[33mcenter\u001B[0m=\u001B[1m(\u001B[0m\u001B[1;36m0.0\u001B[0m, \u001B[1;36m0.0\u001B[0m, \u001B[1;36m0.0\u001B[0m\u001B[1m)\u001B[0m, \u001B[33msize\u001B[0m=\u001B[1m(\u001B[0m\u001B[1;36m2.0\u001B[0m, \u001B[1;36m2.0\u001B[0m, \u001B[1;36m2.0\u001B[0m\u001B[1m)\u001B[0m\u001B[1m)\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m  \u001B[3;33mplot_params\u001B[0m = \u001B[1;35mPlotParams\u001B[0m\u001B[1m(\u001B[0m                                                             \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                    \u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                           \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                    \u001B[33malpha\u001B[0m=\u001B[1;36m1\u001B[0m\u001B[1;36m.0\u001B[0m,                                                          \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                    \u001B[33mzorder\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                        \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                    \u001B[33mtype\u001B[0m=\u001B[32m'PlotParams'\u001B[0m,                                                  \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                    \u001B[33medgecolor\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                     \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                    \u001B[33mfacecolor\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                     \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                    \u001B[33mfill\u001B[0m=\u001B[3;92mTrue\u001B[0m,                                                          \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                    \u001B[33mhatch\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                         \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                    \u001B[33mlinewidth\u001B[0m=\u001B[1;36m1\u001B[0m\u001B[1;36m.0\u001B[0m                                                       \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                \u001B[1m)\u001B[0m                                                                       \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m         \u001B[3;33msize\u001B[0m = \u001B[1m(\u001B[0m\u001B[1;36m2.0\u001B[0m, \u001B[1;36m2.0\u001B[0m, \u001B[1;36m2.0\u001B[0m\u001B[1m)\u001B[0m                                                         \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m         \u001B[3;33mtype\u001B[0m = \u001B[32m'Box'\u001B[0m                                                                   \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m    \u001B[3;33mzero_dims\u001B[0m = \u001B[1m[\u001B[0m\u001B[1m]\u001B[0m                                                                      \u001B[34m│\u001B[0m\n",
+       "\u001B[34m╰────────────────────────────────────────────────────────────────────────────────────────╯\u001B[0m\n"
+      ],
       "text/html": [
        "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #000080; text-decoration-color: #000080\">╭──────────────────── </span><span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">&lt;</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff; font-weight: bold\">class</span><span style=\"color: #000000; text-decoration-color: #000000\"> </span><span style=\"color: #008000; text-decoration-color: #008000\">'tidy3d.components.geometry.base.Box'</span><span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">&gt;</span><span style=\"color: #000080; text-decoration-color: #000080\"> ─────────────────────╮</span>\n",
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">Rectangular prism.</span>                                                                     <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
-       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">   Also base class for :class:`Simulation`, :class:`Monitor`, and :class:`Source`.</span>     <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
+       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">   Also base class for :class:`.Simulation`, :class:`Monitor`, and :class:`Source`.</span>    <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>                                                                                        <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span> <span style=\"color: #008000; text-decoration-color: #008000\">╭────────────────────────────────────────────────────────────────────────────────────╮</span> <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span> <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">Box</span><span style=\"font-weight: bold\">(</span><span style=\"color: #808000; text-decoration-color: #808000\">attrs</span>=<span style=\"font-weight: bold\">{}</span>, <span style=\"color: #808000; text-decoration-color: #808000\">type</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'Box'</span>, <span style=\"color: #808000; text-decoration-color: #808000\">center</span>=<span style=\"font-weight: bold\">(</span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.0</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.0</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.0</span><span style=\"font-weight: bold\">)</span>, <span style=\"color: #808000; text-decoration-color: #808000\">size</span>=<span style=\"font-weight: bold\">(</span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2.0</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2.0</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2.0</span><span style=\"font-weight: bold\">))</span>            <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
@@ -617,40 +752,13 @@
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>    <span style=\"color: #808000; text-decoration-color: #808000; font-style: italic\">zero_dims</span> = <span style=\"font-weight: bold\">[]</span>                                                                      <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
        "<span style=\"color: #000080; text-decoration-color: #000080\">╰────────────────────────────────────────────────────────────────────────────────────────╯</span>\n",
        "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[34m╭─\u001b[0m\u001b[34m───────────────────\u001b[0m\u001b[34m \u001b[0m\u001b[1;34m<\u001b[0m\u001b[1;95mclass\u001b[0m\u001b[39m \u001b[0m\u001b[32m'tidy3d.components.geometry.base.Box'\u001b[0m\u001b[1;34m>\u001b[0m\u001b[34m \u001b[0m\u001b[34m────────────────────\u001b[0m\u001b[34m─╮\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[36mRectangular prism.\u001b[0m                                                                     \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[36m   Also base class for :class:`Simulation`, :class:`Monitor`, and :class:`Source`.\u001b[0m     \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                                                                        \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m╭────────────────────────────────────────────────────────────────────────────────────╮\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[1;35mBox\u001b[0m\u001b[1m(\u001b[0m\u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m, \u001b[33mtype\u001b[0m=\u001b[32m'Box'\u001b[0m, \u001b[33mcenter\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m\u001b[1m)\u001b[0m, \u001b[33msize\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m2.0\u001b[0m, \u001b[1;36m2.0\u001b[0m, \u001b[1;36m2.0\u001b[0m\u001b[1m)\u001b[0m\u001b[1m)\u001b[0m            \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m╰────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                                                                        \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m        \u001b[3;33mattrs\u001b[0m = \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m                                                                      \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[3;33mbounding_box\u001b[0m = \u001b[1;35mBox\u001b[0m\u001b[1m(\u001b[0m\u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m, \u001b[33mtype\u001b[0m=\u001b[32m'Box'\u001b[0m, \u001b[33mcenter\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m\u001b[1m)\u001b[0m, \u001b[33msize\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m2.0\u001b[0m, \u001b[1;36m2.0\u001b[0m, \u001b[1;36m2.0\u001b[0m\u001b[1m)\u001b[0m\u001b[1m)\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m       \u001b[3;33mbounds\u001b[0m = \u001b[1m(\u001b[0m\u001b[1m(\u001b[0m\u001b[1;36m-1.0\u001b[0m, \u001b[1;36m-1.0\u001b[0m, \u001b[1;36m-1.0\u001b[0m\u001b[1m)\u001b[0m, \u001b[1m(\u001b[0m\u001b[1;36m1.0\u001b[0m, \u001b[1;36m1.0\u001b[0m, \u001b[1;36m1.0\u001b[0m\u001b[1m)\u001b[0m\u001b[1m)\u001b[0m                                   \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m       \u001b[3;33mcenter\u001b[0m = \u001b[1m(\u001b[0m\u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m\u001b[1m)\u001b[0m                                                         \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m     \u001b[3;33mgeometry\u001b[0m = \u001b[1;35mBox\u001b[0m\u001b[1m(\u001b[0m\u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m, \u001b[33mtype\u001b[0m=\u001b[32m'Box'\u001b[0m, \u001b[33mcenter\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m\u001b[1m)\u001b[0m, \u001b[33msize\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m2.0\u001b[0m, \u001b[1;36m2.0\u001b[0m, \u001b[1;36m2.0\u001b[0m\u001b[1m)\u001b[0m\u001b[1m)\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m  \u001b[3;33mplot_params\u001b[0m = \u001b[1;35mPlotParams\u001b[0m\u001b[1m(\u001b[0m                                                             \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                    \u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                           \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                    \u001b[33malpha\u001b[0m=\u001b[1;36m1\u001b[0m\u001b[1;36m.0\u001b[0m,                                                          \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                    \u001b[33mzorder\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                        \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                    \u001b[33mtype\u001b[0m=\u001b[32m'PlotParams'\u001b[0m,                                                  \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                    \u001b[33medgecolor\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                     \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                    \u001b[33mfacecolor\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                     \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                    \u001b[33mfill\u001b[0m=\u001b[3;92mTrue\u001b[0m,                                                          \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                    \u001b[33mhatch\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                         \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                    \u001b[33mlinewidth\u001b[0m=\u001b[1;36m1\u001b[0m\u001b[1;36m.0\u001b[0m                                                       \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                \u001b[1m)\u001b[0m                                                                       \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m         \u001b[3;33msize\u001b[0m = \u001b[1m(\u001b[0m\u001b[1;36m2.0\u001b[0m, \u001b[1;36m2.0\u001b[0m, \u001b[1;36m2.0\u001b[0m\u001b[1m)\u001b[0m                                                         \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m         \u001b[3;33mtype\u001b[0m = \u001b[32m'Box'\u001b[0m                                                                   \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m    \u001b[3;33mzero_dims\u001b[0m = \u001b[1m[\u001b[0m\u001b[1m]\u001b[0m                                                                      \u001b[34m│\u001b[0m\n",
-       "\u001b[34m╰────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "name": "stdout",
@@ -663,41 +771,19 @@
     },
     {
      "data": {
-      "image/png": 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EBgbe8qINf3W1hP/zn/9Uafzb8eWXX4omTZoItVotYmNjxUcffVTpVCQhblymJpNJvPzyyyI8PFxoNBrRvn17sWbNmuu+z9atW0WnTp2EVqsVoaGh4tlnnxVGo7HaPw85h0yIW2wrIyJycR9//DFefPFFnD17FnXr1pU6DnkhlikRuTUhBFq1aoVatWrd8mAwImfhqTFE5JZKSkrw66+/YvPmzTh8+DCWL18udSTyYlwzJSK3dPbsWdSvXx+BgYF45pln8Pbbb0sdibwYy5SIiMhBPM+UiIjIQSxTIiIiB/EApFuw2Wy4ePEi/P397+jOHERE5J6EECgqKkJkZORNb2gBsExv6eLFiy5zoXEiIqp558+fR1RU1E3HYZnegr+/P4ArM1Ov10uchoiIaorRaER0dLS9B26GZXoLVzft6vV6likRkReqyi4+HoBERETkIJYpERGRg1imREREDmKZEhEROYhlSkRE5CCWKRERkYNYpkRERA5imRIRETmIZUpEROQglikREZGDWKZEREQOYpkSERE5iGVKRETkIJYpERGRg1imREREDmKZEhEROYhlSkRE5CCWKRERkYNYpkRERA5imRIRETmIZUpEROQglikREZGDWKZEREQOYpkSERE5iGVKRETkIJYpERGRg1imREREDmKZEhEROYhlSkRE5CCWKRERkYNYpkRERA5imRIRETmIZUpEROQglikREZGDWKZEREQOYpkSERE5iGVKRETkILcq0y1btuDee+9FZGQkZDIZli1bdstpUlJS0KZNG2g0GjRs2BDz5893ek4iIvIublWmJSUlaNWqFWbPnl2l8dPT0zFgwAD07NkTBw8exLhx4/DEE09g7dq1Tk5KRETeRCl1gNvRr18/9OvXr8rjz5kzB/Xr18eHH34IAGjatCn++OMPfPTRR+jbt6+zYhIRkZdxqzXT27Vjxw4kJSVVGta3b1/s2LFDokRE7kMIAZvNBpvNBiGE1HGIXJpbrZnerqysLISFhVUaFhYWBqPRCJPJBJ1Od800ZrMZZrPZ/rPRaHR6TiJnEEIgLy8PmZmZuHjxIrKyspCTk4OcnBxcvnwZ+fn5uJyfD4PRgOLiYpSWlPzv798Cq9UKm9Va6fXkcjkUCgVUajW0Wg20Oh38/PwQoNejVnAtBAcHo1atWggJCUFYWBjCw8MRERGBOnXqIDw8HAqFQqI5QeR8Hl2md2L69OmYOnWq1DGIqsRms+HcuXNITU3FiRMnkJaWhlNpaUg7nYbz587D8pcvhgCg8tFAoVMDGjlsKhnkaiVkagVkQXLIQnWQKX2hVcgAuQyQySCTXZlOiP/9wyYgrAJmqw3mChsKygtxrvAyRE4aZOUCsFhhM5WjvMRcaW1WoVQgsk4dNKjfAI0bNULDhg3RuHFjxMXFITY2FiqVqgbnGlH18+gyDQ8PR3Z2dqVh2dnZ0Ov1110rBYCJEydi/Pjx9p+NRiOio6OdmpOoKkpKSnDw4EHs378ff/75J/YfOIDU1OMwlZoAAHKlAupAHwhfJRT+GqjbhEHnp4HCTw25jwpynQoyRc3s2RE2AVtZBWylFtiKLbCWWHC5yIycc4ew69h+VBhMqDCXAwCUSiViGzVE29Zt0KpVK7Ru3Rpt2rRBrVq1aiQrUXXw6DJNTEzE6tWrKw1bv349EhMTbziNRqOBRqNxdjSimxJCIDU1Fdu3b8f27duxbcd2nDpxEjabDXKFAupavkCgGsqWoQgM0kEZqIXcXwPZ1VVJicnkMih8VFD4qIAQ32ueF0LAVloOa6EJFQUmnCvIR8bmVVj4y2JY/1ey0TF10emuRHTq1AmdOnVCq1atuAZLLsutyrS4uBhpaWn2n9PT03Hw4EEEBwejbt26mDhxIi5cuIBvvvkGAPDUU09h1qxZeOWVV/D4449j06ZNWLRoEVatWiXVRyC6LiEEjhw5gk2bNmHT5s34fcvvMBQUQiaTQRPiB1mIDr5dYqAK9YUySFdja5jOIpPJoPBVQ+GrhrpOgH24EAJWQxnKc0twObcEy7esweJffoatwgqtTovExE7o3asXevbsiQ4dOkCpdKtFGHkwmXCjw/RSUlLQs2fPa4aPHDkS8+fPx2OPPYazZ88iJSWl0jQvvvgijh07hqioKLzxxht47LHHqvyeRqMRAQEBMBgM0Ov11fApiK7Iy8vD2rVrsWbNGqxZuxZ5ublX1jrD/aEI84Uqwh+q2n6Qq737wB1htaE8twTlWUWoyCpGRXYxKsrK4ePri969e6HfPVdOmatXr57UUcnD3M7y363KVAosU6pOqampWLZsGZYsW4q9u/dACAFtqD/kkX5QRwVAHe4PmdK91zqdTdgEynOLYblghPVCEcxZRgibQJO4Jrg/+X4kJyejffv2kMs5H8kxLNNqxDIlRwghcPjwYSxevBg/LVyItFOnoFAroaqjh7puANTRgVD4qqWO6dZs5gpYLhhgziiENbMI5aVm1A4Lw9AhQzB06FB06dKFp+XQHWGZViOWKd2J9PR0fP/99/jm229x6uRJKLVqKOvqoakfDE1UANc+nUTYBMqzimBOL0DFOQMsRhNqh4dh+EMPY/jw4WjTpo3LHKRFro9lWo1YplRVRUVFWLx4Mb6e+zW2b9t+ZQ00JhDa2GCoowLc/qAhdyOEQHl2McpOX0ZFugHlJWVo3KQJnhg9Go888ggiIiKkjkgujmVajVimdDNCCOzevRtffPEFflr4E0wmE7RRgVA3qgVtvSDIVNy86AqETcCSaUDZqTxYzhYCQmBA/wF48skncc8993AzMF0Xy7QasUzpekpLS/Hjjz/i408/weE/D0Gt94GqcTB0TUKg8ON5yq7MZq5AWdplWE5chjm3CHWio/DcM8/iiSeeQEhIiNTxyIWwTKsRy5T+KjMzE7NmzcKcL+bAYDBAWzcI2ma1r2zGlXNfnDsRQqAitwSlR7NhOVMAhVyB4Q8/jPHjxyM+Pl7qeOQCWKbViGVKAHDo0CG89957+OmnnyBTyqFuXAu6FmFQ6rVSR6NqYDOVw5SaA0vqZViMJvROSsJrr76K3r1784AlL8YyrUYsU++2fft2THvrLaxdswZqvQ/UzUOgi6vt9RdS8FTCakPZmXyYj+TAnFOEVq0TMHnSG0hOTuZ5q17odpb//Osguo4tW7age4/u6Ny5M1L2/AF9zwYI/Edz+LaMYJF6MJlCDl2jEAQkN0XggDicyEnH4MGD0bR5MyxcuBA2m03qiOSiWKZEf7Fjxw706NkD3bt3x65jBxBwdyMEDG4GXeNQntriRWQyGTRRAQgYGIegQc1wrjQHw4YNQ7MWzfHLL7/wZul0DS4diAAcOXIEAwcORKdOnbDzyD4E9GmEgPubQtsgmPvMvJw63B8B/RojKLkZMoqzMGTIELRp1xYbNmyQOhq5EJYpebULFy5g1KhRaNmyJdZv2wx971gEPNAM2vosUapMHeaPgP5NEHRvUxy/eBp33303ku6+G3/++afU0cgFsEzJK5WWlmLq1Klo2Kghvl/0I/w61UXgkObQNQxhidJNqSP1CLgvDgF9GuGPfTvQunVrPPHEE8jOzpY6GkmIZUpeRQiBRYsWoWHjRpj277cgbxyEwH+0gE+LcO4TpSqTyWTQ1g9GwOBm8OtUFwt++BYNYmPx4Ycfory8XOp4JAEuPchrpKamolfv3njwwQdRoCpD0JAW8L+rLuQa3mCa7oxMIYdPi3AE/aMFRIwvJkyYgObxLbB582apo1ENY5mSxysrK8OkSZMQHx+PHQd2IbBfEwT0bQRlAC+4QNVDrlVB37U+gh5ojvPGLPTq1QuPPPoIcnNzpY5GNYRlSh4tJSUFzVo0x/R334GmZRgCBjeHpm6g1LHIQ6lCfKG/Nw767vWx6JfFaNS4Eb755hueSuMFWKbkkYxGI5588kn07NkTl0yXEfRAc/i1j+J9RMnpZDIZdHG1ETi0BcwhKowcORJ9+vbFuXPnpI5GTsQlC3mcTZs2oWnzZvh6/lz4d6kH/cAmUAbppI5FXkauUyGgdywC72mMLTv/QNNmzTB37lyupXoolil5DJPJhOeffx69e/dGvihG0ODm8GkexlNdSFKamCAEDG4GEeWD0aNHY+DAgTyNxgOxTMkjHDx4EAltWmP255/Bv1MM9AOaQME7upCLkGuU0PdogIC+jbH+941o1rwZVq5cKXUsqkYsU3JrQgh8/PHH6NChAzIuX0DQ/c3gEx/OtVFySdp6QQgc3Byl/gL33nsvnnvuOZSVlUkdi6oBy5TcVn5+Pu677z6MGzcOqia1EHBfUyiDfaSORXRTcp0K+j6N4N85Bp9/MQftOrTHqVOnpI5FDmKZklvas2cPWia0wtqN6xDYtzH8O8fwSF1yGzKZDD4twhGY3BRpmelIaN0aixcvljoWOYBLH3IrQgjMmTMHnTp1Ql65EQH3N4OmXpDUsYjuiKqWL/TJTWGL0OIf//gHxo0bx8sRuimWKbmNsrIyjB49Gk8//TRUjYMRMLAJFP4aqWMROUSuVkDfKxb+nWPwyaefomevnsjJyZE6Ft0mlim5hYsXL6Jrt65Y8O030PdsAH3X+rwwPXkM+2bfgXHYfWAfEtq0xoEDB6SORbeBSyNyeXv37kXrtm1wKPUoAu+Lg65xqNSRiJxCHeGPgOQ4FFQUI7FTIn7++WepI1EVsUzJpS1ZsgRdunaBQZigHxQHVaif1JGInErhp4F+YBPIovwwdOhQ/Oc//+FVk9wAy5RckhACH374IYYMGQJZHb8r+0d91VLHIqoRMqUc+l6x8G1TB6+//jpGjx7NA5NcHG/kSC7HarXixRdfxKeffgqfhAj4dYjmRRjI68hkMvi1j4IiQIP5CxbgfGYmlvzyC/z9/aWORtfBNVNyKWazGQ8OG4ZZs2bBv2s9+HesyyIlr6ZrHIqAfo2RsiUFXbt345G+LoplSi6jqKgI9/Trh6XLlkJ/d0P4NAuTOhKRS9BEBUA/sAmOnUrFXZ0SkZGRIXUk+huWKbmE/Px89OrdC39s/wMB/RpDWz9Y6khELuXKjceb4MLlLHRMvAupqalSR6K/YJmS5HJyctC1ezf8efQw9AOaQB2plzoSkUtS6rXQD2yCQksxOnfpjEOHDkkdif6HZUqSysrKQpduXXHq7GnoBzaGKtRX6khELk3hq4Z+YGOUKMrRrXs37N+/X+pIBJYpSejSpUvo0q0rMi6eh35AYyiDeMcXoqqQa1XQ92+MMo1Aj549sW/fPqkjeT2WKUkiOzsb3Xp0x/msC/Af0BjKQJ3UkYjcilyjhL5fI5T7AL169+LlByXGMqUal5eXh569eiLj4vkrRRqglToSkVuSa5Twv6cRzNorhXrkyBGpI3ktlinVKIPBgKQ+dyMt4wz0/VmkRI66uoZqUlrRs1dP3mhcIixTqjEmkwkDBg7A0ePH4N+vEZRB3LRLVB2uFmqR1YQevXoiMzNT6kheh2VKNaKiogJDhw7Fzt274N+3IVS1eNQuUXWS61Tw79cIecZ89L47Cfn5+VJH8iosU3I6IQTGjh2L1b/9Bv/esVCH89qiRM6g8NPAv18jpJ87i379+8FkMkkdyWuwTMnp3nzzTcybNw/+3etBUzdQ6jhEHk0ZqIN/34bYd2A/hg0bBqvVKnUkr8AyJaeaP38+pk2bBr8OUbypN1ENUdX2g3+vBlixYgVefPFFqeN4BZYpOU1KSgrGjBkDXVwofBIipY5D5FU0MUHw6xyDTz/9FLNnz5Y6jsdjmZJTpKWlYVDyICjD/eDfpR5vo0YkAZ/mYfBpEY7nn38e69atkzqOR2OZUrUzGo3oP3AAzHIr/JNiIVPwz4xIKn6JdaGOCsCQoUNw8uRJqeN4LC7lqFrZbDY8/PDDSM84C78+sZBrlFJHIvJqMrkM/r0awKK0YcC9A2E0GqWO5JFYplStpk2bhlWrV8OvZ31eb5fIRcg1SvjdHYuzGWfxyCOPwGazSR3J47BMqdqsXr0aU6dOhW+7OjwFhsjFKAN18OtZHytWrMC7774rdRyPwzKlapGRkYGHHn4I2pgg+LbmkbtErkgTEwTfNpF4fdIkbN68Weo4HoVlSg6zWCwYMnQIylAO/x4NeOQukQvzbRsFTaQe/3jwH8jKypI6jsdgmZLDJk6ciP3798OvVwPItTzgiMiVyeQy+PVsAIOpGA89/DD3n1YTlik5ZM2aNZgxYwZ8OkRBVdtP6jhEVAUKHxV8u9dDSkoK3nvvPanjeASWKd2xnJwcPPLoI9DWDYJPfLjUcYjoNmiiAuDTKhyTJk3Cnj17pI7j9limdEeEEHj88cdhNBXDr3t97iclckN+7aKgDPHFgw8NQ0lJidRx3BrLlO7I3LlzsWrVKvh0iYHCRyV1HCK6AzKFHH496uHcuXOYMGGC1HHcGsuUbtvZs2fx/AvPQxcXCm29IKnjEJEDlIE6+HSog88//xwbNmyQOo7bYpnSbRFCYNTjj6NCIeB3V12p4xBRNdA1D4M2KhAjHhvJyw3eIZYp3Zb//ve/SNm8GT5d6vK6u0QeQiaTwa9rDHJyc/Dqq69KHcctsUypyi5evIgXx4+HrkkoNNGBUschomqk0Gvh074O5syZg61bt0odx+2wTKnKnvvnc7CIcm7eJfJQuuZh0EToMWr04zCbzVLHcStuV6azZ89GvXr1oNVq0bFjR+zevfuG486fPx8ymazSQ6vV1mBaz7Fy5UosXbIUPndF8ypHRB5KJpPBr0sMzpw+w4s53Ca3KtOFCxdi/PjxmDJlCvbv349WrVqhb9++yMnJueE0er0ely5dsj8yMjJqMLFnKC0txdPPPgNtdBA0scFSxyEiJ1IG+0DXMgxv/fvfOH36tNRx3IZblemMGTMwZswYjBo1Cs2aNcOcOXPg4+ODuXPn3nAamUyG8PBw+yMsLKwGE3uGd955BxcvXoRv57q8OAORF/BrUwcyrQL/fP6fUkdxG25TphaLBfv27UNSUpJ9mFwuR1JSEnbs2HHD6YqLixETE4Po6GgMGjQIR48erYm4HuPMmTN45913oYsPgzKAm8iJvIFMpYCuYxR+W/0bVq1aJXUct+A2ZZqXlwer1XrNmmVYWNgNbyPUpEkTzJ07F8uXL8d3330Hm82GTp06ITMz84bvYzabYTQaKz282fiXxkOmVfAepUReRlM/CNqoQPzzhedhsVikjuPy3KZM70RiYiJGjBiBhIQEdO/eHUuWLEFoaCi++OKLG04zffp0BAQE2B/R0dE1mNi1pKSkYPmy5dC2i4RMpZA6DhHVIJlMBt/EaJw9k47Zs2dLHcfluU2ZhoSEQKFQIDs7u9Lw7OxshIdX7Y4lKpUKrVu3Rlpa2g3HmThxIgwGg/1x/vx5h3K7K5vNhufHvQBtuB7ahrWkjkNEElAG+0AbF4opb76J/Px8qeO4NLcpU7VajbZt22Ljxo32YTabDRs3bkRiYmKVXsNqteLw4cOIiIi44TgajQZ6vb7Swxv98MMPOPznIeg6RPGgIyIv5tsuCqVmE/79739LHcWluU2ZAsD48ePx1VdfYcGCBTh+/DiefvpplJSUYNSoUQCAESNGYOLEifbxp02bhnXr1uHMmTPYv38/HnnkEWRkZOCJJ56Q6iO4BbPZjNf+NRHa+sFQR/hLHYeIJKTwUUEbH4ZZs2bh3LlzUsdxWW519v2DDz6I3NxcTJ48GVlZWUhISMCaNWvsByWdO3cOcvn/fz8oKCjAmDFjkJWVhaCgILRt2xbbt29Hs2bNpPoIbuHLL7/ExcwLCB4aL3UUInIBPi3DYTmehylTpmDevHlSx3FJMiGEkDqEKzMajQgICIDBYPCKTb4lJSWIqV8PpcEy6Hs0kDoOEbmI0iNZKN5xHseOHkVcXJzUcWrE7Sz/3WozLznfZ599hvzL+fBtW0fqKETkQnRNa0Plp8HUqVOljuKSWKZkV1JSgnfefQfaJiFQ+GukjkNELkSmkEPTKgwLFy7E8ePHpY7jclimZDdnzhwUFBTyAg1EdF26JqFQ+Wkx7a1pUkdxOSxTAgCUlZXhnffehaZRLa6VEtF1yRRyaFrWxqKFi256vr43YpkSgCu3q7ucm8e1UiK6KV1cbSh0at6i7W9YpgSr1XplrbRBMC9mT0Q3JVPKoWkegvkLFtzwuujeiGVKWLZsGTLSz8KnVdUuy0hE3k3XLAw2mcCsWbOkjuIyWKaE9z94H9o6gVCF+kkdhYjcgFyjhKZxLcyaPQulpaVSx3EJLFMvt3v3buzauQua5qFSRyEiN6JrEQaDwYBvv/1W6igugWXq5T7++GOoA32giQmSOgoRuRGlXgttvWB8NHMmeCE9lqlXy8nJwaLFi6GOC4FMzjvDENHt0TarjROpqfj999+ljiI5lqkXmzt3LgRs0DUJkToKEbkhdR09NMF+mMWbh7NMvZXNZsNnn38OVf0gyLUqqeMQkRuSyWRQNQnGsmVLkZ2dLXUcSbFMvdSmTZtw/tw56JrWljoKEbkxXeNQCAALFiyQOoqkWKZe6r///S80wX5QhfF0GCK6c3KtEup6gfjyq6+8+kAklqkXKiwsxJKlS6FqFASZjAceEZFjtE1CcTotDTt37pQ6imRYpl5o0aJFqCgvh7YRDzwiIsep6+ih1uswf/58qaNIhmXqheYvmA9NdCAUvmqpoxCRB5DJZFA2CMJPC3+C2WyWOo4kWKZeJiMjAzu274A6NljqKETkQXSNasFoMGLNmjVSR5EEy9TLLFy4EAqVEpr6vOIREVUfZbAPtKH++PHHH6WOIgmWqZf5/scfoIrWQ65SSB2FiDyMsl4Alv+63Csvfs8y9SLp6ek4dPBPaBpwEy8RVT9NbC2Umcq8clMvy9SLLFmyBAqVAuq6gVJHISIPpAzQQhvqj59//lnqKDWOZepFflnyC1SR3MRLRM6jqKvHipUrYLFYpI5So1imXiI3Nxc7d+yEul6g1FGIyINp6gWhuKgYW7ZskTpKjWKZeonVq1dDCAF1XR7FS0TOo6zlA7Veh5UrV0odpUaxTL3EypUroQ3TQ+HDO8QQkfPIZDIo6vhj+a/LpY5So1imXqCiogJr162FIspf6ihE5AXUdQNwNv0s0tLSpI5SY1imXmDPnj0oMhZBHR0gdRQi8gLqyADI5HKsW7dO6ig1hmXqBTZs2AClVg1VKG+3RkTOJ1croAn3x1qWKXmStevWQhnuB5mct1sjopqhiPDD5s2bYLVapY5SI1imHs5kMmH3rt1QRXJ/KRHVHHUdPYqMRTh48KDUUWoEy9TD7dy5E+Xl5VBF6qWOQkReRFXbD3KVAr///rvUUWoEy9TD/fHHH1Bq1VAG66SOQkReRKaQQ13bH797ycUbWKYebsuWLVDW9oVMxv2lRFSzFGE++GPbHxBCSB3F6VimHsxms2HHzp1QhPlKHYWIvJAqzB/5eZdx5swZqaM4HcvUg6WmpqKkuBiq2jwlhohq3tVlz86dOyVO4nwsUw+2e/duQAaoQrlmSkQ1T65VQhPke2VZ5OFYph5s79690Ab7Qa5RSh2FiLyUrJYWO3fvkjqG07FMPdjuvXuAII3UMYjIiylDfHHozz89/uINLFMPZbPZcOTwYShDuImXiKSjrOWDMlOZx1/0nmXqoU6fPg1TqYnnlxKRpFS1fAAAf/75p8RJnItl6qGOHDkCAFAG+0ichIi8mVyngtpPZ18meSqWqYc6evQoVD4ayHkzcCKSmDxQwzIl93T8+HEoArS88hERSU4WqMHhoyxTckNHjh4BAtRSxyAigjJAi7Nn0lFRUSF1FKdhmXogIQTS0k5DGaCVOgoRERSBOlRUVCAjI0PqKE7DMvVAubm5KC0pgULPMiUi6Sn1V8539+TTY1imHujqRaUVAbxgAxFJT+6ngUwu9+gL3rNMPdDZs2cBAAo/likRSU8ml0Gt13EzL7mXc+fOQalV8Zq8ROQyZL5K+xd9T8Qy9UDnz5+H0o/7S4nIhfgocfYc10zJjVy4cAFCp5A6BhGRndxXjczMTKljOA3L1AOdzzwPmY6beInIdSh81MjJzoEQQuooTsEy9UCXsrJ4GUEicilynQrlFguMRqPUUZyCZeqB8i9fhlzHMiUi13H1C35OTo7ESZyDZephysrKYCo1Qa7lZl4ich1Xl0l5eXkSJ3EOlqmHyc/PBwCeFkNELkX2v2XS1WWUp2GZepjCwkIA//+HS0TkCq5+wS8oKJA4iXOwTD2MwWAAAMjVPDWGiFyIQga5Qm5fRnkalqmHKSoqAgDIVCxTInIdMpkMCo3KvozyNCxTD1NcXAwAkKn4qyUi1yJXKVBSUiJ1DKfgEtfDmEwmAIBMwV8tEbkWmVJuX0Z5Grdb4s6ePRv16tWDVqtFx44dsXv37puOv3jxYsTFxUGr1SI+Ph6rV6+uoaTSKCsru/IfSrf71RKRh5PJ5f+/jPIwbrXEXbhwIcaPH48pU6Zg//79aNWqFfr27XvDk4C3b9+Ohx56CKNHj8aBAweQnJyM5ORkHDlypIaT1xyLxQKZXAaZTCZ1FCKiyhQyWCwWqVM4xR2Vaa9evTB16tRrhhcUFKBXr14Oh7qRGTNmYMyYMRg1ahSaNWuGOXPmwMfHB3Pnzr3u+B9//DHuueceTJgwAU2bNsVbb72FNm3aYNasWU7LKLXy8nJu4iUi1yQDKioqpE7hFHe01E1JScGsWbOQnJxcaWeyxWLB77//Xm3h/spisWDfvn1ISkqyD5PL5UhKSsKOHTuuO82OHTsqjQ8Affv2veH4nsBms3GtlIhck0wGq9UqdQqnuONVmA0bNiArKwt33XVXjdzwNS8vD1arFWFhYZWGh4WFISsr67rTZGVl3db4AGA2m2E0Gis93A3LlIhckfDgRdMdl2lERAR+//13xMfHo3379khJSanGWNKZPn06AgIC7I/o6GipI902T73FERG5N5kHL5ruqEyvrvloNBr88MMPeOGFF3DPPffgs88+q9ZwfxUSEgKFQoHs7OxKw7OzsxEeHn7dacLDw29rfACYOHEiDAaD/XH+/HnHw9cguVzOMiUi1yQEFArPvKDMHZXp3xfWkyZNwvfff48PP/ywWkJdj1qtRtu2bbFx40b7MJvNho0bNyIxMfG60yQmJlYaHwDWr19/w/GBK18Q9Hp9pYc7USqVEFab1DGIiK4lriyjPNEdfar09HSEhoZWGjZ48GDExcVh79691RLsesaPH4+RI0eiXbt26NChA2bOnImSkhKMGjUKADBixAjUqVMH06dPBwC88MIL6N69Oz788EMMGDAAP/30E/bu3Ysvv/zSaRmlplarIWwCQgjuOyUi12ITUKk8817Ld1SmMTEx1x3evHlzNG/e3KFAN/Pggw8iNzcXkydPRlZWFhISErBmzRr7QUbnzp2DXP7/K9udOnXCDz/8gEmTJuFf//oXGjVqhGXLlqFFixZOyyg1rVZ75T+sAlCyTInIdQir7f+XUR7G7da3n3vuOTz33HPXfe56B0ENHToUQ4cOdXIq1+Hj4wMAEBU2yHgVJCJyIaLCZl9GeRoubT2Mr68vAECUe+a5XETkvmzlVvsyytOwTD2Mv78/AJYpEbkWIQSs5nL7MsrTsEw9TEBAAADAZmGZEpELsQrYrDa3O0OiqlimHiYwMBAAIFimRORCbOYr1+QNCgqSOIlzsEw9THBwMADAVuaZF5MmIvck/lemV5dRnoZl6mF0Oh20Oi1sZeVSRyEisrv6BT8kJETiJM7BMvVAwbVqwWZimRKR67i6TKpdu7bESZyDZeqBwsPCYDNxMy8RuQ6bqRwqlcp+kKSnYZl6oOioaIhSrpkSkeuwlpQjNKy2x17mlGXqgerUqQNZGY/mJSLXYSu1oE5kHaljOA3L1ANFR0fDWmyWOgYR0f8rKUf9evWkTuE0LFMPVLduXZSbLLBZuN+UiFxEqfWGN0nxBCxTD1Tvf9/+rEUWaYMQEQEQNgGzodS+bPJELFMP1KBBAwCA1VgmcRIiIsBWYoGw2VC/fn2pozgNy9QDhYWFQefjA6uR+02JSHoVhitf7Bs2bChxEudhmXogmUyGBrENYC00SR2FiAhWQxnkCgU385L7iW/eAsLIfaZEJD1rYRli6sVApVJJHcVpWKYeqmnTprAWcp8pEUnPaihDfPMWUsdwKpaph2revDnKS828Ri8RSU4UmhEfHy91DKdimXqoFi2ufAssv1wqcRIi8ma2sgpYikz2ZZKnYpl6qIYNG0Kj1aAin2VKRNKpuFwCAGjZsqXESZyLZeqhFAoFmrdogYo8likRSaf8cinUGg0aN24sdRSnYpl6sA7t2gMFPNeUiKRTkVuC+Ph4KJVKqaM4FcvUg7Vv3x5ll4tgs/AOMkQkkQIz7urYUeoUTscy9WDt27cHBFCRVyJ1FCLyQjZzBcouF6NDhw5SR3E6lqkHa9asGXQ+PijPKZY6ChF5oavLnrvuukviJM7HMvVgCoUCHTt2REU2y5SIal55djECggLRqFEjqaM4HcvUw3Xr2hXWnFIIIaSOQkRexppdgi6dO0Mmk0kdxelYph6ua9euKC81w1rAi94TUc0RVhvKc4rRrWs3qaPUCJaph0tMTIRCqYDlolHqKETkRcpzS2C1VKB79+5SR6kRLFMP5+vri/bt26P8YpHUUYjIi1guGuHj64u2bdtKHaVGsEy9QJ+7+8CaVQJh435TIqoZ1otF6NGju8dfrOEqlqkXSEpKQrnJzPNNiahGiHIrLFnF6Nunr9RRagzL1Avcdddd8PH1hTnTIHUUIvIClotG2KxW9OnTR+ooNYZl6gVUKhXuvvtuWDO535SInM983oCo6Cg0adJE6ig1hmXqJe4dOBDmLCNvFk5ETiWEgC2zCIPuG+QV55dexTL1EgMGDIAQAubzhVJHISIPVpFvgtlQioEDB0odpUaxTL1EeHg42rZrB8vZQqmjEJEHM2cUQOfjg549e0odpUaxTL3IkMGDUX7BCFHOW7IRkXNYMwwYOGAANBqN1FFqFMvUizzwwAOwWip4VC8ROYXVWIaynCIMHjxY6ig1jmXqRRo3boymzZrBfCZf6ihE5IHKzuRDrVGjf//+UkepcSxTLzP84YdRfs7ATb1EVO0qzhowYMBA+Pv7Sx2lxrFMvcywYcOubOrNKJQ6ChF5kIpCE8qyjXj4oYekjiIJlqmXiY2NRdv27WA+fVnqKETkQcpOXYavnx8GDBggdRRJsEy90GMjRsJ8zsALOBBRtRBCoPxMAf4xdCh0Op3UcSTBMvVCw4YNg0Iuh+lUntRRiMgDlF8qgqWwFI899pjUUSTDMvVCISEhGHjvvSg/lQ8heFs2InKM6UQuYurVQ9euXaWOIhmWqZca88QTMOcVoyKXt2UjojtnM1egPL0QY554wquuxft3LFMv1bdvX0RERsJ0PEfqKETkxsrSLkPYbBg1apTUUSTFMvVSCoUCTz35JCxnCmAzV0gdh4jckBACltQ8DBw4EJGRkVLHkRTL1Is98cQTgFWg7CQPRCKi21eeVQRzXjGefeZZqaNIjmXqxSIjI5F8//2wpObxQCQium2mozloEBuLpKQkqaNIjmXq5ca98ALM+SWwnOfF74mo6qzFZpjT8zHuhRcgl7NKOAe8XOfOnZHQpjXKjmRLHYWI3EjpkWz4+vp69bmlf8Uy9XIymQyvvDwBZecLUX6Zp8kQ0a3ZLFZYTlzGk2Of9MqL2l8Py5QwZMgQREbVQemfWVJHISI3YDqeA1Fuxbhx46SO4jJYpgSVSoVXJ7wC8+nLsBaZpY5DRC5MWG2wHM3FI488gqioKKnjuAyWKQEARo8ejcDAQJQcvCh1FCJyYaaTeSgvLsOrr74qdRSXwjIlAICvry9efullmE9ehrXEInUcInJBwmqD+VA2ku+/H02bNpU6jkthmZLds88+Cz9fX66dEtF1lZ26DEthKaZMnix1FJfDMiW7gIAATHh5AsypebAWc98pEf0/YbWh7M8sJN+fjFatWkkdx+WwTKmS559/Hnp/f5Qc4NopEf0/04k8lBtMmDZ1mtRRXBLLlCrR6/X418R/oSw1DxWGMqnjEJELEBU2mA9m4cEHH0R8fLzUcVyS25Rpfn4+hg8fDr1ej8DAQIwePRrFxcU3naZHjx6QyWSVHk899VQNJXZfzz33HGrXDkXp3gtSRyEiF1B6JAvWUgveeustqaO4LLcp0+HDh+Po0aNYv349Vq5ciS1btmDs2LG3nG7MmDG4dOmS/fHee+/VQFr3ptPp8O+3/g1TWh7Kc2/+hYWIPJutrBxlf2Zj7NixaNiwodRxXJZMuMHtQo4fP45mzZphz549aNeuHQBgzZo16N+/PzIzM294H70ePXogISEBM2fOvOP3NhqNCAgIgMFggF6vv+PXcTcVFRWIb9USZwsvQj+wCWQymdSRiEgCRdsygPQipJ85g9q1a0sdp0bdzvLfLdZMd+zYgcDAQHuRAkBSUhLkcjl27dp102m///57hISEoEWLFpg4cSJKS0tvOr7ZbIbRaKz08EZKpRIffTgDZRcNMKcXSB2HiCRQUWiC6VgOJr3+utcV6e1SSh2gKrKysq75RSqVSgQHByMr68bXk3344YcRExODyMhIHDp0CK+++ipOnDiBJUuW3HCa6dOnY+rUqdWW3Z3dc8896NO3L1J2bYWmbiBkSrf47kVE1aRk53nUiaqDF198UeooLk/SpeNrr712zQFCf3+kpqbe8euPHTsWffv2RXx8PIYPH45vvvkGS5cuxenTp284zcSJE2EwGOyP8+fP3/H7e4JPPv4Y1iIzSg5dkjoKEdUg87lClGUUYOaMj6DVaqWO4/IkXTN96aWXbnkvvAYNGiA8PBw5OTmVhldUVCA/Px/h4eFVfr+OHTsCANLS0hAbG3vdcTQaDTQaTZVf09M1adIE48aNw8xPPoauUQgU/pw3RJ5OVNhg2nEePXr2xAMPPCB1HLcgaZmGhoYiNDT0luMlJiaisLAQ+/btQ9u2bQEAmzZtgs1msxdkVRw8eBAAEBERcUd5vdWUKVPw3fffwbD9HAL6NpI6DhE5WcnBi7AWW/D5Z5/x4MMqcoudYE2bNsU999yDMWPGYPfu3di2bRuee+45DBs2zH4k74ULFxAXF4fdu3cDAE6fPo233noL+/btw9mzZ/Hrr79ixIgR6NatG1q2bCnlx3E7/v7+mPXpLJSdzUfZ2Xyp4xCRE1UUmmD6Mwsvv/wy4uLipI7jNtyiTIErR+XGxcWhd+/e6N+/P7p06YIvv/zS/nx5eTlOnDhhP1pXrVZjw4YN6NOnD+Li4vDSSy9h8ODBWLFihVQfwa0NHjwYfe+5B6btmbBZrFLHISInEEKgZNs5REVF4Y033pA6jltxi/NMpeSt55leT0ZGBpo2awrU84e+a32p4xBRNTOl5sD4ezrWrVuHu+++W+o4kvO480zJNcTExOCd6e/AdCwHloveef4tkaeyllhQuusCRowYwSK9AyxTui3PPvss7kpMROnWDIhybu4l8gRCCBRvPYuggECHrhjnzVimdFsUCgW+WbAAKLOiaJd3n4NL5CnKTuSiLKMAX3/1XwQFBUkdxy2xTOm2NWrUCO+/9z5MR7NhzjRIHYeIHGA1lqF0ZyZGjhyJe++9V+o4botlSnfk2WefRc9evVC65SxsZeVSxyGiOyBsAkUpZxFWOwyffPKJ1HHcGsuU7ohcLse333wDnUKD4q0Z4EHhRO6n5MBFWLKL8OP3P3j92QqOYpnSHatTpw7mzZ0H05nLMB3PufUEROQyLFlFKN1/Aa//61/o2rWr1HHcHsuUHHL//ffjySefROnO8yi/fPPb2xGRa7CVVaBkczo6duyIKVOmSB3HI7BMyWEfffQR4uKaomTjGV4dicjFCSFQ9PsZ6ORqLFq4CEqlW9yJ0+WxTMlhOp0OS39ZAoUFKNqSzv2nRC6s9OBFlJ0twA/f/4Do6Gip43gMlilVi0aNGuGbBQtQdvoySg/f+IbtRCQdc6YBJXsu4F//+hf69+8vdRyPwjKlajN48GC8/PLLKNl1HpYLPP+UyJVYi8wo2ZyOXr17Y9q0aVLH8TgsU6pW06dPR48ePVG8KR3WIrPUcYgIgCi3omj9aYSHhmHhTz9BoVBIHcnjsEypWimVSixetAgRtcNRtC6NByQRSUwIAWNKOuQlFVi1YiVq1aoldSSPxDKlalerVi2sXrkKCpNA0eYzEDYekEQklZK9mSg7cxk/fP8D4uPjpY7jsVim5BTNmzfHz4sXw3yuEMU7z0kdh8grmU7momT/RUyfPh3JyclSx/FoLFNymn79+uGTjz9G6eEslB7hEb5ENclywYDiLWcxatQovPrqq1LH8XgsU3Kq5557DuPHj0fR9nMoO5MvdRwir1B+uRRF60+jZ89e+OKLLyCTyaSO5PF46Qtyuvfffx/nMzPxy5JfINcqoY7kBbWJnMVaZEbx2jQ0jWuKpUuWQKVSSR3JK3DNlJzu6h1munbpiqJ1aSjPK5E6EpFHspnKYfztFMJr1ca6NWvh7+8vdSSvwTKlGqHRaLDi118R37wFitacQkWhSepIRB7FZq6A8bdTCFD5YNOGjQgPD5c6kldhmVKN8ff3x7q161A/uh6KVp+C1VgmdSQij2Art6Jo7Sloy+XYtHETYmNjpY7kdVimVKNCQkKQsmkzIkPDYVx9ildJInKQKLeiaM0pKIpsWL9uPVq0aCF1JK/EMqUaFxERgS0pvyMsMATG1SdhLWahEt0JUW6FcV0a5IZyrFu7Fu3bt5c6ktdimZIkoqOjsfX3LaitrwXjqpNcQyW6TbZyKwxrT0GWb8baNWvRqVMnqSN5NZYpSSYmJgZ/bNmK8MBQGFedRIWB+1CJqsJmqbiyabewAuvXrUeXLl2kjuT1WKYkqZiYGGzb+geiQiNgXHkCFQWlUkcicmm2snIYV5+CqtiGTRs3onPnzlJHIrBMyQVERUVh+x/b0KheLIwrT6I8p1jqSEQuyVpigXHlSfhWKLHl9y3o2LGj1JHof1im5BLCwsLwx5ataB3fCoZVJ2DO5M3Fif6qotAE44oTqKULwPZt25GQkCB1JPoLlim5jKCgIGzauAm9e/aGcc1JmE7lSR2JyCVYsotgXHEC9SKisWvHTjRp0kTqSPQ3LFNyKb6+vli5YgVGPDoCxk2nUXLgAoTg/VDJe5Wl58Ow6gTaJbTBjm3bERUVJXUkug6WKbkclUqFuXPnYvLkySjenYmiLekQVpvUsYhqlBACJX9egmF9Gu4fdD82bdyE4OBgqWPRDbBMySXJZDJMnToVCxYsQHlaAYy/nYStrFzqWEQ1QlhtKNqSjuKd5/DqK69g0cKF0Gq1Useim2CZkksbMWIENm3aBJ1JDuPyVFTk89QZ8mw2UzmMq0+iPK0A8+bNwzvvvAO5nItqV8ffELm8rl27Yt/efWhQpx4Kf01FWTpvMk6eqTy3BIZlx+FrUSIlJQWPPfaY1JGoilim5Bbq16+P3Tt3Ifne+2BYdwpFu85B2HhgEnkO04lcGFYcR/OGcTiw/wAvxuBmWKbkNvz8/LB40WK89957MB3KhvG3k7CWcj8quTdRYYPx9zMwppzByEdHYvu27YiOjpY6Ft0mlim5FZlMhgkTJmDTxo3wNSthWHoMlgu8wAO5p4pCEwy/psKabsDXX3+Nr7/+mgcauSmWKbmlHj164Mihw+jUriMKVp1A8Z5MbvYltyGEgOlkLgqXHkOdgNrYs3sPHn/8caljkQNYpuS2wsPDsXHDRrw1bRpMf16CcWUqKoy88wy5Npu5AkWbz8C4+QyGD3sYfx44iJYtW0odixzEMiW3plAoMGnSJGzdshWh6kAU/nIMptRcXjWJXJLlggGGJcegyDLjhx9+wIIFC+Dn5yd1LKoGLFPyCJ06dcKRQ4fx6MPDrxzMsS4N1hKL1LGIAACi3ArjtrMoWJmKjgntcPTIETz00ENSx6JqxDIlj6HX6zFv3jwsW7YMvsUyFP5yFKaTXEslaVkuGlG45Bispwrw0UcfIWVzCurWrSt1LKpmLFPyOIMGDcKJ1BMYkvwAjJvPwLjmFKxFZqljkZexmStg3JqOghXH0aZpKxw+dBjjxo3j1Yw8FH+r5JFq1aqFH3/4EStWrEBghRYFPx9ByZ+XeMF8cjohBMpOX0bhz0chyyjGp59+im1//IHGjRtLHY2ciGVKHm3gwIE4mXoCzzz5NEp2Z8Kw7Dgsl4qkjkUeqsJQBuNvp2DYkIZ7et6N1OOpeO6557g26gX4GyaP5+/vj08++QR79+xBi3pNUPDrMRg3neYBSlRtbOVWFO06j4KfjyBE5ofly5fj119/5ZWMvAjLlLxGmzZtsHvXbvz3v/+FLt+GgkWHUbz/AkQFN/3SnRFCwHQiF4WLjqDieB7eeH0STqaewH333Sd1NKphLFPyKnK5HKNHj8bptNN44bnnYT6QhcJFR2A6kcsrKNFtMWcaYFh6HMaUMxjU716cPHESb775JnQ6ndTRSAIsU/JKgYGB+PDDD3H8+HEM7NMPxpQzMCw9BnNGAU+loZsqzy2BYfVJFK5KRasGTbFt2zYsXrQIMTExUkcjCbFMyas1bNgQv/z8C3bs2IH2TRNQuOYkjCtSYc40sFSpkor8UhjWn0L+kiOI0obgl19+wc4dO9GpUyepo5ELYJkSAbjrrruw5fctWLt2LZpFNkThqlQYV55gqRLKL5fCsCENlxcfRkiFL+bNm4fjx47hgQcegEwmkzoeuQiWKdH/yGQy9OnTB3v37MWKFSsQF97gSqn+moqys9z8623Ks4thWHcK+T8fRki5D7788kucPpWGxx57DEqlUup45GJYpkR/I5PJMHDgQOzfuw+//fYb2sS2gGHtSRh+OQZTag6P/vVgQgiYMwpgWJmK/GVHUUcZjHnz5uFM2mmMGTMGarVa6ojkomSCX7dvymg0IiAgAAaDAXq9Xuo4JJFt27bhnXfewapVq6D00UAdVwu6ZrWh8OHC1RPYyq0oO5kHy9FcmAtK0L5De7z26mtITk7mBRe82O0s/1mmt8Aypb86efIkZs6ciXnz58FisUBdPwi6ZmFQhftx/5kbqigwofRYNspP5cNWbkXy/ffjpfHjeVARAWCZViuWKV1PQUEB5s+fj08+/RRn09OhCfGDqlEwdI1CINeppI5HNyHKrShLz4flxGWUXTQgqFYwnhr7JJ566inezYUqYZlWI5Yp3YzNZsOmTZsw54svsHzZMtiEDeqYQGgbhUAdHQCZgpsIXYEQAuXZxSg7mYfyMwWoMJejW/duePqpp3H//fdDo9FIHZFcEMu0GrFMqapyc3Px3Xff4et5c3H08BGofDRQ1guAtmEtqML9uRm4hgkhYC0woSztMirSC2EuLEVknToY9dhjGDVqFGJjY6WOSC6OZVqNWKZ0Jw4dOoTvv/8e3373HS5dvAi1vw6KGD209YOvFKucxeoMQghUXC6FOb0AFRkGmC8XQx+gx9AhQ/HII4+gW7duPKCIqoxlWo1YpuQIm82GHTt2YNGiRVi0eDGyLl2CykcDRZQ/NHUDoY4KgFzDcxYdISpssFwywpxRCGtmESyGUvjr/XF/8v0YOnQo+vTpw1Na6I6wTKsRy5SqixACe/bswfLly7Fk6RKkHk+FTC6HJtwfijr+0EQFQBniy7XWWxBCwFpYBkumAeUXjCi/VASrpQIRkRFIHpSM+++/Hz169IBKxQPByDEs02rEMiVnOXv2LH777Tf8tmYNNm7ciNKSEig1KijD/aCM8Ic63B/KEB+vP4jp6r5PS1YRLBeLILJLYCkug0qlQmKnRPTv1x/9+vVDfHw890tTtfLIMn377bexatUqHDx4EGq1GoWFhbecRgiBKVOm4KuvvkJhYSE6d+6Mzz//HI0aNary+7JMqSaUl5djz5492LRpEzZu2oQdO7bDXGaGQqWEKtQX8hAfqGr7QhnqC4W/xqNLw1pqQUVuCcpzSmDNK0FFbikqTBbIFXIktG6Nu3snoWfPnujSpQt8fX2ljksezCPLdMqUKQgMDERmZia+/vrrKpXpu+++i+nTp2PBggWoX78+3njjDRw+fBjHjh2DVqut0vuyTEkK5eXl2L9/P7Zt24bt27dj+84duHThIgBApVNDEaSDLFgLZZAPlEE6KIO0kGvda7OmrdwKa6EJFQUmVOSbYC0wQeSbYSk2AQACg4NwV8eO6JTYCZ07d0bHjh1ZnlSjPLJMr5o/fz7GjRt3yzIVQiAyMhIvvfQSXn75ZQCAwWBAWFgY5s+fj2HDhlXp/Vim5CpycnKwb98+HDhw4Mrjz4NIP5MOm9UKAFcObArQAn5KKPy1UPirIffTQOGrhtxXBZlKUaNrtKLCBmuJBbYSC6zFFliLzbAazUCxBcJogbnIZB83MqoOEloloHVCAtq0aYM2bdogJibGo9fAyfXdzvLfYw8jTE9PR1ZWFpKSkuzDAgIC0LFjR+zYseOGZWo2m2E2m+0/G41Gp2clqoratWujX79+6Nevn32Y2WzGyZMnkZqaihMnTuDUqVM4ceokzpw+jdycC5WmV6iVUPpoINMqIdQyyNQKyDRKyFRyyFUKyFQKQCG7so9WLrtyINTVLhNXvqDCKiBsAqiwQVTYIMqtsJVbISxWCLMVMosNMFtRUWpBRZml0vsHBAWiUb16iGsdh9jYWDRu3BhNmzZFXFwc/P39nT37iJzKY8s0KysLABAWFlZpeFhYmP2565k+fTqmTp3q1GxE1UWj0SA+Ph7x8fHXPGc2m3HhwgVkZmbi4sWLuHTpErKzs5GXl4fLly8j73Ie8gsKYMw3ori4GGUmE8xl5irdak6t0UCr08LX1xd6fRACawUiJLgWQkJCEBISgrCwMISHhyMyMhJ16tRBdHQ0N9GSR5O0TF977TW8++67Nx3n+PHjiIuLq6FEwMSJEzF+/Hj7z0ajEdHR0TX2/kTVRaPRoEGDBmjQoEGVpxFCoKKiAhaLBVarFUIICCEgk8mgUCigUqmgVqu5+ZXobyQt05deegmPPfbYTce5nQXBX4WHhwMAsrOzERERYR+enZ2NhISEG06n0Wh4nU7yWjKZDCqViudoEt0mScs0NDQUoaGhTnnt+vXrIzw8HBs3brSXp9FoxK5du/D000875T2JiMg7uc3Z4OfOncPBgwdx7tw5WK1WHDx4EAcPHkRxcbF9nLi4OCxduhTAlW/Y48aNw7///W/8+uuvOHz4MEaMGIHIyEgkJydL9CmIiMgTuc0BSJMnT8aCBQvsP7du3RoAsHnzZvTo0QMAcOLECRgMBvs4r7zyCkpKSjB27FgUFhaiS5cuWLNmTZXPMSUiIqoKtzvPtKbxPFMiIu90O8t/t9nMS0RE5KpYpkRERA5imRIRETmIZUpEROQglikREZGDWKZEREQOYpkSERE5iGVKRETkIJYpERGRg1imREREDmKZEhEROYhlSkRE5CCWKRERkYNYpkRERA5imRIRETmIZUpEROQglikREZGDWKZEREQOYpkSERE5iGVKRETkIJYpERGRg1imREREDmKZEhEROYhlSkRE5CCWKRERkYNYpkRERA5imRIRETmIZUpEROQglikREZGDWKZEREQOYpkSERE5iGVKRETkIJYpERGRg1imREREDmKZEhEROYhlSkRE5CCWKRERkYOUUgdwdUIIAIDRaJQ4CRER1aSry/2rPXAzLNNbKCoqAgBER0dLnISIiKRQVFSEgICAm44jE1WpXC9ms9lw8eJF+Pv7QyaTSR3nloxGI6Kjo3H+/Hno9Xqp47gszqeq4XyqGs6nqnG3+SSEQFFRESIjIyGX33yvKNdMb0EulyMqKkrqGLdNr9e7xR+r1DifqobzqWo4n6rGnebTrdZIr+IBSERERA5imRIRETmIZephNBoNpkyZAo1GI3UUl8b5VDWcT1XD+VQ1njyfeAASERGRg7hmSkRE5CCWKRERkYNYpkRERA5imXqAt99+G506dYKPjw8CAwOrNI0QApMnT0ZERAR0Oh2SkpJw6tQp5waVWH5+PoYPHw69Xo/AwECMHj0axcXFN52mR48ekMlklR5PPfVUDSWuGbNnz0a9evWg1WrRsWNH7N69+6bjL168GHFxcdBqtYiPj8fq1atrKKm0bmc+zZ8//5q/G61WW4NppbFlyxbce++9iIyMhEwmw7Jly245TUpKCtq0aQONRoOGDRti/vz5Ts/pDCxTD2CxWDB06FA8/fTTVZ7mvffewyeffII5c+Zg165d8PX1Rd++fVFWVubEpNIaPnw4jh49ivXr12PlypXYsmULxo4de8vpxowZg0uXLtkf7733Xg2krRkLFy7E+PHjMWXKFOzfvx+tWrVC3759kZOTc93xt2/fjoceegijR4/GgQMHkJycjOTkZBw5cqSGk9es251PwJULE/z17yYjI6MGE0ujpKQErVq1wuzZs6s0fnp6OgYMGICePXvi4MGDGDduHJ544gmsXbvWyUmdQJDHmDdvnggICLjleDabTYSHh4v333/fPqywsFBoNBrx448/OjGhdI4dOyYAiD179tiH/fbbb0Imk4kLFy7ccLru3buLF154oQYSSqNDhw7i2Weftf9stVpFZGSkmD59+nXH/8c//iEGDBhQaVjHjh3Fk08+6dScUrvd+VTV/xc9GQCxdOnSm47zyiuviObNm1ca9uCDD4q+ffs6MZlzcM3UC6WnpyMrKwtJSUn2YQEBAejYsSN27NghYTLn2bFjBwIDA9GuXTv7sKSkJMjlcuzateum037//fcICQlBixYtMHHiRJSWljo7bo2wWCzYt29fpb8DuVyOpKSkG/4d7Nixo9L4ANC3b1+P/bsB7mw+AUBxcTFiYmIQHR2NQYMG4ejRozUR16140t8Tr83rhbKysgAAYWFhlYaHhYXZn/M0WVlZqF27dqVhSqUSwcHBN/3MDz/8MGJiYhAZGYlDhw7h1VdfxYkTJ7BkyRJnR3a6vLw8WK3W6/4dpKamXnearKwsr/q7Ae5sPjVp0gRz585Fy5YtYTAY8MEHH6BTp044evSoW17r21lu9PdkNBphMpmg0+kkSnb7uGbqol577bVrDmD4++NG/yN7E2fPp7Fjx6Jv376Ij4/H8OHD8c0332Dp0qU4ffp0NX4K8jSJiYkYMWIEEhIS0L17dyxZsgShoaH44osvpI5GTsI1Uxf10ksv4bHHHrvpOA0aNLij1w4PDwcAZGdnIyIiwj48OzsbCQkJd/SaUqnqfAoPD7/mYJGKigrk5+fb50dVdOzYEQCQlpaG2NjY287rSkJCQqBQKJCdnV1peHZ29g3nSXh4+G2N7wnuZD79nUqlQuvWrZGWluaMiG7rRn9Per3erdZKAZapywoNDUVoaKhTXrt+/foIDw/Hxo0b7eVpNBqxa9eu2zoi2BVUdT4lJiaisLAQ+/btQ9u2bQEAmzZtgs1msxdkVRw8eBAAKn0JcVdqtRpt27bFxo0bkZycDODK/Xs3btyI55577rrTJCYmYuPGjRg3bpx92Pr165GYmFgDiaVxJ/Pp76xWKw4fPoz+/fs7Man7SUxMvObUKrf9e5L6CChyXEZGhjhw4ICYOnWq8PPzEwcOHBAHDhwQRUVF9nGaNGkilixZYv/5nXfeEYGBgWL58uXi0KFDYtCgQaJ+/frCZDJJ8RFqxD333CNat24tdu3aJf744w/RqFEj8dBDD9mfz8zMFE2aNBG7du0SQgiRlpYmpk2bJvbu3SvS09PF8uXLRYMGDUS3bt2k+gjV7qeffhIajUbMnz9fHDt2TIwdO1YEBgaKrKwsIYQQjz76qHjttdfs42/btk0olUrxwQcfiOPHj4spU6YIlUolDh8+LNVHqBG3O5+mTp0q1q5dK06fPi327dsnhg0bJrRarTh69KhUH6FGFBUV2Zc/AMSMGTPEgQMHREZGhhBCiNdee008+uij9vHPnDkjfHx8xIQJE8Tx48fF7NmzhUKhEGvWrJHqI9wxlqkHGDlypABwzWPz5s32cQCIefPm2X+22WzijTfeEGFhYUKj0YjevXuLEydO1Hz4GnT58mXx0EMPCT8/P6HX68WoUaMqfeFIT0+vNN/OnTsnunXrJoKDg4VGoxENGzYUEyZMEAaDQaJP4ByffvqpqFu3rlCr1aJDhw5i586d9ue6d+8uRo4cWWn8RYsWicaNGwu1Wi2aN28uVq1aVcOJpXE782ncuHH2ccPCwkT//v3F/v37JUhdszZv3nzdZdHVeTNy5EjRvXv3a6ZJSEgQarVaNGjQoNJyyp3wrjFEREQO4tG8REREDmKZEhEROYhlSkRE5CCWKRERkYNYpkRERA5imRIRETmIZUpEROQglikREZGDWKZEREQOYpkSERE5iGVKRETkIJYpEVWSm5uL8PBw/Oc//7EP2759O9RqNTZu3ChhMiLXxQvdE9E1Vq9ejeTkZGzfvh1NmjRBQkICBg0ahBkzZkgdjcglsUyJ6LqeffZZbNiwAe3atcPhw4exZ88eaDQaqWMRuSSWKRFdl8lkQosWLXD+/Hns27cP8fHxUkciclncZ0pE13X69GlcvHgRNpsNZ8+elToOkUvjmikRXcNisaBDhw5ISEhAkyZNMHPmTBw+fBi1a9eWOhqRS2KZEtE1JkyYgJ9//hl//vkn/Pz80L17dwQEBGDlypVSRyNySdzMS0SVpKSkYObMmfj222+h1+shl8vx7bffYuvWrfj888+ljkfkkrhmSkRE5CCumRIRETmIZUpEROQglikREZGDWKZEREQOYpkSERE5iGVKRETkIJYpERGRg1imREREDmKZEhEROYhlSkRE5CCWKRERkYNYpkRERA76P3UVXqYi01hDAAAAAElFTkSuQmCC",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
-      ]
+      ],
+      "image/png": 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"
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     }
    ],
-   "source": [
-    "s1 = td.Sphere(radius=1, center=(0, 0, 0))\n",
-    "s2 = td.Box(center=(1, 1, 1), size=(1, 1, 1))\n",
-    "\n",
-    "# do two geometric objects intersect?\n",
-    "print(s1.intersects(s2))\n",
-    "\n",
-    "# does the object intersect a plane?\n",
-    "print(s1.intersects_plane(z=10))\n",
-    "\n",
-    "# get polygons that intersect sphere at plane x=0\n",
-    "print(s1.intersects_plane(x=0))\n",
-    "\n",
-    "# get bounds (rmin, rmax) of geometry\n",
-    "print(s1.bounds)\n",
-    "\n",
-    "# get td.Box() for bounding box of geometry\n",
-    "print(s1.bounding_box.help())\n",
-    "\n",
-    "# evaluate whether point(s) are inside of geometry\n",
-    "print(s1.inside(x=0, y=1, z=1))\n",
-    "print(s1.inside(x=np.linspace(-1, 1, 5), y=np.zeros(5), z=np.ones(5)))\n",
-    "\n",
-    "# plot the geometry at a cross sectional plane\n",
-    "ax = s1.plot(y=0)"
-   ]
+   "execution_count": 12
   },
   {
    "cell_type": "markdown",
@@ -713,18 +799,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
    "id": "07727a55",
    "metadata": {
-    "tags": []
+    "tags": [],
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:07:20.439352Z",
+     "start_time": "2025-10-29T14:07:20.437611Z"
+    }
    },
-   "outputs": [],
    "source": [
     "dielectric_box = td.Structure(\n",
     "    geometry=td.Box(center=(0, 0, 0), size=(1, 1, 1)),\n",
     "    medium=td.Medium(permittivity=2.0),\n",
     ")"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": 13
   },
   {
    "cell_type": "markdown",
@@ -738,12 +828,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
    "id": "b06caa0b",
    "metadata": {
-    "tags": []
+    "tags": [],
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:07:20.486381Z",
+     "start_time": "2025-10-29T14:07:20.483730Z"
+    }
    },
-   "outputs": [],
    "source": [
     "# define time dependence\n",
     "gaussian = td.GaussianPulse(freq0=150e12, fwidth=10e12)\n",
@@ -761,7 +853,9 @@
     "    pol_angle=np.pi / 2,\n",
     "    direction=\"-\",\n",
     ")"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": 14
   },
   {
    "cell_type": "markdown",
@@ -793,10 +887,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
    "id": "f37ac987",
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:07:20.530672Z",
+     "start_time": "2025-10-29T14:07:20.528797Z"
+    }
+   },
    "source": [
     "# measures Ex, Ey, Hz fields on the plane at frequency 150THz\n",
     "mon1 = td.FieldMonitor(\n",
@@ -816,7 +913,9 @@
     "    interval=5,\n",
     "    name=\"flux_over_time\",\n",
     ")"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": 15
   },
   {
    "cell_type": "markdown",
@@ -832,10 +931,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
    "id": "86f4f9e1",
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:07:20.574715Z",
+     "start_time": "2025-10-29T14:07:20.572953Z"
+    }
+   },
    "source": [
     "# default mode solver spec (returns first mode)\n",
     "fundamental = td.ModeSpec()\n",
@@ -845,7 +947,9 @@
     "\n",
     "# have mode solver return 4 modes around the target effective index\n",
     "complicated = td.ModeSpec(num_modes=4, target_neff=2.0)"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": 16
   },
   {
    "cell_type": "markdown",
@@ -857,10 +961,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
    "id": "5b42e241",
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:07:20.620050Z",
+     "start_time": "2025-10-29T14:07:20.618034Z"
+    }
+   },
    "source": [
     "# inject the fundamental mode\n",
     "mode_source = td.ModeSource(\n",
@@ -880,7 +987,9 @@
     "    mode_spec=first_4_modes,\n",
     "    name=\"modes\",\n",
     ")"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": 17
   },
   {
    "cell_type": "markdown",
@@ -916,18 +1025,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
    "id": "bda9c2eb",
    "metadata": {
-    "tags": []
+    "tags": [],
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:07:20.664906Z",
+     "start_time": "2025-10-29T14:07:20.663178Z"
+    }
    },
-   "outputs": [],
    "source": [
     "# standard absorber on x, PML with 20 layers on y, no PML on z (periodic BC)\n",
     "boundary_spec = td.BoundarySpec(\n",
     "    x=td.Boundary.absorber(), y=td.Boundary.pml(num_layers=20), z=td.Boundary.periodic()\n",
     ")"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": 18
   },
   {
    "cell_type": "markdown",
@@ -947,12 +1060,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
    "id": "11cf6c24",
    "metadata": {
-    "tags": []
+    "tags": [],
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:07:20.710941Z",
+     "start_time": "2025-10-29T14:07:20.706821Z"
+    }
    },
-   "outputs": [],
    "source": [
     "sim = td.Simulation(\n",
     "    size=(4, 4, 4),\n",
@@ -965,7 +1080,9 @@
     "    sources=[dipole],\n",
     "    monitors=[mon1, mon2],\n",
     ")"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": 19
   },
   {
    "cell_type": "markdown",
@@ -977,11 +1094,33 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
    "id": "c9ccd22a",
    "metadata": {
-    "tags": []
+    "tags": [],
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:07:20.984865Z",
+     "start_time": "2025-10-29T14:07:20.753588Z"
+    }
    },
+   "source": [
+    "# get permittivity at yee cell centers in a volume defined by a box.\n",
+    "sim.epsilon(td.Box(size=(1, 0, 1)), \"centers\")\n",
+    "\n",
+    "# get a `td.Grid` containing all information about spatial locations in the FDTD / yee grid\n",
+    "print(sim.grid.centers)\n",
+    "\n",
+    "# plot the simulation cross section\n",
+    "f, (ax1, ax2) = plt.subplots(1, 2, tight_layout=True, figsize=(10, 4))\n",
+    "\n",
+    "# plot the structures, PML, sources, mediums\n",
+    "ax1 = sim.plot(x=0, ax=ax1)\n",
+    "\n",
+    "# same thing but plot structure in grayscale using permittivity value\n",
+    "ax1 = sim.plot_eps(x=0, ax=ax2)\n",
+    "\n",
+    "# add the FDTD grid boundaries\n",
+    "ax2 = sim.plot_grid(x=0, ax=ax2)"
+   ],
    "outputs": [
     {
      "name": "stdout",
@@ -997,34 +1136,19 @@
     },
     {
      "data": {
-      "image/png": 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",
       "text/plain": [
        "<Figure size 1000x400 with 3 Axes>"
-      ]
+      ],
+      "image/png": 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"
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     }
    ],
-   "source": [
-    "# get permittivity at yee cell centers in a volume defined by a box.\n",
-    "sim.epsilon(td.Box(size=(1, 0, 1)), \"centers\")\n",
-    "\n",
-    "# get a `td.Grid` containing all information about spatial locations in the FDTD / yee grid\n",
-    "print(sim.grid.centers)\n",
-    "\n",
-    "# plot the simulation cross section\n",
-    "f, (ax1, ax2) = plt.subplots(1, 2, tight_layout=True, figsize=(10, 4))\n",
-    "\n",
-    "# plot the structures, PML, sources, mediums\n",
-    "ax1 = sim.plot(x=0, ax=ax1)\n",
-    "\n",
-    "# same thing but plot structure in grayscale using permittivity value\n",
-    "ax1 = sim.plot_eps(x=0, ax=ax2)\n",
-    "\n",
-    "# add the FDTD grid boundaries\n",
-    "ax2 = sim.plot_grid(x=0, ax=ax2)"
-   ]
+   "execution_count": 20
   },
   {
    "cell_type": "markdown",
@@ -1044,15 +1168,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
    "id": "9f16e7e9",
    "metadata": {
-    "tags": []
+    "tags": [],
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:07:21.103223Z",
+     "start_time": "2025-10-29T14:07:20.988221Z"
+    }
    },
-   "outputs": [],
    "source": [
     "import tidy3d.web as web"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": 21
   },
   {
    "cell_type": "markdown",
@@ -1068,304 +1196,371 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
    "id": "1f75f482",
    "metadata": {
-    "tags": []
+    "tags": [],
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:07:40.157833Z",
+     "start_time": "2025-10-29T14:07:21.109648Z"
+    }
    },
+   "source": [
+    "sim_data = web.run(sim, task_name=\"web_demo\", path=\"data/data.hdf5\", verbose=True)"
+   ],
    "outputs": [
     {
      "data": {
+      "text/plain": [
+       "\u001B[2;36m15:07:22 CET\u001B[0m\u001B[2;36m \u001B[0mCreated task \u001B[32m'web_demo'\u001B[0m with resource_id                           \n",
+       "\u001B[2;36m             \u001B[0m\u001B[32m'fdve-fae17aac-8105-4166-a1a7-6cf1b414a498'\u001B[0m and task_type \u001B[32m'FDTD'\u001B[0m.  \n"
+      ],
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">12:45:57 CEST </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'web_demo'</span> with task_id                              \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">              </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-c6b4767e-c643-4268-94d8-752d2f8d6b0a'</span> and task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>. \n",
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">15:07:22 CET </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'web_demo'</span> with resource_id                           \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-fae17aac-8105-4166-a1a7-6cf1b414a498'</span> and task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.  \n",
        "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m12:45:57 CEST\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'web_demo'\u001b[0m with task_id                              \n",
-       "\u001b[2;36m              \u001b[0m\u001b[32m'fdve-c6b4767e-c643-4268-94d8-752d2f8d6b0a'\u001b[0m and task_type \u001b[32m'FDTD'\u001b[0m. \n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
+      "text/plain": [
+       "\u001B[2;36m            \u001B[0m\u001B[2;36m \u001B[0mView task using web UI at                                          \n",
+       "\u001B[2;36m             \u001B[0m\u001B]8;id=931149;https://tidy3d.simulation.cloud/workbench?taskId=fdve-fae17aac-8105-4166-a1a7-6cf1b414a498\u001B\\\u001B[32m'https://tidy3d.simulation.cloud/workbench?\u001B[0m\u001B]8;;\u001B\\\u001B]8;id=902976;https://tidy3d.simulation.cloud/workbench?taskId=fdve-fae17aac-8105-4166-a1a7-6cf1b414a498\u001B\\\u001B[32mtaskId\u001B[0m\u001B]8;;\u001B\\\u001B]8;id=931149;https://tidy3d.simulation.cloud/workbench?taskId=fdve-fae17aac-8105-4166-a1a7-6cf1b414a498\u001B\\\u001B[32m=\u001B[0m\u001B]8;;\u001B\\\u001B]8;id=868005;https://tidy3d.simulation.cloud/workbench?taskId=fdve-fae17aac-8105-4166-a1a7-6cf1b414a498\u001B\\\u001B[32mfdve\u001B[0m\u001B]8;;\u001B\\\u001B]8;id=931149;https://tidy3d.simulation.cloud/workbench?taskId=fdve-fae17aac-8105-4166-a1a7-6cf1b414a498\u001B\\\u001B[32m-fae17aac-810\u001B[0m\u001B]8;;\u001B\\\n",
+       "\u001B[2;36m             \u001B[0m\u001B]8;id=931149;https://tidy3d.simulation.cloud/workbench?taskId=fdve-fae17aac-8105-4166-a1a7-6cf1b414a498\u001B\\\u001B[32m5-4166-a1a7-6cf1b414a498'\u001B[0m\u001B]8;;\u001B\\.                                         \n"
+      ],
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">              </span>View task using web UI at                                         \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">              </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-c6b4767e-c643-4268-94d8-752d2f8d6b0a\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-c6b4767e-c6</span></a>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">              </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-c6b4767e-c643-4268-94d8-752d2f8d6b0a\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">43-4268-94d8-752d2f8d6b0a'</span></a>.                                       \n",
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>View task using web UI at                                          \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-fae17aac-8105-4166-a1a7-6cf1b414a498\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-fae17aac-810</span></a>\n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-fae17aac-8105-4166-a1a7-6cf1b414a498\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">5-4166-a1a7-6cf1b414a498'</span></a>.                                         \n",
        "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m             \u001b[0m\u001b[2;36m \u001b[0mView task using web UI at                                         \n",
-       "\u001b[2;36m              \u001b[0m\u001b]8;id=191040;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c6b4767e-c643-4268-94d8-752d2f8d6b0a\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=727469;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c6b4767e-c643-4268-94d8-752d2f8d6b0a\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=191040;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c6b4767e-c643-4268-94d8-752d2f8d6b0a\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=37895;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c6b4767e-c643-4268-94d8-752d2f8d6b0a\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=191040;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c6b4767e-c643-4268-94d8-752d2f8d6b0a\u001b\\\u001b[32m-c6b4767e-c6\u001b[0m\u001b]8;;\u001b\\\n",
-       "\u001b[2;36m              \u001b[0m\u001b]8;id=191040;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c6b4767e-c643-4268-94d8-752d2f8d6b0a\u001b\\\u001b[32m43-4268-94d8-752d2f8d6b0a'\u001b[0m\u001b]8;;\u001b\\.                                       \n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
+      "text/plain": [
+       "\u001B[2;36m            \u001B[0m\u001B[2;36m \u001B[0mTask folder: \u001B]8;id=289248;https://tidy3d.simulation.cloud/folders/folder-df61810d-cad6-4474-8ea9-e4f00d5dfcb0\u001B\\\u001B[32m'default'\u001B[0m\u001B]8;;\u001B\\.                                            \n"
+      ],
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">              </span>Task folder: <a href=\"https://tidy3d.simulation.cloud/folders/9b36e144-ddb6-41f8-8dd8-30b62b26a870\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'default'</span></a>.                                           \n",
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>Task folder: <a href=\"https://tidy3d.simulation.cloud/folders/folder-df61810d-cad6-4474-8ea9-e4f00d5dfcb0\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'default'</span></a>.                                            \n",
        "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m             \u001b[0m\u001b[2;36m \u001b[0mTask folder: \u001b]8;id=530263;https://tidy3d.simulation.cloud/folders/9b36e144-ddb6-41f8-8dd8-30b62b26a870\u001b\\\u001b[32m'default'\u001b[0m\u001b]8;;\u001b\\.                                           \n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "e71a116f60a147bdbbdb17b5e153bbd5",
-       "version_major": 2,
-       "version_minor": 0
-      },
       "text/plain": [
        "Output()"
-      ]
+      ],
+      "application/vnd.jupyter.widget-view+json": {
+       "version_major": 2,
+       "version_minor": 0,
+       "model_id": "9bffc984a9704fb087642b024516c78f"
+      }
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
+      "text/plain": [],
       "text/html": [
        "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
-      ],
-      "text/plain": []
+      ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
+      "text/plain": [
+       "\u001B[2;36m15:07:24 CET\u001B[0m\u001B[2;36m \u001B[0mEstimated FlexCredit cost: \u001B[1;36m0.025\u001B[0m. Minimum cost depends on task     \n",
+       "\u001B[2;36m             \u001B[0mexecution details. Use \u001B[32m'web.real_cost\u001B[0m\u001B[32m(\u001B[0m\u001B[32mtask_id\u001B[0m\u001B[32m)\u001B[0m\u001B[32m'\u001B[0m to get the billed  \n",
+       "\u001B[2;36m             \u001B[0mFlexCredit cost after a simulation run.                            \n"
+      ],
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">12:46:00 CEST </span>Maximum FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.025</span>. Minimum cost depends on task      \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">              </span>execution details. Use <span style=\"color: #008000; text-decoration-color: #008000\">'web.real_cost(task_id)'</span> to get the billed \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">              </span>FlexCredit cost after a simulation run.                           \n",
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">15:07:24 CET </span>Estimated FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.025</span>. Minimum cost depends on task     \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>execution details. Use <span style=\"color: #008000; text-decoration-color: #008000\">'web.real_cost(task_id)'</span> to get the billed  \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>FlexCredit cost after a simulation run.                            \n",
        "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m12:46:00 CEST\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.025\u001b[0m. Minimum cost depends on task      \n",
-       "\u001b[2;36m              \u001b[0mexecution details. Use \u001b[32m'web.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed \n",
-       "\u001b[2;36m              \u001b[0mFlexCredit cost after a simulation run.                           \n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
+      "text/plain": [
+       "\u001B[2;36m15:07:28 CET\u001B[0m\u001B[2;36m \u001B[0mstatus = queued                                                    \n"
+      ],
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">12:46:01 CEST </span>status = queued                                                   \n",
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">15:07:28 CET </span>status = queued                                                    \n",
        "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m12:46:01 CEST\u001b[0m\u001b[2;36m \u001b[0mstatus = queued                                                   \n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
+      "text/plain": [
+       "\u001B[2;36m            \u001B[0m\u001B[2;36m \u001B[0mTo cancel the simulation, use \u001B[32m'web.abort\u001B[0m\u001B[32m(\u001B[0m\u001B[32mtask_id\u001B[0m\u001B[32m)\u001B[0m\u001B[32m'\u001B[0m or              \n",
+       "\u001B[2;36m             \u001B[0m\u001B[32m'web.delete\u001B[0m\u001B[32m(\u001B[0m\u001B[32mtask_id\u001B[0m\u001B[32m)\u001B[0m\u001B[32m'\u001B[0m or abort/delete the task in the web UI.      \n",
+       "\u001B[2;36m             \u001B[0mTerminating the Python script will not stop the job running on the \n",
+       "\u001B[2;36m             \u001B[0mcloud.                                                             \n"
+      ],
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">              </span>To cancel the simulation, use <span style=\"color: #008000; text-decoration-color: #008000\">'web.abort(task_id)'</span> or             \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">              </span><span style=\"color: #008000; text-decoration-color: #008000\">'web.delete(task_id)'</span> or abort/delete the task in the web UI.     \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">              </span>Terminating the Python script will not stop the job running on the\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">              </span>cloud.                                                            \n",
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>To cancel the simulation, use <span style=\"color: #008000; text-decoration-color: #008000\">'web.abort(task_id)'</span> or              \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'web.delete(task_id)'</span> or abort/delete the task in the web UI.      \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>Terminating the Python script will not stop the job running on the \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>cloud.                                                             \n",
        "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m             \u001b[0m\u001b[2;36m \u001b[0mTo cancel the simulation, use \u001b[32m'web.abort\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m or             \n",
-       "\u001b[2;36m              \u001b[0m\u001b[32m'web.delete\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m or abort/delete the task in the web UI.     \n",
-       "\u001b[2;36m              \u001b[0mTerminating the Python script will not stop the job running on the\n",
-       "\u001b[2;36m              \u001b[0mcloud.                                                            \n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "8f52ed0e3cc34d778fed8d4ea5cdeb6d",
-       "version_major": 2,
-       "version_minor": 0
-      },
       "text/plain": [
        "Output()"
-      ]
+      ],
+      "application/vnd.jupyter.widget-view+json": {
+       "version_major": 2,
+       "version_minor": 0,
+       "model_id": "16707bb8bc7d451c880f2da99069b66d"
+      }
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
+      "text/plain": [],
       "text/html": [
        "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
-      ],
-      "text/plain": []
+      ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
+      "text/plain": [
+       "\u001B[2;36m15:07:36 CET\u001B[0m\u001B[2;36m \u001B[0mstarting up solver                                                 \n"
+      ],
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">12:46:08 CEST </span>starting up solver                                                \n",
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">15:07:36 CET </span>starting up solver                                                 \n",
        "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m12:46:08 CEST\u001b[0m\u001b[2;36m \u001b[0mstarting up solver                                                \n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
+      "text/plain": [
+       "\u001B[2;36m            \u001B[0m\u001B[2;36m \u001B[0mrunning solver                                                     \n"
+      ],
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">12:46:09 CEST </span>running solver                                                    \n",
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>running solver                                                     \n",
        "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m12:46:09 CEST\u001b[0m\u001b[2;36m \u001b[0mrunning solver                                                    \n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
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     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
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-       "version_major": 2,
-       "version_minor": 0
-      },
       "text/plain": [
        "Output()"
-      ]
+      ],
+      "application/vnd.jupyter.widget-view+json": {
+       "version_major": 2,
+       "version_minor": 0,
+       "model_id": "d07527d88d2544169b48447f305621ea"
+      }
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
+      "text/plain": [],
       "text/html": [
        "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
-      ],
-      "text/plain": []
+      ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
+      "text/plain": [
+       "\u001B[2;36m15:07:37 CET\u001B[0m\u001B[2;36m \u001B[0mstatus = success                                                   \n"
+      ],
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">              </span>status = success                                                  \n",
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">15:07:37 CET </span>status = success                                                   \n",
        "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m             \u001b[0m\u001b[2;36m \u001b[0mstatus = success                                                  \n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
+      "text/plain": [],
       "text/html": [
        "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
-      ],
-      "text/plain": []
+      ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
+      "text/plain": [
+       "\u001B[2;36m            \u001B[0m\u001B[2;36m \u001B[0mView simulation result at                                          \n",
+       "\u001B[2;36m             \u001B[0m\u001B]8;id=107730;https://tidy3d.simulation.cloud/workbench?taskId=fdve-fae17aac-8105-4166-a1a7-6cf1b414a498\u001B\\\u001B[4;34m'https://tidy3d.simulation.cloud/workbench?\u001B[0m\u001B]8;;\u001B\\\u001B]8;id=30983;https://tidy3d.simulation.cloud/workbench?taskId=fdve-fae17aac-8105-4166-a1a7-6cf1b414a498\u001B\\\u001B[4;34mtaskId\u001B[0m\u001B]8;;\u001B\\\u001B]8;id=107730;https://tidy3d.simulation.cloud/workbench?taskId=fdve-fae17aac-8105-4166-a1a7-6cf1b414a498\u001B\\\u001B[4;34m=\u001B[0m\u001B]8;;\u001B\\\u001B]8;id=150243;https://tidy3d.simulation.cloud/workbench?taskId=fdve-fae17aac-8105-4166-a1a7-6cf1b414a498\u001B\\\u001B[4;34mfdve\u001B[0m\u001B]8;;\u001B\\\u001B]8;id=107730;https://tidy3d.simulation.cloud/workbench?taskId=fdve-fae17aac-8105-4166-a1a7-6cf1b414a498\u001B\\\u001B[4;34m-fae17aac-810\u001B[0m\u001B]8;;\u001B\\\n",
+       "\u001B[2;36m             \u001B[0m\u001B]8;id=107730;https://tidy3d.simulation.cloud/workbench?taskId=fdve-fae17aac-8105-4166-a1a7-6cf1b414a498\u001B\\\u001B[4;34m5-4166-a1a7-6cf1b414a498'\u001B[0m\u001B]8;;\u001B\\\u001B[4;34m.\u001B[0m                                         \n"
+      ],
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">              </span>View simulation result at                                         \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">              </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-c6b4767e-c643-4268-94d8-752d2f8d6b0a\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-c6b4767e-c6</span></a>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">              </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-c6b4767e-c643-4268-94d8-752d2f8d6b0a\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">43-4268-94d8-752d2f8d6b0a'</span></a><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">.</span>                                       \n",
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>View simulation result at                                          \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-fae17aac-8105-4166-a1a7-6cf1b414a498\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-fae17aac-810</span></a>\n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-fae17aac-8105-4166-a1a7-6cf1b414a498\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">5-4166-a1a7-6cf1b414a498'</span></a><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">.</span>                                         \n",
        "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m             \u001b[0m\u001b[2;36m \u001b[0mView simulation result at                                         \n",
-       "\u001b[2;36m              \u001b[0m\u001b]8;id=40432;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c6b4767e-c643-4268-94d8-752d2f8d6b0a\u001b\\\u001b[4;34m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=616319;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c6b4767e-c643-4268-94d8-752d2f8d6b0a\u001b\\\u001b[4;34mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=40432;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c6b4767e-c643-4268-94d8-752d2f8d6b0a\u001b\\\u001b[4;34m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=217017;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c6b4767e-c643-4268-94d8-752d2f8d6b0a\u001b\\\u001b[4;34mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=40432;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c6b4767e-c643-4268-94d8-752d2f8d6b0a\u001b\\\u001b[4;34m-c6b4767e-c6\u001b[0m\u001b]8;;\u001b\\\n",
-       "\u001b[2;36m              \u001b[0m\u001b]8;id=40432;https://tidy3d.simulation.cloud/workbench?taskId=fdve-c6b4767e-c643-4268-94d8-752d2f8d6b0a\u001b\\\u001b[4;34m43-4268-94d8-752d2f8d6b0a'\u001b[0m\u001b]8;;\u001b\\\u001b[4;34m.\u001b[0m                                       \n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "ba1573a181244ba4a146c24c675b3279",
-       "version_major": 2,
-       "version_minor": 0
-      },
       "text/plain": [
        "Output()"
-      ]
+      ],
+      "application/vnd.jupyter.widget-view+json": {
+       "version_major": 2,
+       "version_minor": 0,
+       "model_id": "f5f26b8688c5414a8b552ea38351f003"
+      }
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
+      "text/plain": [],
       "text/html": [
        "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
-      ],
-      "text/plain": []
+      ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
+      "text/plain": [
+       "\u001B[2;36m15:07:40 CET\u001B[0m\u001B[2;36m \u001B[0mLoading simulation from data/data.hdf5                             \n"
+      ],
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">12:46:11 CEST </span>loading simulation from data/data.hdf5                            \n",
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">15:07:40 CET </span>Loading simulation from data/data.hdf5                             \n",
        "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m12:46:11 CEST\u001b[0m\u001b[2;36m \u001b[0mloading simulation from data/data.hdf5                            \n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
+      "text/plain": [
+       "\u001B[2;36m            \u001B[0m\u001B[2;36m \u001B[0m\u001B[31mWARNING: Simulation final field decay value of \u001B[0m\u001B[1;36m0.00665\u001B[0m\u001B[31m is greater  \u001B[0m\n",
+       "\u001B[2;36m             \u001B[0m\u001B[31mthan the simulation shutoff threshold of \u001B[0m\u001B[1;36m1e-05\u001B[0m\u001B[31m. Consider running   \u001B[0m\n",
+       "\u001B[2;36m             \u001B[0m\u001B[31mthe simulation again with a larger \u001B[0m\u001B[32m'run_time'\u001B[0m\u001B[31m duration for more    \u001B[0m\n",
+       "\u001B[2;36m             \u001B[0m\u001B[31maccurate results.                                                  \u001B[0m\n"
+      ],
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">              </span><span style=\"color: #800000; text-decoration-color: #800000\">WARNING: Simulation final field decay value of </span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00665</span><span style=\"color: #800000; text-decoration-color: #800000\"> is greater </span>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">              </span><span style=\"color: #800000; text-decoration-color: #800000\">than the simulation shutoff threshold of </span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1e-05</span><span style=\"color: #800000; text-decoration-color: #800000\">. Consider running  </span>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">              </span><span style=\"color: #800000; text-decoration-color: #800000\">the simulation again with a larger </span><span style=\"color: #008000; text-decoration-color: #008000\">'run_time'</span><span style=\"color: #800000; text-decoration-color: #800000\"> duration for more   </span>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">              </span><span style=\"color: #800000; text-decoration-color: #800000\">accurate results.                                                 </span>\n",
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #800000; text-decoration-color: #800000\">WARNING: Simulation final field decay value of </span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00665</span><span style=\"color: #800000; text-decoration-color: #800000\"> is greater  </span>\n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #800000; text-decoration-color: #800000\">than the simulation shutoff threshold of </span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1e-05</span><span style=\"color: #800000; text-decoration-color: #800000\">. Consider running   </span>\n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #800000; text-decoration-color: #800000\">the simulation again with a larger </span><span style=\"color: #008000; text-decoration-color: #008000\">'run_time'</span><span style=\"color: #800000; text-decoration-color: #800000\"> duration for more    </span>\n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #800000; text-decoration-color: #800000\">accurate results.                                                  </span>\n",
        "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m             \u001b[0m\u001b[2;36m \u001b[0m\u001b[31mWARNING: Simulation final field decay value of \u001b[0m\u001b[1;36m0.00665\u001b[0m\u001b[31m is greater \u001b[0m\n",
-       "\u001b[2;36m              \u001b[0m\u001b[31mthan the simulation shutoff threshold of \u001b[0m\u001b[1;36m1e-05\u001b[0m\u001b[31m. Consider running  \u001b[0m\n",
-       "\u001b[2;36m              \u001b[0m\u001b[31mthe simulation again with a larger \u001b[0m\u001b[32m'run_time'\u001b[0m\u001b[31m duration for more   \u001b[0m\n",
-       "\u001b[2;36m              \u001b[0m\u001b[31maccurate results.                                                 \u001b[0m\n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     }
    ],
-   "source": [
-    "sim_data = web.run(sim, task_name=\"web_demo\", path=\"data/data.hdf5\", verbose=True)"
-   ]
+   "execution_count": 22
   },
   {
    "cell_type": "markdown",
@@ -1381,14 +1576,13 @@
    "metadata": {},
    "source": [
     "### Containers and Batching\n",
+    "Since `Tidy3D` version `2.10`, [web.run](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.web.api.run.run.html) is also capable of running any nested combination of lists, tuples, and dictionaries of simulations and returning them in the same structure. The legacy function `web.run_async` will be deprecated.\n",
     "\n",
     "The convenience containers [Job](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.web.api.container.Job.html#tidy3d.web.Job) and [Batch](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.web.api.container.Batch.html#tidy3d.web.Batch) allow one to manage single and multiple tasks in a more \"object oriented\" fashion.\n",
     "\n",
     "They follow the same basic API as the `web.` functions, except [Batch](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.web.api.container.Batch.html#tidy3d.web.Batch) objects accept a dictionary of simulations and return generators that can be iterated through to give [SimulationData](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.SimulationData.html) for each task, rather than returning it one by one.  This cuts down on memory for several large jobs.  \n",
     "\n",
-    "While we won't cover all of the details here, for more information, see the [tutorial on the Web API](../notebooks/Webapi/index.html) or look at the examples in the other notebooks.\n",
-    "\n",
-    "Finally, we provide [web.run_async](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.web.api.asynchronous.run_async.html), which is like `web.run()` but runs a dictionary of simulations asynchronously, and is more convenient than `Batch` in some cases."
+    "While we won't cover all of the details here, for more information, see the [tutorial on the Web API](../notebooks/Webapi/index.html) or look at the examples in the other notebooks.\n"
    ]
   },
   {
@@ -1419,43 +1613,54 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
    "id": "b4632332",
-   "metadata": {},
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:07:40.324750Z",
+     "start_time": "2025-10-29T14:07:40.163427Z"
+    }
+   },
+   "source": [
+    "# print the log, which is stored as an attribute rather than as its own file\n",
+    "print(sim_data.log)\n",
+    "\n",
+    "# get a copy of the original Simulation, so it also doesn't need to be stored separately\n",
+    "sim_data.simulation.help()"
+   ],
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[10:46:03] USER: Simulation domain Nx, Ny, Nz: [20, 44, 20]                     \n",
+      "[14:07:31] USER: Simulation domain Nx, Ny, Nz: [20, 44, 20]                     \n",
       "           USER: Applied symmetries: (0, 0, 0)                                  \n",
       "           USER: Number of computational grid points: 1.8400e+04.               \n",
       "           USER: Subpixel averaging method: SubpixelSpec(attrs={},              \n",
       "           dielectric=PolarizedAveraging(attrs={}, type='PolarizedAveraging'),  \n",
       "           metal=Staircasing(attrs={}, type='Staircasing'),                     \n",
       "           pec=PECConformal(attrs={}, type='PECConformal',                      \n",
-      "           timestep_reduction=0.3, edge_singularity_correction=False),          \n",
+      "           timestep_reduction=0.3, edge_singularity_correction=True),           \n",
       "           pmc=Staircasing(attrs={}, type='Staircasing'),                       \n",
       "           lossy_metal=SurfaceImpedance(attrs={}, type='SurfaceImpedance',      \n",
-      "           timestep_reduction=0.0, edge_singularity_correction=False),          \n",
+      "           timestep_reduction=0.0, edge_singularity_correction=True),           \n",
       "           type='SubpixelSpec')                                                 \n",
       "           USER: Number of time steps: 2.6240e+03                               \n",
       "           USER: Automatic shutoff factor: 1.00e-05                             \n",
       "           USER: Time step (s): 3.8131e-16                                      \n",
       "           USER:                                                                \n",
       "                                                                                \n",
-      "           USER: Compute source modes time (s):     0.0580                      \n",
-      "[10:46:04] USER: Rest of setup time (s):            0.4879                      \n",
-      "[10:46:05] USER: Compute monitor modes time (s):    0.0001                      \n",
-      "           USER: Solver time (s):                   0.3410                      \n",
-      "           USER: Time-stepping speed (cells/s):     1.48e+08                    \n",
-      "[10:46:06] USER: Post-processing time (s):          0.3213                      \n",
+      "           USER: Compute source modes time (s):     0.0500                      \n",
+      "           USER: Rest of setup time (s):            0.2928                      \n",
+      "[14:07:32] USER: Compute monitor modes time (s):    0.0001                      \n",
+      "           USER: Solver time (s):                   0.3610                      \n",
+      "           USER: Time-stepping speed (cells/s):     1.40e+08                    \n",
+      "[14:07:33] USER: Post-processing time (s):          0.1782                      \n",
       "\n",
       " ====== SOLVER LOG ====== \n",
       "\n",
       "Processing grid and structures...\n",
       "Building FDTD update coefficients...\n",
-      "Solver setup time (s):             0.0125\n",
+      "Solver setup time (s):             0.0139\n",
       "\n",
       "Running solver for 2624 time steps...\n",
       "- Time step    104 / time 3.97e-14s (  4 % done), field decay: 1.00e+00\n",
@@ -1483,73 +1688,873 @@
       "- Time step   2414 / time 9.20e-13s ( 92 % done), field decay: 2.74e-02\n",
       "- Time step   2519 / time 9.61e-13s ( 96 % done), field decay: 6.95e-03\n",
       "- Time step   2623 / time 1.00e-12s (100 % done), field decay: 6.65e-03\n",
-      "Time-stepping time (s):            0.3278\n",
-      "Data write time (s):               0.0009\n",
+      "Time-stepping time (s):            0.3460\n",
+      "Data write time (s):               0.0014\n",
       "\n"
      ]
     },
     {
      "data": {
+      "text/plain": [
+       "\u001B[2;36m            \u001B[0m\u001B[2;36m \u001B[0m\u001B[31mWARNING: \u001B[0m\u001B[32m'Simulation.background_structure'\u001B[0m\u001B[31m will be removed in      \u001B[0m\n",
+       "\u001B[2;36m             \u001B[0m\u001B[31mTidy3D \u001B[0m\u001B[1;36m3.0\u001B[0m\u001B[31m. Use \u001B[0m\u001B[32m'Simulation.scene.background_structure'\u001B[0m\u001B[31m instead.   \u001B[0m\n"
+      ],
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">12:46:12 CEST </span><span style=\"color: #800000; text-decoration-color: #800000\">WARNING: </span><span style=\"color: #008000; text-decoration-color: #008000\">'Simulation.background_structure'</span><span style=\"color: #800000; text-decoration-color: #800000\"> will be removed in     </span>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">              </span><span style=\"color: #800000; text-decoration-color: #800000\">Tidy3D </span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.0</span><span style=\"color: #800000; text-decoration-color: #800000\">. Use </span><span style=\"color: #008000; text-decoration-color: #008000\">'Simulation.scene.background_structure'</span><span style=\"color: #800000; text-decoration-color: #800000\"> instead.  </span>\n",
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #800000; text-decoration-color: #800000\">WARNING: </span><span style=\"color: #008000; text-decoration-color: #008000\">'Simulation.background_structure'</span><span style=\"color: #800000; text-decoration-color: #800000\"> will be removed in      </span>\n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #800000; text-decoration-color: #800000\">Tidy3D </span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.0</span><span style=\"color: #800000; text-decoration-color: #800000\">. Use </span><span style=\"color: #008000; text-decoration-color: #008000\">'Simulation.scene.background_structure'</span><span style=\"color: #800000; text-decoration-color: #800000\"> instead.   </span>\n",
        "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m12:46:12 CEST\u001b[0m\u001b[2;36m \u001b[0m\u001b[31mWARNING: \u001b[0m\u001b[32m'Simulation.background_structure'\u001b[0m\u001b[31m will be removed in     \u001b[0m\n",
-       "\u001b[2;36m              \u001b[0m\u001b[31mTidy3D \u001b[0m\u001b[1;36m3.0\u001b[0m\u001b[31m. Use \u001b[0m\u001b[32m'Simulation.scene.background_structure'\u001b[0m\u001b[31m instead.  \u001b[0m\n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
+      "text/plain": [
+       "\u001B[2;36m            \u001B[0m\u001B[2;36m \u001B[0m\u001B[31mWARNING: \u001B[0m\u001B[32m'Simulation.bounds_pml'\u001B[0m\u001B[31m will be removed in Tidy3D \u001B[0m\u001B[1;36m3.0\u001B[0m\u001B[31m. Use\u001B[0m\n",
+       "\u001B[2;36m             \u001B[0m\u001B[32m'Simulation.simulation_bounds'\u001B[0m\u001B[31m instead.                            \u001B[0m\n"
+      ],
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">              </span><span style=\"color: #800000; text-decoration-color: #800000\">WARNING: </span><span style=\"color: #008000; text-decoration-color: #008000\">'Simulation.bounds_pml'</span><span style=\"color: #800000; text-decoration-color: #800000\"> will be removed in Tidy3D </span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.0</span><span style=\"color: #800000; text-decoration-color: #800000\">.   </span>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">              </span><span style=\"color: #800000; text-decoration-color: #800000\">Use </span><span style=\"color: #008000; text-decoration-color: #008000\">'Simulation.simulation_bounds'</span><span style=\"color: #800000; text-decoration-color: #800000\"> instead.                       </span>\n",
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #800000; text-decoration-color: #800000\">WARNING: </span><span style=\"color: #008000; text-decoration-color: #008000\">'Simulation.bounds_pml'</span><span style=\"color: #800000; text-decoration-color: #800000\"> will be removed in Tidy3D </span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.0</span><span style=\"color: #800000; text-decoration-color: #800000\">. Use</span>\n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'Simulation.simulation_bounds'</span><span style=\"color: #800000; text-decoration-color: #800000\"> instead.                            </span>\n",
        "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m             \u001b[0m\u001b[2;36m \u001b[0m\u001b[31mWARNING: \u001b[0m\u001b[32m'Simulation.bounds_pml'\u001b[0m\u001b[31m will be removed in Tidy3D \u001b[0m\u001b[1;36m3.0\u001b[0m\u001b[31m.   \u001b[0m\n",
-       "\u001b[2;36m              \u001b[0m\u001b[31mUse \u001b[0m\u001b[32m'Simulation.simulation_bounds'\u001b[0m\u001b[31m instead.                       \u001b[0m\n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
+      "text/plain": [
+       "\u001B[2;36m            \u001B[0m\u001B[2;36m \u001B[0m\u001B[31mWARNING: \u001B[0m\u001B[32m'Simulation.medium_map'\u001B[0m\u001B[31m will be removed in Tidy3D \u001B[0m\u001B[1;36m3.0\u001B[0m\u001B[31m. Use\u001B[0m\n",
+       "\u001B[2;36m             \u001B[0m\u001B[32m'Simulation.scene.medium_map'\u001B[0m\u001B[31m instead.                             \u001B[0m\n"
+      ],
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">              </span><span style=\"color: #800000; text-decoration-color: #800000\">WARNING: </span><span style=\"color: #008000; text-decoration-color: #008000\">'Simulation.medium_map'</span><span style=\"color: #800000; text-decoration-color: #800000\"> will be removed in Tidy3D </span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.0</span><span style=\"color: #800000; text-decoration-color: #800000\">.   </span>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">              </span><span style=\"color: #800000; text-decoration-color: #800000\">Use </span><span style=\"color: #008000; text-decoration-color: #008000\">'Simulation.scene.medium_map'</span><span style=\"color: #800000; text-decoration-color: #800000\"> instead.                        </span>\n",
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #800000; text-decoration-color: #800000\">WARNING: </span><span style=\"color: #008000; text-decoration-color: #008000\">'Simulation.medium_map'</span><span style=\"color: #800000; text-decoration-color: #800000\"> will be removed in Tidy3D </span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.0</span><span style=\"color: #800000; text-decoration-color: #800000\">. Use</span>\n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'Simulation.scene.medium_map'</span><span style=\"color: #800000; text-decoration-color: #800000\"> instead.                             </span>\n",
        "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m             \u001b[0m\u001b[2;36m \u001b[0m\u001b[31mWARNING: \u001b[0m\u001b[32m'Simulation.medium_map'\u001b[0m\u001b[31m will be removed in Tidy3D \u001b[0m\u001b[1;36m3.0\u001b[0m\u001b[31m.   \u001b[0m\n",
-       "\u001b[2;36m              \u001b[0m\u001b[31mUse \u001b[0m\u001b[32m'Simulation.scene.medium_map'\u001b[0m\u001b[31m instead.                        \u001b[0m\n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
+      "text/plain": [
+       "\u001B[2;36m            \u001B[0m\u001B[2;36m \u001B[0m\u001B[31mWARNING: \u001B[0m\u001B[32m'Simulation.mediums'\u001B[0m\u001B[31m will be removed in Tidy3D \u001B[0m\u001B[1;36m3.0\u001B[0m\u001B[31m. Use   \u001B[0m\n",
+       "\u001B[2;36m             \u001B[0m\u001B[32m'Simulation.scene.mediums'\u001B[0m\u001B[31m instead.                                \u001B[0m\n"
+      ],
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">              </span><span style=\"color: #800000; text-decoration-color: #800000\">WARNING: </span><span style=\"color: #008000; text-decoration-color: #008000\">'Simulation.mediums'</span><span style=\"color: #800000; text-decoration-color: #800000\"> will be removed in Tidy3D </span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.0</span><span style=\"color: #800000; text-decoration-color: #800000\">. Use  </span>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">              </span><span style=\"color: #008000; text-decoration-color: #008000\">'Simulation.scene.mediums'</span><span style=\"color: #800000; text-decoration-color: #800000\"> instead.                               </span>\n",
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #800000; text-decoration-color: #800000\">WARNING: </span><span style=\"color: #008000; text-decoration-color: #008000\">'Simulation.mediums'</span><span style=\"color: #800000; text-decoration-color: #800000\"> will be removed in Tidy3D </span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.0</span><span style=\"color: #800000; text-decoration-color: #800000\">. Use   </span>\n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'Simulation.scene.mediums'</span><span style=\"color: #800000; text-decoration-color: #800000\"> instead.                                </span>\n",
        "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m             \u001b[0m\u001b[2;36m \u001b[0m\u001b[31mWARNING: \u001b[0m\u001b[32m'Simulation.mediums'\u001b[0m\u001b[31m will be removed in Tidy3D \u001b[0m\u001b[1;36m3.0\u001b[0m\u001b[31m. Use  \u001b[0m\n",
-       "\u001b[2;36m              \u001b[0m\u001b[32m'Simulation.scene.mediums'\u001b[0m\u001b[31m instead.                               \u001b[0m\n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
+      "text/plain": [
+       "\u001B[34m╭─\u001B[0m\u001B[34m──────────────────────────────\u001B[0m\u001B[34m \u001B[0m\u001B[1;34m<\u001B[0m\u001B[1;95mclass\u001B[0m\u001B[39m \u001B[0m\u001B[32m'tidy3d.components.simulation.Simulation'\u001B[0m\u001B[1;34m>\u001B[0m\u001B[34m \u001B[0m\u001B[34m──────────────────────────────\u001B[0m\u001B[34m─╮\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[36mCustom implementation of Maxwell’s equations which represents the physical model to be solved using the FDTD\u001B[0m    \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[36mmethod.\u001B[0m                                                                                                         \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                                                                                                 \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m╭─────────────────────────────────────────────────────────────────────────────────────────────────────────────╮\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[1;35mSimulation\u001B[0m\u001B[1m(\u001B[0m                                                                                                 \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   \u001B[0m\u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                                                               \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   \u001B[0m\u001B[33mtype\u001B[0m=\u001B[32m'Simulation'\u001B[0m,                                                                                      \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   \u001B[0m\u001B[33mcenter\u001B[0m=\u001B[1m(\u001B[0m\u001B[1;36m0.0\u001B[0m, \u001B[1;36m0.0\u001B[0m, \u001B[1;36m0.0\u001B[0m\u001B[1m)\u001B[0m,                                                                                 \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   \u001B[0m\u001B[33msize\u001B[0m=\u001B[1m(\u001B[0m\u001B[1;36m4.0\u001B[0m, \u001B[1;36m4.0\u001B[0m, \u001B[1;36m4.0\u001B[0m\u001B[1m)\u001B[0m,                                                                                   \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   \u001B[0m\u001B[33mmedium\u001B[0m=\u001B[1;35mMedium\u001B[0m\u001B[1m(\u001B[0m                                                                                          \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   \u001B[0m\u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                                                           \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   \u001B[0m\u001B[33mname\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                                                          \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   \u001B[0m\u001B[33mfrequency_range\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                                               \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   \u001B[0m\u001B[33mallow_gain\u001B[0m=\u001B[3;91mFalse\u001B[0m,                                                                                   \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   \u001B[0m\u001B[33mnonlinear_spec\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                                                \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   \u001B[0m\u001B[33mmodulation_spec\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                                               \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   \u001B[0m\u001B[33mviz_spec\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                                                      \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   \u001B[0m\u001B[33mheat_spec\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                                                     \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   \u001B[0m\u001B[33mtype\u001B[0m=\u001B[32m'Medium'\u001B[0m,                                                                                      \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   \u001B[0m\u001B[33mpermittivity\u001B[0m=\u001B[1;36m1\u001B[0m\u001B[1;36m.0\u001B[0m,                                                                                   \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   \u001B[0m\u001B[33mconductivity\u001B[0m=\u001B[1;36m0\u001B[0m\u001B[1;36m.0\u001B[0m                                                                                    \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   \u001B[0m\u001B[1m)\u001B[0m,                                                                                                      \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   \u001B[0m\u001B[33mstructures\u001B[0m=\u001B[1m(\u001B[0m                                                                                            \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   \u001B[0m\u001B[1;35mStructure\u001B[0m\u001B[1m(\u001B[0m                                                                                          \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   \u001B[0m\u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                                                       \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   \u001B[0m\u001B[33mgeometry\u001B[0m=\u001B[1;35mBox\u001B[0m\u001B[1m(\u001B[0m\u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m, \u001B[33mtype\u001B[0m=\u001B[32m'Box'\u001B[0m, \u001B[33mcenter\u001B[0m=\u001B[1m(\u001B[0m\u001B[1;36m0.0\u001B[0m, \u001B[1;36m0.0\u001B[0m, \u001B[1;36m0.0\u001B[0m\u001B[1m)\u001B[0m, \u001B[33msize\u001B[0m=\u001B[1m(\u001B[0m\u001B[1;36m1.0\u001B[0m, \u001B[1;36m1.0\u001B[0m, \u001B[1;36m1.0\u001B[0m\u001B[1m)\u001B[0m\u001B[1m)\u001B[0m,               \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   \u001B[0m\u001B[33mname\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                                                      \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   \u001B[0m\u001B[33mbackground_permittivity\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                                   \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   \u001B[0m\u001B[33mbackground_medium\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                                         \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   \u001B[0m\u001B[33mpriority\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                                                  \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   \u001B[0m\u001B[33mtype\u001B[0m=\u001B[32m'Structure'\u001B[0m,                                                                               \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   \u001B[0m\u001B[33mmedium\u001B[0m=\u001B[1;35mMedium\u001B[0m\u001B[1m(\u001B[0m                                                                                  \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   │   \u001B[0m\u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                                                   \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   │   \u001B[0m\u001B[33mname\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                                                  \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   │   \u001B[0m\u001B[33mfrequency_range\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                                       \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   │   \u001B[0m\u001B[33mallow_gain\u001B[0m=\u001B[3;91mFalse\u001B[0m,                                                                           \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   │   \u001B[0m\u001B[33mnonlinear_spec\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                                        \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   │   \u001B[0m\u001B[33mmodulation_spec\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                                       \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   │   \u001B[0m\u001B[33mviz_spec\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                                              \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   │   \u001B[0m\u001B[33mheat_spec\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                                             \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   │   \u001B[0m\u001B[33mtype\u001B[0m=\u001B[32m'Medium'\u001B[0m,                                                                              \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   │   \u001B[0m\u001B[33mpermittivity\u001B[0m=\u001B[1;36m2\u001B[0m\u001B[1;36m.0\u001B[0m,                                                                           \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   │   \u001B[0m\u001B[33mconductivity\u001B[0m=\u001B[1;36m0\u001B[0m\u001B[1;36m.0\u001B[0m                                                                            \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   \u001B[0m\u001B[1m)\u001B[0m                                                                                               \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   \u001B[0m\u001B[1m)\u001B[0m,                                                                                                  \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   \u001B[0m\u001B[1m)\u001B[0m,                                                                                                      \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   \u001B[0m\u001B[33msymmetry\u001B[0m=\u001B[1m(\u001B[0m\u001B[1;36m0\u001B[0m, \u001B[1;36m0\u001B[0m, \u001B[1;36m0\u001B[0m\u001B[1m)\u001B[0m,                                                                                     \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   \u001B[0m\u001B[33msources\u001B[0m=\u001B[1m(\u001B[0m                                                                                               \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   \u001B[0m\u001B[1;35mUniformCurrentSource\u001B[0m\u001B[1m(\u001B[0m                                                                               \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   \u001B[0m\u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                                                       \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   \u001B[0m\u001B[33mname\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                                                      \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   \u001B[0m\u001B[33mtype\u001B[0m=\u001B[32m'UniformCurrentSource'\u001B[0m,                                                                    \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   \u001B[0m\u001B[33mcenter\u001B[0m=\u001B[1m(\u001B[0m\u001B[1;36m0.0\u001B[0m, \u001B[1;36m0.0\u001B[0m, \u001B[1;36m0.0\u001B[0m\u001B[1m)\u001B[0m,                                                                         \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   \u001B[0m\u001B[33msize\u001B[0m=\u001B[1m(\u001B[0m\u001B[1;36m0.0\u001B[0m, \u001B[1;36m0.0\u001B[0m, \u001B[1;36m0.0\u001B[0m\u001B[1m)\u001B[0m,                                                                           \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   \u001B[0m\u001B[33msource_time\u001B[0m=\u001B[1;35mGaussianPulse\u001B[0m\u001B[1m(\u001B[0m                                                                      \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   │   \u001B[0m\u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                                                   \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   │   \u001B[0m\u001B[33mamplitude\u001B[0m=\u001B[1;36m1\u001B[0m\u001B[1;36m.0\u001B[0m,                                                                              \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   │   \u001B[0m\u001B[33mphase\u001B[0m=\u001B[1;36m0\u001B[0m\u001B[1;36m.0\u001B[0m,                                                                                  \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   │   \u001B[0m\u001B[33mtype\u001B[0m=\u001B[32m'GaussianPulse'\u001B[0m,                                                                       \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   │   \u001B[0m\u001B[33mfreq0\u001B[0m=\u001B[1;36m150000000000000\u001B[0m\u001B[1;36m.0\u001B[0m,                                                                    \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   │   \u001B[0m\u001B[33mfwidth\u001B[0m=\u001B[1;36m10000000000000\u001B[0m\u001B[1;36m.0\u001B[0m,                                                                    \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   │   \u001B[0m\u001B[33moffset\u001B[0m=\u001B[1;36m5\u001B[0m\u001B[1;36m.0\u001B[0m,                                                                                 \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   │   \u001B[0m\u001B[33mremove_dc_component\u001B[0m=\u001B[3;92mTrue\u001B[0m                                                                    \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   \u001B[0m\u001B[1m)\u001B[0m,                                                                                              \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   \u001B[0m\u001B[33minterpolate\u001B[0m=\u001B[3;92mTrue\u001B[0m,                                                                               \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   \u001B[0m\u001B[33mconfine_to_bounds\u001B[0m=\u001B[3;91mFalse\u001B[0m,                                                                        \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   \u001B[0m\u001B[33mpolarization\u001B[0m=\u001B[32m'Ez'\u001B[0m                                                                               \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   \u001B[0m\u001B[1m)\u001B[0m,                                                                                                  \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   \u001B[0m\u001B[1m)\u001B[0m,                                                                                                      \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   \u001B[0m\u001B[33mboundary_spec\u001B[0m=\u001B[1;35mBoundarySpec\u001B[0m\u001B[1m(\u001B[0m                                                                             \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   \u001B[0m\u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                                                           \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   \u001B[0m\u001B[33mx\u001B[0m=\u001B[1;35mBoundary\u001B[0m\u001B[1m(\u001B[0m                                                                                         \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   \u001B[0m\u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                                                       \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   \u001B[0m\u001B[33mplus\u001B[0m=\u001B[1;35mPeriodic\u001B[0m\u001B[1m(\u001B[0m\u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m, \u001B[33mname\u001B[0m=\u001B[3;35mNone\u001B[0m, \u001B[33mtype\u001B[0m=\u001B[32m'Periodic'\u001B[0m\u001B[1m)\u001B[0m,                                            \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   \u001B[0m\u001B[33mminus\u001B[0m=\u001B[1;35mPeriodic\u001B[0m\u001B[1m(\u001B[0m\u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m, \u001B[33mname\u001B[0m=\u001B[3;35mNone\u001B[0m, \u001B[33mtype\u001B[0m=\u001B[32m'Periodic'\u001B[0m\u001B[1m)\u001B[0m,                                           \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   \u001B[0m\u001B[33mtype\u001B[0m=\u001B[32m'Boundary'\u001B[0m                                                                                 \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   \u001B[0m\u001B[1m)\u001B[0m,                                                                                                  \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   \u001B[0m\u001B[33my\u001B[0m=\u001B[1;35mBoundary\u001B[0m\u001B[1m(\u001B[0m                                                                                         \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   \u001B[0m\u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                                                       \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   \u001B[0m\u001B[33mplus\u001B[0m=\u001B[1;35mPML\u001B[0m\u001B[1m(\u001B[0m                                                                                       \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   │   \u001B[0m\u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                                                   \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   │   \u001B[0m\u001B[33mname\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                                                  \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   │   \u001B[0m\u001B[33mtype\u001B[0m=\u001B[32m'PML'\u001B[0m,                                                                                 \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   │   \u001B[0m\u001B[33mnum_layers\u001B[0m=\u001B[1;36m12\u001B[0m,                                                                              \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   │   \u001B[0m\u001B[33mparameters\u001B[0m=\u001B[1;35mPMLParams\u001B[0m\u001B[1m(\u001B[0m                                                                       \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   │   │   \u001B[0m\u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                                               \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   │   │   \u001B[0m\u001B[33msigma_order\u001B[0m=\u001B[1;36m3\u001B[0m,                                                                          \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   │   │   \u001B[0m\u001B[33msigma_min\u001B[0m=\u001B[1;36m0\u001B[0m\u001B[1;36m.0\u001B[0m,                                                                          \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   │   │   \u001B[0m\u001B[33msigma_max\u001B[0m=\u001B[1;36m1\u001B[0m\u001B[1;36m.5\u001B[0m,                                                                          \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   │   │   \u001B[0m\u001B[33mtype\u001B[0m=\u001B[32m'PMLParams'\u001B[0m,                                                                       \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   │   │   \u001B[0m\u001B[33mkappa_order\u001B[0m=\u001B[1;36m3\u001B[0m,                                                                          \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   │   │   \u001B[0m\u001B[33mkappa_min\u001B[0m=\u001B[1;36m1\u001B[0m\u001B[1;36m.0\u001B[0m,                                                                          \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   │   │   \u001B[0m\u001B[33mkappa_max\u001B[0m=\u001B[1;36m3\u001B[0m\u001B[1;36m.0\u001B[0m,                                                                          \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   │   │   \u001B[0m\u001B[33malpha_order\u001B[0m=\u001B[1;36m1\u001B[0m,                                                                          \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   │   │   \u001B[0m\u001B[33malpha_min\u001B[0m=\u001B[1;36m0\u001B[0m\u001B[1;36m.0\u001B[0m,                                                                          \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   │   │   \u001B[0m\u001B[33malpha_max\u001B[0m=\u001B[1;36m0\u001B[0m\u001B[1;36m.0\u001B[0m                                                                           \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   │   \u001B[0m\u001B[1m)\u001B[0m                                                                                           \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   \u001B[0m\u001B[1m)\u001B[0m,                                                                                              \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   \u001B[0m\u001B[33mminus\u001B[0m=\u001B[1;35mPML\u001B[0m\u001B[1m(\u001B[0m                                                                                      \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   │   \u001B[0m\u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                                                   \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   │   \u001B[0m\u001B[33mname\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                                                  \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   │   \u001B[0m\u001B[33mtype\u001B[0m=\u001B[32m'PML'\u001B[0m,                                                                                 \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   │   \u001B[0m\u001B[33mnum_layers\u001B[0m=\u001B[1;36m12\u001B[0m,                                                                              \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   │   \u001B[0m\u001B[33mparameters\u001B[0m=\u001B[1;35mPMLParams\u001B[0m\u001B[1m(\u001B[0m                                                                       \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   │   │   \u001B[0m\u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                                               \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   │   │   \u001B[0m\u001B[33msigma_order\u001B[0m=\u001B[1;36m3\u001B[0m,                                                                          \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   │   │   \u001B[0m\u001B[33msigma_min\u001B[0m=\u001B[1;36m0\u001B[0m\u001B[1;36m.0\u001B[0m,                                                                          \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   │   │   \u001B[0m\u001B[33msigma_max\u001B[0m=\u001B[1;36m1\u001B[0m\u001B[1;36m.5\u001B[0m,                                                                          \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   │   │   \u001B[0m\u001B[33mtype\u001B[0m=\u001B[32m'PMLParams'\u001B[0m,                                                                       \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   │   │   \u001B[0m\u001B[33mkappa_order\u001B[0m=\u001B[1;36m3\u001B[0m,                                                                          \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   │   │   \u001B[0m\u001B[33mkappa_min\u001B[0m=\u001B[1;36m1\u001B[0m\u001B[1;36m.0\u001B[0m,                                                                          \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   │   │   \u001B[0m\u001B[33mkappa_max\u001B[0m=\u001B[1;36m3\u001B[0m\u001B[1;36m.0\u001B[0m,                                                                          \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   │   │   \u001B[0m\u001B[33malpha_order\u001B[0m=\u001B[1;36m1\u001B[0m,                                                                          \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   │   │   \u001B[0m\u001B[33malpha_min\u001B[0m=\u001B[1;36m0\u001B[0m\u001B[1;36m.0\u001B[0m,                                                                          \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   │   │   \u001B[0m\u001B[33malpha_max\u001B[0m=\u001B[1;36m0\u001B[0m\u001B[1;36m.0\u001B[0m                                                                           \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   │   \u001B[0m\u001B[1m)\u001B[0m                                                                                           \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   \u001B[0m\u001B[1m)\u001B[0m,                                                                                              \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   \u001B[0m\u001B[33mtype\u001B[0m=\u001B[32m'Boundary'\u001B[0m                                                                                 \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   \u001B[0m\u001B[1m)\u001B[0m,                                                                                                  \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   \u001B[0m\u001B[33mz\u001B[0m=\u001B[1;35mBoundary\u001B[0m\u001B[1m(\u001B[0m                                                                                         \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   \u001B[0m\u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                                                       \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   \u001B[0m\u001B[33mplus\u001B[0m=\u001B[1;35mPeriodic\u001B[0m\u001B[1m(\u001B[0m\u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m, \u001B[33mname\u001B[0m=\u001B[3;35mNone\u001B[0m, \u001B[33mtype\u001B[0m=\u001B[32m'Periodic'\u001B[0m\u001B[1m)\u001B[0m,                                            \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   \u001B[0m\u001B[33mminus\u001B[0m=\u001B[1;35mPeriodic\u001B[0m\u001B[1m(\u001B[0m\u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m, \u001B[33mname\u001B[0m=\u001B[3;35mNone\u001B[0m, \u001B[33mtype\u001B[0m=\u001B[32m'Periodic'\u001B[0m\u001B[1m)\u001B[0m,                                           \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   \u001B[0m\u001B[33mtype\u001B[0m=\u001B[32m'Boundary'\u001B[0m                                                                                 \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   \u001B[0m\u001B[1m)\u001B[0m,                                                                                                  \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   \u001B[0m\u001B[33mtype\u001B[0m=\u001B[32m'BoundarySpec'\u001B[0m                                                                                 \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   \u001B[0m\u001B[1m)\u001B[0m,                                                                                                      \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   \u001B[0m\u001B[33mmonitors\u001B[0m=\u001B[1m(\u001B[0m                                                                                              \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   \u001B[0m\u001B[1;35mFieldMonitor\u001B[0m\u001B[1m(\u001B[0m                                                                                       \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   \u001B[0m\u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                                                       \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   \u001B[0m\u001B[33mtype\u001B[0m=\u001B[32m'FieldMonitor'\u001B[0m,                                                                            \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   \u001B[0m\u001B[33mcenter\u001B[0m=\u001B[1m(\u001B[0m\u001B[1;36m1.0\u001B[0m, \u001B[1;36m0.0\u001B[0m, \u001B[1;36m0.0\u001B[0m\u001B[1m)\u001B[0m,                                                                         \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   \u001B[0m\u001B[33msize\u001B[0m=\u001B[1m(\u001B[0minf, inf, \u001B[1;36m0.0\u001B[0m\u001B[1m)\u001B[0m,                                                                           \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   \u001B[0m\u001B[33mname\u001B[0m=\u001B[32m'fields_at_150THz'\u001B[0m,                                                                        \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   \u001B[0m\u001B[33minterval_space\u001B[0m=\u001B[1m(\u001B[0m\u001B[1;36m1\u001B[0m, \u001B[1;36m1\u001B[0m, \u001B[1;36m1\u001B[0m\u001B[1m)\u001B[0m,                                                                       \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   \u001B[0m\u001B[33mcolocate\u001B[0m=\u001B[3;92mTrue\u001B[0m,                                                                                  \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   \u001B[0m\u001B[33mfreqs\u001B[0m=\u001B[1m(\u001B[0m\u001B[1;36m150000000000000.0\u001B[0m,\u001B[1m)\u001B[0m,                                                                     \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   \u001B[0m\u001B[33mapodization\u001B[0m=\u001B[1;35mApodizationSpec\u001B[0m\u001B[1m(\u001B[0m                                                                    \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   │   \u001B[0m\u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                                                   \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   │   \u001B[0m\u001B[33mstart\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                                                 \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   │   \u001B[0m\u001B[33mend\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                                                   \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   │   \u001B[0m\u001B[33mwidth\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                                                 \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   │   \u001B[0m\u001B[33mtype\u001B[0m=\u001B[32m'ApodizationSpec'\u001B[0m                                                                      \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   \u001B[0m\u001B[1m)\u001B[0m,                                                                                              \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   \u001B[0m\u001B[33mfields\u001B[0m=\u001B[1m(\u001B[0m\u001B[32m'Ex'\u001B[0m, \u001B[32m'Ey'\u001B[0m, \u001B[32m'Hz'\u001B[0m\u001B[1m)\u001B[0m                                                                       \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   \u001B[0m\u001B[1m)\u001B[0m,                                                                                                  \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   \u001B[0m\u001B[1;35mFluxTimeMonitor\u001B[0m\u001B[1m(\u001B[0m                                                                                    \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   \u001B[0m\u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                                                       \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   \u001B[0m\u001B[33mtype\u001B[0m=\u001B[32m'FluxTimeMonitor'\u001B[0m,                                                                         \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   \u001B[0m\u001B[33mcenter\u001B[0m=\u001B[1m(\u001B[0m\u001B[1;36m1.0\u001B[0m, \u001B[1;36m0.0\u001B[0m, \u001B[1;36m0.0\u001B[0m\u001B[1m)\u001B[0m,                                                                         \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   \u001B[0m\u001B[33msize\u001B[0m=\u001B[1m(\u001B[0minf, inf, \u001B[1;36m0.0\u001B[0m\u001B[1m)\u001B[0m,                                                                           \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   \u001B[0m\u001B[33mname\u001B[0m=\u001B[32m'flux_over_time'\u001B[0m,                                                                          \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   \u001B[0m\u001B[33minterval_space\u001B[0m=\u001B[1m(\u001B[0m\u001B[1;36m1\u001B[0m, \u001B[1;36m1\u001B[0m, \u001B[1;36m1\u001B[0m\u001B[1m)\u001B[0m,                                                                       \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   \u001B[0m\u001B[33mcolocate\u001B[0m=\u001B[3;92mTrue\u001B[0m,                                                                                  \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   \u001B[0m\u001B[33mstart\u001B[0m=\u001B[1;36m1e\u001B[0m\u001B[1;36m-13\u001B[0m,                                                                                    \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   \u001B[0m\u001B[33mstop\u001B[0m=\u001B[1;36m3e\u001B[0m\u001B[1;36m-13\u001B[0m,                                                                                     \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   \u001B[0m\u001B[33minterval\u001B[0m=\u001B[1;36m5\u001B[0m,                                                                                     \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   \u001B[0m\u001B[33mnormal_dir\u001B[0m=\u001B[32m'+'\u001B[0m,                                                                                 \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   \u001B[0m\u001B[33mexclude_surfaces\u001B[0m=\u001B[3;35mNone\u001B[0m                                                                           \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   \u001B[0m\u001B[1m)\u001B[0m                                                                                                   \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   \u001B[0m\u001B[1m)\u001B[0m,                                                                                                      \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   \u001B[0m\u001B[33mgrid_spec\u001B[0m=\u001B[1;35mGridSpec\u001B[0m\u001B[1m(\u001B[0m                                                                                     \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   \u001B[0m\u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                                                           \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   \u001B[0m\u001B[33mgrid_x\u001B[0m=\u001B[1;35mUniformGrid\u001B[0m\u001B[1m(\u001B[0m\u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m, \u001B[33mtype\u001B[0m=\u001B[32m'UniformGrid'\u001B[0m, \u001B[33mdl\u001B[0m=\u001B[1;36m0\u001B[0m\u001B[1;36m.2\u001B[0m\u001B[1m)\u001B[0m,                                           \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   \u001B[0m\u001B[33mgrid_y\u001B[0m=\u001B[1;35mUniformGrid\u001B[0m\u001B[1m(\u001B[0m\u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m, \u001B[33mtype\u001B[0m=\u001B[32m'UniformGrid'\u001B[0m, \u001B[33mdl\u001B[0m=\u001B[1;36m0\u001B[0m\u001B[1;36m.2\u001B[0m\u001B[1m)\u001B[0m,                                           \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   \u001B[0m\u001B[33mgrid_z\u001B[0m=\u001B[1;35mUniformGrid\u001B[0m\u001B[1m(\u001B[0m\u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m, \u001B[33mtype\u001B[0m=\u001B[32m'UniformGrid'\u001B[0m, \u001B[33mdl\u001B[0m=\u001B[1;36m0\u001B[0m\u001B[1;36m.2\u001B[0m\u001B[1m)\u001B[0m,                                           \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   \u001B[0m\u001B[33mwavelength\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                                                    \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   \u001B[0m\u001B[33moverride_structures\u001B[0m=\u001B[1m(\u001B[0m\u001B[1m)\u001B[0m,                                                                             \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   \u001B[0m\u001B[33msnapping_points\u001B[0m=\u001B[1m(\u001B[0m\u001B[1m)\u001B[0m,                                                                                 \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   \u001B[0m\u001B[33mlayer_refinement_specs\u001B[0m=\u001B[1m(\u001B[0m\u001B[1m)\u001B[0m,                                                                          \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   \u001B[0m\u001B[33mtype\u001B[0m=\u001B[32m'GridSpec'\u001B[0m                                                                                     \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   \u001B[0m\u001B[1m)\u001B[0m,                                                                                                      \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   \u001B[0m\u001B[33mversion\u001B[0m=\u001B[32m'2.10.0rc3'\u001B[0m,                                                                                    \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   \u001B[0m\u001B[33mplot_length_units\u001B[0m=\u001B[32m'μm'\u001B[0m,                                                                                 \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   \u001B[0m\u001B[33mstructure_priority_mode\u001B[0m=\u001B[32m'equal'\u001B[0m,                                                                        \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   \u001B[0m\u001B[33mlumped_elements\u001B[0m=\u001B[1m(\u001B[0m\u001B[1m)\u001B[0m,                                                                                     \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   \u001B[0m\u001B[33msubpixel\u001B[0m=\u001B[1;35mSubpixelSpec\u001B[0m\u001B[1m(\u001B[0m                                                                                  \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   \u001B[0m\u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                                                           \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   \u001B[0m\u001B[33mdielectric\u001B[0m=\u001B[1;35mPolarizedAveraging\u001B[0m\u001B[1m(\u001B[0m\u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m, \u001B[33mtype\u001B[0m=\u001B[32m'PolarizedAveraging'\u001B[0m\u001B[1m)\u001B[0m,                                 \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   \u001B[0m\u001B[33mmetal\u001B[0m=\u001B[1;35mStaircasing\u001B[0m\u001B[1m(\u001B[0m\u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m, \u001B[33mtype\u001B[0m=\u001B[32m'Staircasing'\u001B[0m\u001B[1m)\u001B[0m,                                                    \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   \u001B[0m\u001B[33mpec\u001B[0m=\u001B[1;35mPECConformal\u001B[0m\u001B[1m(\u001B[0m                                                                                   \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   \u001B[0m\u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                                                       \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   \u001B[0m\u001B[33mtype\u001B[0m=\u001B[32m'PECConformal'\u001B[0m,                                                                            \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   \u001B[0m\u001B[33mtimestep_reduction\u001B[0m=\u001B[1;36m0\u001B[0m\u001B[1;36m.3\u001B[0m,                                                                         \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   \u001B[0m\u001B[33medge_singularity_correction\u001B[0m=\u001B[3;92mTrue\u001B[0m                                                                \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   \u001B[0m\u001B[1m)\u001B[0m,                                                                                                  \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   \u001B[0m\u001B[33mpmc\u001B[0m=\u001B[1;35mStaircasing\u001B[0m\u001B[1m(\u001B[0m\u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m, \u001B[33mtype\u001B[0m=\u001B[32m'Staircasing'\u001B[0m\u001B[1m)\u001B[0m,                                                      \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   \u001B[0m\u001B[33mlossy_metal\u001B[0m=\u001B[1;35mSurfaceImpedance\u001B[0m\u001B[1m(\u001B[0m                                                                       \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   \u001B[0m\u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                                                       \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   \u001B[0m\u001B[33mtype\u001B[0m=\u001B[32m'SurfaceImpedance'\u001B[0m,                                                                        \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   \u001B[0m\u001B[33mtimestep_reduction\u001B[0m=\u001B[1;36m0\u001B[0m\u001B[1;36m.0\u001B[0m,                                                                         \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   │   \u001B[0m\u001B[33medge_singularity_correction\u001B[0m=\u001B[3;92mTrue\u001B[0m                                                                \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   \u001B[0m\u001B[1m)\u001B[0m,                                                                                                  \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   │   \u001B[0m\u001B[33mtype\u001B[0m=\u001B[32m'SubpixelSpec'\u001B[0m                                                                                 \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   \u001B[0m\u001B[1m)\u001B[0m,                                                                                                      \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   \u001B[0m\u001B[33msimulation_type\u001B[0m=\u001B[32m'tidy3d'\u001B[0m,                                                                               \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   \u001B[0m\u001B[33mpost_norm\u001B[0m=\u001B[1;36m1\u001B[0m\u001B[1;36m.0\u001B[0m,                                                                                          \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   \u001B[0m\u001B[33minternal_absorbers\u001B[0m=\u001B[1m(\u001B[0m\u001B[1m)\u001B[0m,                                                                                  \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   \u001B[0m\u001B[33mcourant\u001B[0m=\u001B[1;36m0\u001B[0m\u001B[1;36m.99\u001B[0m,                                                                                           \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   \u001B[0m\u001B[33mprecision\u001B[0m=\u001B[32m'hybrid'\u001B[0m,                                                                                     \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   \u001B[0m\u001B[33mnormalize_index\u001B[0m=\u001B[1;36m0\u001B[0m,                                                                                      \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   \u001B[0m\u001B[33mshutoff\u001B[0m=\u001B[1;36m1e\u001B[0m\u001B[1;36m-05\u001B[0m,                                                                                          \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   \u001B[0m\u001B[33mrun_time\u001B[0m=\u001B[1;36m1e\u001B[0m\u001B[1;36m-12\u001B[0m,                                                                                         \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[2;32m│   \u001B[0m\u001B[33mlow_freq_smoothing\u001B[0m=\u001B[3;35mNone\u001B[0m                                                                                 \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m│\u001B[0m \u001B[1m)\u001B[0m                                                                                                           \u001B[32m│\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[32m╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────╯\u001B[0m \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                                                                                                 \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                \u001B[3;33mall_structures\u001B[0m = \u001B[1m[\u001B[0m                                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[1;35mStructure\u001B[0m\u001B[1m(\u001B[0m                                                                  \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mgeometry\u001B[0m=\u001B[1;35mBox\u001B[0m\u001B[1m(\u001B[0m                                                           \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                           \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mtype\u001B[0m=\u001B[32m'Box'\u001B[0m,                                                         \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mcenter\u001B[0m=\u001B[1m(\u001B[0m\u001B[1;36m0.0\u001B[0m, \u001B[1;36m0.0\u001B[0m, \u001B[1;36m0.0\u001B[0m\u001B[1m)\u001B[0m,                                             \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33msize\u001B[0m=\u001B[1m(\u001B[0minf, inf, inf\u001B[1m)\u001B[0m                                                \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[1m)\u001B[0m,                                                                      \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mname\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                              \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mbackground_permittivity\u001B[0m=\u001B[3;35mNone\u001B[0m,                                           \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mbackground_medium\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                 \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mpriority\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                          \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mtype\u001B[0m=\u001B[32m'Structure'\u001B[0m,                                                       \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mmedium\u001B[0m=\u001B[1;35mMedium\u001B[0m\u001B[1m(\u001B[0m                                                          \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                           \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mname\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                          \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mfrequency_range\u001B[0m=\u001B[3;35mNone\u001B[0m,                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mallow_gain\u001B[0m=\u001B[3;91mFalse\u001B[0m,                                                   \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mnonlinear_spec\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mmodulation_spec\u001B[0m=\u001B[3;35mNone\u001B[0m,                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mviz_spec\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                      \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mheat_spec\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                     \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mtype\u001B[0m=\u001B[32m'Medium'\u001B[0m,                                                      \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mpermittivity\u001B[0m=\u001B[1;36m1\u001B[0m\u001B[1;36m.0\u001B[0m,                                                   \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mconductivity\u001B[0m=\u001B[1;36m0\u001B[0m\u001B[1;36m.0\u001B[0m                                                    \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[1m)\u001B[0m                                                                       \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[1m)\u001B[0m,                                                                          \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[1;35mStructure\u001B[0m\u001B[1m(\u001B[0m                                                                  \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mgeometry\u001B[0m=\u001B[1;35mBox\u001B[0m\u001B[1m(\u001B[0m                                                           \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                           \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mtype\u001B[0m=\u001B[32m'Box'\u001B[0m,                                                         \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mcenter\u001B[0m=\u001B[1m(\u001B[0m\u001B[1;36m0.0\u001B[0m, \u001B[1;36m0.0\u001B[0m, \u001B[1;36m0.0\u001B[0m\u001B[1m)\u001B[0m,                                             \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33msize\u001B[0m=\u001B[1m(\u001B[0m\u001B[1;36m1.0\u001B[0m, \u001B[1;36m1.0\u001B[0m, \u001B[1;36m1.0\u001B[0m\u001B[1m)\u001B[0m                                                \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[1m)\u001B[0m,                                                                      \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mname\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                              \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mbackground_permittivity\u001B[0m=\u001B[3;35mNone\u001B[0m,                                           \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mbackground_medium\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                 \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mpriority\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                          \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mtype\u001B[0m=\u001B[32m'Structure'\u001B[0m,                                                       \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mmedium\u001B[0m=\u001B[1;35mMedium\u001B[0m\u001B[1m(\u001B[0m                                                          \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                           \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mname\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                          \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mfrequency_range\u001B[0m=\u001B[3;35mNone\u001B[0m,                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mallow_gain\u001B[0m=\u001B[3;91mFalse\u001B[0m,                                                   \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mnonlinear_spec\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mmodulation_spec\u001B[0m=\u001B[3;35mNone\u001B[0m,                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mviz_spec\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                      \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mheat_spec\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                     \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mtype\u001B[0m=\u001B[32m'Medium'\u001B[0m,                                                      \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mpermittivity\u001B[0m=\u001B[1;36m2\u001B[0m\u001B[1;36m.0\u001B[0m,                                                   \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mconductivity\u001B[0m=\u001B[1;36m0\u001B[0m\u001B[1;36m.0\u001B[0m                                                    \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[1m)\u001B[0m                                                                       \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[1m)\u001B[0m                                                                           \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                 \u001B[1m]\u001B[0m                                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                    \u001B[3;33mallow_gain\u001B[0m = \u001B[3;91mFalse\u001B[0m                                                                           \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                         \u001B[3;33mattrs\u001B[0m = \u001B[1m{\u001B[0m\u001B[1m}\u001B[0m                                                                              \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                    \u001B[3;33maux_fields\u001B[0m = \u001B[1m[\u001B[0m\u001B[1m]\u001B[0m                                                                              \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m          \u001B[3;33mbackground_structure\u001B[0m = \u001B[1;35mStructure\u001B[0m\u001B[1m(\u001B[0m                                                                      \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                                   \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mgeometry\u001B[0m=\u001B[1;35mBox\u001B[0m\u001B[1m(\u001B[0m                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mtype\u001B[0m=\u001B[32m'Box'\u001B[0m,                                                             \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mcenter\u001B[0m=\u001B[1m(\u001B[0m\u001B[1;36m0.0\u001B[0m, \u001B[1;36m0.0\u001B[0m, \u001B[1;36m0.0\u001B[0m\u001B[1m)\u001B[0m,                                                 \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33msize\u001B[0m=\u001B[1m(\u001B[0minf, inf, inf\u001B[1m)\u001B[0m                                                    \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[1m)\u001B[0m,                                                                          \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mname\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                                  \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mbackground_permittivity\u001B[0m=\u001B[3;35mNone\u001B[0m,                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mbackground_medium\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                     \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mpriority\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                              \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mtype\u001B[0m=\u001B[32m'Structure'\u001B[0m,                                                           \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mmedium\u001B[0m=\u001B[1;35mMedium\u001B[0m\u001B[1m(\u001B[0m                                                              \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mname\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                              \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mfrequency_range\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                   \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mallow_gain\u001B[0m=\u001B[3;91mFalse\u001B[0m,                                                       \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mnonlinear_spec\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                    \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mmodulation_spec\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                   \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mviz_spec\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                          \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mheat_spec\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                         \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mtype\u001B[0m=\u001B[32m'Medium'\u001B[0m,                                                          \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mpermittivity\u001B[0m=\u001B[1;36m1\u001B[0m\u001B[1;36m.0\u001B[0m,                                                       \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mconductivity\u001B[0m=\u001B[1;36m0\u001B[0m\u001B[1;36m.0\u001B[0m                                                        \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[1m)\u001B[0m                                                                           \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                 \u001B[1m)\u001B[0m                                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                 \u001B[3;33mboundary_spec\u001B[0m = \u001B[1;35mBoundarySpec\u001B[0m\u001B[1m(\u001B[0m                                                                   \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                                   \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mx\u001B[0m=\u001B[1;35mBoundary\u001B[0m\u001B[1m(\u001B[0m                                                                 \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mplus\u001B[0m=\u001B[1;35mPeriodic\u001B[0m\u001B[1m(\u001B[0m\u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m, \u001B[33mname\u001B[0m=\u001B[3;35mNone\u001B[0m, \u001B[33mtype\u001B[0m=\u001B[32m'Periodic'\u001B[0m\u001B[1m)\u001B[0m,                    \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mminus\u001B[0m=\u001B[1;35mPeriodic\u001B[0m\u001B[1m(\u001B[0m\u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m, \u001B[33mname\u001B[0m=\u001B[3;35mNone\u001B[0m, \u001B[33mtype\u001B[0m=\u001B[32m'Periodic'\u001B[0m\u001B[1m)\u001B[0m,                   \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mtype\u001B[0m=\u001B[32m'Boundary'\u001B[0m                                                         \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[1m)\u001B[0m,                                                                          \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33my\u001B[0m=\u001B[1;35mBoundary\u001B[0m\u001B[1m(\u001B[0m                                                                 \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mplus\u001B[0m=\u001B[1;35mPML\u001B[0m\u001B[1m(\u001B[0m                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                           \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mname\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                          \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mtype\u001B[0m=\u001B[32m'PML'\u001B[0m,                                                         \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mnum_layers\u001B[0m=\u001B[1;36m12\u001B[0m,                                                      \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mparameters\u001B[0m=\u001B[1;35mPMLParams\u001B[0m\u001B[1m(\u001B[0m                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                                 \u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                       \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                                 \u001B[33msigma_order\u001B[0m=\u001B[1;36m3\u001B[0m,                                                  \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                                 \u001B[33msigma_min\u001B[0m=\u001B[1;36m0\u001B[0m\u001B[1;36m.0\u001B[0m,                                                  \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                                 \u001B[33msigma_max\u001B[0m=\u001B[1;36m1\u001B[0m\u001B[1;36m.5\u001B[0m,                                                  \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                                 \u001B[33mtype\u001B[0m=\u001B[32m'PMLParams'\u001B[0m,                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                                 \u001B[33mkappa_order\u001B[0m=\u001B[1;36m3\u001B[0m,                                                  \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                                 \u001B[33mkappa_min\u001B[0m=\u001B[1;36m1\u001B[0m\u001B[1;36m.0\u001B[0m,                                                  \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                                 \u001B[33mkappa_max\u001B[0m=\u001B[1;36m3\u001B[0m\u001B[1;36m.0\u001B[0m,                                                  \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                                 \u001B[33malpha_order\u001B[0m=\u001B[1;36m1\u001B[0m,                                                  \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                                 \u001B[33malpha_min\u001B[0m=\u001B[1;36m0\u001B[0m\u001B[1;36m.0\u001B[0m,                                                  \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                                 \u001B[33malpha_max\u001B[0m=\u001B[1;36m0\u001B[0m\u001B[1;36m.0\u001B[0m                                                   \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[1m)\u001B[0m                                                                   \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[1m)\u001B[0m,                                                                      \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mminus\u001B[0m=\u001B[1;35mPML\u001B[0m\u001B[1m(\u001B[0m                                                              \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                           \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mname\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                          \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mtype\u001B[0m=\u001B[32m'PML'\u001B[0m,                                                         \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mnum_layers\u001B[0m=\u001B[1;36m12\u001B[0m,                                                      \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mparameters\u001B[0m=\u001B[1;35mPMLParams\u001B[0m\u001B[1m(\u001B[0m                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                                 \u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                       \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                                 \u001B[33msigma_order\u001B[0m=\u001B[1;36m3\u001B[0m,                                                  \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                                 \u001B[33msigma_min\u001B[0m=\u001B[1;36m0\u001B[0m\u001B[1;36m.0\u001B[0m,                                                  \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                                 \u001B[33msigma_max\u001B[0m=\u001B[1;36m1\u001B[0m\u001B[1;36m.5\u001B[0m,                                                  \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                                 \u001B[33mtype\u001B[0m=\u001B[32m'PMLParams'\u001B[0m,                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                                 \u001B[33mkappa_order\u001B[0m=\u001B[1;36m3\u001B[0m,                                                  \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                                 \u001B[33mkappa_min\u001B[0m=\u001B[1;36m1\u001B[0m\u001B[1;36m.0\u001B[0m,                                                  \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                                 \u001B[33mkappa_max\u001B[0m=\u001B[1;36m3\u001B[0m\u001B[1;36m.0\u001B[0m,                                                  \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                                 \u001B[33malpha_order\u001B[0m=\u001B[1;36m1\u001B[0m,                                                  \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                                 \u001B[33malpha_min\u001B[0m=\u001B[1;36m0\u001B[0m\u001B[1;36m.0\u001B[0m,                                                  \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                                 \u001B[33malpha_max\u001B[0m=\u001B[1;36m0\u001B[0m\u001B[1;36m.0\u001B[0m                                                   \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[1m)\u001B[0m                                                                   \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[1m)\u001B[0m,                                                                      \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mtype\u001B[0m=\u001B[32m'Boundary'\u001B[0m                                                         \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[1m)\u001B[0m,                                                                          \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mz\u001B[0m=\u001B[1;35mBoundary\u001B[0m\u001B[1m(\u001B[0m                                                                 \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mplus\u001B[0m=\u001B[1;35mPeriodic\u001B[0m\u001B[1m(\u001B[0m\u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m, \u001B[33mname\u001B[0m=\u001B[3;35mNone\u001B[0m, \u001B[33mtype\u001B[0m=\u001B[32m'Periodic'\u001B[0m\u001B[1m)\u001B[0m,                    \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mminus\u001B[0m=\u001B[1;35mPeriodic\u001B[0m\u001B[1m(\u001B[0m\u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m, \u001B[33mname\u001B[0m=\u001B[3;35mNone\u001B[0m, \u001B[33mtype\u001B[0m=\u001B[32m'Periodic'\u001B[0m\u001B[1m)\u001B[0m,                   \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mtype\u001B[0m=\u001B[32m'Boundary'\u001B[0m                                                         \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[1m)\u001B[0m,                                                                          \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mtype\u001B[0m=\u001B[32m'BoundarySpec'\u001B[0m                                                         \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                 \u001B[1m)\u001B[0m                                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                  \u001B[3;33mbounding_box\u001B[0m = \u001B[1;35mBox\u001B[0m\u001B[1m(\u001B[0m\u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m, \u001B[33mtype\u001B[0m=\u001B[32m'Box'\u001B[0m, \u001B[33mcenter\u001B[0m=\u001B[1m(\u001B[0m\u001B[1;36m0.0\u001B[0m, \u001B[1;36m0.0\u001B[0m, \u001B[1;36m0.0\u001B[0m\u001B[1m)\u001B[0m, \u001B[33msize\u001B[0m=\u001B[1m(\u001B[0m\u001B[1;36m4.0\u001B[0m, \u001B[1;36m4.0\u001B[0m, \u001B[1;36m4.0\u001B[0m\u001B[1m)\u001B[0m\u001B[1m)\u001B[0m         \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                        \u001B[3;33mbounds\u001B[0m = \u001B[1m(\u001B[0m\u001B[1m(\u001B[0m\u001B[1;36m-2.0\u001B[0m, \u001B[1;36m-2.0\u001B[0m, \u001B[1;36m-2.0\u001B[0m\u001B[1m)\u001B[0m, \u001B[1m(\u001B[0m\u001B[1;36m2.0\u001B[0m, \u001B[1;36m2.0\u001B[0m, \u001B[1;36m2.0\u001B[0m\u001B[1m)\u001B[0m\u001B[1m)\u001B[0m                                           \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                    \u001B[3;33mbounds_pml\u001B[0m = \u001B[1m(\u001B[0m                                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[1m(\u001B[0m\u001B[1;35mnp.float64\u001B[0m\u001B[1m(\u001B[0m\u001B[1;36m-2.0\u001B[0m\u001B[1m)\u001B[0m, \u001B[1;35mnp.float64\u001B[0m\u001B[1m(\u001B[0m\u001B[1;36m-4.3999999999999995\u001B[0m\u001B[1m)\u001B[0m, \u001B[1;35mnp.float64\u001B[0m\u001B[1m(\u001B[0m\u001B[1;36m-2.0\u001B[0m\u001B[1m)\u001B[0m\u001B[1m)\u001B[0m,      \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[1m(\u001B[0m\u001B[1;35mnp.float64\u001B[0m\u001B[1m(\u001B[0m\u001B[1;36m2.0\u001B[0m\u001B[1m)\u001B[0m, \u001B[1;35mnp.float64\u001B[0m\u001B[1m(\u001B[0m\u001B[1;36m4.399999999999997\u001B[0m\u001B[1m)\u001B[0m, \u001B[1;35mnp.float64\u001B[0m\u001B[1m(\u001B[0m\u001B[1;36m2.0\u001B[0m\u001B[1m)\u001B[0m\u001B[1m)\u001B[0m           \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                 \u001B[1m)\u001B[0m                                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                        \u001B[3;33mcenter\u001B[0m = \u001B[1m(\u001B[0m\u001B[1;36m0.0\u001B[0m, \u001B[1;36m0.0\u001B[0m, \u001B[1;36m0.0\u001B[0m\u001B[1m)\u001B[0m                                                                 \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                \u001B[3;33mcomplex_fields\u001B[0m = \u001B[3;91mFalse\u001B[0m                                                                           \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                       \u001B[3;33mcourant\u001B[0m = \u001B[1;36m0.99\u001B[0m                                                                            \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m               \u001B[3;33mcustom_datasets\u001B[0m = \u001B[1m[\u001B[0m\u001B[1m]\u001B[0m                                                                              \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                            \u001B[3;33mdt\u001B[0m = \u001B[1;35mnp.float64\u001B[0m\u001B[1m(\u001B[0m\u001B[1;36m3.813149739062003e-16\u001B[0m\u001B[1m)\u001B[0m                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m               \u001B[3;33mfrequency_range\u001B[0m = \u001B[1m(\u001B[0m\u001B[1;36m110770887769698.48\u001B[0m, \u001B[1;36m190588842668354.53\u001B[0m\u001B[1m)\u001B[0m                                        \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                      \u001B[3;33mgeometry\u001B[0m = \u001B[1;35mBox\u001B[0m\u001B[1m(\u001B[0m\u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m, \u001B[33mtype\u001B[0m=\u001B[32m'Box'\u001B[0m, \u001B[33mcenter\u001B[0m=\u001B[1m(\u001B[0m\u001B[1;36m0.0\u001B[0m, \u001B[1;36m0.0\u001B[0m, \u001B[1;36m0.0\u001B[0m\u001B[1m)\u001B[0m, \u001B[33msize\u001B[0m=\u001B[1m(\u001B[0m\u001B[1;36m4.0\u001B[0m, \u001B[1;36m4.0\u001B[0m, \u001B[1;36m4.0\u001B[0m\u001B[1m)\u001B[0m\u001B[1m)\u001B[0m         \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                          \u001B[3;33mgrid\u001B[0m = \u001B[1;35mGrid\u001B[0m\u001B[1m(\u001B[0m                                                                           \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                                   \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mboundaries\u001B[0m=\u001B[1;35mCoords\u001B[0m\u001B[1m(\u001B[0m                                                          \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mx\u001B[0m=\u001B[1;35marray\u001B[0m\u001B[1m(\u001B[0m\u001B[1m[\u001B[0m\u001B[1;36m-2\u001B[0m. , \u001B[1;36m-1.8\u001B[0m, \u001B[1;36m-1.6\u001B[0m, \u001B[1;36m-1.4\u001B[0m, \u001B[1;36m-1.2\u001B[0m, \u001B[1;36m-1\u001B[0m. , \u001B[1;36m-0.8\u001B[0m, \u001B[1;36m-0.6\u001B[0m, \u001B[1;36m-0.4\u001B[0m, \u001B[1;36m-0.2\u001B[0m,    \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                 \u001B[1;36m0\u001B[0m. ,                                                                            \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[1;36m0.2\u001B[0m,  \u001B[1;36m0.4\u001B[0m,  \u001B[1;36m0.6\u001B[0m,  \u001B[1;36m0.8\u001B[0m,  \u001B[1;36m1\u001B[0m. ,  \u001B[1;36m1.2\u001B[0m,  \u001B[1;36m1.4\u001B[0m,  \u001B[1;36m1.6\u001B[0m,  \u001B[1;36m1.8\u001B[0m,  \u001B[1;36m2\u001B[0m. \u001B[1m]\u001B[0m\u001B[1m)\u001B[0m,            \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33my\u001B[0m=\u001B[1;35marray\u001B[0m\u001B[1m(\u001B[0m\u001B[1m[\u001B[0m\u001B[1;36m-4.4\u001B[0m, \u001B[1;36m-4.2\u001B[0m, \u001B[1;36m-4\u001B[0m. , \u001B[1;36m-3.8\u001B[0m, \u001B[1;36m-3.6\u001B[0m, \u001B[1;36m-3.4\u001B[0m, \u001B[1;36m-3.2\u001B[0m, \u001B[1;36m-3\u001B[0m. , \u001B[1;36m-2.8\u001B[0m, \u001B[1;36m-2.6\u001B[0m,    \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                 \u001B[1;36m-2.4\u001B[0m,                                                                           \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                        \u001B[1;36m-2.2\u001B[0m, \u001B[1;36m-2\u001B[0m. , \u001B[1;36m-1.8\u001B[0m, \u001B[1;36m-1.6\u001B[0m, \u001B[1;36m-1.4\u001B[0m, \u001B[1;36m-1.2\u001B[0m, \u001B[1;36m-1\u001B[0m. , \u001B[1;36m-0.8\u001B[0m, \u001B[1;36m-0.6\u001B[0m, \u001B[1;36m-0.4\u001B[0m, \u001B[1;36m-0.2\u001B[0m,        \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[1;36m0\u001B[0m. ,  \u001B[1;36m0.2\u001B[0m,  \u001B[1;36m0.4\u001B[0m,  \u001B[1;36m0.6\u001B[0m,  \u001B[1;36m0.8\u001B[0m,  \u001B[1;36m1\u001B[0m. ,  \u001B[1;36m1.2\u001B[0m,  \u001B[1;36m1.4\u001B[0m,  \u001B[1;36m1.6\u001B[0m,  \u001B[1;36m1.8\u001B[0m,  \u001B[1;36m2\u001B[0m. ,        \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[1;36m2.2\u001B[0m,  \u001B[1;36m2.4\u001B[0m,  \u001B[1;36m2.6\u001B[0m,  \u001B[1;36m2.8\u001B[0m,  \u001B[1;36m3\u001B[0m. ,  \u001B[1;36m3.2\u001B[0m,  \u001B[1;36m3.4\u001B[0m,  \u001B[1;36m3.6\u001B[0m,  \u001B[1;36m3.8\u001B[0m,  \u001B[1;36m4\u001B[0m. ,  \u001B[1;36m4.2\u001B[0m,        \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[1;36m4.4\u001B[0m\u001B[1m]\u001B[0m\u001B[1m)\u001B[0m,                                                                  \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mz\u001B[0m=\u001B[1;35marray\u001B[0m\u001B[1m(\u001B[0m\u001B[1m[\u001B[0m\u001B[1;36m-2\u001B[0m. , \u001B[1;36m-1.8\u001B[0m, \u001B[1;36m-1.6\u001B[0m, \u001B[1;36m-1.4\u001B[0m, \u001B[1;36m-1.2\u001B[0m, \u001B[1;36m-1\u001B[0m. , \u001B[1;36m-0.8\u001B[0m, \u001B[1;36m-0.6\u001B[0m, \u001B[1;36m-0.4\u001B[0m, \u001B[1;36m-0.2\u001B[0m,    \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                 \u001B[1;36m0\u001B[0m. ,                                                                            \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[1;36m0.2\u001B[0m,  \u001B[1;36m0.4\u001B[0m,  \u001B[1;36m0.6\u001B[0m,  \u001B[1;36m0.8\u001B[0m,  \u001B[1;36m1\u001B[0m. ,  \u001B[1;36m1.2\u001B[0m,  \u001B[1;36m1.4\u001B[0m,  \u001B[1;36m1.6\u001B[0m,  \u001B[1;36m1.8\u001B[0m,  \u001B[1;36m2\u001B[0m. \u001B[1m]\u001B[0m\u001B[1m)\u001B[0m,            \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mtype\u001B[0m=\u001B[32m'Coords'\u001B[0m                                                           \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[1m)\u001B[0m,                                                                          \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mtype\u001B[0m=\u001B[32m'Grid'\u001B[0m                                                                 \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                 \u001B[1m)\u001B[0m                                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                     \u001B[3;33mgrid_info\u001B[0m = \u001B[1m{\u001B[0m                                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[32m'Nx'\u001B[0m: \u001B[1;36m20\u001B[0m,                                                                   \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[32m'Ny'\u001B[0m: \u001B[1;36m44\u001B[0m,                                                                   \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[32m'Nz'\u001B[0m: \u001B[1;36m20\u001B[0m,                                                                   \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[32m'grid_points'\u001B[0m: \u001B[1;36m17600\u001B[0m,                                                       \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[32m'min_grid_size'\u001B[0m: \u001B[1;36m0.1999999999999993\u001B[0m,                                        \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[32m'max_grid_size'\u001B[0m: \u001B[1;36m0.20000000000000018\u001B[0m,                                       \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[32m'computational_complexity'\u001B[0m: \u001B[1;36m88000.0000000003\u001B[0m                                \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                 \u001B[1m}\u001B[0m                                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                     \u001B[3;33mgrid_spec\u001B[0m = \u001B[1;35mGridSpec\u001B[0m\u001B[1m(\u001B[0m                                                                       \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                                   \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mgrid_x\u001B[0m=\u001B[1;35mUniformGrid\u001B[0m\u001B[1m(\u001B[0m\u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m, \u001B[33mtype\u001B[0m=\u001B[32m'UniformGrid'\u001B[0m, \u001B[33mdl\u001B[0m=\u001B[1;36m0\u001B[0m\u001B[1;36m.2\u001B[0m\u001B[1m)\u001B[0m,                   \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mgrid_y\u001B[0m=\u001B[1;35mUniformGrid\u001B[0m\u001B[1m(\u001B[0m\u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m, \u001B[33mtype\u001B[0m=\u001B[32m'UniformGrid'\u001B[0m, \u001B[33mdl\u001B[0m=\u001B[1;36m0\u001B[0m\u001B[1;36m.2\u001B[0m\u001B[1m)\u001B[0m,                   \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mgrid_z\u001B[0m=\u001B[1;35mUniformGrid\u001B[0m\u001B[1m(\u001B[0m\u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m, \u001B[33mtype\u001B[0m=\u001B[32m'UniformGrid'\u001B[0m, \u001B[33mdl\u001B[0m=\u001B[1;36m0\u001B[0m\u001B[1;36m.2\u001B[0m\u001B[1m)\u001B[0m,                   \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mwavelength\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                            \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33moverride_structures\u001B[0m=\u001B[1m(\u001B[0m\u001B[1m)\u001B[0m,                                                     \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33msnapping_points\u001B[0m=\u001B[1m(\u001B[0m\u001B[1m)\u001B[0m,                                                         \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mlayer_refinement_specs\u001B[0m=\u001B[1m(\u001B[0m\u001B[1m)\u001B[0m,                                                  \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mtype\u001B[0m=\u001B[32m'GridSpec'\u001B[0m                                                             \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                 \u001B[1m)\u001B[0m                                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m            \u001B[3;33minternal_absorbers\u001B[0m = \u001B[1m(\u001B[0m\u001B[1m)\u001B[0m                                                                              \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m  \u001B[3;33minternal_override_structures\u001B[0m = \u001B[1m[\u001B[0m\u001B[1m]\u001B[0m                                                                              \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m      \u001B[3;33minternal_snapping_points\u001B[0m = \u001B[1m[\u001B[0m\u001B[1m]\u001B[0m                                                                              \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m            \u001B[3;33mlow_freq_smoothing\u001B[0m = \u001B[3;35mNone\u001B[0m                                                                            \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m               \u001B[3;33mlumped_elements\u001B[0m = \u001B[1m(\u001B[0m\u001B[1m)\u001B[0m                                                                              \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                        \u001B[3;33mmedium\u001B[0m = \u001B[1;35mMedium\u001B[0m\u001B[1m(\u001B[0m                                                                         \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                                   \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mname\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                                  \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mfrequency_range\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                       \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mallow_gain\u001B[0m=\u001B[3;91mFalse\u001B[0m,                                                           \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mnonlinear_spec\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                        \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mmodulation_spec\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                       \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mviz_spec\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                              \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mheat_spec\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                             \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mtype\u001B[0m=\u001B[32m'Medium'\u001B[0m,                                                              \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mpermittivity\u001B[0m=\u001B[1;36m1\u001B[0m\u001B[1;36m.0\u001B[0m,                                                           \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mconductivity\u001B[0m=\u001B[1;36m0\u001B[0m\u001B[1;36m.0\u001B[0m                                                            \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                 \u001B[1m)\u001B[0m                                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                    \u001B[3;33mmedium_map\u001B[0m = \u001B[1m{\u001B[0m                                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[1;35mMedium\u001B[0m\u001B[1m(\u001B[0m\u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m, \u001B[33mname\u001B[0m=\u001B[3;35mNone\u001B[0m, \u001B[33mfrequency_range\u001B[0m=\u001B[3;35mNone\u001B[0m, \u001B[33mallow_gain\u001B[0m=\u001B[3;91mFalse\u001B[0m,         \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                 \u001B[33mnonlinear_spec\u001B[0m=\u001B[3;35mNone\u001B[0m, \u001B[33mmodulation_spec\u001B[0m=\u001B[3;35mNone\u001B[0m, \u001B[33mviz_spec\u001B[0m=\u001B[3;35mNone\u001B[0m, \u001B[33mheat_spec\u001B[0m=\u001B[3;35mNone\u001B[0m,       \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                 \u001B[33mtype\u001B[0m=\u001B[32m'Medium'\u001B[0m, \u001B[33mpermittivity\u001B[0m=\u001B[1;36m1\u001B[0m\u001B[1;36m.0\u001B[0m, \u001B[33mconductivity\u001B[0m=\u001B[1;36m0\u001B[0m\u001B[1;36m.0\u001B[0m\u001B[1m)\u001B[0m: \u001B[1;36m0\u001B[0m,                          \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[1;35mMedium\u001B[0m\u001B[1m(\u001B[0m\u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m, \u001B[33mname\u001B[0m=\u001B[3;35mNone\u001B[0m, \u001B[33mfrequency_range\u001B[0m=\u001B[3;35mNone\u001B[0m, \u001B[33mallow_gain\u001B[0m=\u001B[3;91mFalse\u001B[0m,         \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                 \u001B[33mnonlinear_spec\u001B[0m=\u001B[3;35mNone\u001B[0m, \u001B[33mmodulation_spec\u001B[0m=\u001B[3;35mNone\u001B[0m, \u001B[33mviz_spec\u001B[0m=\u001B[3;35mNone\u001B[0m, \u001B[33mheat_spec\u001B[0m=\u001B[3;35mNone\u001B[0m,       \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                 \u001B[33mtype\u001B[0m=\u001B[32m'Medium'\u001B[0m, \u001B[33mpermittivity\u001B[0m=\u001B[1;36m2\u001B[0m\u001B[1;36m.0\u001B[0m, \u001B[33mconductivity\u001B[0m=\u001B[1;36m0\u001B[0m\u001B[1;36m.0\u001B[0m\u001B[1m)\u001B[0m: \u001B[1;36m1\u001B[0m                           \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                 \u001B[1m}\u001B[0m                                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                       \u001B[3;33mmediums\u001B[0m = \u001B[1m[\u001B[0m                                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[1;35mMedium\u001B[0m\u001B[1m(\u001B[0m                                                                     \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mname\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                              \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mfrequency_range\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                   \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mallow_gain\u001B[0m=\u001B[3;91mFalse\u001B[0m,                                                       \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mnonlinear_spec\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                    \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mmodulation_spec\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                   \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mviz_spec\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                          \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mheat_spec\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                         \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mtype\u001B[0m=\u001B[32m'Medium'\u001B[0m,                                                          \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mpermittivity\u001B[0m=\u001B[1;36m1\u001B[0m\u001B[1;36m.0\u001B[0m,                                                       \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mconductivity\u001B[0m=\u001B[1;36m0\u001B[0m\u001B[1;36m.0\u001B[0m                                                        \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[1m)\u001B[0m,                                                                          \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[1;35mMedium\u001B[0m\u001B[1m(\u001B[0m                                                                     \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mname\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                              \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mfrequency_range\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                   \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mallow_gain\u001B[0m=\u001B[3;91mFalse\u001B[0m,                                                       \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mnonlinear_spec\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                    \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mmodulation_spec\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                   \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mviz_spec\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                          \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mheat_spec\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                         \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mtype\u001B[0m=\u001B[32m'Medium'\u001B[0m,                                                          \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mpermittivity\u001B[0m=\u001B[1;36m2\u001B[0m\u001B[1;36m.0\u001B[0m,                                                       \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mconductivity\u001B[0m=\u001B[1;36m0\u001B[0m\u001B[1;36m.0\u001B[0m                                                        \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[1m)\u001B[0m                                                                           \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                 \u001B[1m]\u001B[0m                                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                      \u001B[3;33mmonitors\u001B[0m = \u001B[1m(\u001B[0m                                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[1;35mFieldMonitor\u001B[0m\u001B[1m(\u001B[0m                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mtype\u001B[0m=\u001B[32m'FieldMonitor'\u001B[0m,                                                    \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mcenter\u001B[0m=\u001B[1m(\u001B[0m\u001B[1;36m1.0\u001B[0m, \u001B[1;36m0.0\u001B[0m, \u001B[1;36m0.0\u001B[0m\u001B[1m)\u001B[0m,                                                 \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33msize\u001B[0m=\u001B[1m(\u001B[0minf, inf, \u001B[1;36m0.0\u001B[0m\u001B[1m)\u001B[0m,                                                   \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mname\u001B[0m=\u001B[32m'fields_at_150THz'\u001B[0m,                                                \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33minterval_space\u001B[0m=\u001B[1m(\u001B[0m\u001B[1;36m1\u001B[0m, \u001B[1;36m1\u001B[0m, \u001B[1;36m1\u001B[0m\u001B[1m)\u001B[0m,                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mcolocate\u001B[0m=\u001B[3;92mTrue\u001B[0m,                                                          \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mfreqs\u001B[0m=\u001B[1m(\u001B[0m\u001B[1;36m150000000000000.0\u001B[0m,\u001B[1m)\u001B[0m,                                             \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mapodization\u001B[0m=\u001B[1;35mApodizationSpec\u001B[0m\u001B[1m(\u001B[0m                                            \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                           \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mstart\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                         \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mend\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                           \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mwidth\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                         \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mtype\u001B[0m=\u001B[32m'ApodizationSpec'\u001B[0m                                              \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[1m)\u001B[0m,                                                                      \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mfields\u001B[0m=\u001B[1m(\u001B[0m\u001B[32m'Ex'\u001B[0m, \u001B[32m'Ey'\u001B[0m, \u001B[32m'Hz'\u001B[0m\u001B[1m)\u001B[0m                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[1m)\u001B[0m,                                                                          \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[1;35mFluxTimeMonitor\u001B[0m\u001B[1m(\u001B[0m                                                            \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mtype\u001B[0m=\u001B[32m'FluxTimeMonitor'\u001B[0m,                                                 \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mcenter\u001B[0m=\u001B[1m(\u001B[0m\u001B[1;36m1.0\u001B[0m, \u001B[1;36m0.0\u001B[0m, \u001B[1;36m0.0\u001B[0m\u001B[1m)\u001B[0m,                                                 \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33msize\u001B[0m=\u001B[1m(\u001B[0minf, inf, \u001B[1;36m0.0\u001B[0m\u001B[1m)\u001B[0m,                                                   \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mname\u001B[0m=\u001B[32m'flux_over_time'\u001B[0m,                                                  \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33minterval_space\u001B[0m=\u001B[1m(\u001B[0m\u001B[1;36m1\u001B[0m, \u001B[1;36m1\u001B[0m, \u001B[1;36m1\u001B[0m\u001B[1m)\u001B[0m,                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mcolocate\u001B[0m=\u001B[3;92mTrue\u001B[0m,                                                          \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mstart\u001B[0m=\u001B[1;36m1e\u001B[0m\u001B[1;36m-13\u001B[0m,                                                            \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mstop\u001B[0m=\u001B[1;36m3e\u001B[0m\u001B[1;36m-13\u001B[0m,                                                             \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33minterval\u001B[0m=\u001B[1;36m5\u001B[0m,                                                             \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mnormal_dir\u001B[0m=\u001B[32m'+'\u001B[0m,                                                         \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mexclude_surfaces\u001B[0m=\u001B[3;35mNone\u001B[0m                                                   \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[1m)\u001B[0m                                                                           \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                 \u001B[1m)\u001B[0m                                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m            \u001B[3;33mmonitors_data_size\u001B[0m = \u001B[1m{\u001B[0m\u001B[32m'fields_at_150THz'\u001B[0m: \u001B[1;36m22680.0\u001B[0m, \u001B[32m'flux_over_time'\u001B[0m: \u001B[1;36m416.0\u001B[0m\u001B[1m}\u001B[0m                          \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                         \u001B[1;3;31mn_max\u001B[0m\u001B[1;31m =\u001B[0m \u001B[1;35mAttributeError\u001B[0m\u001B[1m(\u001B[0m\u001B[32m\"'Simulation' object has no attribute 'freq_max'\"\u001B[0m\u001B[1m)\u001B[0m               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m               \u001B[3;33mnormalize_index\u001B[0m = \u001B[1;36m0\u001B[0m                                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                     \u001B[3;33mnum_cells\u001B[0m = \u001B[1;36m17600\u001B[0m                                                                           \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m \u001B[3;33mnum_computational_grid_points\u001B[0m = \u001B[1;35mnp.int64\u001B[0m\u001B[1m(\u001B[0m\u001B[1;36m18400\u001B[0m\u001B[1m)\u001B[0m                                                                 \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                \u001B[3;33mnum_pml_layers\u001B[0m = \u001B[1m[\u001B[0m\u001B[1m[\u001B[0m\u001B[1;36m0\u001B[0m, \u001B[1;36m0\u001B[0m\u001B[1m]\u001B[0m, \u001B[1m[\u001B[0m\u001B[1;36m12\u001B[0m, \u001B[1;36m12\u001B[0m\u001B[1m]\u001B[0m, \u001B[1m[\u001B[0m\u001B[1;36m0\u001B[0m, \u001B[1;36m0\u001B[0m\u001B[1m]\u001B[0m\u001B[1m]\u001B[0m                                                      \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                \u001B[3;33mnum_time_steps\u001B[0m = \u001B[1;36m2624\u001B[0m                                                                            \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                  \u001B[3;33mnyquist_step\u001B[0m = \u001B[1;36m5\u001B[0m                                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m             \u001B[3;33mplot_length_units\u001B[0m = \u001B[32m'μm'\u001B[0m                                                                            \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                   \u001B[3;33mplot_params\u001B[0m = \u001B[1;35mPlotParams\u001B[0m\u001B[1m(\u001B[0m                                                                     \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                                   \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33malpha\u001B[0m=\u001B[1;36m1\u001B[0m\u001B[1;36m.0\u001B[0m,                                                                  \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mzorder\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                                \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mtype\u001B[0m=\u001B[32m'PlotParams'\u001B[0m,                                                          \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33medgecolor\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                             \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mfacecolor\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                             \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mfill\u001B[0m=\u001B[3;92mTrue\u001B[0m,                                                                  \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mhatch\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                                 \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mlinewidth\u001B[0m=\u001B[1;36m1\u001B[0m\u001B[1;36m.0\u001B[0m                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                 \u001B[1m)\u001B[0m                                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m               \u001B[3;33mpml_thicknesses\u001B[0m = \u001B[1m[\u001B[0m                                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[1m(\u001B[0m\u001B[1;35mnp.float64\u001B[0m\u001B[1m(\u001B[0m\u001B[1;36m0.0\u001B[0m\u001B[1m)\u001B[0m, \u001B[1;35mnp.float64\u001B[0m\u001B[1m(\u001B[0m\u001B[1;36m0.0\u001B[0m\u001B[1m)\u001B[0m\u001B[1m)\u001B[0m,                                         \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[1m(\u001B[0m\u001B[1;35mnp.float64\u001B[0m\u001B[1m(\u001B[0m\u001B[1;36m2.3999999999999995\u001B[0m\u001B[1m)\u001B[0m, \u001B[1;35mnp.float64\u001B[0m\u001B[1m(\u001B[0m\u001B[1;36m2.399999999999997\u001B[0m\u001B[1m)\u001B[0m\u001B[1m)\u001B[0m,            \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[1m(\u001B[0m\u001B[1;35mnp.float64\u001B[0m\u001B[1m(\u001B[0m\u001B[1;36m0.0\u001B[0m\u001B[1m)\u001B[0m, \u001B[1;35mnp.float64\u001B[0m\u001B[1m(\u001B[0m\u001B[1;36m0.0\u001B[0m\u001B[1m)\u001B[0m\u001B[1m)\u001B[0m                                          \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                 \u001B[1m]\u001B[0m                                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                     \u001B[3;33mpost_norm\u001B[0m = \u001B[1;36m1.0\u001B[0m                                                                             \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                     \u001B[3;33mprecision\u001B[0m = \u001B[32m'hybrid'\u001B[0m                                                                        \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                      \u001B[3;33mrun_time\u001B[0m = \u001B[1;36m1e-12\u001B[0m                                                                           \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                \u001B[3;33mscaled_courant\u001B[0m = \u001B[1;36m0.99\u001B[0m                                                                            \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                         \u001B[3;33mscene\u001B[0m = \u001B[1;35mScene\u001B[0m\u001B[1m(\u001B[0m                                                                          \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                                   \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mmedium\u001B[0m=\u001B[1;35mMedium\u001B[0m\u001B[1m(\u001B[0m                                                              \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mname\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                              \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mfrequency_range\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                   \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mallow_gain\u001B[0m=\u001B[3;91mFalse\u001B[0m,                                                       \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mnonlinear_spec\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                    \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mmodulation_spec\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                   \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mviz_spec\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                          \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mheat_spec\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                         \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mtype\u001B[0m=\u001B[32m'Medium'\u001B[0m,                                                          \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mpermittivity\u001B[0m=\u001B[1;36m1\u001B[0m\u001B[1;36m.0\u001B[0m,                                                       \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mconductivity\u001B[0m=\u001B[1;36m0\u001B[0m\u001B[1;36m.0\u001B[0m                                                        \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[1m)\u001B[0m,                                                                          \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mstructures\u001B[0m=\u001B[1m(\u001B[0m                                                                \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[1;35mStructure\u001B[0m\u001B[1m(\u001B[0m                                                              \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                           \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mgeometry\u001B[0m=\u001B[1;35mBox\u001B[0m\u001B[1m(\u001B[0m                                                       \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                                 \u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                       \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                                 \u001B[33mtype\u001B[0m=\u001B[32m'Box'\u001B[0m,                                                     \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                                 \u001B[33mcenter\u001B[0m=\u001B[1m(\u001B[0m\u001B[1;36m0.0\u001B[0m, \u001B[1;36m0.0\u001B[0m, \u001B[1;36m0.0\u001B[0m\u001B[1m)\u001B[0m,                                         \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                                 \u001B[33msize\u001B[0m=\u001B[1m(\u001B[0m\u001B[1;36m1.0\u001B[0m, \u001B[1;36m1.0\u001B[0m, \u001B[1;36m1.0\u001B[0m\u001B[1m)\u001B[0m                                            \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[1m)\u001B[0m,                                                                  \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mname\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                          \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mbackground_permittivity\u001B[0m=\u001B[3;35mNone\u001B[0m,                                       \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mbackground_medium\u001B[0m=\u001B[3;35mNone\u001B[0m,                                             \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mpriority\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                      \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mtype\u001B[0m=\u001B[32m'Structure'\u001B[0m,                                                   \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mmedium\u001B[0m=\u001B[1;35mMedium\u001B[0m\u001B[1m(\u001B[0m                                                      \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                                 \u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                       \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                                 \u001B[33mname\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                      \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                                 \u001B[33mfrequency_range\u001B[0m=\u001B[3;35mNone\u001B[0m,                                           \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                                 \u001B[33mallow_gain\u001B[0m=\u001B[3;91mFalse\u001B[0m,                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                                 \u001B[33mnonlinear_spec\u001B[0m=\u001B[3;35mNone\u001B[0m,                                            \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                                 \u001B[33mmodulation_spec\u001B[0m=\u001B[3;35mNone\u001B[0m,                                           \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                                 \u001B[33mviz_spec\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                  \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                                 \u001B[33mheat_spec\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                 \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                                 \u001B[33mtype\u001B[0m=\u001B[32m'Medium'\u001B[0m,                                                  \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                                 \u001B[33mpermittivity\u001B[0m=\u001B[1;36m2\u001B[0m\u001B[1;36m.0\u001B[0m,                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                                 \u001B[33mconductivity\u001B[0m=\u001B[1;36m0\u001B[0m\u001B[1;36m.0\u001B[0m                                                \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[1m)\u001B[0m                                                                   \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[1m)\u001B[0m,                                                                      \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[1m)\u001B[0m,                                                                          \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mstructure_priority_mode\u001B[0m=\u001B[32m'equal'\u001B[0m,                                            \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mplot_length_units\u001B[0m=\u001B[32m'μm'\u001B[0m,                                                     \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mtype\u001B[0m=\u001B[32m'Scene'\u001B[0m                                                                \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                 \u001B[1m)\u001B[0m                                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                \u001B[3;33mself_structure\u001B[0m = \u001B[1;35mStructure\u001B[0m\u001B[1m(\u001B[0m                                                                      \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                                   \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mgeometry\u001B[0m=\u001B[1;35mBox\u001B[0m\u001B[1m(\u001B[0m                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mtype\u001B[0m=\u001B[32m'Box'\u001B[0m,                                                             \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mcenter\u001B[0m=\u001B[1m(\u001B[0m\u001B[1;36m0.0\u001B[0m, \u001B[1;36m0.0\u001B[0m, \u001B[1;36m0.0\u001B[0m\u001B[1m)\u001B[0m,                                                 \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33msize\u001B[0m=\u001B[1m(\u001B[0minf, inf, inf\u001B[1m)\u001B[0m                                                    \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[1m)\u001B[0m,                                                                          \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mname\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                                  \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mbackground_permittivity\u001B[0m=\u001B[3;35mNone\u001B[0m,                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mbackground_medium\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                     \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mpriority\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                              \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mtype\u001B[0m=\u001B[32m'Structure'\u001B[0m,                                                           \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mmedium\u001B[0m=\u001B[1;35mMedium\u001B[0m\u001B[1m(\u001B[0m                                                              \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mname\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                              \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mfrequency_range\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                   \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mallow_gain\u001B[0m=\u001B[3;91mFalse\u001B[0m,                                                       \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mnonlinear_spec\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                    \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mmodulation_spec\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                   \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mviz_spec\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                          \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mheat_spec\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                         \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mtype\u001B[0m=\u001B[32m'Medium'\u001B[0m,                                                          \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mpermittivity\u001B[0m=\u001B[1;36m1\u001B[0m\u001B[1;36m.0\u001B[0m,                                                       \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mconductivity\u001B[0m=\u001B[1;36m0\u001B[0m\u001B[1;36m.0\u001B[0m                                                        \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[1m)\u001B[0m                                                                           \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                 \u001B[1m)\u001B[0m                                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                       \u001B[3;33mshutoff\u001B[0m = \u001B[1;36m1e-05\u001B[0m                                                                           \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m             \u001B[3;33msimulation_bounds\u001B[0m = \u001B[1m(\u001B[0m                                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[1m(\u001B[0m\u001B[1;35mnp.float64\u001B[0m\u001B[1m(\u001B[0m\u001B[1;36m-2.0\u001B[0m\u001B[1m)\u001B[0m, \u001B[1;35mnp.float64\u001B[0m\u001B[1m(\u001B[0m\u001B[1;36m-4.3999999999999995\u001B[0m\u001B[1m)\u001B[0m, \u001B[1;35mnp.float64\u001B[0m\u001B[1m(\u001B[0m\u001B[1;36m-2.0\u001B[0m\u001B[1m)\u001B[0m\u001B[1m)\u001B[0m,      \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[1m(\u001B[0m\u001B[1;35mnp.float64\u001B[0m\u001B[1m(\u001B[0m\u001B[1;36m2.0\u001B[0m\u001B[1m)\u001B[0m, \u001B[1;35mnp.float64\u001B[0m\u001B[1m(\u001B[0m\u001B[1;36m4.399999999999997\u001B[0m\u001B[1m)\u001B[0m, \u001B[1;35mnp.float64\u001B[0m\u001B[1m(\u001B[0m\u001B[1;36m2.0\u001B[0m\u001B[1m)\u001B[0m\u001B[1m)\u001B[0m           \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                 \u001B[1m)\u001B[0m                                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m           \u001B[3;33msimulation_geometry\u001B[0m = \u001B[1;35mBox\u001B[0m\u001B[1m(\u001B[0m                                                                            \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                                   \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mtype\u001B[0m=\u001B[32m'Box'\u001B[0m,                                                                 \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mcenter\u001B[0m=\u001B[1m(\u001B[0m                                                                    \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[1;35mnp.float64\u001B[0m\u001B[1m(\u001B[0m\u001B[1;36m0.0\u001B[0m\u001B[1m)\u001B[0m,                                                        \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[1;35mnp.float64\u001B[0m\u001B[1m(\u001B[0m\u001B[1;36m-1.3322676295501878e-15\u001B[0m\u001B[1m)\u001B[0m,                                    \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[1;35mnp.float64\u001B[0m\u001B[1m(\u001B[0m\u001B[1;36m0.0\u001B[0m\u001B[1m)\u001B[0m                                                         \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[1m)\u001B[0m,                                                                          \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33msize\u001B[0m=\u001B[1m(\u001B[0m\u001B[1;35mnp.float64\u001B[0m\u001B[1m(\u001B[0m\u001B[1;36m4.0\u001B[0m\u001B[1m)\u001B[0m, \u001B[1;35mnp.float64\u001B[0m\u001B[1m(\u001B[0m\u001B[1;36m8.799999999999997\u001B[0m\u001B[1m)\u001B[0m, \u001B[1;35mnp.float64\u001B[0m\u001B[1m(\u001B[0m\u001B[1;36m4.0\u001B[0m\u001B[1m)\u001B[0m\u001B[1m)\u001B[0m      \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                 \u001B[1m)\u001B[0m                                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m          \u001B[3;33msimulation_structure\u001B[0m = \u001B[1;35mStructure\u001B[0m\u001B[1m(\u001B[0m                                                                      \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                                   \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mgeometry\u001B[0m=\u001B[1;35mBox\u001B[0m\u001B[1m(\u001B[0m                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mtype\u001B[0m=\u001B[32m'Box'\u001B[0m,                                                             \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mcenter\u001B[0m=\u001B[1m(\u001B[0m                                                                \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[1;35mnp.float64\u001B[0m\u001B[1m(\u001B[0m\u001B[1;36m0.0\u001B[0m\u001B[1m)\u001B[0m,                                                    \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[1;35mnp.float64\u001B[0m\u001B[1m(\u001B[0m\u001B[1;36m-1.3322676295501878e-15\u001B[0m\u001B[1m)\u001B[0m,                                \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[1;35mnp.float64\u001B[0m\u001B[1m(\u001B[0m\u001B[1;36m0.0\u001B[0m\u001B[1m)\u001B[0m                                                     \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[1m)\u001B[0m,                                                                      \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33msize\u001B[0m=\u001B[1m(\u001B[0m                                                                  \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[1;35mnp.float64\u001B[0m\u001B[1m(\u001B[0m\u001B[1;36m4.0\u001B[0m\u001B[1m)\u001B[0m,                                                    \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[1;35mnp.float64\u001B[0m\u001B[1m(\u001B[0m\u001B[1;36m8.799999999999997\u001B[0m\u001B[1m)\u001B[0m,                                      \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[1;35mnp.float64\u001B[0m\u001B[1m(\u001B[0m\u001B[1;36m4.0\u001B[0m\u001B[1m)\u001B[0m                                                     \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[1m)\u001B[0m                                                                       \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[1m)\u001B[0m,                                                                          \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mname\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                                  \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mbackground_permittivity\u001B[0m=\u001B[3;35mNone\u001B[0m,                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mbackground_medium\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                     \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mpriority\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                              \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mtype\u001B[0m=\u001B[32m'Structure'\u001B[0m,                                                           \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mmedium\u001B[0m=\u001B[1;35mMedium\u001B[0m\u001B[1m(\u001B[0m                                                              \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mname\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                              \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mfrequency_range\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                   \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mallow_gain\u001B[0m=\u001B[3;91mFalse\u001B[0m,                                                       \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mnonlinear_spec\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                    \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mmodulation_spec\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                   \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mviz_spec\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                          \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mheat_spec\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                         \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mtype\u001B[0m=\u001B[32m'Medium'\u001B[0m,                                                          \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mpermittivity\u001B[0m=\u001B[1;36m1\u001B[0m\u001B[1;36m.0\u001B[0m,                                                       \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mconductivity\u001B[0m=\u001B[1;36m0\u001B[0m\u001B[1;36m.0\u001B[0m                                                        \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[1m)\u001B[0m                                                                           \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                 \u001B[1m)\u001B[0m                                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m               \u001B[3;33msimulation_type\u001B[0m = \u001B[32m'tidy3d'\u001B[0m                                                                        \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                          \u001B[3;33msize\u001B[0m = \u001B[1m(\u001B[0m\u001B[1;36m4.0\u001B[0m, \u001B[1;36m4.0\u001B[0m, \u001B[1;36m4.0\u001B[0m\u001B[1m)\u001B[0m                                                                 \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                       \u001B[3;33msources\u001B[0m = \u001B[1m(\u001B[0m                                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[1;35mUniformCurrentSource\u001B[0m\u001B[1m(\u001B[0m                                                       \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mname\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                              \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mtype\u001B[0m=\u001B[32m'UniformCurrentSource'\u001B[0m,                                            \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mcenter\u001B[0m=\u001B[1m(\u001B[0m\u001B[1;36m0.0\u001B[0m, \u001B[1;36m0.0\u001B[0m, \u001B[1;36m0.0\u001B[0m\u001B[1m)\u001B[0m,                                                 \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33msize\u001B[0m=\u001B[1m(\u001B[0m\u001B[1;36m0.0\u001B[0m, \u001B[1;36m0.0\u001B[0m, \u001B[1;36m0.0\u001B[0m\u001B[1m)\u001B[0m,                                                   \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33msource_time\u001B[0m=\u001B[1;35mGaussianPulse\u001B[0m\u001B[1m(\u001B[0m                                              \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                           \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mamplitude\u001B[0m=\u001B[1;36m1\u001B[0m\u001B[1;36m.0\u001B[0m,                                                      \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mphase\u001B[0m=\u001B[1;36m0\u001B[0m\u001B[1;36m.0\u001B[0m,                                                          \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mtype\u001B[0m=\u001B[32m'GaussianPulse'\u001B[0m,                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mfreq0\u001B[0m=\u001B[1;36m150000000000000\u001B[0m\u001B[1;36m.0\u001B[0m,                                            \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mfwidth\u001B[0m=\u001B[1;36m10000000000000\u001B[0m\u001B[1;36m.0\u001B[0m,                                            \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33moffset\u001B[0m=\u001B[1;36m5\u001B[0m\u001B[1;36m.0\u001B[0m,                                                         \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mremove_dc_component\u001B[0m=\u001B[3;92mTrue\u001B[0m                                            \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[1m)\u001B[0m,                                                                      \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33minterpolate\u001B[0m=\u001B[3;92mTrue\u001B[0m,                                                       \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mconfine_to_bounds\u001B[0m=\u001B[3;91mFalse\u001B[0m,                                                \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mpolarization\u001B[0m=\u001B[32m'Ez'\u001B[0m                                                       \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[1m)\u001B[0m,                                                                          \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                 \u001B[1m)\u001B[0m                                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m             \u001B[3;33mstatic_structures\u001B[0m = \u001B[1m[\u001B[0m                                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[1;35mStructure\u001B[0m\u001B[1m(\u001B[0m                                                                  \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mgeometry\u001B[0m=\u001B[1;35mBox\u001B[0m\u001B[1m(\u001B[0m                                                           \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                           \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mtype\u001B[0m=\u001B[32m'Box'\u001B[0m,                                                         \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mcenter\u001B[0m=\u001B[1m(\u001B[0m\u001B[1;36m0.0\u001B[0m, \u001B[1;36m0.0\u001B[0m, \u001B[1;36m0.0\u001B[0m\u001B[1m)\u001B[0m,                                             \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33msize\u001B[0m=\u001B[1m(\u001B[0m\u001B[1;36m1.0\u001B[0m, \u001B[1;36m1.0\u001B[0m, \u001B[1;36m1.0\u001B[0m\u001B[1m)\u001B[0m                                                \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[1m)\u001B[0m,                                                                      \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mname\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                              \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mbackground_permittivity\u001B[0m=\u001B[3;35mNone\u001B[0m,                                           \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mbackground_medium\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                 \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mpriority\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                          \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mtype\u001B[0m=\u001B[32m'Structure'\u001B[0m,                                                       \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mmedium\u001B[0m=\u001B[1;35mMedium\u001B[0m\u001B[1m(\u001B[0m                                                          \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                           \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mname\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                          \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mfrequency_range\u001B[0m=\u001B[3;35mNone\u001B[0m,                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mallow_gain\u001B[0m=\u001B[3;91mFalse\u001B[0m,                                                   \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mnonlinear_spec\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mmodulation_spec\u001B[0m=\u001B[3;35mNone\u001B[0m,                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mviz_spec\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                      \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mheat_spec\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                     \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mtype\u001B[0m=\u001B[32m'Medium'\u001B[0m,                                                      \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mpermittivity\u001B[0m=\u001B[1;36m2\u001B[0m\u001B[1;36m.0\u001B[0m,                                                   \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mconductivity\u001B[0m=\u001B[1;36m0\u001B[0m\u001B[1;36m.0\u001B[0m                                                    \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[1m)\u001B[0m                                                                       \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[1m)\u001B[0m                                                                           \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                 \u001B[1m]\u001B[0m                                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m       \u001B[3;33mstructure_priority_mode\u001B[0m = \u001B[32m'equal'\u001B[0m                                                                         \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                    \u001B[3;33mstructures\u001B[0m = \u001B[1m(\u001B[0m                                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[1;35mStructure\u001B[0m\u001B[1m(\u001B[0m                                                                  \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mgeometry\u001B[0m=\u001B[1;35mBox\u001B[0m\u001B[1m(\u001B[0m                                                           \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                           \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mtype\u001B[0m=\u001B[32m'Box'\u001B[0m,                                                         \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mcenter\u001B[0m=\u001B[1m(\u001B[0m\u001B[1;36m0.0\u001B[0m, \u001B[1;36m0.0\u001B[0m, \u001B[1;36m0.0\u001B[0m\u001B[1m)\u001B[0m,                                             \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33msize\u001B[0m=\u001B[1m(\u001B[0m\u001B[1;36m1.0\u001B[0m, \u001B[1;36m1.0\u001B[0m, \u001B[1;36m1.0\u001B[0m\u001B[1m)\u001B[0m                                                \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[1m)\u001B[0m,                                                                      \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mname\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                              \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mbackground_permittivity\u001B[0m=\u001B[3;35mNone\u001B[0m,                                           \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mbackground_medium\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                 \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mpriority\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                          \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mtype\u001B[0m=\u001B[32m'Structure'\u001B[0m,                                                       \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mmedium\u001B[0m=\u001B[1;35mMedium\u001B[0m\u001B[1m(\u001B[0m                                                          \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                           \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mname\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                          \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mfrequency_range\u001B[0m=\u001B[3;35mNone\u001B[0m,                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mallow_gain\u001B[0m=\u001B[3;91mFalse\u001B[0m,                                                   \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mnonlinear_spec\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mmodulation_spec\u001B[0m=\u001B[3;35mNone\u001B[0m,                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mviz_spec\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                      \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mheat_spec\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                     \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mtype\u001B[0m=\u001B[32m'Medium'\u001B[0m,                                                      \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mpermittivity\u001B[0m=\u001B[1;36m2\u001B[0m\u001B[1;36m.0\u001B[0m,                                                   \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mconductivity\u001B[0m=\u001B[1;36m0\u001B[0m\u001B[1;36m.0\u001B[0m                                                    \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[1m)\u001B[0m                                                                       \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[1m)\u001B[0m,                                                                          \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                 \u001B[1m)\u001B[0m                                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                      \u001B[3;33msubpixel\u001B[0m = \u001B[1;35mSubpixelSpec\u001B[0m\u001B[1m(\u001B[0m                                                                   \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                                   \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mdielectric\u001B[0m=\u001B[1;35mPolarizedAveraging\u001B[0m\u001B[1m(\u001B[0m\u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m, \u001B[33mtype\u001B[0m=\u001B[32m'PolarizedAveraging'\u001B[0m\u001B[1m)\u001B[0m,         \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mmetal\u001B[0m=\u001B[1;35mStaircasing\u001B[0m\u001B[1m(\u001B[0m\u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m, \u001B[33mtype\u001B[0m=\u001B[32m'Staircasing'\u001B[0m\u001B[1m)\u001B[0m,                            \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mpec\u001B[0m=\u001B[1;35mPECConformal\u001B[0m\u001B[1m(\u001B[0m                                                           \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mtype\u001B[0m=\u001B[32m'PECConformal'\u001B[0m,                                                    \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mtimestep_reduction\u001B[0m=\u001B[1;36m0\u001B[0m\u001B[1;36m.3\u001B[0m,                                                 \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33medge_singularity_correction\u001B[0m=\u001B[3;92mTrue\u001B[0m                                        \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[1m)\u001B[0m,                                                                          \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mpmc\u001B[0m=\u001B[1;35mStaircasing\u001B[0m\u001B[1m(\u001B[0m\u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m, \u001B[33mtype\u001B[0m=\u001B[32m'Staircasing'\u001B[0m\u001B[1m)\u001B[0m,                              \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mlossy_metal\u001B[0m=\u001B[1;35mSurfaceImpedance\u001B[0m\u001B[1m(\u001B[0m                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mtype\u001B[0m=\u001B[32m'SurfaceImpedance'\u001B[0m,                                                \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mtimestep_reduction\u001B[0m=\u001B[1;36m0\u001B[0m\u001B[1;36m.0\u001B[0m,                                                 \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33medge_singularity_correction\u001B[0m=\u001B[3;92mTrue\u001B[0m                                        \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[1m)\u001B[0m,                                                                          \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[33mtype\u001B[0m=\u001B[32m'SubpixelSpec'\u001B[0m                                                         \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                 \u001B[1m)\u001B[0m                                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                      \u001B[3;33msymmetry\u001B[0m = \u001B[1m(\u001B[0m\u001B[1;36m0\u001B[0m, \u001B[1;36m0\u001B[0m, \u001B[1;36m0\u001B[0m\u001B[1m)\u001B[0m                                                                       \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                         \u001B[3;33mtmesh\u001B[0m = \u001B[1;35marray\u001B[0m\u001B[1m(\u001B[0m\u001B[1m[\u001B[0m\u001B[1;36m0.00000000e+00\u001B[0m, \u001B[1;36m3.81314974e-16\u001B[0m, \u001B[1;36m7.62629948e-16\u001B[0m, \u001B[33m...\u001B[0m,                     \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                        \u001B[1;36m9.99426547e-13\u001B[0m, \u001B[1;36m9.99807862e-13\u001B[0m, \u001B[1;36m1.00018918e-12\u001B[0m\u001B[1m]\u001B[0m, \u001B[33mshape\u001B[0m=\u001B[1m(\u001B[0m\u001B[1;36m2624\u001B[0m,\u001B[1m)\u001B[0m\u001B[1m)\u001B[0m          \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                          \u001B[3;33mtype\u001B[0m = \u001B[32m'Simulation'\u001B[0m                                                                    \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                       \u001B[3;33mversion\u001B[0m = \u001B[32m'2.10.0rc3'\u001B[0m                                                                     \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m         \u001B[3;33mvolumetric_structures\u001B[0m = \u001B[1m[\u001B[0m                                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[1;35mStructure\u001B[0m\u001B[1m(\u001B[0m                                                                  \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mgeometry\u001B[0m=\u001B[1;35mBox\u001B[0m\u001B[1m(\u001B[0m                                                           \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                           \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mtype\u001B[0m=\u001B[32m'Box'\u001B[0m,                                                         \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mcenter\u001B[0m=\u001B[1m(\u001B[0m\u001B[1;36m0.0\u001B[0m, \u001B[1;36m0.0\u001B[0m, \u001B[1;36m0.0\u001B[0m\u001B[1m)\u001B[0m,                                             \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33msize\u001B[0m=\u001B[1m(\u001B[0m\u001B[1;36m1.0\u001B[0m, \u001B[1;36m1.0\u001B[0m, \u001B[1;36m1.0\u001B[0m\u001B[1m)\u001B[0m                                                \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[1m)\u001B[0m,                                                                      \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mname\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                              \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mbackground_permittivity\u001B[0m=\u001B[3;35mNone\u001B[0m,                                           \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mbackground_medium\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                 \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mpriority\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                          \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mtype\u001B[0m=\u001B[32m'Structure'\u001B[0m,                                                       \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[33mmedium\u001B[0m=\u001B[1;35mMedium\u001B[0m\u001B[1m(\u001B[0m                                                          \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mattrs\u001B[0m=\u001B[1m{\u001B[0m\u001B[1m}\u001B[0m,                                                           \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mname\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                          \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mfrequency_range\u001B[0m=\u001B[3;35mNone\u001B[0m,                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mallow_gain\u001B[0m=\u001B[3;91mFalse\u001B[0m,                                                   \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mnonlinear_spec\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mmodulation_spec\u001B[0m=\u001B[3;35mNone\u001B[0m,                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mviz_spec\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                      \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mheat_spec\u001B[0m=\u001B[3;35mNone\u001B[0m,                                                     \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mtype\u001B[0m=\u001B[32m'Medium'\u001B[0m,                                                      \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mpermittivity\u001B[0m=\u001B[1;36m2\u001B[0m\u001B[1;36m.0\u001B[0m,                                                   \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                             \u001B[33mconductivity\u001B[0m=\u001B[1;36m0\u001B[0m\u001B[1;36m.0\u001B[0m                                                    \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                         \u001B[1m)\u001B[0m                                                                       \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                     \u001B[1m)\u001B[0m                                                                           \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                                 \u001B[1m]\u001B[0m                                                                               \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                   \u001B[3;33mwvl_mat_min\u001B[0m = \u001B[1;35mnp.float64\u001B[0m\u001B[1m(\u001B[0m\u001B[1;36m1.4132352000025548\u001B[0m\u001B[1m)\u001B[0m                                                  \u001B[34m│\u001B[0m\n",
+       "\u001B[34m│\u001B[0m                     \u001B[3;33mzero_dims\u001B[0m = \u001B[1m[\u001B[0m\u001B[1m]\u001B[0m                                                                              \u001B[34m│\u001B[0m\n",
+       "\u001B[34m╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯\u001B[0m\n"
+      ],
       "text/html": [
        "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #000080; text-decoration-color: #000080\">╭─────────────────────────────── </span><span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">&lt;</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff; font-weight: bold\">class</span><span style=\"color: #000000; text-decoration-color: #000000\"> </span><span style=\"color: #008000; text-decoration-color: #008000\">'tidy3d.components.simulation.Simulation'</span><span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">&gt;</span><span style=\"color: #000080; text-decoration-color: #000080\"> ───────────────────────────────╮</span>\n",
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span> <span style=\"color: #008080; text-decoration-color: #008080\">Custom implementation of Maxwell’s equations which represents the physical model to be solved using the FDTD</span>    <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
@@ -1724,7 +2729,7 @@
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span> <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">layer_refinement_specs</span>=<span style=\"font-weight: bold\">()</span>,                                                                          <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span> <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">type</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'GridSpec'</span>                                                                                     <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span> <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"font-weight: bold\">)</span>,                                                                                                      <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
-       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span> <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">version</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'2.9.0'</span>,                                                                                        <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
+       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span> <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">version</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'2.10.0rc3'</span>,                                                                                    <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span> <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">plot_length_units</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'μm'</span>,                                                                                 <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span> <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">structure_priority_mode</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'equal'</span>,                                                                        <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span> <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">lumped_elements</span>=<span style=\"font-weight: bold\">()</span>,                                                                                     <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
@@ -1736,24 +2741,26 @@
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span> <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">attrs</span>=<span style=\"font-weight: bold\">{}</span>,                                                                                       <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span> <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">type</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'PECConformal'</span>,                                                                            <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span> <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">timestep_reduction</span>=<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.3</span>,                                                                         <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
-       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span> <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">edge_singularity_correction</span>=<span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                               <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
+       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span> <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">edge_singularity_correction</span>=<span style=\"color: #00ff00; text-decoration-color: #00ff00; font-style: italic\">True</span>                                                                <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span> <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"font-weight: bold\">)</span>,                                                                                                  <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span> <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">pmc</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">Staircasing</span><span style=\"font-weight: bold\">(</span><span style=\"color: #808000; text-decoration-color: #808000\">attrs</span>=<span style=\"font-weight: bold\">{}</span>, <span style=\"color: #808000; text-decoration-color: #808000\">type</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'Staircasing'</span><span style=\"font-weight: bold\">)</span>,                                                      <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span> <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">lossy_metal</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">SurfaceImpedance</span><span style=\"font-weight: bold\">(</span>                                                                       <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span> <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">attrs</span>=<span style=\"font-weight: bold\">{}</span>,                                                                                       <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span> <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">type</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'SurfaceImpedance'</span>,                                                                        <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span> <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">timestep_reduction</span>=<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.0</span>,                                                                         <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
-       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span> <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">edge_singularity_correction</span>=<span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                                               <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
+       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span> <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">edge_singularity_correction</span>=<span style=\"color: #00ff00; text-decoration-color: #00ff00; font-style: italic\">True</span>                                                                <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span> <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"font-weight: bold\">)</span>,                                                                                                  <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span> <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">type</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'SubpixelSpec'</span>                                                                                 <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span> <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"font-weight: bold\">)</span>,                                                                                                      <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span> <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">simulation_type</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'tidy3d'</span>,                                                                               <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span> <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">post_norm</span>=<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.0</span>,                                                                                          <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
+       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span> <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">internal_absorbers</span>=<span style=\"font-weight: bold\">()</span>,                                                                                  <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span> <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">courant</span>=<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.99</span>,                                                                                           <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span> <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">precision</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'hybrid'</span>,                                                                                     <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span> <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">normalize_index</span>=<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0</span>,                                                                                      <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span> <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">shutoff</span>=<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1e-05</span>,                                                                                          <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
-       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span> <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">run_time</span>=<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1e-12</span>                                                                                          <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
+       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span> <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">run_time</span>=<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1e-12</span>,                                                                                         <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
+       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span> <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">low_freq_smoothing</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-style: italic\">None</span>                                                                                 <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span> <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"font-weight: bold\">)</span>                                                                                                           <span style=\"color: #008000; text-decoration-color: #008000\">│</span> <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span> <span style=\"color: #008000; text-decoration-color: #008000\">╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────╯</span> <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>                                                                                                                 <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
@@ -1912,7 +2919,7 @@
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>                       <span style=\"color: #808000; text-decoration-color: #808000; font-style: italic\">courant</span> = <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.99</span>                                                                            <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>               <span style=\"color: #808000; text-decoration-color: #808000; font-style: italic\">custom_datasets</span> = <span style=\"font-weight: bold\">[]</span>                                                                              <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>                            <span style=\"color: #808000; text-decoration-color: #808000; font-style: italic\">dt</span> = <span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">np.float64</span><span style=\"font-weight: bold\">(</span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.813149739062003e-16</span><span style=\"font-weight: bold\">)</span>                                               <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
-       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>               <span style=\"color: #808000; text-decoration-color: #808000; font-style: italic\">frequency_range</span> = <span style=\"font-weight: bold\">(</span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">110000000000000.0</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">190000000000000.0</span><span style=\"font-weight: bold\">)</span>                                          <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
+       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>               <span style=\"color: #808000; text-decoration-color: #808000; font-style: italic\">frequency_range</span> = <span style=\"font-weight: bold\">(</span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">110770887769698.48</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">190588842668354.53</span><span style=\"font-weight: bold\">)</span>                                        <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>                      <span style=\"color: #808000; text-decoration-color: #808000; font-style: italic\">geometry</span> = <span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">Box</span><span style=\"font-weight: bold\">(</span><span style=\"color: #808000; text-decoration-color: #808000\">attrs</span>=<span style=\"font-weight: bold\">{}</span>, <span style=\"color: #808000; text-decoration-color: #808000\">type</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'Box'</span>, <span style=\"color: #808000; text-decoration-color: #808000\">center</span>=<span style=\"font-weight: bold\">(</span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.0</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.0</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.0</span><span style=\"font-weight: bold\">)</span>, <span style=\"color: #808000; text-decoration-color: #808000\">size</span>=<span style=\"font-weight: bold\">(</span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">4.0</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">4.0</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">4.0</span><span style=\"font-weight: bold\">))</span>         <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>                          <span style=\"color: #808000; text-decoration-color: #808000; font-style: italic\">grid</span> = <span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">Grid</span><span style=\"font-weight: bold\">(</span>                                                                           <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>                                     <span style=\"color: #808000; text-decoration-color: #808000\">attrs</span>=<span style=\"font-weight: bold\">{}</span>,                                                                   <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
@@ -1954,8 +2961,10 @@
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>                                     <span style=\"color: #808000; text-decoration-color: #808000\">layer_refinement_specs</span>=<span style=\"font-weight: bold\">()</span>,                                                  <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>                                     <span style=\"color: #808000; text-decoration-color: #808000\">type</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'GridSpec'</span>                                                             <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>                                 <span style=\"font-weight: bold\">)</span>                                                                               <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
+       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>            <span style=\"color: #808000; text-decoration-color: #808000; font-style: italic\">internal_absorbers</span> = <span style=\"font-weight: bold\">()</span>                                                                              <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>  <span style=\"color: #808000; text-decoration-color: #808000; font-style: italic\">internal_override_structures</span> = <span style=\"font-weight: bold\">[]</span>                                                                              <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>      <span style=\"color: #808000; text-decoration-color: #808000; font-style: italic\">internal_snapping_points</span> = <span style=\"font-weight: bold\">[]</span>                                                                              <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
+       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>            <span style=\"color: #808000; text-decoration-color: #808000; font-style: italic\">low_freq_smoothing</span> = <span style=\"color: #800080; text-decoration-color: #800080; font-style: italic\">None</span>                                                                            <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>               <span style=\"color: #808000; text-decoration-color: #808000; font-style: italic\">lumped_elements</span> = <span style=\"font-weight: bold\">()</span>                                                                              <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>                        <span style=\"color: #808000; text-decoration-color: #808000; font-style: italic\">medium</span> = <span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">Medium</span><span style=\"font-weight: bold\">(</span>                                                                         <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>                                     <span style=\"color: #808000; text-decoration-color: #808000\">attrs</span>=<span style=\"font-weight: bold\">{}</span>,                                                                   <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
@@ -2285,14 +3294,14 @@
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>                                         <span style=\"color: #808000; text-decoration-color: #808000\">attrs</span>=<span style=\"font-weight: bold\">{}</span>,                                                               <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>                                         <span style=\"color: #808000; text-decoration-color: #808000\">type</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'PECConformal'</span>,                                                    <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>                                         <span style=\"color: #808000; text-decoration-color: #808000\">timestep_reduction</span>=<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.3</span>,                                                 <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
-       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>                                         <span style=\"color: #808000; text-decoration-color: #808000\">edge_singularity_correction</span>=<span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                       <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
+       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>                                         <span style=\"color: #808000; text-decoration-color: #808000\">edge_singularity_correction</span>=<span style=\"color: #00ff00; text-decoration-color: #00ff00; font-style: italic\">True</span>                                        <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>                                     <span style=\"font-weight: bold\">)</span>,                                                                          <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>                                     <span style=\"color: #808000; text-decoration-color: #808000\">pmc</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">Staircasing</span><span style=\"font-weight: bold\">(</span><span style=\"color: #808000; text-decoration-color: #808000\">attrs</span>=<span style=\"font-weight: bold\">{}</span>, <span style=\"color: #808000; text-decoration-color: #808000\">type</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'Staircasing'</span><span style=\"font-weight: bold\">)</span>,                              <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>                                     <span style=\"color: #808000; text-decoration-color: #808000\">lossy_metal</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">SurfaceImpedance</span><span style=\"font-weight: bold\">(</span>                                               <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>                                         <span style=\"color: #808000; text-decoration-color: #808000\">attrs</span>=<span style=\"font-weight: bold\">{}</span>,                                                               <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>                                         <span style=\"color: #808000; text-decoration-color: #808000\">type</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'SurfaceImpedance'</span>,                                                <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>                                         <span style=\"color: #808000; text-decoration-color: #808000\">timestep_reduction</span>=<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.0</span>,                                                 <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
-       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>                                         <span style=\"color: #808000; text-decoration-color: #808000\">edge_singularity_correction</span>=<span style=\"color: #ff0000; text-decoration-color: #ff0000; font-style: italic\">False</span>                                       <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
+       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>                                         <span style=\"color: #808000; text-decoration-color: #808000\">edge_singularity_correction</span>=<span style=\"color: #00ff00; text-decoration-color: #00ff00; font-style: italic\">True</span>                                        <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>                                     <span style=\"font-weight: bold\">)</span>,                                                                          <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>                                     <span style=\"color: #808000; text-decoration-color: #808000\">type</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'SubpixelSpec'</span>                                                         <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>                                 <span style=\"font-weight: bold\">)</span>                                                                               <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
@@ -2300,7 +3309,7 @@
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>                         <span style=\"color: #808000; text-decoration-color: #808000; font-style: italic\">tmesh</span> = <span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">array</span><span style=\"font-weight: bold\">([</span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00000000e+00</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.81314974e-16</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">7.62629948e-16</span>, <span style=\"color: #808000; text-decoration-color: #808000\">...</span>,                     <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>                                        <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">9.99426547e-13</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">9.99807862e-13</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.00018918e-12</span><span style=\"font-weight: bold\">]</span>, <span style=\"color: #808000; text-decoration-color: #808000\">shape</span>=<span style=\"font-weight: bold\">(</span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2624</span>,<span style=\"font-weight: bold\">))</span>          <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>                          <span style=\"color: #808000; text-decoration-color: #808000; font-style: italic\">type</span> = <span style=\"color: #008000; text-decoration-color: #008000\">'Simulation'</span>                                                                    <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
-       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>                       <span style=\"color: #808000; text-decoration-color: #808000; font-style: italic\">version</span> = <span style=\"color: #008000; text-decoration-color: #008000\">'2.9.0'</span>                                                                         <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
+       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>                       <span style=\"color: #808000; text-decoration-color: #808000; font-style: italic\">version</span> = <span style=\"color: #008000; text-decoration-color: #008000\">'2.10.0rc3'</span>                                                                     <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>         <span style=\"color: #808000; text-decoration-color: #808000; font-style: italic\">volumetric_structures</span> = <span style=\"font-weight: bold\">[</span>                                                                               <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>                                     <span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">Structure</span><span style=\"font-weight: bold\">(</span>                                                                  <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>                                         <span style=\"color: #808000; text-decoration-color: #808000\">attrs</span>=<span style=\"font-weight: bold\">{}</span>,                                                               <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
@@ -2334,803 +3343,16 @@
        "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>                     <span style=\"color: #808000; text-decoration-color: #808000; font-style: italic\">zero_dims</span> = <span style=\"font-weight: bold\">[]</span>                                                                              <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
        "<span style=\"color: #000080; text-decoration-color: #000080\">╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯</span>\n",
        "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[34m╭─\u001b[0m\u001b[34m──────────────────────────────\u001b[0m\u001b[34m \u001b[0m\u001b[1;34m<\u001b[0m\u001b[1;95mclass\u001b[0m\u001b[39m \u001b[0m\u001b[32m'tidy3d.components.simulation.Simulation'\u001b[0m\u001b[1;34m>\u001b[0m\u001b[34m \u001b[0m\u001b[34m──────────────────────────────\u001b[0m\u001b[34m─╮\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[36mCustom implementation of Maxwell’s equations which represents the physical model to be solved using the FDTD\u001b[0m    \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[36mmethod.\u001b[0m                                                                                                         \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                                                                                                 \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m╭─────────────────────────────────────────────────────────────────────────────────────────────────────────────╮\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[1;35mSimulation\u001b[0m\u001b[1m(\u001b[0m                                                                                                 \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   \u001b[0m\u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                                                               \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   \u001b[0m\u001b[33mtype\u001b[0m=\u001b[32m'Simulation'\u001b[0m,                                                                                      \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   \u001b[0m\u001b[33mcenter\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m\u001b[1m)\u001b[0m,                                                                                 \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   \u001b[0m\u001b[33msize\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m4.0\u001b[0m, \u001b[1;36m4.0\u001b[0m, \u001b[1;36m4.0\u001b[0m\u001b[1m)\u001b[0m,                                                                                   \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   \u001b[0m\u001b[33mmedium\u001b[0m=\u001b[1;35mMedium\u001b[0m\u001b[1m(\u001b[0m                                                                                          \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   \u001b[0m\u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                                                           \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   \u001b[0m\u001b[33mname\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                                                          \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   \u001b[0m\u001b[33mfrequency_range\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                                               \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   \u001b[0m\u001b[33mallow_gain\u001b[0m=\u001b[3;91mFalse\u001b[0m,                                                                                   \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   \u001b[0m\u001b[33mnonlinear_spec\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                                                \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   \u001b[0m\u001b[33mmodulation_spec\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                                               \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   \u001b[0m\u001b[33mviz_spec\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                                                      \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   \u001b[0m\u001b[33mheat_spec\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                                                     \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   \u001b[0m\u001b[33mtype\u001b[0m=\u001b[32m'Medium'\u001b[0m,                                                                                      \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   \u001b[0m\u001b[33mpermittivity\u001b[0m=\u001b[1;36m1\u001b[0m\u001b[1;36m.0\u001b[0m,                                                                                   \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   \u001b[0m\u001b[33mconductivity\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.0\u001b[0m                                                                                    \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   \u001b[0m\u001b[1m)\u001b[0m,                                                                                                      \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   \u001b[0m\u001b[33mstructures\u001b[0m=\u001b[1m(\u001b[0m                                                                                            \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   \u001b[0m\u001b[1;35mStructure\u001b[0m\u001b[1m(\u001b[0m                                                                                          \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   \u001b[0m\u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                                                       \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   \u001b[0m\u001b[33mgeometry\u001b[0m=\u001b[1;35mBox\u001b[0m\u001b[1m(\u001b[0m\u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m, \u001b[33mtype\u001b[0m=\u001b[32m'Box'\u001b[0m, \u001b[33mcenter\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m\u001b[1m)\u001b[0m, \u001b[33msize\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m1.0\u001b[0m, \u001b[1;36m1.0\u001b[0m, \u001b[1;36m1.0\u001b[0m\u001b[1m)\u001b[0m\u001b[1m)\u001b[0m,               \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   \u001b[0m\u001b[33mname\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                                                      \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   \u001b[0m\u001b[33mbackground_permittivity\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                                   \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   \u001b[0m\u001b[33mbackground_medium\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                                         \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   \u001b[0m\u001b[33mpriority\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                                                  \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   \u001b[0m\u001b[33mtype\u001b[0m=\u001b[32m'Structure'\u001b[0m,                                                                               \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   \u001b[0m\u001b[33mmedium\u001b[0m=\u001b[1;35mMedium\u001b[0m\u001b[1m(\u001b[0m                                                                                  \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   │   \u001b[0m\u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                                                   \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   │   \u001b[0m\u001b[33mname\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                                                  \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   │   \u001b[0m\u001b[33mfrequency_range\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                                       \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   │   \u001b[0m\u001b[33mallow_gain\u001b[0m=\u001b[3;91mFalse\u001b[0m,                                                                           \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   │   \u001b[0m\u001b[33mnonlinear_spec\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                                        \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   │   \u001b[0m\u001b[33mmodulation_spec\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                                       \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   │   \u001b[0m\u001b[33mviz_spec\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                                              \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   │   \u001b[0m\u001b[33mheat_spec\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                                             \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   │   \u001b[0m\u001b[33mtype\u001b[0m=\u001b[32m'Medium'\u001b[0m,                                                                              \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   │   \u001b[0m\u001b[33mpermittivity\u001b[0m=\u001b[1;36m2\u001b[0m\u001b[1;36m.0\u001b[0m,                                                                           \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   │   \u001b[0m\u001b[33mconductivity\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.0\u001b[0m                                                                            \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   \u001b[0m\u001b[1m)\u001b[0m                                                                                               \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   \u001b[0m\u001b[1m)\u001b[0m,                                                                                                  \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   \u001b[0m\u001b[1m)\u001b[0m,                                                                                                      \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   \u001b[0m\u001b[33msymmetry\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m\u001b[1m)\u001b[0m,                                                                                     \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   \u001b[0m\u001b[33msources\u001b[0m=\u001b[1m(\u001b[0m                                                                                               \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   \u001b[0m\u001b[1;35mUniformCurrentSource\u001b[0m\u001b[1m(\u001b[0m                                                                               \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   \u001b[0m\u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                                                       \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   \u001b[0m\u001b[33mname\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                                                      \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   \u001b[0m\u001b[33mtype\u001b[0m=\u001b[32m'UniformCurrentSource'\u001b[0m,                                                                    \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   \u001b[0m\u001b[33mcenter\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m\u001b[1m)\u001b[0m,                                                                         \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   \u001b[0m\u001b[33msize\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m\u001b[1m)\u001b[0m,                                                                           \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   \u001b[0m\u001b[33msource_time\u001b[0m=\u001b[1;35mGaussianPulse\u001b[0m\u001b[1m(\u001b[0m                                                                      \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   │   \u001b[0m\u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                                                   \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   │   \u001b[0m\u001b[33mamplitude\u001b[0m=\u001b[1;36m1\u001b[0m\u001b[1;36m.0\u001b[0m,                                                                              \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   │   \u001b[0m\u001b[33mphase\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.0\u001b[0m,                                                                                  \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   │   \u001b[0m\u001b[33mtype\u001b[0m=\u001b[32m'GaussianPulse'\u001b[0m,                                                                       \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   │   \u001b[0m\u001b[33mfreq0\u001b[0m=\u001b[1;36m150000000000000\u001b[0m\u001b[1;36m.0\u001b[0m,                                                                    \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   │   \u001b[0m\u001b[33mfwidth\u001b[0m=\u001b[1;36m10000000000000\u001b[0m\u001b[1;36m.0\u001b[0m,                                                                    \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   │   \u001b[0m\u001b[33moffset\u001b[0m=\u001b[1;36m5\u001b[0m\u001b[1;36m.0\u001b[0m,                                                                                 \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   │   \u001b[0m\u001b[33mremove_dc_component\u001b[0m=\u001b[3;92mTrue\u001b[0m                                                                    \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   \u001b[0m\u001b[1m)\u001b[0m,                                                                                              \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   \u001b[0m\u001b[33minterpolate\u001b[0m=\u001b[3;92mTrue\u001b[0m,                                                                               \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   \u001b[0m\u001b[33mconfine_to_bounds\u001b[0m=\u001b[3;91mFalse\u001b[0m,                                                                        \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   \u001b[0m\u001b[33mpolarization\u001b[0m=\u001b[32m'Ez'\u001b[0m                                                                               \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   \u001b[0m\u001b[1m)\u001b[0m,                                                                                                  \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   \u001b[0m\u001b[1m)\u001b[0m,                                                                                                      \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   \u001b[0m\u001b[33mboundary_spec\u001b[0m=\u001b[1;35mBoundarySpec\u001b[0m\u001b[1m(\u001b[0m                                                                             \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   \u001b[0m\u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                                                           \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   \u001b[0m\u001b[33mx\u001b[0m=\u001b[1;35mBoundary\u001b[0m\u001b[1m(\u001b[0m                                                                                         \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   \u001b[0m\u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                                                       \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   \u001b[0m\u001b[33mplus\u001b[0m=\u001b[1;35mPeriodic\u001b[0m\u001b[1m(\u001b[0m\u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m, \u001b[33mname\u001b[0m=\u001b[3;35mNone\u001b[0m, \u001b[33mtype\u001b[0m=\u001b[32m'Periodic'\u001b[0m\u001b[1m)\u001b[0m,                                            \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   \u001b[0m\u001b[33mminus\u001b[0m=\u001b[1;35mPeriodic\u001b[0m\u001b[1m(\u001b[0m\u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m, \u001b[33mname\u001b[0m=\u001b[3;35mNone\u001b[0m, \u001b[33mtype\u001b[0m=\u001b[32m'Periodic'\u001b[0m\u001b[1m)\u001b[0m,                                           \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   \u001b[0m\u001b[33mtype\u001b[0m=\u001b[32m'Boundary'\u001b[0m                                                                                 \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   \u001b[0m\u001b[1m)\u001b[0m,                                                                                                  \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   \u001b[0m\u001b[33my\u001b[0m=\u001b[1;35mBoundary\u001b[0m\u001b[1m(\u001b[0m                                                                                         \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   \u001b[0m\u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                                                       \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   \u001b[0m\u001b[33mplus\u001b[0m=\u001b[1;35mPML\u001b[0m\u001b[1m(\u001b[0m                                                                                       \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   │   \u001b[0m\u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                                                   \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   │   \u001b[0m\u001b[33mname\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                                                  \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   │   \u001b[0m\u001b[33mtype\u001b[0m=\u001b[32m'PML'\u001b[0m,                                                                                 \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   │   \u001b[0m\u001b[33mnum_layers\u001b[0m=\u001b[1;36m12\u001b[0m,                                                                              \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   │   \u001b[0m\u001b[33mparameters\u001b[0m=\u001b[1;35mPMLParams\u001b[0m\u001b[1m(\u001b[0m                                                                       \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   │   │   \u001b[0m\u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                                               \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   │   │   \u001b[0m\u001b[33msigma_order\u001b[0m=\u001b[1;36m3\u001b[0m,                                                                          \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   │   │   \u001b[0m\u001b[33msigma_min\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.0\u001b[0m,                                                                          \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   │   │   \u001b[0m\u001b[33msigma_max\u001b[0m=\u001b[1;36m1\u001b[0m\u001b[1;36m.5\u001b[0m,                                                                          \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   │   │   \u001b[0m\u001b[33mtype\u001b[0m=\u001b[32m'PMLParams'\u001b[0m,                                                                       \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   │   │   \u001b[0m\u001b[33mkappa_order\u001b[0m=\u001b[1;36m3\u001b[0m,                                                                          \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   │   │   \u001b[0m\u001b[33mkappa_min\u001b[0m=\u001b[1;36m1\u001b[0m\u001b[1;36m.0\u001b[0m,                                                                          \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   │   │   \u001b[0m\u001b[33mkappa_max\u001b[0m=\u001b[1;36m3\u001b[0m\u001b[1;36m.0\u001b[0m,                                                                          \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   │   │   \u001b[0m\u001b[33malpha_order\u001b[0m=\u001b[1;36m1\u001b[0m,                                                                          \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   │   │   \u001b[0m\u001b[33malpha_min\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.0\u001b[0m,                                                                          \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   │   │   \u001b[0m\u001b[33malpha_max\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.0\u001b[0m                                                                           \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   │   \u001b[0m\u001b[1m)\u001b[0m                                                                                           \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   \u001b[0m\u001b[1m)\u001b[0m,                                                                                              \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   \u001b[0m\u001b[33mminus\u001b[0m=\u001b[1;35mPML\u001b[0m\u001b[1m(\u001b[0m                                                                                      \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   │   \u001b[0m\u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                                                   \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   │   \u001b[0m\u001b[33mname\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                                                  \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   │   \u001b[0m\u001b[33mtype\u001b[0m=\u001b[32m'PML'\u001b[0m,                                                                                 \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   │   \u001b[0m\u001b[33mnum_layers\u001b[0m=\u001b[1;36m12\u001b[0m,                                                                              \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   │   \u001b[0m\u001b[33mparameters\u001b[0m=\u001b[1;35mPMLParams\u001b[0m\u001b[1m(\u001b[0m                                                                       \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   │   │   \u001b[0m\u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                                               \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   │   │   \u001b[0m\u001b[33msigma_order\u001b[0m=\u001b[1;36m3\u001b[0m,                                                                          \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   │   │   \u001b[0m\u001b[33msigma_min\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.0\u001b[0m,                                                                          \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   │   │   \u001b[0m\u001b[33msigma_max\u001b[0m=\u001b[1;36m1\u001b[0m\u001b[1;36m.5\u001b[0m,                                                                          \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   │   │   \u001b[0m\u001b[33mtype\u001b[0m=\u001b[32m'PMLParams'\u001b[0m,                                                                       \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   │   │   \u001b[0m\u001b[33mkappa_order\u001b[0m=\u001b[1;36m3\u001b[0m,                                                                          \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   │   │   \u001b[0m\u001b[33mkappa_min\u001b[0m=\u001b[1;36m1\u001b[0m\u001b[1;36m.0\u001b[0m,                                                                          \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   │   │   \u001b[0m\u001b[33mkappa_max\u001b[0m=\u001b[1;36m3\u001b[0m\u001b[1;36m.0\u001b[0m,                                                                          \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   │   │   \u001b[0m\u001b[33malpha_order\u001b[0m=\u001b[1;36m1\u001b[0m,                                                                          \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   │   │   \u001b[0m\u001b[33malpha_min\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.0\u001b[0m,                                                                          \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   │   │   \u001b[0m\u001b[33malpha_max\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.0\u001b[0m                                                                           \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   │   \u001b[0m\u001b[1m)\u001b[0m                                                                                           \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   \u001b[0m\u001b[1m)\u001b[0m,                                                                                              \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   \u001b[0m\u001b[33mtype\u001b[0m=\u001b[32m'Boundary'\u001b[0m                                                                                 \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   \u001b[0m\u001b[1m)\u001b[0m,                                                                                                  \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   \u001b[0m\u001b[33mz\u001b[0m=\u001b[1;35mBoundary\u001b[0m\u001b[1m(\u001b[0m                                                                                         \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   \u001b[0m\u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                                                       \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   \u001b[0m\u001b[33mplus\u001b[0m=\u001b[1;35mPeriodic\u001b[0m\u001b[1m(\u001b[0m\u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m, \u001b[33mname\u001b[0m=\u001b[3;35mNone\u001b[0m, \u001b[33mtype\u001b[0m=\u001b[32m'Periodic'\u001b[0m\u001b[1m)\u001b[0m,                                            \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   \u001b[0m\u001b[33mminus\u001b[0m=\u001b[1;35mPeriodic\u001b[0m\u001b[1m(\u001b[0m\u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m, \u001b[33mname\u001b[0m=\u001b[3;35mNone\u001b[0m, \u001b[33mtype\u001b[0m=\u001b[32m'Periodic'\u001b[0m\u001b[1m)\u001b[0m,                                           \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   \u001b[0m\u001b[33mtype\u001b[0m=\u001b[32m'Boundary'\u001b[0m                                                                                 \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   \u001b[0m\u001b[1m)\u001b[0m,                                                                                                  \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   \u001b[0m\u001b[33mtype\u001b[0m=\u001b[32m'BoundarySpec'\u001b[0m                                                                                 \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   \u001b[0m\u001b[1m)\u001b[0m,                                                                                                      \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   \u001b[0m\u001b[33mmonitors\u001b[0m=\u001b[1m(\u001b[0m                                                                                              \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   \u001b[0m\u001b[1;35mFieldMonitor\u001b[0m\u001b[1m(\u001b[0m                                                                                       \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   \u001b[0m\u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                                                       \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   \u001b[0m\u001b[33mtype\u001b[0m=\u001b[32m'FieldMonitor'\u001b[0m,                                                                            \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   \u001b[0m\u001b[33mcenter\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m1.0\u001b[0m, \u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m\u001b[1m)\u001b[0m,                                                                         \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   \u001b[0m\u001b[33msize\u001b[0m=\u001b[1m(\u001b[0minf, inf, \u001b[1;36m0.0\u001b[0m\u001b[1m)\u001b[0m,                                                                           \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   \u001b[0m\u001b[33mname\u001b[0m=\u001b[32m'fields_at_150THz'\u001b[0m,                                                                        \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   \u001b[0m\u001b[33minterval_space\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m1\u001b[0m, \u001b[1;36m1\u001b[0m, \u001b[1;36m1\u001b[0m\u001b[1m)\u001b[0m,                                                                       \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   \u001b[0m\u001b[33mcolocate\u001b[0m=\u001b[3;92mTrue\u001b[0m,                                                                                  \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   \u001b[0m\u001b[33mfreqs\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m150000000000000.0\u001b[0m,\u001b[1m)\u001b[0m,                                                                     \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   \u001b[0m\u001b[33mapodization\u001b[0m=\u001b[1;35mApodizationSpec\u001b[0m\u001b[1m(\u001b[0m                                                                    \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   │   \u001b[0m\u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                                                   \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   │   \u001b[0m\u001b[33mstart\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                                                 \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   │   \u001b[0m\u001b[33mend\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                                                   \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   │   \u001b[0m\u001b[33mwidth\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                                                 \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   │   \u001b[0m\u001b[33mtype\u001b[0m=\u001b[32m'ApodizationSpec'\u001b[0m                                                                      \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   \u001b[0m\u001b[1m)\u001b[0m,                                                                                              \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   \u001b[0m\u001b[33mfields\u001b[0m=\u001b[1m(\u001b[0m\u001b[32m'Ex'\u001b[0m, \u001b[32m'Ey'\u001b[0m, \u001b[32m'Hz'\u001b[0m\u001b[1m)\u001b[0m                                                                       \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   \u001b[0m\u001b[1m)\u001b[0m,                                                                                                  \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   \u001b[0m\u001b[1;35mFluxTimeMonitor\u001b[0m\u001b[1m(\u001b[0m                                                                                    \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   \u001b[0m\u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                                                       \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   \u001b[0m\u001b[33mtype\u001b[0m=\u001b[32m'FluxTimeMonitor'\u001b[0m,                                                                         \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   \u001b[0m\u001b[33mcenter\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m1.0\u001b[0m, \u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m\u001b[1m)\u001b[0m,                                                                         \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   \u001b[0m\u001b[33msize\u001b[0m=\u001b[1m(\u001b[0minf, inf, \u001b[1;36m0.0\u001b[0m\u001b[1m)\u001b[0m,                                                                           \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   \u001b[0m\u001b[33mname\u001b[0m=\u001b[32m'flux_over_time'\u001b[0m,                                                                          \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   \u001b[0m\u001b[33minterval_space\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m1\u001b[0m, \u001b[1;36m1\u001b[0m, \u001b[1;36m1\u001b[0m\u001b[1m)\u001b[0m,                                                                       \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   \u001b[0m\u001b[33mcolocate\u001b[0m=\u001b[3;92mTrue\u001b[0m,                                                                                  \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   \u001b[0m\u001b[33mstart\u001b[0m=\u001b[1;36m1e\u001b[0m\u001b[1;36m-13\u001b[0m,                                                                                    \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   \u001b[0m\u001b[33mstop\u001b[0m=\u001b[1;36m3e\u001b[0m\u001b[1;36m-13\u001b[0m,                                                                                     \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   \u001b[0m\u001b[33minterval\u001b[0m=\u001b[1;36m5\u001b[0m,                                                                                     \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   \u001b[0m\u001b[33mnormal_dir\u001b[0m=\u001b[32m'+'\u001b[0m,                                                                                 \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   \u001b[0m\u001b[33mexclude_surfaces\u001b[0m=\u001b[3;35mNone\u001b[0m                                                                           \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   \u001b[0m\u001b[1m)\u001b[0m                                                                                                   \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   \u001b[0m\u001b[1m)\u001b[0m,                                                                                                      \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   \u001b[0m\u001b[33mgrid_spec\u001b[0m=\u001b[1;35mGridSpec\u001b[0m\u001b[1m(\u001b[0m                                                                                     \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   \u001b[0m\u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                                                           \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   \u001b[0m\u001b[33mgrid_x\u001b[0m=\u001b[1;35mUniformGrid\u001b[0m\u001b[1m(\u001b[0m\u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m, \u001b[33mtype\u001b[0m=\u001b[32m'UniformGrid'\u001b[0m, \u001b[33mdl\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.2\u001b[0m\u001b[1m)\u001b[0m,                                           \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   \u001b[0m\u001b[33mgrid_y\u001b[0m=\u001b[1;35mUniformGrid\u001b[0m\u001b[1m(\u001b[0m\u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m, \u001b[33mtype\u001b[0m=\u001b[32m'UniformGrid'\u001b[0m, \u001b[33mdl\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.2\u001b[0m\u001b[1m)\u001b[0m,                                           \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   \u001b[0m\u001b[33mgrid_z\u001b[0m=\u001b[1;35mUniformGrid\u001b[0m\u001b[1m(\u001b[0m\u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m, \u001b[33mtype\u001b[0m=\u001b[32m'UniformGrid'\u001b[0m, \u001b[33mdl\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.2\u001b[0m\u001b[1m)\u001b[0m,                                           \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   \u001b[0m\u001b[33mwavelength\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                                                    \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   \u001b[0m\u001b[33moverride_structures\u001b[0m=\u001b[1m(\u001b[0m\u001b[1m)\u001b[0m,                                                                             \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   \u001b[0m\u001b[33msnapping_points\u001b[0m=\u001b[1m(\u001b[0m\u001b[1m)\u001b[0m,                                                                                 \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   \u001b[0m\u001b[33mlayer_refinement_specs\u001b[0m=\u001b[1m(\u001b[0m\u001b[1m)\u001b[0m,                                                                          \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   \u001b[0m\u001b[33mtype\u001b[0m=\u001b[32m'GridSpec'\u001b[0m                                                                                     \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   \u001b[0m\u001b[1m)\u001b[0m,                                                                                                      \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   \u001b[0m\u001b[33mversion\u001b[0m=\u001b[32m'2.9.0'\u001b[0m,                                                                                        \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   \u001b[0m\u001b[33mplot_length_units\u001b[0m=\u001b[32m'μm'\u001b[0m,                                                                                 \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   \u001b[0m\u001b[33mstructure_priority_mode\u001b[0m=\u001b[32m'equal'\u001b[0m,                                                                        \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   \u001b[0m\u001b[33mlumped_elements\u001b[0m=\u001b[1m(\u001b[0m\u001b[1m)\u001b[0m,                                                                                     \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   \u001b[0m\u001b[33msubpixel\u001b[0m=\u001b[1;35mSubpixelSpec\u001b[0m\u001b[1m(\u001b[0m                                                                                  \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   \u001b[0m\u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                                                           \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   \u001b[0m\u001b[33mdielectric\u001b[0m=\u001b[1;35mPolarizedAveraging\u001b[0m\u001b[1m(\u001b[0m\u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m, \u001b[33mtype\u001b[0m=\u001b[32m'PolarizedAveraging'\u001b[0m\u001b[1m)\u001b[0m,                                 \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   \u001b[0m\u001b[33mmetal\u001b[0m=\u001b[1;35mStaircasing\u001b[0m\u001b[1m(\u001b[0m\u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m, \u001b[33mtype\u001b[0m=\u001b[32m'Staircasing'\u001b[0m\u001b[1m)\u001b[0m,                                                    \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   \u001b[0m\u001b[33mpec\u001b[0m=\u001b[1;35mPECConformal\u001b[0m\u001b[1m(\u001b[0m                                                                                   \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   \u001b[0m\u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                                                       \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   \u001b[0m\u001b[33mtype\u001b[0m=\u001b[32m'PECConformal'\u001b[0m,                                                                            \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   \u001b[0m\u001b[33mtimestep_reduction\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.3\u001b[0m,                                                                         \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   \u001b[0m\u001b[33medge_singularity_correction\u001b[0m=\u001b[3;91mFalse\u001b[0m                                                               \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   \u001b[0m\u001b[1m)\u001b[0m,                                                                                                  \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   \u001b[0m\u001b[33mpmc\u001b[0m=\u001b[1;35mStaircasing\u001b[0m\u001b[1m(\u001b[0m\u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m, \u001b[33mtype\u001b[0m=\u001b[32m'Staircasing'\u001b[0m\u001b[1m)\u001b[0m,                                                      \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   \u001b[0m\u001b[33mlossy_metal\u001b[0m=\u001b[1;35mSurfaceImpedance\u001b[0m\u001b[1m(\u001b[0m                                                                       \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   \u001b[0m\u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                                                       \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   \u001b[0m\u001b[33mtype\u001b[0m=\u001b[32m'SurfaceImpedance'\u001b[0m,                                                                        \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   \u001b[0m\u001b[33mtimestep_reduction\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.0\u001b[0m,                                                                         \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   │   \u001b[0m\u001b[33medge_singularity_correction\u001b[0m=\u001b[3;91mFalse\u001b[0m                                                               \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   \u001b[0m\u001b[1m)\u001b[0m,                                                                                                  \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   │   \u001b[0m\u001b[33mtype\u001b[0m=\u001b[32m'SubpixelSpec'\u001b[0m                                                                                 \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   \u001b[0m\u001b[1m)\u001b[0m,                                                                                                      \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   \u001b[0m\u001b[33msimulation_type\u001b[0m=\u001b[32m'tidy3d'\u001b[0m,                                                                               \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   \u001b[0m\u001b[33mpost_norm\u001b[0m=\u001b[1;36m1\u001b[0m\u001b[1;36m.0\u001b[0m,                                                                                          \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   \u001b[0m\u001b[33mcourant\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.99\u001b[0m,                                                                                           \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   \u001b[0m\u001b[33mprecision\u001b[0m=\u001b[32m'hybrid'\u001b[0m,                                                                                     \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   \u001b[0m\u001b[33mnormalize_index\u001b[0m=\u001b[1;36m0\u001b[0m,                                                                                      \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   \u001b[0m\u001b[33mshutoff\u001b[0m=\u001b[1;36m1e\u001b[0m\u001b[1;36m-05\u001b[0m,                                                                                          \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│   \u001b[0m\u001b[33mrun_time\u001b[0m=\u001b[1;36m1e\u001b[0m\u001b[1;36m-12\u001b[0m                                                                                          \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[1m)\u001b[0m                                                                                                           \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[32m╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                                                                                                 \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                \u001b[3;33mall_structures\u001b[0m = \u001b[1m[\u001b[0m                                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[1;35mStructure\u001b[0m\u001b[1m(\u001b[0m                                                                  \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mgeometry\u001b[0m=\u001b[1;35mBox\u001b[0m\u001b[1m(\u001b[0m                                                           \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                           \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mtype\u001b[0m=\u001b[32m'Box'\u001b[0m,                                                         \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mcenter\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m\u001b[1m)\u001b[0m,                                             \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33msize\u001b[0m=\u001b[1m(\u001b[0minf, inf, inf\u001b[1m)\u001b[0m                                                \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[1m)\u001b[0m,                                                                      \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mname\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                              \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mbackground_permittivity\u001b[0m=\u001b[3;35mNone\u001b[0m,                                           \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mbackground_medium\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                 \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mpriority\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                          \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mtype\u001b[0m=\u001b[32m'Structure'\u001b[0m,                                                       \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mmedium\u001b[0m=\u001b[1;35mMedium\u001b[0m\u001b[1m(\u001b[0m                                                          \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                           \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mname\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                          \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mfrequency_range\u001b[0m=\u001b[3;35mNone\u001b[0m,                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mallow_gain\u001b[0m=\u001b[3;91mFalse\u001b[0m,                                                   \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mnonlinear_spec\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mmodulation_spec\u001b[0m=\u001b[3;35mNone\u001b[0m,                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mviz_spec\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                      \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mheat_spec\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                     \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mtype\u001b[0m=\u001b[32m'Medium'\u001b[0m,                                                      \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mpermittivity\u001b[0m=\u001b[1;36m1\u001b[0m\u001b[1;36m.0\u001b[0m,                                                   \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mconductivity\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.0\u001b[0m                                                    \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[1m)\u001b[0m                                                                       \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[1m)\u001b[0m,                                                                          \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[1;35mStructure\u001b[0m\u001b[1m(\u001b[0m                                                                  \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mgeometry\u001b[0m=\u001b[1;35mBox\u001b[0m\u001b[1m(\u001b[0m                                                           \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                           \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mtype\u001b[0m=\u001b[32m'Box'\u001b[0m,                                                         \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mcenter\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m\u001b[1m)\u001b[0m,                                             \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33msize\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m1.0\u001b[0m, \u001b[1;36m1.0\u001b[0m, \u001b[1;36m1.0\u001b[0m\u001b[1m)\u001b[0m                                                \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[1m)\u001b[0m,                                                                      \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mname\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                              \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mbackground_permittivity\u001b[0m=\u001b[3;35mNone\u001b[0m,                                           \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mbackground_medium\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                 \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mpriority\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                          \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mtype\u001b[0m=\u001b[32m'Structure'\u001b[0m,                                                       \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mmedium\u001b[0m=\u001b[1;35mMedium\u001b[0m\u001b[1m(\u001b[0m                                                          \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                           \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mname\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                          \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mfrequency_range\u001b[0m=\u001b[3;35mNone\u001b[0m,                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mallow_gain\u001b[0m=\u001b[3;91mFalse\u001b[0m,                                                   \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mnonlinear_spec\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mmodulation_spec\u001b[0m=\u001b[3;35mNone\u001b[0m,                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mviz_spec\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                      \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mheat_spec\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                     \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mtype\u001b[0m=\u001b[32m'Medium'\u001b[0m,                                                      \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mpermittivity\u001b[0m=\u001b[1;36m2\u001b[0m\u001b[1;36m.0\u001b[0m,                                                   \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mconductivity\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.0\u001b[0m                                                    \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[1m)\u001b[0m                                                                       \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[1m)\u001b[0m                                                                           \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                 \u001b[1m]\u001b[0m                                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                    \u001b[3;33mallow_gain\u001b[0m = \u001b[3;91mFalse\u001b[0m                                                                           \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                         \u001b[3;33mattrs\u001b[0m = \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m                                                                              \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                    \u001b[3;33maux_fields\u001b[0m = \u001b[1m[\u001b[0m\u001b[1m]\u001b[0m                                                                              \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m          \u001b[3;33mbackground_structure\u001b[0m = \u001b[1;35mStructure\u001b[0m\u001b[1m(\u001b[0m                                                                      \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                                   \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mgeometry\u001b[0m=\u001b[1;35mBox\u001b[0m\u001b[1m(\u001b[0m                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mtype\u001b[0m=\u001b[32m'Box'\u001b[0m,                                                             \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mcenter\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m\u001b[1m)\u001b[0m,                                                 \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33msize\u001b[0m=\u001b[1m(\u001b[0minf, inf, inf\u001b[1m)\u001b[0m                                                    \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[1m)\u001b[0m,                                                                          \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mname\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                                  \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mbackground_permittivity\u001b[0m=\u001b[3;35mNone\u001b[0m,                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mbackground_medium\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                     \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mpriority\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                              \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mtype\u001b[0m=\u001b[32m'Structure'\u001b[0m,                                                           \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mmedium\u001b[0m=\u001b[1;35mMedium\u001b[0m\u001b[1m(\u001b[0m                                                              \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mname\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                              \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mfrequency_range\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                   \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mallow_gain\u001b[0m=\u001b[3;91mFalse\u001b[0m,                                                       \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mnonlinear_spec\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                    \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mmodulation_spec\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                   \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mviz_spec\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                          \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mheat_spec\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                         \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mtype\u001b[0m=\u001b[32m'Medium'\u001b[0m,                                                          \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mpermittivity\u001b[0m=\u001b[1;36m1\u001b[0m\u001b[1;36m.0\u001b[0m,                                                       \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mconductivity\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.0\u001b[0m                                                        \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[1m)\u001b[0m                                                                           \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                 \u001b[1m)\u001b[0m                                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                 \u001b[3;33mboundary_spec\u001b[0m = \u001b[1;35mBoundarySpec\u001b[0m\u001b[1m(\u001b[0m                                                                   \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                                   \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mx\u001b[0m=\u001b[1;35mBoundary\u001b[0m\u001b[1m(\u001b[0m                                                                 \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mplus\u001b[0m=\u001b[1;35mPeriodic\u001b[0m\u001b[1m(\u001b[0m\u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m, \u001b[33mname\u001b[0m=\u001b[3;35mNone\u001b[0m, \u001b[33mtype\u001b[0m=\u001b[32m'Periodic'\u001b[0m\u001b[1m)\u001b[0m,                    \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mminus\u001b[0m=\u001b[1;35mPeriodic\u001b[0m\u001b[1m(\u001b[0m\u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m, \u001b[33mname\u001b[0m=\u001b[3;35mNone\u001b[0m, \u001b[33mtype\u001b[0m=\u001b[32m'Periodic'\u001b[0m\u001b[1m)\u001b[0m,                   \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mtype\u001b[0m=\u001b[32m'Boundary'\u001b[0m                                                         \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[1m)\u001b[0m,                                                                          \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33my\u001b[0m=\u001b[1;35mBoundary\u001b[0m\u001b[1m(\u001b[0m                                                                 \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mplus\u001b[0m=\u001b[1;35mPML\u001b[0m\u001b[1m(\u001b[0m                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                           \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mname\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                          \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mtype\u001b[0m=\u001b[32m'PML'\u001b[0m,                                                         \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mnum_layers\u001b[0m=\u001b[1;36m12\u001b[0m,                                                      \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mparameters\u001b[0m=\u001b[1;35mPMLParams\u001b[0m\u001b[1m(\u001b[0m                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                                 \u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                       \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                                 \u001b[33msigma_order\u001b[0m=\u001b[1;36m3\u001b[0m,                                                  \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                                 \u001b[33msigma_min\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.0\u001b[0m,                                                  \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                                 \u001b[33msigma_max\u001b[0m=\u001b[1;36m1\u001b[0m\u001b[1;36m.5\u001b[0m,                                                  \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                                 \u001b[33mtype\u001b[0m=\u001b[32m'PMLParams'\u001b[0m,                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                                 \u001b[33mkappa_order\u001b[0m=\u001b[1;36m3\u001b[0m,                                                  \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                                 \u001b[33mkappa_min\u001b[0m=\u001b[1;36m1\u001b[0m\u001b[1;36m.0\u001b[0m,                                                  \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                                 \u001b[33mkappa_max\u001b[0m=\u001b[1;36m3\u001b[0m\u001b[1;36m.0\u001b[0m,                                                  \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                                 \u001b[33malpha_order\u001b[0m=\u001b[1;36m1\u001b[0m,                                                  \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                                 \u001b[33malpha_min\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.0\u001b[0m,                                                  \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                                 \u001b[33malpha_max\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.0\u001b[0m                                                   \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[1m)\u001b[0m                                                                   \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[1m)\u001b[0m,                                                                      \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mminus\u001b[0m=\u001b[1;35mPML\u001b[0m\u001b[1m(\u001b[0m                                                              \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                           \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mname\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                          \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mtype\u001b[0m=\u001b[32m'PML'\u001b[0m,                                                         \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mnum_layers\u001b[0m=\u001b[1;36m12\u001b[0m,                                                      \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mparameters\u001b[0m=\u001b[1;35mPMLParams\u001b[0m\u001b[1m(\u001b[0m                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                                 \u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                       \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                                 \u001b[33msigma_order\u001b[0m=\u001b[1;36m3\u001b[0m,                                                  \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                                 \u001b[33msigma_min\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.0\u001b[0m,                                                  \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                                 \u001b[33msigma_max\u001b[0m=\u001b[1;36m1\u001b[0m\u001b[1;36m.5\u001b[0m,                                                  \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                                 \u001b[33mtype\u001b[0m=\u001b[32m'PMLParams'\u001b[0m,                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                                 \u001b[33mkappa_order\u001b[0m=\u001b[1;36m3\u001b[0m,                                                  \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                                 \u001b[33mkappa_min\u001b[0m=\u001b[1;36m1\u001b[0m\u001b[1;36m.0\u001b[0m,                                                  \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                                 \u001b[33mkappa_max\u001b[0m=\u001b[1;36m3\u001b[0m\u001b[1;36m.0\u001b[0m,                                                  \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                                 \u001b[33malpha_order\u001b[0m=\u001b[1;36m1\u001b[0m,                                                  \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                                 \u001b[33malpha_min\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.0\u001b[0m,                                                  \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                                 \u001b[33malpha_max\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.0\u001b[0m                                                   \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[1m)\u001b[0m                                                                   \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[1m)\u001b[0m,                                                                      \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mtype\u001b[0m=\u001b[32m'Boundary'\u001b[0m                                                         \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[1m)\u001b[0m,                                                                          \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mz\u001b[0m=\u001b[1;35mBoundary\u001b[0m\u001b[1m(\u001b[0m                                                                 \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mplus\u001b[0m=\u001b[1;35mPeriodic\u001b[0m\u001b[1m(\u001b[0m\u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m, \u001b[33mname\u001b[0m=\u001b[3;35mNone\u001b[0m, \u001b[33mtype\u001b[0m=\u001b[32m'Periodic'\u001b[0m\u001b[1m)\u001b[0m,                    \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mminus\u001b[0m=\u001b[1;35mPeriodic\u001b[0m\u001b[1m(\u001b[0m\u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m, \u001b[33mname\u001b[0m=\u001b[3;35mNone\u001b[0m, \u001b[33mtype\u001b[0m=\u001b[32m'Periodic'\u001b[0m\u001b[1m)\u001b[0m,                   \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mtype\u001b[0m=\u001b[32m'Boundary'\u001b[0m                                                         \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[1m)\u001b[0m,                                                                          \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mtype\u001b[0m=\u001b[32m'BoundarySpec'\u001b[0m                                                         \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                 \u001b[1m)\u001b[0m                                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                  \u001b[3;33mbounding_box\u001b[0m = \u001b[1;35mBox\u001b[0m\u001b[1m(\u001b[0m\u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m, \u001b[33mtype\u001b[0m=\u001b[32m'Box'\u001b[0m, \u001b[33mcenter\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m\u001b[1m)\u001b[0m, \u001b[33msize\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m4.0\u001b[0m, \u001b[1;36m4.0\u001b[0m, \u001b[1;36m4.0\u001b[0m\u001b[1m)\u001b[0m\u001b[1m)\u001b[0m         \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                        \u001b[3;33mbounds\u001b[0m = \u001b[1m(\u001b[0m\u001b[1m(\u001b[0m\u001b[1;36m-2.0\u001b[0m, \u001b[1;36m-2.0\u001b[0m, \u001b[1;36m-2.0\u001b[0m\u001b[1m)\u001b[0m, \u001b[1m(\u001b[0m\u001b[1;36m2.0\u001b[0m, \u001b[1;36m2.0\u001b[0m, \u001b[1;36m2.0\u001b[0m\u001b[1m)\u001b[0m\u001b[1m)\u001b[0m                                           \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                    \u001b[3;33mbounds_pml\u001b[0m = \u001b[1m(\u001b[0m                                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[1m(\u001b[0m\u001b[1;35mnp.float64\u001b[0m\u001b[1m(\u001b[0m\u001b[1;36m-2.0\u001b[0m\u001b[1m)\u001b[0m, \u001b[1;35mnp.float64\u001b[0m\u001b[1m(\u001b[0m\u001b[1;36m-4.3999999999999995\u001b[0m\u001b[1m)\u001b[0m, \u001b[1;35mnp.float64\u001b[0m\u001b[1m(\u001b[0m\u001b[1;36m-2.0\u001b[0m\u001b[1m)\u001b[0m\u001b[1m)\u001b[0m,      \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[1m(\u001b[0m\u001b[1;35mnp.float64\u001b[0m\u001b[1m(\u001b[0m\u001b[1;36m2.0\u001b[0m\u001b[1m)\u001b[0m, \u001b[1;35mnp.float64\u001b[0m\u001b[1m(\u001b[0m\u001b[1;36m4.399999999999997\u001b[0m\u001b[1m)\u001b[0m, \u001b[1;35mnp.float64\u001b[0m\u001b[1m(\u001b[0m\u001b[1;36m2.0\u001b[0m\u001b[1m)\u001b[0m\u001b[1m)\u001b[0m           \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                 \u001b[1m)\u001b[0m                                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                        \u001b[3;33mcenter\u001b[0m = \u001b[1m(\u001b[0m\u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m\u001b[1m)\u001b[0m                                                                 \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                \u001b[3;33mcomplex_fields\u001b[0m = \u001b[3;91mFalse\u001b[0m                                                                           \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                       \u001b[3;33mcourant\u001b[0m = \u001b[1;36m0.99\u001b[0m                                                                            \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m               \u001b[3;33mcustom_datasets\u001b[0m = \u001b[1m[\u001b[0m\u001b[1m]\u001b[0m                                                                              \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                            \u001b[3;33mdt\u001b[0m = \u001b[1;35mnp.float64\u001b[0m\u001b[1m(\u001b[0m\u001b[1;36m3.813149739062003e-16\u001b[0m\u001b[1m)\u001b[0m                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m               \u001b[3;33mfrequency_range\u001b[0m = \u001b[1m(\u001b[0m\u001b[1;36m110000000000000.0\u001b[0m, \u001b[1;36m190000000000000.0\u001b[0m\u001b[1m)\u001b[0m                                          \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                      \u001b[3;33mgeometry\u001b[0m = \u001b[1;35mBox\u001b[0m\u001b[1m(\u001b[0m\u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m, \u001b[33mtype\u001b[0m=\u001b[32m'Box'\u001b[0m, \u001b[33mcenter\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m\u001b[1m)\u001b[0m, \u001b[33msize\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m4.0\u001b[0m, \u001b[1;36m4.0\u001b[0m, \u001b[1;36m4.0\u001b[0m\u001b[1m)\u001b[0m\u001b[1m)\u001b[0m         \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                          \u001b[3;33mgrid\u001b[0m = \u001b[1;35mGrid\u001b[0m\u001b[1m(\u001b[0m                                                                           \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                                   \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mboundaries\u001b[0m=\u001b[1;35mCoords\u001b[0m\u001b[1m(\u001b[0m                                                          \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mx\u001b[0m=\u001b[1;35marray\u001b[0m\u001b[1m(\u001b[0m\u001b[1m[\u001b[0m\u001b[1;36m-2\u001b[0m. , \u001b[1;36m-1.8\u001b[0m, \u001b[1;36m-1.6\u001b[0m, \u001b[1;36m-1.4\u001b[0m, \u001b[1;36m-1.2\u001b[0m, \u001b[1;36m-1\u001b[0m. , \u001b[1;36m-0.8\u001b[0m, \u001b[1;36m-0.6\u001b[0m, \u001b[1;36m-0.4\u001b[0m, \u001b[1;36m-0.2\u001b[0m,    \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                 \u001b[1;36m0\u001b[0m. ,                                                                            \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[1;36m0.2\u001b[0m,  \u001b[1;36m0.4\u001b[0m,  \u001b[1;36m0.6\u001b[0m,  \u001b[1;36m0.8\u001b[0m,  \u001b[1;36m1\u001b[0m. ,  \u001b[1;36m1.2\u001b[0m,  \u001b[1;36m1.4\u001b[0m,  \u001b[1;36m1.6\u001b[0m,  \u001b[1;36m1.8\u001b[0m,  \u001b[1;36m2\u001b[0m. \u001b[1m]\u001b[0m\u001b[1m)\u001b[0m,            \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33my\u001b[0m=\u001b[1;35marray\u001b[0m\u001b[1m(\u001b[0m\u001b[1m[\u001b[0m\u001b[1;36m-4.4\u001b[0m, \u001b[1;36m-4.2\u001b[0m, \u001b[1;36m-4\u001b[0m. , \u001b[1;36m-3.8\u001b[0m, \u001b[1;36m-3.6\u001b[0m, \u001b[1;36m-3.4\u001b[0m, \u001b[1;36m-3.2\u001b[0m, \u001b[1;36m-3\u001b[0m. , \u001b[1;36m-2.8\u001b[0m, \u001b[1;36m-2.6\u001b[0m,    \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                 \u001b[1;36m-2.4\u001b[0m,                                                                           \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                        \u001b[1;36m-2.2\u001b[0m, \u001b[1;36m-2\u001b[0m. , \u001b[1;36m-1.8\u001b[0m, \u001b[1;36m-1.6\u001b[0m, \u001b[1;36m-1.4\u001b[0m, \u001b[1;36m-1.2\u001b[0m, \u001b[1;36m-1\u001b[0m. , \u001b[1;36m-0.8\u001b[0m, \u001b[1;36m-0.6\u001b[0m, \u001b[1;36m-0.4\u001b[0m, \u001b[1;36m-0.2\u001b[0m,        \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[1;36m0\u001b[0m. ,  \u001b[1;36m0.2\u001b[0m,  \u001b[1;36m0.4\u001b[0m,  \u001b[1;36m0.6\u001b[0m,  \u001b[1;36m0.8\u001b[0m,  \u001b[1;36m1\u001b[0m. ,  \u001b[1;36m1.2\u001b[0m,  \u001b[1;36m1.4\u001b[0m,  \u001b[1;36m1.6\u001b[0m,  \u001b[1;36m1.8\u001b[0m,  \u001b[1;36m2\u001b[0m. ,        \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[1;36m2.2\u001b[0m,  \u001b[1;36m2.4\u001b[0m,  \u001b[1;36m2.6\u001b[0m,  \u001b[1;36m2.8\u001b[0m,  \u001b[1;36m3\u001b[0m. ,  \u001b[1;36m3.2\u001b[0m,  \u001b[1;36m3.4\u001b[0m,  \u001b[1;36m3.6\u001b[0m,  \u001b[1;36m3.8\u001b[0m,  \u001b[1;36m4\u001b[0m. ,  \u001b[1;36m4.2\u001b[0m,        \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[1;36m4.4\u001b[0m\u001b[1m]\u001b[0m\u001b[1m)\u001b[0m,                                                                  \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mz\u001b[0m=\u001b[1;35marray\u001b[0m\u001b[1m(\u001b[0m\u001b[1m[\u001b[0m\u001b[1;36m-2\u001b[0m. , \u001b[1;36m-1.8\u001b[0m, \u001b[1;36m-1.6\u001b[0m, \u001b[1;36m-1.4\u001b[0m, \u001b[1;36m-1.2\u001b[0m, \u001b[1;36m-1\u001b[0m. , \u001b[1;36m-0.8\u001b[0m, \u001b[1;36m-0.6\u001b[0m, \u001b[1;36m-0.4\u001b[0m, \u001b[1;36m-0.2\u001b[0m,    \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                 \u001b[1;36m0\u001b[0m. ,                                                                            \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[1;36m0.2\u001b[0m,  \u001b[1;36m0.4\u001b[0m,  \u001b[1;36m0.6\u001b[0m,  \u001b[1;36m0.8\u001b[0m,  \u001b[1;36m1\u001b[0m. ,  \u001b[1;36m1.2\u001b[0m,  \u001b[1;36m1.4\u001b[0m,  \u001b[1;36m1.6\u001b[0m,  \u001b[1;36m1.8\u001b[0m,  \u001b[1;36m2\u001b[0m. \u001b[1m]\u001b[0m\u001b[1m)\u001b[0m,            \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mtype\u001b[0m=\u001b[32m'Coords'\u001b[0m                                                           \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[1m)\u001b[0m,                                                                          \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mtype\u001b[0m=\u001b[32m'Grid'\u001b[0m                                                                 \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                 \u001b[1m)\u001b[0m                                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                     \u001b[3;33mgrid_info\u001b[0m = \u001b[1m{\u001b[0m                                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[32m'Nx'\u001b[0m: \u001b[1;36m20\u001b[0m,                                                                   \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[32m'Ny'\u001b[0m: \u001b[1;36m44\u001b[0m,                                                                   \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[32m'Nz'\u001b[0m: \u001b[1;36m20\u001b[0m,                                                                   \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[32m'grid_points'\u001b[0m: \u001b[1;36m17600\u001b[0m,                                                       \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[32m'min_grid_size'\u001b[0m: \u001b[1;36m0.1999999999999993\u001b[0m,                                        \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[32m'max_grid_size'\u001b[0m: \u001b[1;36m0.20000000000000018\u001b[0m,                                       \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[32m'computational_complexity'\u001b[0m: \u001b[1;36m88000.0000000003\u001b[0m                                \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                 \u001b[1m}\u001b[0m                                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                     \u001b[3;33mgrid_spec\u001b[0m = \u001b[1;35mGridSpec\u001b[0m\u001b[1m(\u001b[0m                                                                       \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                                   \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mgrid_x\u001b[0m=\u001b[1;35mUniformGrid\u001b[0m\u001b[1m(\u001b[0m\u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m, \u001b[33mtype\u001b[0m=\u001b[32m'UniformGrid'\u001b[0m, \u001b[33mdl\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.2\u001b[0m\u001b[1m)\u001b[0m,                   \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mgrid_y\u001b[0m=\u001b[1;35mUniformGrid\u001b[0m\u001b[1m(\u001b[0m\u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m, \u001b[33mtype\u001b[0m=\u001b[32m'UniformGrid'\u001b[0m, \u001b[33mdl\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.2\u001b[0m\u001b[1m)\u001b[0m,                   \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mgrid_z\u001b[0m=\u001b[1;35mUniformGrid\u001b[0m\u001b[1m(\u001b[0m\u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m, \u001b[33mtype\u001b[0m=\u001b[32m'UniformGrid'\u001b[0m, \u001b[33mdl\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.2\u001b[0m\u001b[1m)\u001b[0m,                   \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mwavelength\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                            \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33moverride_structures\u001b[0m=\u001b[1m(\u001b[0m\u001b[1m)\u001b[0m,                                                     \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33msnapping_points\u001b[0m=\u001b[1m(\u001b[0m\u001b[1m)\u001b[0m,                                                         \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mlayer_refinement_specs\u001b[0m=\u001b[1m(\u001b[0m\u001b[1m)\u001b[0m,                                                  \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mtype\u001b[0m=\u001b[32m'GridSpec'\u001b[0m                                                             \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                 \u001b[1m)\u001b[0m                                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m  \u001b[3;33minternal_override_structures\u001b[0m = \u001b[1m[\u001b[0m\u001b[1m]\u001b[0m                                                                              \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m      \u001b[3;33minternal_snapping_points\u001b[0m = \u001b[1m[\u001b[0m\u001b[1m]\u001b[0m                                                                              \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m               \u001b[3;33mlumped_elements\u001b[0m = \u001b[1m(\u001b[0m\u001b[1m)\u001b[0m                                                                              \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                        \u001b[3;33mmedium\u001b[0m = \u001b[1;35mMedium\u001b[0m\u001b[1m(\u001b[0m                                                                         \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                                   \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mname\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                                  \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mfrequency_range\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                       \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mallow_gain\u001b[0m=\u001b[3;91mFalse\u001b[0m,                                                           \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mnonlinear_spec\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                        \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mmodulation_spec\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                       \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mviz_spec\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                              \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mheat_spec\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                             \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mtype\u001b[0m=\u001b[32m'Medium'\u001b[0m,                                                              \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mpermittivity\u001b[0m=\u001b[1;36m1\u001b[0m\u001b[1;36m.0\u001b[0m,                                                           \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mconductivity\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.0\u001b[0m                                                            \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                 \u001b[1m)\u001b[0m                                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                    \u001b[3;33mmedium_map\u001b[0m = \u001b[1m{\u001b[0m                                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[1;35mMedium\u001b[0m\u001b[1m(\u001b[0m\u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m, \u001b[33mname\u001b[0m=\u001b[3;35mNone\u001b[0m, \u001b[33mfrequency_range\u001b[0m=\u001b[3;35mNone\u001b[0m, \u001b[33mallow_gain\u001b[0m=\u001b[3;91mFalse\u001b[0m,         \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                 \u001b[33mnonlinear_spec\u001b[0m=\u001b[3;35mNone\u001b[0m, \u001b[33mmodulation_spec\u001b[0m=\u001b[3;35mNone\u001b[0m, \u001b[33mviz_spec\u001b[0m=\u001b[3;35mNone\u001b[0m, \u001b[33mheat_spec\u001b[0m=\u001b[3;35mNone\u001b[0m,       \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                 \u001b[33mtype\u001b[0m=\u001b[32m'Medium'\u001b[0m, \u001b[33mpermittivity\u001b[0m=\u001b[1;36m1\u001b[0m\u001b[1;36m.0\u001b[0m, \u001b[33mconductivity\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.0\u001b[0m\u001b[1m)\u001b[0m: \u001b[1;36m0\u001b[0m,                          \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[1;35mMedium\u001b[0m\u001b[1m(\u001b[0m\u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m, \u001b[33mname\u001b[0m=\u001b[3;35mNone\u001b[0m, \u001b[33mfrequency_range\u001b[0m=\u001b[3;35mNone\u001b[0m, \u001b[33mallow_gain\u001b[0m=\u001b[3;91mFalse\u001b[0m,         \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                 \u001b[33mnonlinear_spec\u001b[0m=\u001b[3;35mNone\u001b[0m, \u001b[33mmodulation_spec\u001b[0m=\u001b[3;35mNone\u001b[0m, \u001b[33mviz_spec\u001b[0m=\u001b[3;35mNone\u001b[0m, \u001b[33mheat_spec\u001b[0m=\u001b[3;35mNone\u001b[0m,       \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                 \u001b[33mtype\u001b[0m=\u001b[32m'Medium'\u001b[0m, \u001b[33mpermittivity\u001b[0m=\u001b[1;36m2\u001b[0m\u001b[1;36m.0\u001b[0m, \u001b[33mconductivity\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.0\u001b[0m\u001b[1m)\u001b[0m: \u001b[1;36m1\u001b[0m                           \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                 \u001b[1m}\u001b[0m                                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                       \u001b[3;33mmediums\u001b[0m = \u001b[1m[\u001b[0m                                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[1;35mMedium\u001b[0m\u001b[1m(\u001b[0m                                                                     \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mname\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                              \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mfrequency_range\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                   \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mallow_gain\u001b[0m=\u001b[3;91mFalse\u001b[0m,                                                       \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mnonlinear_spec\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                    \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mmodulation_spec\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                   \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mviz_spec\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                          \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mheat_spec\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                         \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mtype\u001b[0m=\u001b[32m'Medium'\u001b[0m,                                                          \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mpermittivity\u001b[0m=\u001b[1;36m1\u001b[0m\u001b[1;36m.0\u001b[0m,                                                       \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mconductivity\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.0\u001b[0m                                                        \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[1m)\u001b[0m,                                                                          \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[1;35mMedium\u001b[0m\u001b[1m(\u001b[0m                                                                     \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mname\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                              \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mfrequency_range\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                   \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mallow_gain\u001b[0m=\u001b[3;91mFalse\u001b[0m,                                                       \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mnonlinear_spec\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                    \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mmodulation_spec\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                   \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mviz_spec\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                          \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mheat_spec\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                         \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mtype\u001b[0m=\u001b[32m'Medium'\u001b[0m,                                                          \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mpermittivity\u001b[0m=\u001b[1;36m2\u001b[0m\u001b[1;36m.0\u001b[0m,                                                       \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mconductivity\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.0\u001b[0m                                                        \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[1m)\u001b[0m                                                                           \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                 \u001b[1m]\u001b[0m                                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                      \u001b[3;33mmonitors\u001b[0m = \u001b[1m(\u001b[0m                                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[1;35mFieldMonitor\u001b[0m\u001b[1m(\u001b[0m                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mtype\u001b[0m=\u001b[32m'FieldMonitor'\u001b[0m,                                                    \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mcenter\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m1.0\u001b[0m, \u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m\u001b[1m)\u001b[0m,                                                 \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33msize\u001b[0m=\u001b[1m(\u001b[0minf, inf, \u001b[1;36m0.0\u001b[0m\u001b[1m)\u001b[0m,                                                   \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mname\u001b[0m=\u001b[32m'fields_at_150THz'\u001b[0m,                                                \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33minterval_space\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m1\u001b[0m, \u001b[1;36m1\u001b[0m, \u001b[1;36m1\u001b[0m\u001b[1m)\u001b[0m,                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mcolocate\u001b[0m=\u001b[3;92mTrue\u001b[0m,                                                          \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mfreqs\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m150000000000000.0\u001b[0m,\u001b[1m)\u001b[0m,                                             \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mapodization\u001b[0m=\u001b[1;35mApodizationSpec\u001b[0m\u001b[1m(\u001b[0m                                            \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                           \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mstart\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                         \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mend\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                           \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mwidth\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                         \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mtype\u001b[0m=\u001b[32m'ApodizationSpec'\u001b[0m                                              \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[1m)\u001b[0m,                                                                      \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mfields\u001b[0m=\u001b[1m(\u001b[0m\u001b[32m'Ex'\u001b[0m, \u001b[32m'Ey'\u001b[0m, \u001b[32m'Hz'\u001b[0m\u001b[1m)\u001b[0m                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[1m)\u001b[0m,                                                                          \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[1;35mFluxTimeMonitor\u001b[0m\u001b[1m(\u001b[0m                                                            \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mtype\u001b[0m=\u001b[32m'FluxTimeMonitor'\u001b[0m,                                                 \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mcenter\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m1.0\u001b[0m, \u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m\u001b[1m)\u001b[0m,                                                 \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33msize\u001b[0m=\u001b[1m(\u001b[0minf, inf, \u001b[1;36m0.0\u001b[0m\u001b[1m)\u001b[0m,                                                   \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mname\u001b[0m=\u001b[32m'flux_over_time'\u001b[0m,                                                  \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33minterval_space\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m1\u001b[0m, \u001b[1;36m1\u001b[0m, \u001b[1;36m1\u001b[0m\u001b[1m)\u001b[0m,                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mcolocate\u001b[0m=\u001b[3;92mTrue\u001b[0m,                                                          \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mstart\u001b[0m=\u001b[1;36m1e\u001b[0m\u001b[1;36m-13\u001b[0m,                                                            \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mstop\u001b[0m=\u001b[1;36m3e\u001b[0m\u001b[1;36m-13\u001b[0m,                                                             \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33minterval\u001b[0m=\u001b[1;36m5\u001b[0m,                                                             \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mnormal_dir\u001b[0m=\u001b[32m'+'\u001b[0m,                                                         \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mexclude_surfaces\u001b[0m=\u001b[3;35mNone\u001b[0m                                                   \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[1m)\u001b[0m                                                                           \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                 \u001b[1m)\u001b[0m                                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m            \u001b[3;33mmonitors_data_size\u001b[0m = \u001b[1m{\u001b[0m\u001b[32m'fields_at_150THz'\u001b[0m: \u001b[1;36m22680.0\u001b[0m, \u001b[32m'flux_over_time'\u001b[0m: \u001b[1;36m416.0\u001b[0m\u001b[1m}\u001b[0m                          \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                         \u001b[1;3;31mn_max\u001b[0m\u001b[1;31m =\u001b[0m \u001b[1;35mAttributeError\u001b[0m\u001b[1m(\u001b[0m\u001b[32m\"'Simulation' object has no attribute 'freq_max'\"\u001b[0m\u001b[1m)\u001b[0m               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m               \u001b[3;33mnormalize_index\u001b[0m = \u001b[1;36m0\u001b[0m                                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                     \u001b[3;33mnum_cells\u001b[0m = \u001b[1;36m17600\u001b[0m                                                                           \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m \u001b[3;33mnum_computational_grid_points\u001b[0m = \u001b[1;35mnp.int64\u001b[0m\u001b[1m(\u001b[0m\u001b[1;36m18400\u001b[0m\u001b[1m)\u001b[0m                                                                 \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                \u001b[3;33mnum_pml_layers\u001b[0m = \u001b[1m[\u001b[0m\u001b[1m[\u001b[0m\u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m\u001b[1m]\u001b[0m, \u001b[1m[\u001b[0m\u001b[1;36m12\u001b[0m, \u001b[1;36m12\u001b[0m\u001b[1m]\u001b[0m, \u001b[1m[\u001b[0m\u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m\u001b[1m]\u001b[0m\u001b[1m]\u001b[0m                                                      \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                \u001b[3;33mnum_time_steps\u001b[0m = \u001b[1;36m2624\u001b[0m                                                                            \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                  \u001b[3;33mnyquist_step\u001b[0m = \u001b[1;36m5\u001b[0m                                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m             \u001b[3;33mplot_length_units\u001b[0m = \u001b[32m'μm'\u001b[0m                                                                            \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                   \u001b[3;33mplot_params\u001b[0m = \u001b[1;35mPlotParams\u001b[0m\u001b[1m(\u001b[0m                                                                     \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                                   \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33malpha\u001b[0m=\u001b[1;36m1\u001b[0m\u001b[1;36m.0\u001b[0m,                                                                  \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mzorder\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                                \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mtype\u001b[0m=\u001b[32m'PlotParams'\u001b[0m,                                                          \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33medgecolor\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                             \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mfacecolor\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                             \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mfill\u001b[0m=\u001b[3;92mTrue\u001b[0m,                                                                  \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mhatch\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                                 \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mlinewidth\u001b[0m=\u001b[1;36m1\u001b[0m\u001b[1;36m.0\u001b[0m                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                 \u001b[1m)\u001b[0m                                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m               \u001b[3;33mpml_thicknesses\u001b[0m = \u001b[1m[\u001b[0m                                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[1m(\u001b[0m\u001b[1;35mnp.float64\u001b[0m\u001b[1m(\u001b[0m\u001b[1;36m0.0\u001b[0m\u001b[1m)\u001b[0m, \u001b[1;35mnp.float64\u001b[0m\u001b[1m(\u001b[0m\u001b[1;36m0.0\u001b[0m\u001b[1m)\u001b[0m\u001b[1m)\u001b[0m,                                         \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[1m(\u001b[0m\u001b[1;35mnp.float64\u001b[0m\u001b[1m(\u001b[0m\u001b[1;36m2.3999999999999995\u001b[0m\u001b[1m)\u001b[0m, \u001b[1;35mnp.float64\u001b[0m\u001b[1m(\u001b[0m\u001b[1;36m2.399999999999997\u001b[0m\u001b[1m)\u001b[0m\u001b[1m)\u001b[0m,            \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[1m(\u001b[0m\u001b[1;35mnp.float64\u001b[0m\u001b[1m(\u001b[0m\u001b[1;36m0.0\u001b[0m\u001b[1m)\u001b[0m, \u001b[1;35mnp.float64\u001b[0m\u001b[1m(\u001b[0m\u001b[1;36m0.0\u001b[0m\u001b[1m)\u001b[0m\u001b[1m)\u001b[0m                                          \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                 \u001b[1m]\u001b[0m                                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                     \u001b[3;33mpost_norm\u001b[0m = \u001b[1;36m1.0\u001b[0m                                                                             \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                     \u001b[3;33mprecision\u001b[0m = \u001b[32m'hybrid'\u001b[0m                                                                        \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                      \u001b[3;33mrun_time\u001b[0m = \u001b[1;36m1e-12\u001b[0m                                                                           \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                \u001b[3;33mscaled_courant\u001b[0m = \u001b[1;36m0.99\u001b[0m                                                                            \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                         \u001b[3;33mscene\u001b[0m = \u001b[1;35mScene\u001b[0m\u001b[1m(\u001b[0m                                                                          \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                                   \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mmedium\u001b[0m=\u001b[1;35mMedium\u001b[0m\u001b[1m(\u001b[0m                                                              \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mname\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                              \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mfrequency_range\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                   \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mallow_gain\u001b[0m=\u001b[3;91mFalse\u001b[0m,                                                       \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mnonlinear_spec\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                    \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mmodulation_spec\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                   \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mviz_spec\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                          \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mheat_spec\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                         \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mtype\u001b[0m=\u001b[32m'Medium'\u001b[0m,                                                          \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mpermittivity\u001b[0m=\u001b[1;36m1\u001b[0m\u001b[1;36m.0\u001b[0m,                                                       \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mconductivity\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.0\u001b[0m                                                        \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[1m)\u001b[0m,                                                                          \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mstructures\u001b[0m=\u001b[1m(\u001b[0m                                                                \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[1;35mStructure\u001b[0m\u001b[1m(\u001b[0m                                                              \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                           \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mgeometry\u001b[0m=\u001b[1;35mBox\u001b[0m\u001b[1m(\u001b[0m                                                       \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                                 \u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                       \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                                 \u001b[33mtype\u001b[0m=\u001b[32m'Box'\u001b[0m,                                                     \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                                 \u001b[33mcenter\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m\u001b[1m)\u001b[0m,                                         \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                                 \u001b[33msize\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m1.0\u001b[0m, \u001b[1;36m1.0\u001b[0m, \u001b[1;36m1.0\u001b[0m\u001b[1m)\u001b[0m                                            \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[1m)\u001b[0m,                                                                  \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mname\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                          \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mbackground_permittivity\u001b[0m=\u001b[3;35mNone\u001b[0m,                                       \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mbackground_medium\u001b[0m=\u001b[3;35mNone\u001b[0m,                                             \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mpriority\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                      \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mtype\u001b[0m=\u001b[32m'Structure'\u001b[0m,                                                   \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mmedium\u001b[0m=\u001b[1;35mMedium\u001b[0m\u001b[1m(\u001b[0m                                                      \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                                 \u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                       \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                                 \u001b[33mname\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                      \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                                 \u001b[33mfrequency_range\u001b[0m=\u001b[3;35mNone\u001b[0m,                                           \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                                 \u001b[33mallow_gain\u001b[0m=\u001b[3;91mFalse\u001b[0m,                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                                 \u001b[33mnonlinear_spec\u001b[0m=\u001b[3;35mNone\u001b[0m,                                            \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                                 \u001b[33mmodulation_spec\u001b[0m=\u001b[3;35mNone\u001b[0m,                                           \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                                 \u001b[33mviz_spec\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                  \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                                 \u001b[33mheat_spec\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                 \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                                 \u001b[33mtype\u001b[0m=\u001b[32m'Medium'\u001b[0m,                                                  \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                                 \u001b[33mpermittivity\u001b[0m=\u001b[1;36m2\u001b[0m\u001b[1;36m.0\u001b[0m,                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                                 \u001b[33mconductivity\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.0\u001b[0m                                                \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[1m)\u001b[0m                                                                   \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[1m)\u001b[0m,                                                                      \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[1m)\u001b[0m,                                                                          \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mstructure_priority_mode\u001b[0m=\u001b[32m'equal'\u001b[0m,                                            \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mplot_length_units\u001b[0m=\u001b[32m'μm'\u001b[0m,                                                     \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mtype\u001b[0m=\u001b[32m'Scene'\u001b[0m                                                                \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                 \u001b[1m)\u001b[0m                                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                \u001b[3;33mself_structure\u001b[0m = \u001b[1;35mStructure\u001b[0m\u001b[1m(\u001b[0m                                                                      \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                                   \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mgeometry\u001b[0m=\u001b[1;35mBox\u001b[0m\u001b[1m(\u001b[0m                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mtype\u001b[0m=\u001b[32m'Box'\u001b[0m,                                                             \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mcenter\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m\u001b[1m)\u001b[0m,                                                 \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33msize\u001b[0m=\u001b[1m(\u001b[0minf, inf, inf\u001b[1m)\u001b[0m                                                    \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[1m)\u001b[0m,                                                                          \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mname\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                                  \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mbackground_permittivity\u001b[0m=\u001b[3;35mNone\u001b[0m,                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mbackground_medium\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                     \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mpriority\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                              \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mtype\u001b[0m=\u001b[32m'Structure'\u001b[0m,                                                           \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mmedium\u001b[0m=\u001b[1;35mMedium\u001b[0m\u001b[1m(\u001b[0m                                                              \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mname\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                              \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mfrequency_range\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                   \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mallow_gain\u001b[0m=\u001b[3;91mFalse\u001b[0m,                                                       \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mnonlinear_spec\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                    \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mmodulation_spec\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                   \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mviz_spec\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                          \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mheat_spec\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                         \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mtype\u001b[0m=\u001b[32m'Medium'\u001b[0m,                                                          \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mpermittivity\u001b[0m=\u001b[1;36m1\u001b[0m\u001b[1;36m.0\u001b[0m,                                                       \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mconductivity\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.0\u001b[0m                                                        \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[1m)\u001b[0m                                                                           \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                 \u001b[1m)\u001b[0m                                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                       \u001b[3;33mshutoff\u001b[0m = \u001b[1;36m1e-05\u001b[0m                                                                           \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m             \u001b[3;33msimulation_bounds\u001b[0m = \u001b[1m(\u001b[0m                                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[1m(\u001b[0m\u001b[1;35mnp.float64\u001b[0m\u001b[1m(\u001b[0m\u001b[1;36m-2.0\u001b[0m\u001b[1m)\u001b[0m, \u001b[1;35mnp.float64\u001b[0m\u001b[1m(\u001b[0m\u001b[1;36m-4.3999999999999995\u001b[0m\u001b[1m)\u001b[0m, \u001b[1;35mnp.float64\u001b[0m\u001b[1m(\u001b[0m\u001b[1;36m-2.0\u001b[0m\u001b[1m)\u001b[0m\u001b[1m)\u001b[0m,      \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[1m(\u001b[0m\u001b[1;35mnp.float64\u001b[0m\u001b[1m(\u001b[0m\u001b[1;36m2.0\u001b[0m\u001b[1m)\u001b[0m, \u001b[1;35mnp.float64\u001b[0m\u001b[1m(\u001b[0m\u001b[1;36m4.399999999999997\u001b[0m\u001b[1m)\u001b[0m, \u001b[1;35mnp.float64\u001b[0m\u001b[1m(\u001b[0m\u001b[1;36m2.0\u001b[0m\u001b[1m)\u001b[0m\u001b[1m)\u001b[0m           \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                 \u001b[1m)\u001b[0m                                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m           \u001b[3;33msimulation_geometry\u001b[0m = \u001b[1;35mBox\u001b[0m\u001b[1m(\u001b[0m                                                                            \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                                   \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mtype\u001b[0m=\u001b[32m'Box'\u001b[0m,                                                                 \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mcenter\u001b[0m=\u001b[1m(\u001b[0m                                                                    \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[1;35mnp.float64\u001b[0m\u001b[1m(\u001b[0m\u001b[1;36m0.0\u001b[0m\u001b[1m)\u001b[0m,                                                        \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[1;35mnp.float64\u001b[0m\u001b[1m(\u001b[0m\u001b[1;36m-1.3322676295501878e-15\u001b[0m\u001b[1m)\u001b[0m,                                    \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[1;35mnp.float64\u001b[0m\u001b[1m(\u001b[0m\u001b[1;36m0.0\u001b[0m\u001b[1m)\u001b[0m                                                         \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[1m)\u001b[0m,                                                                          \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33msize\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;35mnp.float64\u001b[0m\u001b[1m(\u001b[0m\u001b[1;36m4.0\u001b[0m\u001b[1m)\u001b[0m, \u001b[1;35mnp.float64\u001b[0m\u001b[1m(\u001b[0m\u001b[1;36m8.799999999999997\u001b[0m\u001b[1m)\u001b[0m, \u001b[1;35mnp.float64\u001b[0m\u001b[1m(\u001b[0m\u001b[1;36m4.0\u001b[0m\u001b[1m)\u001b[0m\u001b[1m)\u001b[0m      \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                 \u001b[1m)\u001b[0m                                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m          \u001b[3;33msimulation_structure\u001b[0m = \u001b[1;35mStructure\u001b[0m\u001b[1m(\u001b[0m                                                                      \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                                   \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mgeometry\u001b[0m=\u001b[1;35mBox\u001b[0m\u001b[1m(\u001b[0m                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mtype\u001b[0m=\u001b[32m'Box'\u001b[0m,                                                             \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mcenter\u001b[0m=\u001b[1m(\u001b[0m                                                                \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[1;35mnp.float64\u001b[0m\u001b[1m(\u001b[0m\u001b[1;36m0.0\u001b[0m\u001b[1m)\u001b[0m,                                                    \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[1;35mnp.float64\u001b[0m\u001b[1m(\u001b[0m\u001b[1;36m-1.3322676295501878e-15\u001b[0m\u001b[1m)\u001b[0m,                                \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[1;35mnp.float64\u001b[0m\u001b[1m(\u001b[0m\u001b[1;36m0.0\u001b[0m\u001b[1m)\u001b[0m                                                     \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[1m)\u001b[0m,                                                                      \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33msize\u001b[0m=\u001b[1m(\u001b[0m                                                                  \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[1;35mnp.float64\u001b[0m\u001b[1m(\u001b[0m\u001b[1;36m4.0\u001b[0m\u001b[1m)\u001b[0m,                                                    \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[1;35mnp.float64\u001b[0m\u001b[1m(\u001b[0m\u001b[1;36m8.799999999999997\u001b[0m\u001b[1m)\u001b[0m,                                      \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[1;35mnp.float64\u001b[0m\u001b[1m(\u001b[0m\u001b[1;36m4.0\u001b[0m\u001b[1m)\u001b[0m                                                     \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[1m)\u001b[0m                                                                       \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[1m)\u001b[0m,                                                                          \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mname\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                                  \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mbackground_permittivity\u001b[0m=\u001b[3;35mNone\u001b[0m,                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mbackground_medium\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                     \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mpriority\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                              \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mtype\u001b[0m=\u001b[32m'Structure'\u001b[0m,                                                           \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mmedium\u001b[0m=\u001b[1;35mMedium\u001b[0m\u001b[1m(\u001b[0m                                                              \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mname\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                              \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mfrequency_range\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                   \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mallow_gain\u001b[0m=\u001b[3;91mFalse\u001b[0m,                                                       \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mnonlinear_spec\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                    \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mmodulation_spec\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                   \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mviz_spec\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                          \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mheat_spec\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                         \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mtype\u001b[0m=\u001b[32m'Medium'\u001b[0m,                                                          \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mpermittivity\u001b[0m=\u001b[1;36m1\u001b[0m\u001b[1;36m.0\u001b[0m,                                                       \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mconductivity\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.0\u001b[0m                                                        \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[1m)\u001b[0m                                                                           \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                 \u001b[1m)\u001b[0m                                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m               \u001b[3;33msimulation_type\u001b[0m = \u001b[32m'tidy3d'\u001b[0m                                                                        \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                          \u001b[3;33msize\u001b[0m = \u001b[1m(\u001b[0m\u001b[1;36m4.0\u001b[0m, \u001b[1;36m4.0\u001b[0m, \u001b[1;36m4.0\u001b[0m\u001b[1m)\u001b[0m                                                                 \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                       \u001b[3;33msources\u001b[0m = \u001b[1m(\u001b[0m                                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[1;35mUniformCurrentSource\u001b[0m\u001b[1m(\u001b[0m                                                       \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mname\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                              \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mtype\u001b[0m=\u001b[32m'UniformCurrentSource'\u001b[0m,                                            \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mcenter\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m\u001b[1m)\u001b[0m,                                                 \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33msize\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m\u001b[1m)\u001b[0m,                                                   \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33msource_time\u001b[0m=\u001b[1;35mGaussianPulse\u001b[0m\u001b[1m(\u001b[0m                                              \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                           \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mamplitude\u001b[0m=\u001b[1;36m1\u001b[0m\u001b[1;36m.0\u001b[0m,                                                      \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mphase\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.0\u001b[0m,                                                          \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mtype\u001b[0m=\u001b[32m'GaussianPulse'\u001b[0m,                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mfreq0\u001b[0m=\u001b[1;36m150000000000000\u001b[0m\u001b[1;36m.0\u001b[0m,                                            \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mfwidth\u001b[0m=\u001b[1;36m10000000000000\u001b[0m\u001b[1;36m.0\u001b[0m,                                            \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33moffset\u001b[0m=\u001b[1;36m5\u001b[0m\u001b[1;36m.0\u001b[0m,                                                         \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mremove_dc_component\u001b[0m=\u001b[3;92mTrue\u001b[0m                                            \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[1m)\u001b[0m,                                                                      \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33minterpolate\u001b[0m=\u001b[3;92mTrue\u001b[0m,                                                       \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mconfine_to_bounds\u001b[0m=\u001b[3;91mFalse\u001b[0m,                                                \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mpolarization\u001b[0m=\u001b[32m'Ez'\u001b[0m                                                       \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[1m)\u001b[0m,                                                                          \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                 \u001b[1m)\u001b[0m                                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m             \u001b[3;33mstatic_structures\u001b[0m = \u001b[1m[\u001b[0m                                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[1;35mStructure\u001b[0m\u001b[1m(\u001b[0m                                                                  \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mgeometry\u001b[0m=\u001b[1;35mBox\u001b[0m\u001b[1m(\u001b[0m                                                           \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                           \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mtype\u001b[0m=\u001b[32m'Box'\u001b[0m,                                                         \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mcenter\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m\u001b[1m)\u001b[0m,                                             \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33msize\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m1.0\u001b[0m, \u001b[1;36m1.0\u001b[0m, \u001b[1;36m1.0\u001b[0m\u001b[1m)\u001b[0m                                                \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[1m)\u001b[0m,                                                                      \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mname\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                              \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mbackground_permittivity\u001b[0m=\u001b[3;35mNone\u001b[0m,                                           \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mbackground_medium\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                 \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mpriority\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                          \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mtype\u001b[0m=\u001b[32m'Structure'\u001b[0m,                                                       \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mmedium\u001b[0m=\u001b[1;35mMedium\u001b[0m\u001b[1m(\u001b[0m                                                          \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                           \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mname\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                          \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mfrequency_range\u001b[0m=\u001b[3;35mNone\u001b[0m,                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mallow_gain\u001b[0m=\u001b[3;91mFalse\u001b[0m,                                                   \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mnonlinear_spec\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mmodulation_spec\u001b[0m=\u001b[3;35mNone\u001b[0m,                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mviz_spec\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                      \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mheat_spec\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                     \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mtype\u001b[0m=\u001b[32m'Medium'\u001b[0m,                                                      \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mpermittivity\u001b[0m=\u001b[1;36m2\u001b[0m\u001b[1;36m.0\u001b[0m,                                                   \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mconductivity\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.0\u001b[0m                                                    \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[1m)\u001b[0m                                                                       \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[1m)\u001b[0m                                                                           \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                 \u001b[1m]\u001b[0m                                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m       \u001b[3;33mstructure_priority_mode\u001b[0m = \u001b[32m'equal'\u001b[0m                                                                         \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                    \u001b[3;33mstructures\u001b[0m = \u001b[1m(\u001b[0m                                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[1;35mStructure\u001b[0m\u001b[1m(\u001b[0m                                                                  \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mgeometry\u001b[0m=\u001b[1;35mBox\u001b[0m\u001b[1m(\u001b[0m                                                           \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                           \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mtype\u001b[0m=\u001b[32m'Box'\u001b[0m,                                                         \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mcenter\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m\u001b[1m)\u001b[0m,                                             \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33msize\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m1.0\u001b[0m, \u001b[1;36m1.0\u001b[0m, \u001b[1;36m1.0\u001b[0m\u001b[1m)\u001b[0m                                                \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[1m)\u001b[0m,                                                                      \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mname\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                              \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mbackground_permittivity\u001b[0m=\u001b[3;35mNone\u001b[0m,                                           \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mbackground_medium\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                 \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mpriority\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                          \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mtype\u001b[0m=\u001b[32m'Structure'\u001b[0m,                                                       \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mmedium\u001b[0m=\u001b[1;35mMedium\u001b[0m\u001b[1m(\u001b[0m                                                          \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                           \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mname\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                          \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mfrequency_range\u001b[0m=\u001b[3;35mNone\u001b[0m,                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mallow_gain\u001b[0m=\u001b[3;91mFalse\u001b[0m,                                                   \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mnonlinear_spec\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mmodulation_spec\u001b[0m=\u001b[3;35mNone\u001b[0m,                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mviz_spec\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                      \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mheat_spec\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                     \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mtype\u001b[0m=\u001b[32m'Medium'\u001b[0m,                                                      \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mpermittivity\u001b[0m=\u001b[1;36m2\u001b[0m\u001b[1;36m.0\u001b[0m,                                                   \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mconductivity\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.0\u001b[0m                                                    \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[1m)\u001b[0m                                                                       \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[1m)\u001b[0m,                                                                          \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                 \u001b[1m)\u001b[0m                                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                      \u001b[3;33msubpixel\u001b[0m = \u001b[1;35mSubpixelSpec\u001b[0m\u001b[1m(\u001b[0m                                                                   \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                                   \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mdielectric\u001b[0m=\u001b[1;35mPolarizedAveraging\u001b[0m\u001b[1m(\u001b[0m\u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m, \u001b[33mtype\u001b[0m=\u001b[32m'PolarizedAveraging'\u001b[0m\u001b[1m)\u001b[0m,         \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mmetal\u001b[0m=\u001b[1;35mStaircasing\u001b[0m\u001b[1m(\u001b[0m\u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m, \u001b[33mtype\u001b[0m=\u001b[32m'Staircasing'\u001b[0m\u001b[1m)\u001b[0m,                            \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mpec\u001b[0m=\u001b[1;35mPECConformal\u001b[0m\u001b[1m(\u001b[0m                                                           \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mtype\u001b[0m=\u001b[32m'PECConformal'\u001b[0m,                                                    \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mtimestep_reduction\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.3\u001b[0m,                                                 \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33medge_singularity_correction\u001b[0m=\u001b[3;91mFalse\u001b[0m                                       \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[1m)\u001b[0m,                                                                          \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mpmc\u001b[0m=\u001b[1;35mStaircasing\u001b[0m\u001b[1m(\u001b[0m\u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m, \u001b[33mtype\u001b[0m=\u001b[32m'Staircasing'\u001b[0m\u001b[1m)\u001b[0m,                              \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mlossy_metal\u001b[0m=\u001b[1;35mSurfaceImpedance\u001b[0m\u001b[1m(\u001b[0m                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mtype\u001b[0m=\u001b[32m'SurfaceImpedance'\u001b[0m,                                                \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mtimestep_reduction\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.0\u001b[0m,                                                 \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33medge_singularity_correction\u001b[0m=\u001b[3;91mFalse\u001b[0m                                       \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[1m)\u001b[0m,                                                                          \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[33mtype\u001b[0m=\u001b[32m'SubpixelSpec'\u001b[0m                                                         \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                 \u001b[1m)\u001b[0m                                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                      \u001b[3;33msymmetry\u001b[0m = \u001b[1m(\u001b[0m\u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m\u001b[1m)\u001b[0m                                                                       \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                         \u001b[3;33mtmesh\u001b[0m = \u001b[1;35marray\u001b[0m\u001b[1m(\u001b[0m\u001b[1m[\u001b[0m\u001b[1;36m0.00000000e+00\u001b[0m, \u001b[1;36m3.81314974e-16\u001b[0m, \u001b[1;36m7.62629948e-16\u001b[0m, \u001b[33m...\u001b[0m,                     \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                        \u001b[1;36m9.99426547e-13\u001b[0m, \u001b[1;36m9.99807862e-13\u001b[0m, \u001b[1;36m1.00018918e-12\u001b[0m\u001b[1m]\u001b[0m, \u001b[33mshape\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m2624\u001b[0m,\u001b[1m)\u001b[0m\u001b[1m)\u001b[0m          \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                          \u001b[3;33mtype\u001b[0m = \u001b[32m'Simulation'\u001b[0m                                                                    \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                       \u001b[3;33mversion\u001b[0m = \u001b[32m'2.9.0'\u001b[0m                                                                         \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m         \u001b[3;33mvolumetric_structures\u001b[0m = \u001b[1m[\u001b[0m                                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[1;35mStructure\u001b[0m\u001b[1m(\u001b[0m                                                                  \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mgeometry\u001b[0m=\u001b[1;35mBox\u001b[0m\u001b[1m(\u001b[0m                                                           \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                           \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mtype\u001b[0m=\u001b[32m'Box'\u001b[0m,                                                         \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mcenter\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m\u001b[1m)\u001b[0m,                                             \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33msize\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m1.0\u001b[0m, \u001b[1;36m1.0\u001b[0m, \u001b[1;36m1.0\u001b[0m\u001b[1m)\u001b[0m                                                \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[1m)\u001b[0m,                                                                      \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mname\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                              \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mbackground_permittivity\u001b[0m=\u001b[3;35mNone\u001b[0m,                                           \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mbackground_medium\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                 \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mpriority\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                          \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mtype\u001b[0m=\u001b[32m'Structure'\u001b[0m,                                                       \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[33mmedium\u001b[0m=\u001b[1;35mMedium\u001b[0m\u001b[1m(\u001b[0m                                                          \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mattrs\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,                                                           \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mname\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                          \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mfrequency_range\u001b[0m=\u001b[3;35mNone\u001b[0m,                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mallow_gain\u001b[0m=\u001b[3;91mFalse\u001b[0m,                                                   \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mnonlinear_spec\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mmodulation_spec\u001b[0m=\u001b[3;35mNone\u001b[0m,                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mviz_spec\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                      \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mheat_spec\u001b[0m=\u001b[3;35mNone\u001b[0m,                                                     \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mtype\u001b[0m=\u001b[32m'Medium'\u001b[0m,                                                      \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mpermittivity\u001b[0m=\u001b[1;36m2\u001b[0m\u001b[1;36m.0\u001b[0m,                                                   \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                             \u001b[33mconductivity\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.0\u001b[0m                                                    \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                         \u001b[1m)\u001b[0m                                                                       \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                     \u001b[1m)\u001b[0m                                                                           \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                                 \u001b[1m]\u001b[0m                                                                               \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                   \u001b[3;33mwvl_mat_min\u001b[0m = \u001b[1;35mnp.float64\u001b[0m\u001b[1m(\u001b[0m\u001b[1;36m1.4132352000025548\u001b[0m\u001b[1m)\u001b[0m                                                  \u001b[34m│\u001b[0m\n",
-       "\u001b[34m│\u001b[0m                     \u001b[3;33mzero_dims\u001b[0m = \u001b[1m[\u001b[0m\u001b[1m]\u001b[0m                                                                              \u001b[34m│\u001b[0m\n",
-       "\u001b[34m╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     }
    ],
-   "source": [
-    "# print the log, which is stored as an attribute rather than as its own file\n",
-    "print(sim_data.log)\n",
-    "\n",
-    "# get a copy of the original Simulation, so it also doesn't need to be stored separately\n",
-    "sim_data.simulation.help()"
-   ]
+   "execution_count": 23
   },
   {
    "cell_type": "markdown",
@@ -3148,29 +3370,36 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
    "id": "5a1d45b1",
    "metadata": {
-    "tags": []
+    "tags": [],
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:07:40.399392Z",
+     "start_time": "2025-10-29T14:07:40.341858Z"
+    }
    },
+   "source": [
+    "flux_data = sim_data[\"flux_over_time\"].flux\n",
+    "flux_data.plot()\n",
+    "plt.title(\"flux over time\")\n",
+    "plt.show()"
+   ],
    "outputs": [
     {
      "data": {
-      "image/png": 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AFoQlAAAAC8ISAACABWEJAADAgrAEAABgQVgCAACwICwBAABYEJYAAAAsCEsAAAAWhCUAAAALwhIAAIAFYQkAAMCCsAQAAGBBWAIAALAgLAEAAFgQlgAAACwISwAAABaEJQAAAAvCEgAAgAVhCQAAwIKwBAAAYEFYAgAAsCAsAQAAWBCWAAAALAhLAAAAFoQlAAAAC8ISAACABWEJAADAgrAEAABgQVgCAACwICwBAABYEJYAAAAsCEsAAAAWhCUAAAALrwtLs2fPVt26dRUYGKjIyEht3rzZOn/JkiVq2rSpAgMD1apVK61atcr5WnZ2tiZOnKhWrVqpYsWKCg8P1+DBg3Xs2LGSbgMAAHgJrwpLixYt0vjx4zV16lRt3bpVbdq0UWxsrE6cOJHv/I0bN2rAgAEaPny4tm3bpri4OMXFxWnXrl2SpHPnzmnr1q165plntHXrVn388cfav3+/7rrrrtJsCwAAeDCHMcaUdRHuioyM1A033KA333xTkpSbm6uIiAg9/PDDmjRpUp75/fr1U2ZmplauXOkc69y5s9q2bas5c+bku49vv/1WnTp10qFDh1S7dm236kpPT1dwcLDS0tIUFBRUhM4AAEBpc/fnt9ecWbp48aKSkpIUExPjHPPx8VFMTIwSExPzXZOYmOgyX5JiY2MLnC9JaWlpcjgcCgkJKZa6AQCAd/Mr6wLcderUKeXk5Cg0NNRlPDQ0VPv27ct3TUpKSr7zU1JS8p1/4cIFTZw4UQMGDLAmzKysLGVlZTmfp6enu9sGAADwMl5zZqmkZWdn67777pMxRm+//bZ17owZMxQcHOx8RERElFKVAACgtHlNWKpWrZp8fX2VmprqMp6amqqwsLB814SFhbk1/3JQOnTokNasWXPF644mT56stLQ05+PIkSNF6AgAAHgDrwlL/v7+6tChg9auXescy83N1dq1axUVFZXvmqioKJf5krRmzRqX+ZeD0oEDB/Tll1+qatWqV6wlICBAQUFBLg8AAHBt8pprliRp/PjxGjJkiDp27KhOnTrp9ddfV2ZmpoYNGyZJGjx4sGrVqqUZM2ZIksaNG6euXbvqlVde0e23366FCxdqy5YteueddyRdCkr33nuvtm7dqpUrVyonJ8d5PVOVKlXk7+9fNo0CAACP4VVhqV+/fjp58qSmTJmilJQUtW3bVqtXr3ZexH348GH5+PzfybIuXbpo/vz5evrpp/Xkk0+qUaNGWr58uVq2bClJOnr0qFasWCFJatu2rcu+1q1bp27dupVKXwAAwHN51X2WPBX3WQIAwPtcc/dZAgAAKAuEJQAAAAvCEgAAgAVhCQAAwIKwBAAAYEFYAgAAsCAsAQAAWBCWAAAALAhLAAAAFoQlAAAAC8ISAACABWEJAADAgrAEAABgQVgCAACwICwBAABYEJYAAAAsCEsAAAAWhCUAAAALwhIAAIAFYQkAAMCCsAQAAGBBWAIAALAgLAEAAFgQlgAAACwISwAAABaEJQAAAAvCEgAAgAVhCQAAwIKwBAAAYEFYAgAAsCAsAQAAWBCWAAAALAhLAAAAFoQlAAAAC8ISAACABWEJAADAws+dSe3bty/URh0Oh1asWKFatWoVqSgAAABP4VZY2r59uyZMmKDrrrvuinONMZo5c6aysrKuujgAAICy5lZYkqTHH39cNWrUcGvuK6+8UuSCAAAAPIlbYSk5OVnVqlVze6N79uxReHh4kYsCAADwFG6FpTp16hRqoxEREUUqBgAAwNO4/W24OnXqaNiwYXr//fd15MiRkqwJAADAY7h9zdKwYcOUkJCghQsX6uLFi6pXr566d++uHj16qHv37goLCyvJOgEAAMqEwxhjCrMgKytL33zzjdavX6+EhARt2rRJ2dnZaty4sXr06KHZs2eXVK0eKz09XcHBwUpLS1NQUFBZlwMAANzg7s/vQoel//Trr7/qlVde0V//+ledPXtWOTk5V7M5r0RYAgDA+7j789vtj+Euu3jxohITE5WQkOA8s1SrVi3de++96tq161UVDQAA4GncDkvPPvusMxzVqVNH//M//6ORI0fqww8/5DYBAADgmuX2x3A+Pj6qXbu2Jk2apL59+6pq1aolXZvX4GM4AAC8j7s/v92+dcDnn3+u/v37Kz4+XuHh4WrVqpUefvhhLV26VCdPniyWogEAADxNkS7wzsjI0Ndff63169dr3bp1+u6779SwYUN1795db775ZknU6dE4swQAgPcplW/D5eTkaPPmzVqxYoXeeustvg1HWAIAwGuUyLfhcnNztWXLFq1bt04JCQn65ptvlJmZqeuvv1733HOPunfvftWFAwAAeBK3w1KvXr20ceNGZWRkKDw8XN27d9drr72m7t27q379+iVZIwAAQJlxOyyFhITopZdeUvfu3dWoUaOSrAkAAMBjuB2WFixYUJJ1AAAAeCS3bh3wxhtv6MKFC25vdM6cOcrIyChyUQAAAJ7CrW/D+fr6KiUlRdWrV3dro0FBQdq+fft/zbVMfBsOAADvU6w3pTTGKDo6Wu3bt3frcf78+WJr5D/Nnj1bdevWVWBgoCIjI7V582br/CVLlqhp06YKDAxUq1attGrVqjy9TZkyRTVr1lT58uUVExOjAwcOlFj9AADAu7h1zdLUqVMLtdG7775bVapUKVJBNosWLdL48eM1Z84cRUZG6vXXX1dsbKz279+vGjVq5Jm/ceNGDRgwQDNmzNAdd9yh+fPnKy4uTlu3blXLli0lSX/5y1/0xhtvaN68eapXr56eeeYZxcbGas+ePQoMDCz2HgAAgHe5qptSlrbIyEjdcMMNzruE5+bmKiIiQg8//LAmTZqUZ36/fv2UmZmplStXOsc6d+6stm3bas6cOTLGKDw8XBMmTNBjjz0mSUpLS1NoaKji4+PVv39/t+oqiY/hjDE6d9H968QAALiWVfAPlMPhKNZtlshNKcvSxYsXlZSUpMmTJzvHfHx8FBMTo8TExHzXJCYmavz48S5jsbGxWr58uSQpOTlZKSkpiomJcb4eHBysyMhIJSYmFhiWsrKylJWV5Xyenp5e1LYKdO7iBTUYx00+AQCQpB9nrVPFgPJlsm+3/yHdsnbq1Cnl5OQoNDTUZTw0NFQpKSn5rklJSbHOv/zfwmxTkmbMmKHg4GDnIyIiotD9AAAA7+A1Z5Y8yeTJk13OWKWnpxd7YKrgH6gfZ60r1m0CAOCtKviX3XXEXhOWqlWrJl9fX6WmprqMp6amKiwsLN81YWFh1vmX/5uamqqaNWu6zGnbtm2BtQQEBCggIKAobbjN4XCU2elGAADwfwr9MZzt5pTHjx+/qmJs/P391aFDB61du9Y5lpubq7Vr1yoqKirfNVFRUS7zJWnNmjXO+fXq1VNYWJjLnPT0dG3atKnAbQIAgP8uhQ5L7du31/bt2/OMf/TRR2rdunVx1FSg8ePH6+9//7vmzZunvXv36qGHHlJmZqaGDRsmSRo8eLDLBeDjxo3T6tWr9corr2jfvn2aNm2atmzZojFjxki6dPbmkUce0fPPP68VK1Zo586dGjx4sMLDwxUXF1eivQAAAO9Q6I/hunXrps6dO2v69OmaOHGiMjMzNXr0aC1evFh//vOfS6JGp379+unkyZOaMmWKUlJS1LZtW61evdp5gfbhw4fl4/N/+a9Lly6aP3++nn76aT355JNq1KiRli9f7rzHkiQ98cQTyszM1MiRI3XmzBnddNNNWr16NfdYAgAAkop4n6XPPvtMI0aMUMOGDXX8+HFdd911+uCDD1xCyH8T/rkTAAC8T4neZ6lXr17q3bu33n77bfn5+enTTz/9rw1KAADg2lboa5Z+/PFHRUVFaeXKlfriiy/0xBNP6K677tITTzyh7OzskqgRAACgzBQ6LLVt21b16tXTd999p1tuuUXPP/+81q1bp48//lidOnUqiRoBAADKTKHD0ltvvaWFCxcqJCTEOdalSxdt27ZN7du3L87aAAAAypxX/UO6nooLvAEA8D4ldoH3+++/X+BrDodDgwYNKuwmAQAAPFahzyxVrlzZ5Xl2drbOnTsnf39/VahQQb/88kuxFugNOLMEAID3cffnd6GvWfr1119dHmfPntX+/ft10003acGCBVdVNAAAgKcpdFjKT6NGjTRz5kyNGzeuODYHAADgMYolLEmSn5+fjh07VlybAwAA8AiFvsB7xYoVLs+NMTp+/LjefPNN3XjjjcVWGAAAgCcodFiKi4tzee5wOFS9enX16NFDr7zySnHVBQAA4BEKHZZyc3NLog4AAACPVGzXLAEAAFyL3DqzNH78eLc3+Oqrrxa5GAAAAE/jVljatm2bWxtzOBxXVQwAAICncSsszZo1Sy1atJCvr29J1wMAAOBR3LpmqV27ds5/xqR+/fo6ffp0iRYFAADgKdwKSyEhIfrpp58kSQcPHuQbcQAA4L+GWx/D9enTR127dlXNmjXlcDjUsWPHAj+SuxyqAAAArgVuhaV33nlHvXv31g8//KCxY8fqwQcfVKVKlUq6NgAAgDLn9k0pe/bsKUlKSkrSuHHjCEsAAOC/QqHv4D137tySqAMAAMAjcQdvAAAAC8ISAACABWEJAADAgrAEAABgQVgCAACwICwBAABYEJYAAAAsCEsAAAAWhCUAAAALwhIAAIAFYQkAAMCCsAQAAGBBWAIAALAgLAEAAFgQlgAAACwISwAAABaEJQAAAAvCEgAAgAVhCQAAwIKwBAAAYEFYAgAAsCAsAQAAWBCWAAAALAhLAAAAFoQlAAAAC8ISAACABWEJAADAgrAEAABgQVgCAACwICwBAABYEJYAAAAsCEsAAAAWhCUAAAALrwlLv/zyiwYOHKigoCCFhIRo+PDhOnv2rHXNhQsXNHr0aFWtWlXXXXed+vTpo9TUVOfr3333nQYMGKCIiAiVL19ezZo106xZs0q6FQAA4EW8JiwNHDhQu3fv1po1a7Ry5Upt2LBBI0eOtK559NFH9emnn2rJkiVav369jh07pt69eztfT0pKUo0aNfTBBx9o9+7deuqppzR58mS9+eabJd0OAADwEg5jjCnrIq5k7969at68ub799lt17NhRkrR69Wrddttt+vnnnxUeHp5nTVpamqpXr6758+fr3nvvlSTt27dPzZo1U2Jiojp37pzvvkaPHq29e/fqq6++cru+9PR0BQcHKy0tTUFBQUXoEAAAlDZ3f357xZmlxMREhYSEOIOSJMXExMjHx0ebNm3Kd01SUpKys7MVExPjHGvatKlq166txMTEAveVlpamKlWqWOvJyspSenq6ywMAAFybvCIspaSkqEaNGi5jfn5+qlKlilJSUgpc4+/vr5CQEJfx0NDQAtds3LhRixYtuuLHezNmzFBwcLDzERER4X4zAADAq5RpWJo0aZIcDof1sW/fvlKpZdeuXbr77rs1depU3Xrrrda5kydPVlpamvNx5MiRUqkRAACUPr+y3PmECRM0dOhQ65z69esrLCxMJ06ccBn/7bff9MsvvygsLCzfdWFhYbp48aLOnDnjcnYpNTU1z5o9e/YoOjpaI0eO1NNPP33FugMCAhQQEHDFeQAAwPuVaViqXr26qlevfsV5UVFROnPmjJKSktShQwdJ0ldffaXc3FxFRkbmu6ZDhw4qV66c1q5dqz59+kiS9u/fr8OHDysqKso5b/fu3erRo4eGDBmiP//5z8XQFQAAuJZ4xbfhJKlXr15KTU3VnDlzlJ2drWHDhqljx46aP3++JOno0aOKjo7W+++/r06dOkmSHnroIa1atUrx8fEKCgrSww8/LOnStUnSpY/eevToodjYWL300kvOffn6+roV4i7j23AAAHgfd39+l+mZpcL48MMPNWbMGEVHR8vHx0d9+vTRG2+84Xw9Oztb+/fv17lz55xjr732mnNuVlaWYmNj9dZbbzlfX7p0qU6ePKkPPvhAH3zwgXO8Tp06OnjwYKn0BQAAPJvXnFnyZJxZAgDA+1xT91kCAAAoK4QlAAAAC8ISAACABWEJAADAgrAEAABgQVgCAACwICwBAABYEJYAAAAsCEsAAAAWhCUAAAALwhIAAIAFYQkAAMCCsAQAAGBBWAIAALAgLAEAAFgQlgAAACwISwAAABaEJQAAAAvCEgAAgAVhCQAAwIKwBAAAYEFYAgAAsCAsAQAAWBCWAAAALAhLAAAAFoQlAAAAC8ISAACABWEJAADAgrAEAABgQVgCAACwICwBAABYEJYAAAAsCEsAAAAWhCUAAAALwhIAAIAFYQkAAMCCsAQAAGBBWAIAALAgLAEAAFgQlgAAACwISwAAABaEJQAAAAvCEgAAgAVhCQAAwIKwBAAAYEFYAgAAsCAsAQAAWBCWAAAALAhLAAAAFoQlAAAAC8ISAACABWEJAADAgrAEAABgQVgCAACwICwBAABYEJYAAAAsvCYs/fLLLxo4cKCCgoIUEhKi4cOH6+zZs9Y1Fy5c0OjRo1W1alVdd9116tOnj1JTU/Ode/r0aV1//fVyOBw6c+ZMCXQAAAC8kdeEpYEDB2r37t1as2aNVq5cqQ0bNmjkyJHWNY8++qg+/fRTLVmyROvXr9exY8fUu3fvfOcOHz5crVu3LonSAQCAF3MYY0xZF3Ele/fuVfPmzfXtt9+qY8eOkqTVq1frtttu088//6zw8PA8a9LS0lS9enXNnz9f9957ryRp3759atasmRITE9W5c2fn3LfffluLFi3SlClTFB0drV9//VUhISFu15eenq7g4GClpaUpKCjo6poFAAClwt2f315xZikxMVEhISHOoCRJMTEx8vHx0aZNm/Jdk5SUpOzsbMXExDjHmjZtqtq1aysxMdE5tmfPHj377LN6//335ePj3i9HVlaW0tPTXR4AAODa5BVhKSUlRTVq1HAZ8/PzU5UqVZSSklLgGn9//zxniEJDQ51rsrKyNGDAAL300kuqXbu22/XMmDFDwcHBzkdEREThGgIAAF6jTMPSpEmT5HA4rI99+/aV2P4nT56sZs2a6f777y/0urS0NOfjyJEjJVQhAAAoa35lufMJEyZo6NCh1jn169dXWFiYTpw44TL+22+/6ZdfflFYWFi+68LCwnTx4kWdOXPG5exSamqqc81XX32lnTt3aunSpZKky5dvVatWTU899ZSmT5+e77YDAgIUEBDgTosAAMDLlWlYql69uqpXr37FeVFRUTpz5oySkpLUoUMHSZeCTm5uriIjI/Nd06FDB5UrV05r165Vnz59JEn79+/X4cOHFRUVJUn66KOPdP78eeeab7/9Vg888IC+/vprNWjQ4GrbAwAA14AyDUvuatasmXr27KkHH3xQc+bMUXZ2tsaMGaP+/fs7vwl39OhRRUdH6/3331enTp0UHBys4cOHa/z48apSpYqCgoL08MMPKyoqyvlNuP8MRKdOnXLurzDfhgMAANcurwhLkvThhx9qzJgxio6Olo+Pj/r06aM33njD+Xp2drb279+vc+fOOcdee+0159ysrCzFxsbqrbfeKovyAQCAl/KK+yx5Ou6zBACA97mm7rMEAABQVghLAAAAFoQlAAAAC8ISAACABWEJAADAgrAEAABgQVgCAACwICwBAABYEJYAAAAsCEsAAAAWhCUAAAALwhIAAIAFYQkAAMCCsAQAAGBBWAIAALAgLAEAAFgQlgAAACwISwAAABaEJQAAAAvCEgAAgAVhCQAAwIKwBAAAYEFYAgAAsCAsAQAAWBCWAAAALAhLAAAAFoQlAAAAC8ISAACABWEJAADAgrAEAABgQVgCAACwICwBAABYEJYAAAAsCEsAAAAWhCUAAAALwhIAAIAFYQkAAMCCsAQAAGBBWAIAALAgLAEAAFgQlgAAACwISwAAABaEJQAAAAu/si7gWmCMkSSlp6eXcSUAAMBdl39uX/45XhDCUjHIyMiQJEVERJRxJQAAoLAyMjIUHBxc4OsOc6U4hSvKzc3VsWPHVKlSJTkcjmLZZnp6uiIiInTkyBEFBQUVyzY9DT1eG+jx2kCP3u9a708q/h6NMcrIyFB4eLh8fAq+MokzS8XAx8dH119/fYlsOygo6Jr9TX8ZPV4b6PHaQI/e71rvTyreHm1nlC7jAm8AAAALwhIAAIAFYclDBQQEaOrUqQoICCjrUkoMPV4b6PHaQI/e71rvTyq7HrnAGwAAwIIzSwAAABaEJQAAAAvCEgAAgAVhCQAAwIKwVEo2bNigO++8U+Hh4XI4HFq+fPkV1yQkJKh9+/YKCAhQw4YNFR8fn2fO7NmzVbduXQUGBioyMlKbN28u/uLdUNj+Pv74Y91yyy2qXr26goKCFBUVpS+++MJlzrRp0+RwOFweTZs2LcEu7ArbY0JCQp76HQ6HUlJSXOZ5yjGUCt/j0KFD8+2xRYsWzjmedhxnzJihG264QZUqVVKNGjUUFxen/fv3X3HdkiVL1LRpUwUGBqpVq1ZatWqVy+vGGE2ZMkU1a9ZU+fLlFRMTowMHDpRUGwUqSn9///vfdfPNN6ty5cqqXLmyYmJi8vw+zO9Y9+zZsyRbKVBReoyPj89Tf2BgoMscTzmGUtF67NatW77vx9tvv905x5OO49tvv63WrVs7bzAZFRWlzz//3LqmrN6HhKVSkpmZqTZt2mj27NluzU9OTtbtt9+u7t27a/v27XrkkUc0YsQIl0CxaNEijR8/XlOnTtXWrVvVpk0bxcbG6sSJEyXVRoEK29+GDRt0yy23aNWqVUpKSlL37t115513atu2bS7zWrRooePHjzsf//rXv0qifLcUtsfL9u/f79JDjRo1nK950jGUCt/jrFmzXHo7cuSIqlSpor59+7rM86TjuH79eo0ePVr//ve/tWbNGmVnZ+vWW29VZmZmgWs2btyoAQMGaPjw4dq2bZvi4uIUFxenXbt2Oef85S9/0RtvvKE5c+Zo06ZNqlixomJjY3XhwoXSaMupKP0lJCRowIABWrdunRITExUREaFbb71VR48edZnXs2dPl+O4YMGCkm4nX0XpUbp01+ff13/o0CGX1z3lGEpF6/Hjjz926W/Xrl3y9fXN8370lON4/fXXa+bMmUpKStKWLVvUo0cP3X333dq9e3e+88v0fWhQ6iSZZcuWWec88cQTpkWLFi5j/fr1M7Gxsc7nnTp1MqNHj3Y+z8nJMeHh4WbGjBnFWm9hudNffpo3b26mT5/ufD516lTTpk2b4iusGLnT47p164wk8+uvvxY4x1OPoTFFO47Lli0zDofDHDx40DnmycfRGGNOnDhhJJn169cXOOe+++4zt99+u8tYZGSkGTVqlDHGmNzcXBMWFmZeeukl5+tnzpwxAQEBZsGCBSVTuJvc6e8//fbbb6ZSpUpm3rx5zrEhQ4aYu+++uwQqvHru9Dh37lwTHBxc4OuefAyNKdpxfO2110ylSpXM2bNnnWOefByNMaZy5crmf//3f/N9rSzfh5xZ8lCJiYmKiYlxGYuNjVViYqIk6eLFi0pKSnKZ4+Pjo5iYGOccb5Kbm6uMjAxVqVLFZfzAgQMKDw9X/fr1NXDgQB0+fLiMKiy6tm3bqmbNmrrlllv0zTffOMevtWMoSe+++65iYmJUp04dl3FPPo5paWmSlOf33u9d6f2YnJyslJQUlznBwcGKjIws82PpTn//6dy5c8rOzs6zJiEhQTVq1FCTJk300EMP6fTp08Vaa1G52+PZs2dVp04dRURE5DmD4cnHUCracXz33XfVv39/VaxY0WXcE49jTk6OFi5cqMzMTEVFReU7pyzfh4QlD5WSkqLQ0FCXsdDQUKWnp+v8+fM6deqUcnJy8p3zn9fEeIOXX35ZZ8+e1X333ecci4yMVHx8vFavXq23335bycnJuvnmm5WRkVGGlbqvZs2amjNnjj766CN99NFHioiIULdu3bR161ZJuuaO4bFjx/T5559rxIgRLuOefBxzc3P1yCOP6MYbb1TLli0LnFfQ+/Hycbr8X087lu72958mTpyo8PBwlx86PXv21Pvvv6+1a9fqxRdf1Pr169WrVy/l5OSUROluc7fHJk2a6L333tMnn3yiDz74QLm5uerSpYt+/vlnSZ57DKWiHcfNmzdr165ded6PnnYcd+7cqeuuu04BAQH64x//qGXLlql58+b5zi3L96HfVa0GisH8+fM1ffp0ffLJJy7X8/Tq1cv5/61bt1ZkZKTq1KmjxYsXa/jw4WVRaqE0adJETZo0cT7v0qWLfvzxR7322mv6xz/+UYaVlYx58+YpJCREcXFxLuOefBxHjx6tXbt2lek1VCWpKP3NnDlTCxcuVEJCgssF0P3793f+f6tWrdS6dWs1aNBACQkJio6OLta6C8PdHqOiolzOWHTp0kXNmjXT3/72Nz333HMlXeZVKcpxfPfdd9WqVSt16tTJZdzTjmOTJk20fft2paWlaenSpRoyZIjWr19fYGAqK5xZ8lBhYWFKTU11GUtNTVVQUJDKly+vatWqydfXN985YWFhpVnqVVm4cKFGjBihxYsX5zm9+p9CQkLUuHFj/fDDD6VUXfHr1KmTs/5r5RhKl76B8t5772nQoEHy9/e3zvWU4zhmzBitXLlS69at0/XXX2+dW9D78fJxuvxfTzqWhenvspdfflkzZ87UP//5T7Vu3do6t379+qpWrVqZHsei9HhZuXLl1K5dO2f9nngMpaL1mJmZqYULF7r1l5GyPo7+/v5q2LChOnTooBkzZqhNmzaaNWtWvnPL8n1IWPJQUVFRWrt2rcvYmjVrnH8z8vf3V4cOHVzm5Obmau3atQV+3utpFixYoGHDhmnBggUuX20tyNmzZ/Xjjz+qZs2apVBdydi+fbuz/mvhGF62fv16/fDDD2794VzWx9EYozFjxmjZsmX66quvVK9evSuuudL7sV69egoLC3OZk56erk2bNpX6sSxKf9KlbxE999xzWr16tTp27HjF+T///LNOnz5dJsexqD3+Xk5Ojnbu3Oms35OOoXR1PS5ZskRZWVm6//77rzi3LI9jfnJzc5WVlZXva2X6Pryqy8PhtoyMDLNt2zazbds2I8m8+uqrZtu2bebQoUPGGGMmTZpkBg0a5Jz/008/mQoVKpjHH3/c7N2718yePdv4+vqa1atXO+csXLjQBAQEmPj4eLNnzx4zcuRIExISYlJSUjy+vw8//ND4+fmZ2bNnm+PHjzsfZ86ccc6ZMGGCSUhIMMnJyeabb74xMTExplq1aubEiROl3p8xhe/xtddeM8uXLzcHDhwwO3fuNOPGjTM+Pj7myy+/dM7xpGNoTOF7vOz+++83kZGR+W7T047jQw89ZIKDg01CQoLL771z58455wwaNMhMmjTJ+fybb74xfn5+5uWXXzZ79+41U6dONeXKlTM7d+50zpk5c6YJCQkxn3zyidmxY4e5++67Tb169cz58+c9vr+ZM2caf39/s3TpUpc1GRkZxphLvy8ee+wxk5iYaJKTk82XX35p2rdvbxo1amQuXLhQqv0Vtcfp06ebL774wvz4448mKSnJ9O/f3wQGBprdu3c753jKMTSmaD1edtNNN5l+/frlGfe04zhp0iSzfv16k5ycbHbs2GEmTZpkHA6H+ec//2mM8az3IWGplFz+Gvl/PoYMGWKMufR1zq5du+ZZ07ZtW+Pv72/q169v5s6dm2e7f/3rX03t2rWNv7+/6dSpk/n3v/9d8s3ko7D9de3a1TrfmEu3SqhZs6bx9/c3tWrVMv369TM//PBD6Tb2O4Xt8cUXXzQNGjQwgYGBpkqVKqZbt27mq6++yrNdTzmGxhTt9+mZM2dM+fLlzTvvvJPvNj3tOObXnySX91fXrl1dfi8aY8zixYtN48aNjb+/v2nRooX57LPPXF7Pzc01zzzzjAkNDTUBAQEmOjra7N+/vxQ6clWU/urUqZPvmqlTpxpjjDl37py59dZbTfXq1U25cuVMnTp1zIMPPlhmob4oPT7yyCPO91loaKi57bbbzNatW1226ynH0Jii/z7dt2+fkeQMHL/nacfxgQceMHXq1DH+/v6mevXqJjo62qVuT3ofOowx5urOTQEAAFy7uGYJAADAgrAEAABgQVgCAACwICwBAABYEJYAAAAsCEsAAAAWhCUAAAALwhIAr5KQkCCHw6EzZ86U+r4dDoccDodCQkJKZX8HDx507rNt27alsk+gqDZs2KA777xT4eHhcjgcWr58eZnvb9q0aWratKkqVqyoypUrKyYmRps2bSr0vghLADxWt27d9Mgjj7iMdenSRcePH1dwcHCZ1DR37lx9//33pbKviIgIHT9+XBMmTCiV/QFXIzMzU23atNHs2bM9Zn+NGzfWm2++qZ07d+pf//qX6tatq1tvvVUnT54s1L78rrZYAChN/v7+ZfqvwIeEhKhGjRqlsi9fX1+FhYXpuuuuK5X9AVejV69e6tWrV4GvZ2Vl6amnntKCBQt05swZtWzZUi+++KK6detWIvuTpD/84Q8uz1999VW9++672rFjh6Kjo93eF2eWAHikoUOHav369Zo1a5bzo6iDBw/m+RguPj5eISEhWrlypZo0aaIKFSro3nvv1blz5zRv3jzVrVtXlStX1tixY5WTk+PcflZWlh577DHVqlVLFStWVGRkpBISEgpd53fffafu3burUqVKCgoKUocOHbRlyxbn6//617908803q3z58oqIiNDYsWOVmZnpUsfEiRMVERGhgIAANWzYUO+++26Rf90ATzVmzBglJiZq4cKF2rFjh/r27auePXvqwIEDpbL/ixcv6p133lFwcLDatGlTqLWcWQLgkWbNmqXvv/9eLVu21LPPPitJql69ug4ePJhn7rlz5/TGG29o4cKFysjIUO/evXXPPfcoJCREq1at0k8//aQ+ffroxhtvVL9+/SRd+oN7z549WrhwocLDw7Vs2TL17NlTO3fuVKNGjdyuc+DAgWrXrp3efvtt+fr6avv27SpXrpwk6ccff1TPnj31/PPP67333tPJkyc1ZswYjRkzRnPnzpUkDR48WImJiXrjjTfUpk0bJScn69SpU1f5qwd4lsOHD2vu3Lk6fPiwwsPDJUmPPfaYVq9erblz5+qFF14osX2vXLlS/fv317lz51SzZk2tWbNG1apVK9xGrvqf4gWAEtK1a1czbtw4l7F169YZSebXX381xhgzd+5cI8n88MMPzjmjRo0yFSpUMBkZGc6x2NhYM2rUKGOMMYcOHTK+vr7m6NGjLtuOjo42kydPLrAeSWbZsmUuY5UqVTLx8fH5zh8+fLgZOXKky9jXX39tfHx8zPnz583+/fuNJLNmzZoC92mMMVOnTjVt2rSxzgE8yX++V1auXGkkmYoVK7o8/Pz8zH333WeMMWbv3r1GkvUxceJEt/b3e2fPnjUHDhwwiYmJ5oEHHjB169Y1qampheqHM0sAvF6FChXUoEED5/PQ0FDVrVvX5Vqf0NBQnThxQpK0c+dO5eTkqHHjxi7bycrKUtWqVQu17/Hjx2vEiBH6xz/+oZiYGPXt29dZy3fffacdO3boww8/dM43xig3N1fJycnauXOnfH191bVr10L3DHiTs2fPytfXV0lJSfL19XV57fL7tH79+tq7d691O4V9f0pSxYoV1bBhQzVs2FCdO3dWo0aN9O6772ry5Mlub4OwBMDrXf7Y6zKHw5HvWG5uriT3/uB217Rp0/SHP/xBn332mT7//HNNnTpVCxcu1D333KOzZ89q1KhRGjt2bJ51tWvX1g8//FCofQHeql27dsrJydGJEyd088035zvH399fTZs2LfFacnNzlZWVVag1hCUAHsvf39/louzi4s4f3IXRuHFjNW7cWI8++qgGDBiguXPn6p577lH79u21Z88eNWzYMN91rVq1Um5urtavX6+YmJirrgMoS2fPnnX5C0BycrK2b9+uKlWqqHHjxho4cKAGDx6sV155Re3atdPJkye1du1atW7dWrfffnux7q927drKzMzUn//8Z911112qWbOmTp06pdmzZ+vo0aPq27dvofbFt+EAeKy6detq06ZNOnjwoE6dOuU8M3S1fv8H98cff6zk5GRt3rxZM2bM0Geffeb2ds6fP68xY8YoISFBhw4d0jfffKNvv/1WzZo1kyRNnDhRGzdu1JgxY7R9+3YdOHBAn3zyicaMGePsb8iQIXrggQe0fPlyJScnKyEhQYsXLy6WPoHStGXLFrVr107t2rWTdOkj6nbt2mnKlCmSLt2jbPDgwZowYYKaNGmiuLg4ffvtt6pdu3aJ7M/X11f79u1Tnz591LhxY9155506ffq0vv76a7Vo0aJQ++LMEgCP9dhjj2nIkCFq3ry5zp8/r+Tk5GLb9ty5c/X8889rwoQJOnr0qKpVq6bOnTvrjjvucHsbvr6+On36tAYPHqzU1FRVq1ZNvXv31vTp0yVJrVu31vr16/XUU0/p5ptvljFGDRo0cH4jT5LefvttPfnkk/rTn/6k06dPq3bt2nryySeLrU+gtHTr1k2XrrXOX7ly5TR9+nTn+6Ok9xcYGKiPP/64WPblMLY9AQCcHA6Hli1bpri4uFLd77Rp07R8+XJt3769VPcL4BLCEgC4yeFwKDAwUFWrVtXPP/9c4vs7fPiwmjdvrosXL6p58+aEJaCM8DEcALjp8p2G//MbdCUlPDzcGZACAgJKZZ8A8uLMEgAAgAXfhgMAALAgLAEAAFgQlgAAACwISwAAABaEJQAAAAvCEgAAgAVhCQAAwIKwBAAAYEFYAgAAsPh/hLBQwd83EboAAAAASUVORK5CYII=",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
-      ]
+      ],
+      "image/png": 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"
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     }
    ],
-   "source": [
-    "flux_data = sim_data[\"flux_over_time\"].flux\n",
-    "flux_data.plot()\n",
-    "plt.title(\"flux over time\")\n",
-    "plt.show()"
-   ]
+   "execution_count": 24
   },
   {
    "cell_type": "markdown",
@@ -3182,28 +3411,36 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
    "id": "9bad3d76",
-   "metadata": {},
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:07:40.482038Z",
+     "start_time": "2025-10-29T14:07:40.403982Z"
+    }
+   },
+   "source": [
+    "Ey = sim_data[\"fields_at_150THz\"].Ey\n",
+    "\n",
+    "Ey.real.plot(x=\"x\", y=\"y\", robust=True)\n",
+    "plt.title(\"real{Ey(x, y)}\")\n",
+    "plt.show()"
+   ],
    "outputs": [
     {
      "data": {
-      "image/png": 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",
       "text/plain": [
        "<Figure size 640x480 with 2 Axes>"
-      ]
+      ],
+      "image/png": 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"
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     }
    ],
-   "source": [
-    "Ey = sim_data[\"fields_at_150THz\"].Ey\n",
-    "\n",
-    "Ey.real.plot(x=\"x\", y=\"y\", robust=True)\n",
-    "plt.title(\"real{Ey(x, y)}\")\n",
-    "plt.show()"
-   ]
+   "execution_count": 25
   },
   {
    "cell_type": "markdown",
@@ -3215,25 +3452,33 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
    "id": "72490bd2",
-   "metadata": {},
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:07:40.574325Z",
+     "start_time": "2025-10-29T14:07:40.485563Z"
+    }
+   },
+   "source": [
+    "sim_data.plot_field(\"fields_at_150THz\", \"Ey\", val=\"real\")\n",
+    "plt.show()"
+   ],
    "outputs": [
     {
      "data": {
-      "image/png": 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WrVvj5Zdfru0/m4XevXujSZMmiI+Px4svvgiFQoEvvviiwqATFhaGNWvWIDExEeHh4fD09MTjjz9eYb0vvvgiLl26hNdeew2rV6+22Na1a1d07doVQO3G8Fu2bInJkydj7ty5KC0tRXh4ONavX49du3Zh5cqVFkMdSUlJ+Ne//oXc3Fy0bt0awK2A36tXL4wePRpHjx5F06ZNsWTJEphMJsyePdviWHPnzsWAAQPQr18/PPPMMzh8+DAWLVqEZ599tty00Du5ubmhX79+2LJlC+bMmVNue1paGoYNG4YHH3wQv/76K5YtW4bGjRvjp59+Qnh4OB577LEaX5uKlJaWYseOHXjhhRdkqY9kVC9zg2xw5swZMXLkSNGsWTOhVqvFPffcIyZMmFDuwauKpm4KcWsaZkhIiHB1dRVarVY8//zzFg9e/fbbb2LMmDGiTZs2ws3NTfj6+oqHH35YbNmyRSqTnp4unnjiCREQECBUKpUICAgQQ4cOLfeY/J2s3a+kpES89957olOnTkKtVosmTZqIsLAwMXv2bGEwGCzKfvbZZ+K+++6TykVFRYnNmzdL2/V6vYiNjRVeXl5WPXi1Zs0aqT5fX98qH7y6U9mUvurs2bNH9OrVS7i7u4uAgADx2muviR9//LFce65duyb+9re/CR8fn2ofvKroQa2yZOuDV0LcWh7hnXfeEa1atRIqlUp06tRJfPnll+XKlU1Zzc3Ntci/cuWKSEhIEH5+fqJx48YiKiqq0p/RdevWidDQUKFWq0XLli3FjBkzRElJiVXtXLt2rVAoFBZTO8umZb7zzjsiOjpaqNVqERwcLL755hvx+uuvi8aNG4vZs2cLIf73b3jn1OHK/s2joqJEp06dLPJ++OEHAUCcPHnSqjZT3VEIYYe/54ioXphMJnTs2BGDBw/Gm2++CQA4ffo0goODsXz5cowaNcrubYiLi4NCoZCGjMhxNJgxfCKqnouLC+bMmYPFixfXy/LIx44dw4YNG6QvG3IsDPhEd5khQ4bgypUr9bI8cocOHXDz5k2rn5ehusWAT0TkJDiGT0TkJNjDJyJyEgz4REROokE9eFWfzGYzLly4AC8vLy4IRQ2KEAJXr15FQEBAlYv7ya2oqAglJSWy1adSqSxWcqWaY8C30oULFxxm4TKi2jh37pxVi6rJoaioCO5evsDNqpd0rgmdTofc3FwGfRsw4FvJy8sLAHDyv/+V/p+oIbh69SratW1bpz+3JSUlwM0baNRxMODianuFplLoj36NkpISBnwbMOBbqWwYx8vLi69sowapPoYiFa5uULioqi9YDaGs3XLcZIkBn4jsRqF0gUKOYC0Y8OXAWTpERE6CPXwishv28B0LAz4R2Y1CIVPANzPgy4FDOkREToI9fCKyG4WLEopavvDegmDfVA4M+ERkN0qZxvA5LVMe/NokInIS7OETkd3INkuHPXxZMOATkd0w4DsWhx7Seffdd6FQKDB58uQqy6WmpiIkJARubm7o0qULNm3aZLFdCIHk5GT4+/vD3d0d0dHROHnypB1bTkTkeBw24B84cAD/+Mc/0LVr1yrL7d27F0OHDkVCQgJycnIQFxeHuLg4HD58WCrz/vvvY+HChVi6dCkyMzPh4eGBmJgYFBUV2fs0iJyaQqmULZHtHPIqXrt2DcOGDcM///lPNGnSpMqyCxYswKOPPopXX30VHTp0wJtvvonu3btj0aJFAG717ufPn48ZM2bgiSeeQNeuXfH555/jwoULWL9+fR2cDZHzKhvSkSOR7Rwy4E+YMAGxsbGIjo6utmxGRka5cjExMcjIyAAA5ObmQq/XW5TRaDSIiIiQyhAROQOHu2m7evVqZGdn48CBA1aV1+v10Gq1FnlarRZ6vV7aXpZXWZmKFBcXo7i4WPpsNBqtag8R/c+t4Rg5bto6ZN+0wXGogH/u3Dm89NJL2Lx5c72/5CAlJQWzZ8+u1zYQNXSyraWj4JCOHBzqazMrKwv5+fno3r07GjVqhEaNGmHHjh1YuHAhGjVqBJPJVG4fnU6HvLw8i7y8vDzodDppe1leZWUqkpSUBIPBIKVz587ZenpERPXKoQJ+37598csvv+DQoUNS6tGjB4YNG4ZDhw7BpYI1OSIjI5Genm6Rt3nzZkRGRgIAgoODodPpLMoYjUZkZmZKZSqiVqvh7e1tkYiohlxcoJAhQY71eMixhnS8vLzQuXNnizwPDw/4+flJ+SNHjkSLFi2QkpICAHjppZcQFRWFefPmITY2FqtXr8bBgwexbNkyAJDm8b/11lto164dgoODMXPmTAQEBCAuLq5Oz4/I2cg1w4azdOThUAHfGmfPnoXyths4vXv3xqpVqzBjxgy8/vrraNeuHdavX2/xxfHaa6+hsLAQ48aNQ0FBAfr06YO0tLR6v09ARFSXFEIIUd+NaAiMRiM0Gg30eXkc3qEGxWg0QqfVwmAw1NnPbtnvi1/s21C62t6xMpcW4Y+N0+v0HO5GDa6HT0QNh1LpAiXX0nEYDnXTloiI7Ic9fCKyG7kevOJaOvJgwCciu+EsHcfCr00iIifBHj4R2Q17+I6FAZ+I7IYB37FwSIeIyEmwh09EdiPXapkKrpYpCwZ8IrIbafEzGeoh23FIh4juSosXL0br1q3h5uaGiIgI7N+/v8ryqampCAkJgZubG7p06YJNmzZVWnb8+PFQKBSYP3++zK22LwZ8IrKbsgevbE81C1Vr1qxBYmIiZs2ahezsbHTr1g0xMTHIz8+vsPzevXsxdOhQJCQkICcnB3FxcYiLi8Phw4fLlV23bh327duHgICAWl2T+sSAT0R2U18vMf/www8xduxYjB49Gh07dsTSpUvRuHFjfPbZZxWWX7BgAR599FG8+uqr6NChA9588010794dixYtsih3/vx5TJo0CStXroSrq2utr0t9YcAnortKSUkJsrKyEB0dLeUplUpER0cjIyOjwn0yMjIsygNATEyMRXmz2YwRI0bg1VdfRadOnezTeDvjTVsishu55+EbjUaLfLVaDbVabZF3+fJlmEwmaLVai3ytVovjx49XWL9er6+wvF6vlz6/9957aNSoEV588cVan0d9Yw+fiOxGqVTIlgAgMDAQGo1GSmVvvrO3rKwsLFiwACtWrIBCoaiTY9oDe/hE1GCcO3fO4gUod/buAaBp06ZwcXFBXl6eRX5eXh50Ol2F9ep0uirL79q1C/n5+QgKCpK2m0wmTJkyBfPnz8fp06dre0p1ij18IrIbhVIhWwIAb29vi1RRwFepVAgLC0N6erqUZzabkZ6ejsjIyArbGRkZaVEeADZv3iyVHzFiBP7zn//g0KFDUgoICMCrr76KH3/8Ua7LZXfs4ROR3SgUClmGQGpaR2JiIuLj49GjRw/07NkT8+fPR2FhIUaPHg0AGDlyJFq0aCENCb300kuIiorCvHnzEBsbi9WrV+PgwYNYtmwZAMDPzw9+fn4Wx3B1dYVOp8O9995r8/nVFQZ8IrrrDBkyBJcuXUJycjL0ej1CQ0ORlpYm3Zg9e/YslLfN7e/duzdWrVqFGTNm4PXXX0e7du2wfv16dO7cub5OwS74EnMr8SXm1FDV50vM24xbCRdVY5vrM5Vcx6llw/gScxuxh09EdqNQ/G/83dZ6yHa8aUtE5CTYwyciu7l9ho2t9ZDtGPCJyG6UCgWUMgzHCA7pyIJDOkREToI9fCKyGw7pOBYGfCKyGwZ8x8IhHSIiJ8EePhHZze0rXdpCsIcvCwZ8IrIbhfJWkqMesh0vIxGRk2APn4jspr5Wy6SKOVwP/+OPP0bXrl2l9a4jIyPxww8/VLlPamoqQkJC4Obmhi5dumDTpk0W24UQSE5Ohr+/P9zd3REdHY2TJ0/a8zSICIBSKddbr+r7TO4ODncZW7ZsiXfffRdZWVk4ePAgHnnkETzxxBM4cuRIheX37t2LoUOHIiEhATk5OYiLi0NcXBwOHz4slXn//fexcOFCLF26FJmZmfDw8EBMTAyKiorq6rSIiOpdg1ge2dfXF3PnzkVCQkK5bUOGDEFhYSE2bNgg5fXq1QuhoaFYunQphBAICAjAlClT8MorrwAADAYDtFotVqxYgWeeecaqNnB5ZGqo6nN55NCp38JF7WFzfabiQhx6byCXR7aRw/Xwb2cymbB69WoUFhZW+mqyjIwMREdHW+TFxMQgIyMDAJCbmwu9Xm9RRqPRICIiQipTkeLiYhiNRotERDVTtjyyzYlj+LJwyID/yy+/wNPTE2q1GuPHj8e6devQsWPHCsvq9XrpLTZltFot9Hq9tL0sr7IyFUlJSYFGo5FSYGCgLadERFTvHDLg33vvvTh06BAyMzPx/PPPIz4+HkePHq3TNiQlJcFgMEjp3LlzdXp8ortB2WqZciSynUNOy1SpVGjbti0AICwsDAcOHMCCBQvwj3/8o1xZnU6HvLw8i7y8vDzodDppe1mev7+/RZnQ0NBK26BWq6FWq209FSLnJtNaOuCTtrJwyB7+ncxmM4qLiyvcFhkZifT0dIu8zZs3S2P+wcHB0Ol0FmWMRiMyMzMrvS9ARHQ3crgeflJSEv76178iKCgIV69exapVq7B9+3b8+OOPAICRI0eiRYsWSElJAQC89NJLiIqKwrx58xAbG4vVq1fj4MGDWLZsGYBbN40mT56Mt956C+3atUNwcDBmzpyJgIAAxMXF1ddpEjkFrpbpWBwu4Ofn52PkyJG4ePEiNBoNunbtih9//BF/+ctfAABnz56F8ranMHr37o1Vq1ZhxowZeP3119GuXTusX78enTt3lsq89tprKCwsxLhx41BQUIA+ffogLS0Nbm5udX5+RM5ErsXT5KiDGsg8fEfAefjUUNXnPPyes75HIzfb5+HfLCrE/tkDOA/fRg7XwyeiuwfX0nEsDPhEZDdcHtmx8DISETkJ9vCJyG5409axMOATkd1wWqZj4ZAOEZGTYA+fiOyGs3QcCwM+EdkNx/AdC4d0iIicBHv4RGQ3ZS9AkaMesh0DPhHZjYtSARcZAr7gkI4sOKRDROQk2MMnIrtRytTDN7OHLwsGfCKyG7mGdBjw5cEhHSIiJ8EePhHZDXv4joUBn4jshgHfsXBIh4jISbCHT0R200gJNJJlHr4MjSEGfCKyHw7pOBZ+bxIROQn28InIbuR68MrEHr4sGPCJyG5cFEq4KG0fSHDhW8xlwatIROQk2MMnIruR66atHHUQAz4R2REDvmPhkA4RkZNgD5+I7IY9fMfCgE9EduOiUMBFhtcTylEHcUiHiMhpsIdPRHYj14NXSg7pyIIBn4jshmP4joVDOkRETsLhAn5KSgrCw8Ph5eWF5s2bIy4uDidOnKh2v9TUVISEhMDNzQ1dunTBpk2bLLYLIZCcnAx/f3+4u7sjOjoaJ0+etNdpEBFuLY0sVyLbOVzA37FjByZMmIB9+/Zh8+bNKC0tRb9+/VBYWFjpPnv37sXQoUORkJCAnJwcxMXFIS4uDocPH5bKvP/++1i4cCGWLl2KzMxMeHh4ICYmBkVFRXVxWkROqWxIR45EtlMIIUR9N6Iqly5dQvPmzbFjxw48+OCDFZYZMmQICgsLsWHDBimvV69eCA0NxdKlSyGEQEBAAKZMmYJXXnkFAGAwGKDVarFixQo888wz1bbDaDRCo9FAn5cHb29veU6OqA4YjUbotFoYDIY6+9kt+315+etMqBt72lxf8fVr+GhwRJ2ew93I4Xr4dzIYDAAAX1/fSstkZGQgOjraIi8mJgYZGRkAgNzcXOj1eosyGo0GERERUpk7FRcXw2g0WiQiqhn28B2LQwd8s9mMyZMn4/7770fnzp0rLafX66HVai3ytFot9Hq9tL0sr7Iyd0pJSYFGo5FSYGCgLadC5JRcFDIFfD54JQuHDvgTJkzA4cOHsXr16jo/dlJSEgwGg5TOnTtX520gIpKTw87DnzhxIjZs2ICdO3eiZcuWVZbV6XTIy8uzyMvLy4NOp5O2l+X5+/tblAkNDa2wTrVaDbVabcMZEBEfvHIsDtfDF0Jg4sSJWLduHbZu3Yrg4OBq94mMjER6erpF3ubNmxEZGQkACA4Ohk6nsyhjNBqRmZkplSEi+XEM37E4XA9/woQJWLVqFb777jt4eXlJY+wajQbu7u4AgJEjR6JFixZISUkBALz00kuIiorCvHnzEBsbi9WrV+PgwYNYtmwZAEChUGDy5Ml466230K5dOwQHB2PmzJkICAhAXFxcvZwnEVFdc7iA//HHHwMAHnroIYv85cuXY9SoUQCAs2fPQnnbezJ79+6NVatWYcaMGXj99dfRrl07rF+/3uJG72uvvYbCwkKMGzcOBQUF6NOnD9LS0uDm5mb3cyJyVlxawbE45JBORaks2APA9u3bsWLFCov9Bg0ahBMnTqC4uBiHDx9G//79LbYrFArMmTMHer0eRUVF2LJlC9q3b18HZ0TkvFyUcg3r1PzYixcvRuvWreHm5oaIiAjs37+/yvJVPa1fWlqKqVOnokuXLvDw8EBAQABGjhyJCxcu1Lxh9cjhAj4Rka3WrFmDxMREzJo1C9nZ2ejWrRtiYmKQn59fYfnqnta/fv06srOzMXPmTGRnZ2Pt2rU4ceIEBgwYUJenZTOHf9LWUfBJW2qo6vNJ27d/yIGbh5fN9RUVXsX0v95n9TlEREQgPDwcixYtAnDrmZ7AwEBMmjQJ06ZNK1e+uqf1K3LgwAH07NkTZ86cQVBQUC3PrG6xh09EdlMfs3RKSkqQlZVl8WS9UqlEdHR0pU/WV/e0fkUMBgMUCgV8fHysblt9c7ibtkRElblziZOKnpe5fPkyTCZThU/WHz9+vMJ6q3ta/05FRUWYOnUqhg4d2qD+4mcPn4jsRilT777swavAwECLJU/KpmbXpdLSUgwePBhCCGlWYUPBHj4R2Y3cLzE/d+6cRY+6oqfhmzZtChcXlyqfvr9TdU/rlykL9mfOnMHWrVsbVO8eYA+fiBoQb29vi1RRwFepVAgLC7N4st5sNiM9Pb3SJ+ure1of+F+wP3nyJLZs2QI/Pz+ZzqrusIdPRHajVCiglKGHX9M6EhMTER8fjx49eqBnz56YP38+CgsLMXr0aAA1f1q/tLQUTz/9NLKzs7FhwwaYTCZpfN/X1xcqlcrmc6wLDPhEZDcuAFxkeEjWpYblhwwZgkuXLiE5ORl6vR6hoaFIS0uTbszW9Gn98+fP4/vvvweAcgsubtu2rdzKAI6K8/CtxHn41FDV5zz8hem/wN3T9nn4N65dxYt9u/CNVzZiD5+I7EZ52wwbW+sh2zHgE5HdyD1Lh2zDWTpERE6CPXwispv6mqVDFWPAJyK7USrkmaXDIXx5cEiHiMhJsIdPRHbDWTqOhQGfiOyGY/iOhUM6REROgj18IrIbF5lu2spRBzHgE5EdcUjHsXBIh4jISbCHT0R2U9P30VZVD9mOAZ+I7IZDOo6FQzpERE6CPXwishvO0nEsDPhEZDcKmYZ0FBzSkQWHdIiInAR7+ERkN5yl41gY8InIbpSQZ2ljDkXIg9eRiMhJsIdPRHbDd9o6Fofr4e/cuROPP/44AgICoFAosH79+mr32b59O7p37w61Wo22bdtixYoV5cosXrwYrVu3hpubGyIiIrB//375G09EFsoevJIjke0cLuAXFhaiW7duWLx4sVXlc3NzERsbi4cffhiHDh3C5MmT8eyzz+LHH3+UyqxZswaJiYmYNWsWsrOz0a1bN8TExCA/P99ep0FE5HAUQghR342ojEKhwLp16xAXF1dpmalTp2Ljxo04fPiwlPfMM8+goKAAaWlpAICIiAiEh4dj0aJFAACz2YzAwEBMmjQJ06ZNs6otRqMRGo0G+rw8eHt71/6kiOqY0WiETquFwWCos5/dst+Xn/6TCw8vL5vrK7x6Ff26BtfpOdyNHK6HX1MZGRmIjo62yIuJiUFGRgYAoKSkBFlZWRZllEoloqOjpTJEZB9KhVzDOvV9JneHBn/TVq/XQ6vVWuRptVoYjUbcuHEDf/75J0wmU4Vljh8/Xmm9xcXFKC4ulj4bjUZ5G05EVMcafA/fXlJSUqDRaKQUGBhY300ianCU/z9Lx9bEm7byaPABX6fTIS8vzyIv7//H2d3d3dG0aVO4uLhUWEan01Vab1JSEgwGg5TOnTtnl/YT3c04S8exNPiAHxkZifT0dIu8zZs3IzIyEgCgUqkQFhZmUcZsNiM9PV0qUxG1Wg1vb2+LRETUkDncGP61a9fw3//+V/qcm5uLQ4cOwdfXF0FBQUhKSsL58+fx+eefAwDGjx+PRYsW4bXXXsOYMWOwdetWfP3119i4caNUR2JiIuLj49GjRw/07NkT8+fPR2FhIUaPHl3n50fkTFyUt5Ic9ZDtHC7gHzx4EA8//LD0OTExEQAQHx+PFStW4OLFizh79qy0PTg4GBs3bsTLL7+MBQsWoGXLlvjkk08QExMjlRkyZAguXbqE5ORk6PV6hIaGIi0trdyNXCKSF9945Vgceh6+I+E8fGqo6nMe/p7jZ+HpZfsxr1014v6QIM7Dt5HD9fCJ6O6hUNxKctRDtmPAJyK7UUIBJWQY0pGhDroLZukQEZF12MMnIrvhkI5jYcAnIru5tZaOPPWQ7TikQ0TkJNjDJyK74ZCOY2HAJyK74Swdx8IhHSIiJ8EePhHZj0xDOuzgy4M9fCIiJ8EePhHZDadlOhYGfCKyGwXkGY1hvJcHh3SIiJwEe/hEZDdcD9+xMOATkd0oINODV7ZXQahFwM/NzcWuXbtw5swZXL9+Hc2aNcN9992HyMhIuLm52aON5ECys7Pruwk10r179/puApHN3n33XYwfPx4+Pj421WN1wF+5ciUWLFiAgwcPQqvVIiAgAO7u7rhy5QpOnToFNzc3DBs2DFOnTkWrVq1sahQR3R2UkOdGoTPfbLx69SpmzJiBqKgoREZG2lSXVQH/vvvug0qlwqhRo/Dtt98iMDDQYntxcTEyMjKwevVq9OjRA0uWLMGgQYNsahgRNXwKhQIKGcZ05KijISgpKcGmTZtw/vx5mEwmFBcXY+PGjWjRogXGjh2Lv/3tb/D09ISLiwv8/f3Rv3//Go2sWBXw3333XYuXgt9JrVbjoYcewkMPPYS3334bp0+ftroBRER0y8iRI/HNN99Ap9PB1dUVrq6uaN++PbZt24Y5c+bg888/R3FxMUwmE/Ly8tClSxccPHjQ6vqtCvhVBfs7+fn5wc/Pz+ryRHT34oNXNfPTTz/hhx9+wF/+8pdy21asWGHx+dSpU2jfvj2uXLkCX19fq+qv9Syd/Px85Ofnw2w2W+R37dq1tlUS0V2GyyPXTJMmTRAaGmpV2TZt2uDee+/F9evX7Rfws7KyEB8fj2PHjkEIAeDW+JoQAgqFAiaTqaZVEhERbvXaa+Lo0aM1Kl/jgD9mzBi0b98en376KbRardPcTCGimuMsHcdS44D/22+/4dtvv0Xbtm3t0R4iuotwlk7tRUVFISEhAYMGDYK7u7ssddb4i7Nv3774+eefZTk4ERFV7L777sMrr7wCnU6HsWPHYt++fTbXWeMe/ieffIL4+HgcPnwYnTt3hqurq8X2AQMG2NwoIro7cJZO7c2fPx8ffPABvv/+e/zrX//Cgw8+iLZt22LMmDEYMWIEtFptjeusccDPyMjAnj178MMPP5Tbxpu2RHQnJ4zVsmnUqBGeeuopPPXUU8jPz8eyZcswc+ZMvP766+jfvz9efPFFPPLII1bXV+MhnUmTJmH48OG4ePEizGazRWKwJyKS3/79+zFr1izMmzcPzZs3R1JSEpo2bYrHHnsMr7zyitX11LiH/8cff+Dll1+u1Z8TRORcOKRTe/n5+fjiiy+wfPlynDx5Eo8//ji++uorxMTESDexR40ahUcffRQffPCBVXXWOOA/9dRT2LZtG9q0aVPTXYnIyXCWTu21bNkSbdq0wZgxYzBq1Cg0a9asXJmuXbsiPDzc6jprHPDbt2+PpKQk7N69G126dCl30/bFF1+saZVERHSH9PR0PPDAA1WW8fb2xrZt26yus1azdDw9PbFjxw7s2LHDYptCoWDAJyIJh3RqLj8/H82bN6802N+8eRPZ2dno2bNnjeuu8U3b3NzcStNvv/1W4wZUZPHixWjdujXc3NwQERGB/fv3V1k+NTUVISEhcHNzQ5cuXbBp0yaL7UIIJCcnw9/fH+7u7oiOjsbJkydlaSsRVU4hY6qphhpH/P39kZ+fL33u0qULzp07J33+448/ar0uvmxPLF+8eBHvv/++zfWsWbMGiYmJmDVrFrKzs9GtWzfExMRYXIDb7d27F0OHDkVCQgJycnIQFxeHuLg4HD58WCrz/vvvY+HChVi6dCkyMzPh4eGBmJgYFBUV2dxeInI8DTmOlK1RVub06dMoLS2tsoy1FKKGe44ZM6bC/DNnzmD//v24evVqrRpSJiIiAuHh4Vi0aBEAwGw2IzAwEJMmTcK0adPKlR8yZAgKCwuxYcMGKa9Xr14IDQ3F0qVLIYRAQEAApkyZIk1fMhgM0Gq1WLFiBZ555hmr2mU0GqHRaKDPy4O3t7dN59iQ8RWHDY/RaIROq4XBYKizn92y35eLenl+X4xGI/x11p+Do8YRayiVSuj1ejRv3hwA4OXlhZ9//hn33HMPACAvLw8BAQG1mgZf4x7+n3/+aZEuX76M/fv3Y/v27VZPDapMSUkJsrKyEB0d/b8GKpWIjo5GRkZGhftkZGRYlAdurd9fVj43Nxd6vd6ijEajQURERKV1EpE8ypZHliNZi3GkcjW+abtu3boK899++22sX78ezz33XK0bc/nyZZhMpnJz/LVaLY4fP17hPnq9vsLyer1e2l6WV1mZihQXF6O4uFj6bDQarT8RIrKLO38P1Wo11Gq1RZ4jxZHaUCgUuHr1Ktzc3KRl569duyaduy2xSLYx/KFDh2L79u1yVVfvUlJSoNFopHTne3yJqHoKIWRLABAYGGjxe5mSklLPZyg/IQTat2+PJk2awNfXF9euXcN9992HJk2aoEmTJrj33ntrXXet33h1p59//hn33XefTXU0bdoULi4uyMvLs8jPy8uDTqercB+dTldl+bL/5uXlwd/f36JMVW+WSUpKQmJiovTZaDQy6BPVlDDfSnLUA+DcuXMWY/h39u4Bx4ojtVGTefU1VeOAf3sQLJOXl4fvvvsOsbGxFts//PDDGtWtUqkQFhaG9PR0xMXFAbh1syU9PR0TJ06scJ/IyEikp6dj8uTJUt7mzZulaUvBwcHQ6XRIT0+X/mGMRiMyMzPx/PPPV9qWiv5UJKL65e3tXe1NW0eKI7URFRUla323q3HAz8nJqTA/PDxces8tUPtHoRMTExEfH48ePXqgZ8+emD9/PgoLCzF69GgAt97q3qJFC+lPuZdeeglRUVGYN28eYmNjsXr1ahw8eBDLli2T2jF58mS89dZbaNeuHYKDgzFz5kwEBARIPwxEZB8KYYZChh5+TetgHKlYjQO+Pf/cAG5Nj7p06RKSk5Oh1+sRGhqKtLQ06WbJ2bNnoVT+79ZD7969sWrVKsyYMQOvv/462rVrh/Xr16Nz585Smddeew2FhYUYN24cCgoK0KdPH6SlpcHNzc2u50Lk9GQe0rFWQ40jCQkJmD9/Pry8vKwq/8ILL2DOnDlo2rSpVeVrPA/fWXEe/i2ch9/w1Oc8/PzzZ2Wbh9+8RVCdnkN98PT0xN69e9G1a9dqy169ehVNmjTB77//Xum9iTtZ1cN/9NFH8cYbb6BXr17VNmDJkiXw9PTEhAkTrGoAEd3FhLiV5KjHCXTv3h39+/dH9+7d0ahRI7i6uqJDhw6YOnUqPvvsM+zZswdFRUUwm804evQodDqd1cEesDLgDxo0CAMHDoRGo8Hjjz+OHj16ICAgAG5ubvjzzz9x9OhR7N69G5s2bUJsbCzmzp1b6xMmortIPQ3pNFQrV67EsmXLcOHCBZjNZhQVFeGTTz5BWloajh8/jujoaGg0Gri4uGDw4MEYOXJkjeq3KuAnJCRg+PDhSE1NxZo1a7Bs2TIYDAYAt25mdOzYETExMThw4AA6dOhQ87MkIiIEBgbizTfftMg7e/YsWrdujQ0bNqB///421W/1TVu1Wo3hw4dj+PDhAG6tI3Hjxg34+fmVWxOfiAgoe/BKjlk6zjGkU5GgoCDExMTIMt+/1g9elT3pRkRUKQ7pyOKHH36QpR7ZllYgIiLHxoBPRPZT1sOXIzmhXbt2Yfjw4YiMjMT58+cBAF988QV2795dq/oY8InIfhjwa+3bb79FTEwM3N3dkZOTI63eazAY8M4779SqTgZ8IiIH9NZbb2Hp0qX45z//aTEx5v7776/1A5A1Dvjx8fHYuXNnrQ5GRE5GmAGzDMkJe/gnTpzAgw8+WC5fo9GgoKCgVnXWOOAbDAZER0ejXbt2eOedd6RxJSKiO5UtniZHcjY6nQ7//e9/y+Xv3r1bet1hTdU44K9fvx7nz5/H888/jzVr1qB169b461//im+++abci3aJiKh2xo4di5deegmZmZlQKBS4cOECVq5ciSlTptR6SeZajeE3a9YMiYmJ+Pnnn5GZmYm2bdtixIgRCAgIwMsvv4yTJ0/WqjFEdJfhTdtamzZtGv72t7+hb9++uHbtGh588EE8++yzeP755/Hss8/Wqk6bbtpevHgRmzdvxubNm+Hi4oL+/fvjl19+QceOHfHRRx/ZUjUR3Q3KFk+TIzkZhUKB6dOn48qVKzh8+DD27duHS5cuQaPRIDg4uFZ11jjgl5aW4ttvv8Vjjz2GVq1aITU1FZMnT8aFCxfwr3/9C1u2bMHXX3+NOXPm1KpBRETOrLi4GElJSejRowfuv/9+bNq0CR07dsSRI0dw7733YsGCBXj55ZdrVXeNl1bw9/eH2WzG0KFDsX///grXd3j44Yfh4+NTqwaRY+P68lQjXFqhxpKTk/GPf/wD0dHR2Lt3LwYNGoTRo0dj3759mDdvHgYNGgQXF5da1V3jgP/RRx9h0KBBVb7lxcfHB7m5ubVqEBHdPbh4Ws2lpqbi888/x4ABA3D48GF07doVN2/exM8//1zrV8eWqXHAHzFihE0HJCKiyv3+++8ICwsDAHTu3BlqtRovv/yyzcEesGG1TCKianFIp8ZMJhNUKpX0uVGjRvD09JSlbgZ8IrIfBvwaE0Jg1KhRUKvVAICioiKMHz8eHh4eFuXWrl1b47oZ8ImIHEh8fLzF57KXTsmBAZ+I7Ic9/Bpbvny53epmwCciu5FrHRxnXEvHHrg8MhGRk2APn4jsp2x5YznqIZsx4BOR/ci1Do4TPXhlTxzSISJyEuzhE5H9cJaOQ2HAJyK74Swdx8IhHSIiJ8EePhHZD4d0HAoDPhHZjxAyBXzO0pEDh3SIiJyEQwX8tWvXol+/fvDz84NCocChQ4es2i81NRUhISFwc3NDly5dsGnTJovtQggkJyfD398f7u7uiI6O5ovWieqCMAFmGZIw1feZ3BUcKuAXFhaiT58+eO+996zeZ+/evRg6dCgSEhKQk5ODuLg4xMXF4fDhw1KZ999/HwsXLsTSpUuRmZkJDw8PxMTEoKioyB6nQUT/T5jNsiWynUIIxxscO336NIKDg5GTk1PhO3NvN2TIEBQWFmLDhg1SXq9evRAaGoqlS5dCCIGAgABMmTIFr7zyCgDAYDBAq9VixYoVeOaZZ6xqk9FohEajgT4vD97e3rU+N6K6ZjQaodNqYTAY6uxnt+z35cqBH+Dt6VH9DtXVd60QvuF/rdNzuBs5VA+/NjIyMhAdHW2RFxMTg4yMDABAbm4u9Hq9RRmNRoOIiAipTEWKi4thNBotEhHVkBzDOWWJbNbgA75er4dWq7XI02q10Ov10vayvMrKVCQlJQUajUZKgYGBMrecyAkw4DuUegv4K1euhKenp5R27dpVX02pUFJSEgwGg5TOnTtX300iIrJJvc3DHzBgACIiIqTPLVq0qFU9Op0OeXl5Fnl5eXnQ6XTS9rI8f39/izJV3R9Qq9XSOyWJqHaEyQRhsr13LkcdVI89fC8vL7Rt21ZK7u7utaonMjIS6enpFnmbN29GZGQkACA4OBg6nc6ijNFoRGZmplSGiOykbD18ORLZzKGetL1y5QrOnj2LCxcuAABOnDgB4FYvvaynPnLkSLRo0QIpKSkAgJdeeglRUVGYN28eYmNjsXr1ahw8eBDLli0DACgUCkyePBlvvfUW2rVrh+DgYMycORMBAQGIi4ur+5MkIqonDhXwv//+e4wePVr6XDZlctasWXjjjTcAAGfPnoVS+b8/THr37o1Vq1ZhxowZeP3119GuXTusX78enTt3lsq89tprKCwsxLhx41BQUIA+ffogLS0Nbm5udXNiRM7KbJbnhit7+LJwyHn4jojz8Kmhqs95+Je3fgVvz8a213ftOpo+MpTz8G3U4KdlEhGRdRxqSIeI7jJCphuuXB5ZFgz4RGQ3wmyCkGEMX446iEM6REROgz18IrIfuZZFYA9fFgz4RGQ/cj00xWmZsuCQDhGRk2APn4jshmvpOBYGfCKyHz5p61A4pENE5CTYwyci++EsHYfCgE9EdiPXC8j5EnN5cEiHiMhJsIdPRPbDIR2HwoBPRPYjZAr4ggFfDhzSISJyEuzhE5Hd8KatY2HAJyL74YNXDoVDOkREToI9fCKyH87ScSgM+ERkN1w8zbFwSIeIyEkw4BOR/ZS9AEWOZCdXrlzBsGHD4O3tDR8fHyQkJODatWtV7lNUVIQJEybAz88Pnp6eGDhwIPLy8qTtP//8M4YOHYrAwEC4u7ujQ4cOWLBggd3OwVoM+ERkP2Vj+HIkOxk2bBiOHDmCzZs3Y8OGDdi5cyfGjRtX5T4vv/wy/v3vfyM1NRU7duzAhQsX8NRTT0nbs7Ky0Lx5c3z55Zc4cuQIpk+fjqSkJCxatMhu52ENhRBC1GsLGgij0QiNRgN9Xh68vb3ruzlEVjMajdBptTAYDHX2s1v2+3Lxs2R4N3azvb7rRfAfM0f2czh27Bg6duyIAwcOoEePHgCAtLQ09O/fH7///jsCAgLK7WMwGNCsWTOsWrUKTz/9NADg+PHj6NChAzIyMtCrV68KjzVhwgQcO3YMW7dula39NcUePhHZjTCbZEvArS+S21NxcbFN7cvIyICPj48U7AEgOjoaSqUSmZmZFe6TlZWF0tJSREdHS3khISEICgpCRkZGpccyGAzw9fW1qb22YsAnIrspe9JWjgQAgYGB0Gg0UkpJSbGpfXq9Hs2bN7fIa9SoEXx9faHX6yvdR6VSwcfHxyJfq9VWus/evXuxZs2aaoeK7I3TMomowTh37pzFkI5ara6w3LRp0/Dee+9VWdexY8dkbVtlDh8+jCeeeAKzZs1Cv3796uSYlWHAJyK7EWYBYZJjLZ1btxq9vb2tGsOfMmUKRo0aVWWZe+65BzqdDvn5+Rb5N2/exJUrV6DT6SrcT6fToaSkBAUFBRa9/Ly8vHL7HD16FH379sW4ceMwY8aMatttbwz4RGQ3wmSWJ+DXsI5mzZqhWbNm1ZaLjIxEQUEBsrKyEBYWBgDYunUrzGYzIiIiKtwnLCwMrq6uSE9Px8CBAwEAJ06cwNmzZxEZGSmVO3LkCB555BHEx8fj7bffrlH77YVj+ETktDp06IBHH30UY8eOxf79+7Fnzx5MnDgRzzzzjDRD5/z58wgJCcH+/fsBABqNBgkJCUhMTMS2bduQlZWF0aNHIzIyUpqhc/jwYTz88MPo168fEhMTodfrodfrcenSpXo7V4A9fCKyo4awPPLKlSsxceJE9O3bF0qlEgMHDsTChQul7aWlpThx4gSuX78u5X300UdS2eLiYsTExGDJkiXS9m+++QaXLl3Cl19+iS+//FLKb9WqFU6fPm23c6mOw/TwS0tLMXXqVHTp0gUeHh4ICAjAyJEjceHChWr3Xbx4MVq3bg03NzdERERI38Rlqnsqjojso2xIR45kL76+vli1ahWuXr0Kg8GAzz77DJ6entL21q1bQwiBhx56SMpzc3PD4sWLceXKFRQWFmLt2rUW4/dvvPEGhBDlUn0Ge8CBAv7169eRnZ2NmTNnIjs7G2vXrsWJEycwYMCAKvdbs2YNEhMTMWvWLGRnZ6Nbt26IiYmxuBFT3VNxRETOwKGftD1w4AB69uyJM2fOICgoqMIyERERCA8Plx5ZNpvNCAwMxKRJkzBt2rRaPxV3Jz5pSw1VfT5pe3reZHi7Vzx1skb13ShG6ynz6/Qc7kYO08OviMFggEKhKPeAQ5mSkhJkZWVZPPGmVCoRHR0tPfFW26fiiMh2wmSCWYbE5ZHl4bA3bYuKijB16lQMHTq00m/0y5cvw2QyQavVWuRrtVocP34cQO2eigOA4uJii8e2jUZjLc+EiMgx1FsPf+XKlfD09JTSrl27pG2lpaUYPHgwhBD4+OOP66V9KSkpFo9wBwYG1ks7iBoyIWRaWkHwnbZyqLce/oABAywebGjRogWA/wX7M2fOYOvWrVWO1zVt2hQuLi7lZtzc/sRbTZ6Ku11SUhISExOlz0ajkUGfqIbq68Erqli99fC9vLzQtm1bKbm7u0vB/uTJk9iyZQv8/PyqrEOlUiEsLAzp6elSntlsRnp6uvTE2+1PxZWp6Km4O6nVaukxbmsf5yYicmQOM4ZfWlqKp59+GtnZ2diwYQNMJpM0xu7r6wuVSgUA6Nu3L5588klMnDgRAJCYmIj4+Hj06NEDPXv2xPz581FYWIjRo0cDsHwqztfXF97e3pg0aZLFU3FEZB/s4TsWhwn458+fx/fffw8ACA0Ntdi2bds26aGHU6dO4fLly9K2IUOG4NKlS0hOToZer0doaCjS0tIsbuRW91QcEdmHMAuZnrR12NnjDYpDz8N3JJyHTw1Vfc7DPzl7HLzcVDbXd7WoBO1mLeM8fBs5TA+fiO4+ZpMZZhmGY+SogxjwiciOOIbvWBz6SVsiIpIPe/hEZDfs4TsWBnwispuyJ23lqIdsxyEdIiInwR4+EdkNh3QcCwM+EdkNA75j4ZAOEZGTYA+fiOzGbDbDLMNNWznqIAZ8IrIjDuk4Fg7pEBE5CfbwichubvXwbX8fLXv48mDAJyK7KXtFoRz1kO04pENE5CTYwyciuxFmmW7asocvCwZ8IrIfmWbpgGP4suCQDhGRk2APn4jshm+8ciwM+ERkN5yl41g4pENE5CTYwyciu+HSCo6FAZ+I7EaYBIRJyFIP2Y5DOkREToI9fCKyG7NZplk6vGkrCwZ8IrIbYRYQZhmGdGSogzikQ0TkNNjDJyK7MZsAs9L23rnZ9hWWCQz4RGRHwmSGUHJapqPgkA4RkZNgD5+I7EaYBIQMQzqchy8PBnwishuzScg0hs+ALwcO6RAROQmHCvhvvPEGQkJC4OHhgSZNmiA6OhqZmZnV7rd48WK0bt0abm5uiIiIwP79+y22FxUVYcKECfDz84OnpycGDhyIvLw8e50GEf2/srV05EhkO4cK+O3bt8eiRYvwyy+/YPfu3WjdujX69euHS5cuVbrPmjVrkJiYiFmzZiE7OxvdunVDTEwM8vPzpTIvv/wy/v3vfyM1NRU7duzAhQsX8NRTT9XFKRE5NbMQMJtlSIJDOnJQCOG4V9JoNEKj0WDLli3o27dvhWUiIiIQHh6ORYsWAbj1CHZgYCAmTZqEadOmwWAwoFmzZli1ahWefvppAMDx48fRoUMHZGRkoFevXjVqiz4vD97e3vKcIFEdMBqN0Gm1MBgMdfazW/b7kt73AXg2sv1W4bWbN9E3fVednsPdyKF6+LcrKSnBsmXLoNFo0K1bt0rLZGVlITo6WspTKpWIjo5GRkYGACArKwulpaUWZUJCQhAUFCSVISI7+f/VMm1N4E1bWTjcLJ0NGzbgmWeewfXr1+Hv74/NmzejadOmFZa9fPkyTCYTtFqtRb5Wq8Xx48cBAHq9HiqVCj4+PuXK6PX6SttRXFyM4uJi6bPRaKzlGRE5L7PJDLOCrzh0FPXWw1+5ciU8PT2ltGvXLgDAww8/jEOHDmHv3r149NFHMXjwYIvx+LqSkpICjUYjpcDAwDpvAxGRnOot4A8YMACHDh2SUo8ePQAAHh4eaNu2LXr16oVPP/0UjRo1wqefflphHU2bNoWLi0u5GTd5eXnQ6XQAAJ1Oh5KSEhQUFFRapiJJSUkwGAxSOnfunA1nS+Sc5BjOkeslKlSPAd/Lywtt27aVkru7e4XlzGazxdDK7VQqFcLCwpCenm5RPj09HZGRkQCAsLAwuLq6WpQ5ceIEzp49K5WpiFqthre3t0UiopphwHcsDjOGX1hYiLfffhsDBgyAv78/Ll++jMWLF+P8+fMYNGiQVK5v37548sknMXHiRABAYmIi4uPj0aNHD/Ts2RPz589HYWEhRo8eDQDQaDRISEhAYmIifH194e3tjUmTJiEyMtLqGTpERHcDhwn4Li4uOH78OP71r3/h8uXL8PPzQ3h4OHbt2oVOnTpJ5U6dOoXLly9Ln4cMGYJLly4hOTkZer0eoaGhSEtLs7iR+9FHH0GpVGLgwIEoLi5GTEwMlixZUqfnR+SMeNPWsTj0PHxHwnn41FDV5zz8TWHh8HCxvV9ZaLqJ/lkHOA/fRg47D5+IiOTlMEM6RHT3MZsEzOBqmY6CAZ+I7EaYBATkeOMVA74cOKRDROQk2MMnIru51cPnG68cBQM+EdkNx/AdC4d0iIicBHv4RGQ3wmyGUChkqYdsx4BPRHbDIR3HwiEdIiInwR4+EdmNMMs0S8fMHr4cGPCJyH5MZghh+xg+OIYvCw7pEJFTu3LlCoYNGwZvb2/4+PggISEB165dq3KfoqIiTJgwAX5+fvD09MTAgQPLvYipzB9//IGWLVtCoVCUexFTXWPAJyK7MZuEbMlehg0bhiNHjmDz5s3YsGEDdu7ciXHjxlW5z8svv4x///vfSE1NxY4dO3DhwgU89dRTFZZNSEhA165d7dH0GmPAJyK7cfQ3Xh07dgxpaWn45JNPEBERgT59+uDvf/87Vq9ejQsXLlS4j8FgwKeffooPP/wQjzzyCMLCwrB8+XLs3bsX+/btsyj78ccfo6CgAK+88opd2l9TDPhE1GAYjUaLVNnrT62VkZEBHx8f6Z3aABAdHQ2lUonMzMwK98nKykJpaSmio6OlvJCQEAQFBSEjI0PKO3r0KObMmYPPP/8cSqVjhFrHaAUR3ZXMQsiWACAwMBAajUZKKSkpNrVPr9ejefPmFnmNGjWCr68v9Hp9pfuoVCr4+PhY5Gu1Wmmf4uJiDB06FHPnzkVQUJBNbZQTZ+kQkd2YhIBJhpfqldVx7tw5izdeqdXqCstPmzYN7733XpV1Hjt2zOZ2VSYpKQkdOnTA8OHD7XaM2mDAJ6IGw9vb26pXHE6ZMgWjRo2qssw999wDnU6H/Px8i/ybN2/iypUr0Ol0Fe6n0+lQUlKCgoICi15+Xl6etM/WrVvxyy+/4JtvvgEAlL1JtmnTppg+fTpmz55d7TnYAwM+EdmNSdxKctRTE82aNUOzZs2qLRcZGYmCggJkZWUhLCwMwK1gbTabERERUeE+YWFhcHV1RXp6OgYOHAgAOHHiBM6ePYvIyEgAwLfffosbN25I+xw4cABjxozBrl270KZNm5qdjIwY8InIbuQe0pFbhw4d8Oijj2Ls2LFYunQpSktLMXHiRDzzzDMICAgAAJw/fx59+/bF559/jp49e0Kj0SAhIQGJiYnw9fWFt7c3Jk2ahMjISPTq1QsAygX1y5cvS8e7c+y/LjHgE5FTW7lyJSZOnIi+fftCqVRi4MCBWLhwobS9tLQUJ06cwPXr16W8jz76SCpbXFyMmJgYLFmypD6aXyMKIez01XmXMRqN0Gg00OflWTWGSOQojEYjdFotDAZDnf3slv2+/NO3PRorXWyu77rZhLFXfq3Tc7gbsYdPRHZjlmlIx8x+qSw4D5+IyEmwh09EdmOCTLN0bK+CwIBPRHZkEgImGdbDt9csHWfDIR0iIifBHj4R2Y1JyDMcw1fayoMBn4jshgHfsXBIh4jISbCHT0R2w5u2joUBn4jsxizTkI6Z8V4WDjukM378eCgUCsyfP7/asosXL0br1q3h5uaGiIgI7N+/32J7TV44TER0t3LIgL9u3Trs27dPWq2uKmvWrEFiYiJmzZqF7OxsdOvWDTExMRZrXNfkhcNEJJ+y1TLlSGQ7hwv458+fx6RJk7By5Uq4urpWW/7DDz/E2LFjMXr0aHTs2BFLly5F48aN8dlnnwGo2QuHiUheZevhy5HIdg4V8M1mM0aMGIFXX30VnTp1qrZ8SUkJsrKyLF4mrFQqER0dLb1M2NoXDt+puLi43AuTiYgaMocK+O+99x4aNWqEF1980aryly9fhslkglartci//WXC1rxwuCIpKSkWL0sODAys2ckQ0f/3zuUY0qnvM7k71FvAX7lyJTw9PaW0Y8cOLFiwACtWrIBCoaivZkmSkpJgMBikdO7cufpuElGDwyEdx1Jv0zIHDBhg8c7I1NRU5OfnIygoSMozmUyYMmUK5s+fj9OnT5ero2nTpnBxcSk34+b2lwlb88LhiqjVaqjV6lqeHRGR46m3Hr6Xlxfatm0rpXHjxuE///kPDh06JKWAgAC8+uqr+PHHHyusQ6VSISwsDOnp6VKe2WxGenq69DLh2184XObOFw4TkX1wlo5jcZgHr/z8/ODn52eR5+rqCp1Oh3vvvVfK69u3L5588klMnDgRAJCYmIj4+Hj06NEDPXv2xPz581FYWIjRo0cDgFUvHCYi+xAAzDLVQ7ZzmIBvrVOnTklvgAeAIUOG4NKlS0hOToZer0doaCjS0tIsbuQ21BcOExHJiS8xtxJfYk4NVX2+xPxVVWuoFbaPHBcLM+aWnOZLzG3U4Hr4RNRwcHlkx+JQ8/CJiMh+2MMnIrvh8siOhQGfiOyGQzqOhUM6REROgj18IrIbDuk4FgZ8IrIbvvHKsXBIh4jISbCHT0R2wyEdx8KAT0R2Y4I8M2zkGBYiBnyrla1AcfXq1XpuCVHNlP3M1scqKiWyLJ0mXz3OjgHfSn/88QcAoF3btvXcEqLa+eOPP6DRaOrkWCqVCjqdDiv152WrU6fTQaVSyVafM+LiaVYqKChAkyZNcPbs2Tr7pbGF0WhEYGAgzp075/CLTTWktgINr70GgwFBQUH4888/y73q056KiopQUlIiW30qlQpubm6y1eeM2MO3klJ5a0KTRqNpEL/kZby9vRtMextSW4GG196yn+G64ubmxgDtYDgtk4jISTDgExE5CQZ8K6nVasyaNavBvNi8IbW3IbUVYHup4eJNWyIiJ8EePhGRk2DAJyJyEgz4REROwmkDfmlpKaZOnYouXbrAw8MDAQEBGDlyJC5cuFDtvosXL0br1q3h5uaGiIgI7N+/32J7UVERJkyYAD8/P3h6emLgwIHIy8uzqb1r165Fv3794OfnB4VCgUOHDlm1X2pqKkJCQuDm5oYuXbpg06ZNFtuFEEhOToa/vz/c3d0RHR2NkydP2tRWoPpr5Cjt3LlzJx5//HEEBARAoVBg/fr11e6zfft2dO/eHWq1Gm3btsWKFSvKlanp+VsjJSUF4eHh8PLyQvPmzREXF4cTJ05Uu199XVtyQMJJFRQUiOjoaLFmzRpx/PhxkZGRIXr27CnCwsKq3G/16tVCpVKJzz77TBw5ckSMHTtW+Pj4iLy8PKnM+PHjRWBgoEhPTxcHDx4UvXr1Er1797apvZ9//rmYPXu2+Oc//ykAiJycnGr32bNnj3BxcRHvv/++OHr0qJgxY4ZwdXUVv/zyi1Tm3XffFRqNRqxfv178/PPPYsCAASI4OFjcuHGj1m215ho5QjuFEGLTpk1i+vTpYu3atQKAWLduXZXlf/vtN9G4cWORmJgojh49Kv7+978LFxcXkZaWVuvzt1ZMTIxYvny5OHz4sDh06JDo37+/CAoKEteuXat0n/q8tuR4nDbgV2T//v0CgDhz5kylZXr27CkmTJggfTaZTCIgIECkpKQIIW59kbi6uorU1FSpzLFjxwQAkZGRYXMbc3NzrQ74gwcPFrGxsRZ5ERER4rnnnhNCCGE2m4VOpxNz586VthcUFAi1Wi2++uqrWrexumvkKO28kzUB/7XXXhOdOnWyyBsyZIiIiYmRPtf0/GsrPz9fABA7duyotIyjXFtyDE47pFMRg8EAhUJR6XojJSUlyMrKQnR0tJSnVCoRHR2NjIwMAEBWVhZKS0styoSEhCAoKEgqU1cyMjIs2gEAMTExUjtyc3Oh1+stymg0GkRERNS6rdZcI0doZ21V19banH9tGQwGAICvr2+t2+tI15bsjwH//xUVFWHq1KkYOnRopeujXL58GSaTCVqt1iJfq9VCr9cDAPR6PVQqVbkvjdvL1BW9Xl9tW8vyKitTU9ZcI0doZ21V1laj0YgbN27U6vxrw2w2Y/Lkybj//vvRuXPnGrfXEa8t2Z/TBPyVK1fC09NTSrt27ZK2lZaWYvDgwRBC4OOPP67HVt5SVVuJAGDChAk4fPgwVq9eXd9NoQbEaVbLHDBgACIiIqTPLVq0APC/YH/mzBls3bq1ytUPmzZtChcXl3IzbvLy8qDT6QDcWrO7pKQEBQUFFr3828vUtq01pdPpqm1rWZ6/v79FmdDQ0Fod05pr5AjtrK3K2urt7Q13d3e4uLjU+PxrauLEidiwYQN27tyJli1b1qq9jnhtyf6cpofv5eWFtm3bSsnd3V0K9idPnsSWLVvg5+dXZR0qlQphYWFIT0+X8sxmM9LT0xEZGQkACAsLg6urq0WZEydO4OzZs1KZ2rS1NiIjIy3aAQCbN2+W2hEcHAydTmdRxmg0IjMz0+q23smaa+QI7ayt6tpam/O3lhACEydOxLp167B161YEBwfb3F5HurZUB+r7rnF9KSkpEQMGDBAtW7YUhw4dEhcvXpRScXGxVO6RRx4Rf//736XPq1evFmq1WqxYsUIcPXpUjBs3Tvj4+Ai9Xi+VGT9+vAgKChJbt24VBw8eFJGRkSIyMtKm9v7xxx8iJydHbNy4UQAQq1evFjk5OeLixYtSmREjRohp06ZJn/fs2SMaNWokPvjgA3Hs2DExa9asCqfk+fj4iO+++0785z//EU888YQs0zKrukaO0k4hhLh69arIyckROTk5AoD48MMPRU5OjjRTa9q0aWLEiBFS+bJpma+++qo4duyYWLx4cYXTMqv7GamN559/Xmg0GrF9+3aLn9fr169LZRzp2pLjcdqAXza9saK0bds2qVyrVq3ErFmzLPb9+9//LoKCgoRKpRI9e/YU+/bts9h+48YN8cILL4gmTZqIxo0biyeffNIiMNfG8uXLK2zr7W2LiooS8fHxFvt9/fXXon379kKlUolOnTqJjRs3Wmw3m81i5syZQqvVCrVaLfr27StOnDhhU1uFqPoaOVI7t23bVuF1LWtffHy8iIqKKrdPaGioUKlU4p577hHLly+v0fnXVmU/r7cf35GuLTkerpZJROQknGYMn4jI2THgExE5CQZ8IiInwYBPROQkGPCJiJwEAz4RkZNgwCcichIM+EREToIBn+rEp59+in79+tn9OGlpaQgNDYXZbLb7sYgaGgZ8sruioiLMnDkTs2bNsvuxHn30Ubi6umLlypV2PxZRQ8OAT3b3zTffwNvbG/fff3+dHG/UqFFYuHBhnRyLqCFhwCerXbp0CTqdDu+8846Ut3fvXqhUqnJL8N5u9erVePzxxy3yHnroIUyePNkiLy4uDqNGjZI+t27dGm+99RZGjhwJT09PtGrVCt9//z0uXbqEJ554Ap6enujatSsOHjxoUc/jjz+OgwcP4tSpU7U/WaK7EAM+Wa1Zs2b47LPP8MYbb+DgwYO4evUqRowYgYkTJ6Jv376V7rd792706NGjVsf86KOPcP/99yMnJwexsbEYMWIERo4cieHDhyM7Oxtt2rTByJEjcfsagEFBQdBqtXxTGNEdGPCpRvr374+xY8di2LBhGD9+PDw8PJCSklJp+YKCAhgMBgQEBNT6eM899xzatWuH5ORkGI1GhIeHY9CgQWjfvj2mTp2KY8eOlXurU0BAAM6cOVOrYxLdrRjwqcY++OAD3Lx5E6mpqVi5ciXUanWlZW/cuAEAcHNzq9WxunbtKv1/2Yu2u3TpUi4vPz/fYj93d3dcv369Vsckulsx4FONnTp1ChcuXIDZbMbp06erLOvn5weFQoE///yz2npNJlO5PFdXV+n/FQpFpXl3TsO8cuUKmjVrVu0xiZwJAz7VSElJCYYPH44hQ4bgzTffxLPPPluud307lUqFjh074ujRo+W23TkM89tvv8nSxqKiIpw6dQr33XefLPUR3S0Y8KlGpk+fDoPBgIULF2Lq1Klo3749xowZU+U+MTEx2L17d7n87777DmvXrsWpU6fw9ttv4+jRozhz5gzOnz9vUxv37dsHtVrNl3AT3YEBn6y2fft2zJ8/H1988QW8vb2hVCrxxRdfYNeuXfj4448r3S8hIQGbNm2CwWCwyI+NjcX777+Pjh07YufOnViyZAn279+PL774wqZ2fvXVVxg2bBgaN25sUz1Edxu+05bqxKBBg9C9e3ckJSUBuDUPPzQ0FPPnz5f1OJcvX8a9996LgwcPIjg4WNa6iRo69vCpTsydOxeenp52P87p06exZMkSBnuiCrCHT/XCXj18IqocAz4RkZPgkA4RkZNgwCcichIM+EREToIBn4jISTDgExE5CQZ8IiInwYBPROQkGPCJiJwEAz4RkZP4P2l7z8rJL96sAAAAAElFTkSuQmCC",
       "text/plain": [
        "<Figure size 640x480 with 2 Axes>"
-      ]
+      ],
+      "image/png": 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"
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     }
    ],
-   "source": [
-    "sim_data.plot_field(\"fields_at_150THz\", \"Ey\", val=\"real\")\n",
-    "plt.show()"
-   ]
+   "execution_count": 26
   },
   {
    "cell_type": "markdown",
@@ -3429,7 +3674,7 @@
         {
          "data": {
           "text/html": "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008000; text-decoration-color: #008000\">🚶 </span> <span style=\"color: #008000; text-decoration-color: #008000; font-weight: bold\">Starting 'web_demo'...</span>\n</pre>\n",
-          "text/plain": "\u001b[32m🚶 \u001b[0m \u001b[1;32mStarting 'web_demo'...\u001b[0m\n"
+          "text/plain": "\u001B[32m🚶 \u001B[0m \u001B[1;32mStarting 'web_demo'...\u001B[0m\n"
          },
          "metadata": {},
          "output_type": "display_data"
@@ -3564,7 +3809,7 @@
         {
          "data": {
           "text/html": "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">solver progress (field decay = 0.00e+00) <span style=\"color: #729c1f; text-decoration-color: #729c1f\">━━━━━━━━━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">100%</span> <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\n</pre>\n",
-          "text/plain": "solver progress (field decay = 0.00e+00) \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[36m0:00:00\u001b[0m\n"
+          "text/plain": "solver progress (field decay = 0.00e+00) \u001B[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━\u001B[0m \u001B[35m100%\u001B[0m \u001B[36m0:00:00\u001B[0m\n"
          },
          "metadata": {},
          "output_type": "display_data"
@@ -3593,7 +3838,7 @@
         {
          "data": {
           "text/html": "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800000; text-decoration-color: #800000; font-weight: bold\">↑</span> <span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">simulation.hdf5.gz</span> <span style=\"color: #729c1f; text-decoration-color: #729c1f\">━━━━━━━━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">100.0%</span> • <span style=\"color: #008000; text-decoration-color: #008000\">1.2/1.2 kB</span> • <span style=\"color: #800000; text-decoration-color: #800000\">?</span> • <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\n</pre>\n",
-          "text/plain": "\u001b[1;31m↑\u001b[0m \u001b[1;34msimulation.hdf5.gz\u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100.0%\u001b[0m • \u001b[32m1.2/1.2 kB\u001b[0m • \u001b[31m?\u001b[0m • \u001b[36m0:00:00\u001b[0m\n"
+          "text/plain": "\u001B[1;31m↑\u001B[0m \u001B[1;34msimulation.hdf5.gz\u001B[0m \u001B[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━\u001B[0m \u001B[35m100.0%\u001B[0m • \u001B[32m1.2/1.2 kB\u001B[0m • \u001B[31m?\u001B[0m • \u001B[36m0:00:00\u001B[0m\n"
          },
          "metadata": {},
          "output_type": "display_data"
@@ -3728,7 +3973,7 @@
         {
          "data": {
           "text/html": "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008000; text-decoration-color: #008000\">🏃 </span> <span style=\"color: #008000; text-decoration-color: #008000; font-weight: bold\">Finishing 'web_demo'...</span>\n</pre>\n",
-          "text/plain": "\u001b[32m🏃 \u001b[0m \u001b[1;32mFinishing 'web_demo'...\u001b[0m\n"
+          "text/plain": "\u001B[32m🏃 \u001B[0m \u001B[1;32mFinishing 'web_demo'...\u001B[0m\n"
          },
          "metadata": {},
          "output_type": "display_data"
@@ -3757,7 +4002,7 @@
         {
          "data": {
           "text/html": "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008000; text-decoration-color: #008000; font-weight: bold\">↓</span> <span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">monitor_data.hdf5</span> <span style=\"color: #729c1f; text-decoration-color: #729c1f\">━━━━━━━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">100.0%</span> • <span style=\"color: #008000; text-decoration-color: #008000\">54.4/54.4 kB</span> • <span style=\"color: #800000; text-decoration-color: #800000\">?</span> • <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\n</pre>\n",
-          "text/plain": "\u001b[1;32m↓\u001b[0m \u001b[1;34mmonitor_data.hdf5\u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100.0%\u001b[0m • \u001b[32m54.4/54.4 kB\u001b[0m • \u001b[31m?\u001b[0m • \u001b[36m0:00:00\u001b[0m\n"
+          "text/plain": "\u001B[1;32m↓\u001B[0m \u001B[1;34mmonitor_data.hdf5\u001B[0m \u001B[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━\u001B[0m \u001B[35m100.0%\u001B[0m • \u001B[32m54.4/54.4 kB\u001B[0m • \u001B[31m?\u001B[0m • \u001B[36m0:00:00\u001B[0m\n"
          },
          "metadata": {},
          "output_type": "display_data"
diff --git a/TidyFab0GC.ipynb b/TidyFab0GC.ipynb
index b7949120..f5f08ab4 100644
--- a/TidyFab0GC.ipynb
+++ b/TidyFab0GC.ipynb
@@ -729,11 +729,11 @@
     "    source = source.updated_copy(center=(fpos, source.center[1], source.center[2]))\n",
     "    sims.append(testsim.updated_copy(sources=[source]))\n",
     "\n",
-    "# Consolidate simulations into a dict for passing to td.web.run_async\n",
+    "# Consolidate simulations into a dict for passing to td.web.run\n",
     "gcsims = {f\"fiber_pos{fpos}\": sim for fpos, sim in zip(fiber_pos, sims)}\n",
     "\n",
     "# Run the batch of simulations.\n",
-    "batchdata = td.web.run_async(gcsims, path_dir=\"simdata\", verbose=False)"
+    "batchdata = td.web.run(gcsims, path=\"simdata\", verbose=False)"
    ]
   },
   {
@@ -1088,7 +1088,7 @@
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m10:35:15 CEST\u001b[0m\u001b[2;36m \u001b[0m\u001b[31mWARNING: No connection: Retrying for \u001b[0m\u001b[1;36m180\u001b[0m\u001b[31m seconds.                 \u001b[0m\n"
+       "\u001B[2;36m10:35:15 CEST\u001B[0m\u001B[2;36m \u001B[0m\u001B[31mWARNING: No connection: Retrying for \u001B[0m\u001B[1;36m180\u001B[0m\u001B[31m seconds.                 \u001B[0m\n"
       ]
      },
      "metadata": {},
diff --git a/WebAPI.ipynb b/WebAPI.ipynb
index f97314ed..a78f335f 100644
--- a/WebAPI.ipynb
+++ b/WebAPI.ipynb
@@ -12,7 +12,6 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
    "id": "e3db6278",
    "metadata": {
     "execution": {
@@ -20,16 +19,44 @@
      "iopub.status.busy": "2023-08-19T02:01:54.139501Z",
      "iopub.status.idle": "2023-08-19T02:01:55.541877Z",
      "shell.execute_reply": "2023-08-19T02:01:55.541238Z"
+    },
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:10:43.465631Z",
+     "start_time": "2025-10-29T14:10:41.995324Z"
     }
    },
-   "outputs": [],
    "source": [
     "import tidy3d as td\n",
     "import tidy3d.web as web\n",
     "\n",
     "# set logging level to ERROR because we'll only running simulations to demonstrate the web API, we don't care about the results.\n",
-    "td.config.logging.level = \"ERROR\""
-   ]
+    "td.config.logging_level = \"ERROR\""
+   ],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "\u001B[2;36m15:10:42 CET\u001B[0m\u001B[2;36m \u001B[0m\u001B[31mWARNING: Using canonical configuration directory at                \u001B[0m\n",
+       "\u001B[2;36m             \u001B[0m\u001B[32m'/home/marco/.config/tidy3d'\u001B[0m\u001B[31m. Found legacy directory at            \u001B[0m\n",
+       "\u001B[2;36m             \u001B[0m\u001B[32m'~/.tidy3d'\u001B[0m\u001B[31m, which will be ignored. Remove it manually or run      \u001B[0m\n",
+       "\u001B[2;36m             \u001B[0m\u001B[32m'tidy3d config migrate --delete-legacy'\u001B[0m\u001B[31m to clean up.               \u001B[0m\n"
+      ],
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">15:10:42 CET </span><span style=\"color: #800000; text-decoration-color: #800000\">WARNING: Using canonical configuration directory at                </span>\n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'/home/marco/.config/tidy3d'</span><span style=\"color: #800000; text-decoration-color: #800000\">. Found legacy directory at            </span>\n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'~/.tidy3d'</span><span style=\"color: #800000; text-decoration-color: #800000\">, which will be ignored. Remove it manually or run      </span>\n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'tidy3d config migrate --delete-legacy'</span><span style=\"color: #800000; text-decoration-color: #800000\"> to clean up.               </span>\n",
+       "</pre>\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
+    }
+   ],
+   "execution_count": 1
   },
   {
    "cell_type": "markdown",
@@ -43,7 +70,6 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
    "id": "0f48e0d0",
    "metadata": {
     "execution": {
@@ -51,9 +77,12 @@
      "iopub.status.busy": "2023-08-19T02:01:55.544021Z",
      "iopub.status.idle": "2023-08-19T02:01:55.566834Z",
      "shell.execute_reply": "2023-08-19T02:01:55.566315Z"
+    },
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:10:43.474238Z",
+     "start_time": "2025-10-29T14:10:43.468817Z"
     }
    },
-   "outputs": [],
    "source": [
     "# whether to print output in web functions, note: if False (default) they will all run silently\n",
     "verbose = True\n",
@@ -97,7 +126,9 @@
     "    run_time=run_time,\n",
     "    boundary_spec=td.BoundarySpec.all_sides(boundary=pml),\n",
     ")"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": 2
   },
   {
    "cell_type": "markdown",
@@ -113,7 +144,6 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
    "id": "00aa7bf9",
    "metadata": {
     "execution": {
@@ -121,369 +151,380 @@
      "iopub.status.busy": "2023-08-19T02:01:55.568697Z",
      "iopub.status.idle": "2023-08-19T02:02:20.757644Z",
      "shell.execute_reply": "2023-08-19T02:02:20.756982Z"
+    },
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:15:06.327931Z",
+     "start_time": "2025-10-29T14:10:43.523307Z"
     }
    },
+   "source": [
+    "# upload the simulation to our servers\n",
+    "task_id = web.upload(sim, task_name=\"webAPI\", verbose=verbose)\n",
+    "\n",
+    "# start the simulation running\n",
+    "web.start(task_id)\n",
+    "\n",
+    "# monitor the simulation, don't move on to next line until completed.\n",
+    "web.monitor(task_id, verbose=verbose)\n",
+    "\n",
+    "# download the results and load into a simulation data object for plotting, post processing etc.\n",
+    "sim_data = web.load(task_id, path=\"data/sim.hdf5\", verbose=verbose)"
+   ],
    "outputs": [
     {
      "data": {
+      "text/plain": [
+       "\u001B[2;36m15:10:45 CET\u001B[0m\u001B[2;36m \u001B[0mCreated task \u001B[32m'webAPI'\u001B[0m with resource_id                             \n",
+       "\u001B[2;36m             \u001B[0m\u001B[32m'fdve-8a9d34dd-4033-4cd9-9315-184865d379f2'\u001B[0m and task_type \u001B[32m'FDTD'\u001B[0m.  \n"
+      ],
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">11:15:25 Eastern Daylight Time </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'webAPI'</span> with task_id               \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-482d8ff4-1de8-4508-8e06-6431135b2c7f'</span> and  \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.                                \n",
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">15:10:45 CET </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'webAPI'</span> with resource_id                             \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-8a9d34dd-4033-4cd9-9315-184865d379f2'</span> and task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.  \n",
        "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m11:15:25 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'webAPI'\u001b[0m with task_id               \n",
-       "\u001b[2;36m                               \u001b[0m\u001b[32m'fdve-482d8ff4-1de8-4508-8e06-6431135b2c7f'\u001b[0m and  \n",
-       "\u001b[2;36m                               \u001b[0mtask_type \u001b[32m'FDTD'\u001b[0m.                                \n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
+      "text/plain": [
+       "\u001B[2;36m            \u001B[0m\u001B[2;36m \u001B[0mView task using web UI at                                          \n",
+       "\u001B[2;36m             \u001B[0m\u001B]8;id=811009;https://tidy3d.simulation.cloud/workbench?taskId=fdve-8a9d34dd-4033-4cd9-9315-184865d379f2\u001B\\\u001B[32m'https://tidy3d.simulation.cloud/workbench?\u001B[0m\u001B]8;;\u001B\\\u001B]8;id=292393;https://tidy3d.simulation.cloud/workbench?taskId=fdve-8a9d34dd-4033-4cd9-9315-184865d379f2\u001B\\\u001B[32mtaskId\u001B[0m\u001B]8;;\u001B\\\u001B]8;id=811009;https://tidy3d.simulation.cloud/workbench?taskId=fdve-8a9d34dd-4033-4cd9-9315-184865d379f2\u001B\\\u001B[32m=\u001B[0m\u001B]8;;\u001B\\\u001B]8;id=246506;https://tidy3d.simulation.cloud/workbench?taskId=fdve-8a9d34dd-4033-4cd9-9315-184865d379f2\u001B\\\u001B[32mfdve\u001B[0m\u001B]8;;\u001B\\\u001B]8;id=811009;https://tidy3d.simulation.cloud/workbench?taskId=fdve-8a9d34dd-4033-4cd9-9315-184865d379f2\u001B\\\u001B[32m-8a9d34dd-403\u001B[0m\u001B]8;;\u001B\\\n",
+       "\u001B[2;36m             \u001B[0m\u001B]8;id=811009;https://tidy3d.simulation.cloud/workbench?taskId=fdve-8a9d34dd-4033-4cd9-9315-184865d379f2\u001B\\\u001B[32m3-4cd9-9315-184865d379f2'\u001B[0m\u001B]8;;\u001B\\.                                         \n"
+      ],
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>View task using web UI at                        \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-482d8ff4-1de8-4508-8e06-6431135b2c7f\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId</span></a>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-482d8ff4-1de8-4508-8e06-6431135b2c7f\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">=fdve-482d8ff4-1de8-4508-8e06-6431135b2c7f'</span></a>.     \n",
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>View task using web UI at                                          \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-8a9d34dd-4033-4cd9-9315-184865d379f2\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-8a9d34dd-403</span></a>\n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-8a9d34dd-4033-4cd9-9315-184865d379f2\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">3-4cd9-9315-184865d379f2'</span></a>.                                         \n",
        "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m                              \u001b[0m\u001b[2;36m \u001b[0mView task using web UI at                        \n",
-       "\u001b[2;36m                               \u001b[0m\u001b]8;id=22457;https://tidy3d.simulation.cloud/workbench?taskId=fdve-482d8ff4-1de8-4508-8e06-6431135b2c7f\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=426983;https://tidy3d.simulation.cloud/workbench?taskId=fdve-482d8ff4-1de8-4508-8e06-6431135b2c7f\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\n",
-       "\u001b[2;36m                               \u001b[0m\u001b]8;id=22457;https://tidy3d.simulation.cloud/workbench?taskId=fdve-482d8ff4-1de8-4508-8e06-6431135b2c7f\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=228768;https://tidy3d.simulation.cloud/workbench?taskId=fdve-482d8ff4-1de8-4508-8e06-6431135b2c7f\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=22457;https://tidy3d.simulation.cloud/workbench?taskId=fdve-482d8ff4-1de8-4508-8e06-6431135b2c7f\u001b\\\u001b[32m-482d8ff4-1de8-4508-8e06-6431135b2c7f'\u001b[0m\u001b]8;;\u001b\\.     \n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "fc4cefa6465642ad828f3a73ab5e0122",
-       "version_major": 2,
-       "version_minor": 0
-      },
       "text/plain": [
-       "Output()"
+       "\u001B[2;36m            \u001B[0m\u001B[2;36m \u001B[0mTask folder: \u001B]8;id=154002;https://tidy3d.simulation.cloud/folders/folder-df61810d-cad6-4474-8ea9-e4f00d5dfcb0\u001B\\\u001B[32m'default'\u001B[0m\u001B]8;;\u001B\\.                                            \n"
+      ],
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>Task folder: <a href=\"https://tidy3d.simulation.cloud/folders/folder-df61810d-cad6-4474-8ea9-e4f00d5dfcb0\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'default'</span></a>.                                            \n",
+       "</pre>\n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
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-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
+      "text/plain": [
+       "Output()"
       ],
-      "text/plain": []
+      "application/vnd.jupyter.widget-view+json": {
+       "version_major": 2,
+       "version_minor": 0,
+       "model_id": "2460efac0b7e4fa7b883c8e2e441dcb1"
+      }
      },
      "metadata": {},
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+     "output_type": "display_data",
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+     }
     },
     {
      "data": {
+      "text/plain": [],
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\n"
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
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     {
      "data": {
+      "text/plain": [
+       "\u001B[2;36m15:10:48 CET\u001B[0m\u001B[2;36m \u001B[0mEstimated FlexCredit cost: \u001B[1;36m0.025\u001B[0m. Minimum cost depends on task     \n",
+       "\u001B[2;36m             \u001B[0mexecution details. Use \u001B[32m'web.real_cost\u001B[0m\u001B[32m(\u001B[0m\u001B[32mtask_id\u001B[0m\u001B[32m)\u001B[0m\u001B[32m'\u001B[0m to get the billed  \n",
+       "\u001B[2;36m             \u001B[0mFlexCredit cost after a simulation run.                            \n"
+      ],
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">11:15:27 Eastern Daylight Time </span>status = queued                                  \n",
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">15:10:48 CET </span>Estimated FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.025</span>. Minimum cost depends on task     \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>execution details. Use <span style=\"color: #008000; text-decoration-color: #008000\">'web.real_cost(task_id)'</span> to get the billed  \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>FlexCredit cost after a simulation run.                            \n",
        "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m11:15:27 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mstatus = queued                                  \n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
+      "text/plain": [
+       "\u001B[2;36m15:10:50 CET\u001B[0m\u001B[2;36m \u001B[0mstatus = queued                                                    \n"
+      ],
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>To cancel the simulation, use                    \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span><span style=\"color: #008000; text-decoration-color: #008000\">'web.abort(task_id)'</span> or <span style=\"color: #008000; text-decoration-color: #008000\">'web.delete(task_id)'</span> or \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>abort/delete the task in the web UI. Terminating \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>the Python script will not stop the job running  \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>on the cloud.                                    \n",
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">15:10:50 CET </span>status = queued                                                    \n",
        "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m                              \u001b[0m\u001b[2;36m \u001b[0mTo cancel the simulation, use                    \n",
-       "\u001b[2;36m                               \u001b[0m\u001b[32m'web.abort\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m or \u001b[32m'web.delete\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m or \n",
-       "\u001b[2;36m                               \u001b[0mabort/delete the task in the web UI. Terminating \n",
-       "\u001b[2;36m                               \u001b[0mthe Python script will not stop the job running  \n",
-       "\u001b[2;36m                               \u001b[0mon the cloud.                                    \n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "",
-       "version_major": 2,
-       "version_minor": 0
-      },
       "text/plain": [
-       "Output()"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
+       "\u001B[2;36m            \u001B[0m\u001B[2;36m \u001B[0mTo cancel the simulation, use \u001B[32m'web.abort\u001B[0m\u001B[32m(\u001B[0m\u001B[32mtask_id\u001B[0m\u001B[32m)\u001B[0m\u001B[32m'\u001B[0m or              \n",
+       "\u001B[2;36m             \u001B[0m\u001B[32m'web.delete\u001B[0m\u001B[32m(\u001B[0m\u001B[32mtask_id\u001B[0m\u001B[32m)\u001B[0m\u001B[32m'\u001B[0m or abort/delete the task in the web UI.      \n",
+       "\u001B[2;36m             \u001B[0mTerminating the Python script will not stop the job running on the \n",
+       "\u001B[2;36m             \u001B[0mcloud.                                                             \n"
+      ],
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">11:15:54 Eastern Daylight Time </span>status = preprocess                              \n",
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>To cancel the simulation, use <span style=\"color: #008000; text-decoration-color: #008000\">'web.abort(task_id)'</span> or              \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'web.delete(task_id)'</span> or abort/delete the task in the web UI.      \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>Terminating the Python script will not stop the job running on the \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>cloud.                                                             \n",
        "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m11:15:54 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mstatus = preprocess                              \n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
+      "text/plain": [
+       "Output()"
       ],
-      "text/plain": []
+      "application/vnd.jupyter.widget-view+json": {
+       "version_major": 2,
+       "version_minor": 0,
+       "model_id": "549b914a46934c3fb7f2c6b7eb0fed68"
+      }
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
+      "text/plain": [
+       "\u001B[2;36m15:14:57 CET\u001B[0m\u001B[2;36m \u001B[0mstatus = success                                                   \n"
+      ],
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">11:15:56 Eastern Daylight Time </span>Maximum FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.025</span>. Use              \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span><span style=\"color: #008000; text-decoration-color: #008000\">'web.real_cost(task_id)'</span> to get the billed       \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>FlexCredit cost after a simulation run.          \n",
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">15:14:57 CET </span>status = success                                                   \n",
        "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m11:15:56 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.025\u001b[0m. Use              \n",
-       "\u001b[2;36m                               \u001b[0m\u001b[32m'web.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed       \n",
-       "\u001b[2;36m                               \u001b[0mFlexCredit cost after a simulation run.          \n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
+      "text/plain": [],
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>starting up solver                               \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m                              \u001b[0m\u001b[2;36m \u001b[0mstarting up solver                               \n"
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
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     {
      "data": {
+      "text/plain": [
+       "\u001B[2;36m15:14:59 CET\u001B[0m\u001B[2;36m \u001B[0mstarting up solver                                                 \n"
+      ],
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">11:15:57 Eastern Daylight Time </span>running solver                                   \n",
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">15:14:59 CET </span>starting up solver                                                 \n",
        "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m11:15:57 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mrunning solver                                   \n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
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     {
      "data": {
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-      },
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-       "Output()"
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-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
+       "\u001B[2;36m            \u001B[0m\u001B[2;36m \u001B[0mrunning solver                                                     \n"
       ],
-      "text/plain": []
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>running solver                                                     \n",
        "</pre>\n"
-      ],
-      "text/plain": [
-       "\n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "",
-       "version_major": 2,
-       "version_minor": 0
-      },
       "text/plain": [
        "Output()"
-      ]
+      ],
+      "application/vnd.jupyter.widget-view+json": {
+       "version_major": 2,
+       "version_minor": 0,
+       "model_id": "18f81371302a405fa72ef378a12ac697"
+      }
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
+      "text/plain": [],
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">11:16:00 Eastern Daylight Time </span>status = postprocess                             \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m11:16:00 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mstatus = postprocess                             \n"
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
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     {
      "data": {
+      "text/plain": [
+       "\u001B[2;36m15:15:00 CET\u001B[0m\u001B[2;36m \u001B[0mstatus = success                                                   \n"
+      ],
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">11:16:05 Eastern Daylight Time </span>status = success                                 \n",
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">15:15:00 CET </span>status = success                                                   \n",
        "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m11:16:05 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mstatus = success                                 \n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
+      "text/plain": [],
       "text/html": [
        "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
-      ],
-      "text/plain": []
+      ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
+      "text/plain": [
+       "\u001B[2;36m            \u001B[0m\u001B[2;36m \u001B[0mView simulation result at                                          \n",
+       "\u001B[2;36m             \u001B[0m\u001B]8;id=673546;https://tidy3d.simulation.cloud/workbench?taskId=fdve-8a9d34dd-4033-4cd9-9315-184865d379f2\u001B\\\u001B[4;34m'https://tidy3d.simulation.cloud/workbench?\u001B[0m\u001B]8;;\u001B\\\u001B]8;id=12410;https://tidy3d.simulation.cloud/workbench?taskId=fdve-8a9d34dd-4033-4cd9-9315-184865d379f2\u001B\\\u001B[4;34mtaskId\u001B[0m\u001B]8;;\u001B\\\u001B]8;id=673546;https://tidy3d.simulation.cloud/workbench?taskId=fdve-8a9d34dd-4033-4cd9-9315-184865d379f2\u001B\\\u001B[4;34m=\u001B[0m\u001B]8;;\u001B\\\u001B]8;id=351622;https://tidy3d.simulation.cloud/workbench?taskId=fdve-8a9d34dd-4033-4cd9-9315-184865d379f2\u001B\\\u001B[4;34mfdve\u001B[0m\u001B]8;;\u001B\\\u001B]8;id=673546;https://tidy3d.simulation.cloud/workbench?taskId=fdve-8a9d34dd-4033-4cd9-9315-184865d379f2\u001B\\\u001B[4;34m-8a9d34dd-403\u001B[0m\u001B]8;;\u001B\\\n",
+       "\u001B[2;36m             \u001B[0m\u001B]8;id=673546;https://tidy3d.simulation.cloud/workbench?taskId=fdve-8a9d34dd-4033-4cd9-9315-184865d379f2\u001B\\\u001B[4;34m3-4cd9-9315-184865d379f2'\u001B[0m\u001B]8;;\u001B\\\u001B[4;34m.\u001B[0m                                         \n"
+      ],
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>View simulation result at                        \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-482d8ff4-1de8-4508-8e06-6431135b2c7f\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">'https://tidy3d.simulation.cloud/workbench?taskId</span></a>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-482d8ff4-1de8-4508-8e06-6431135b2c7f\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">=fdve-482d8ff4-1de8-4508-8e06-6431135b2c7f'</span></a><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">.</span>     \n",
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>View simulation result at                                          \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-8a9d34dd-4033-4cd9-9315-184865d379f2\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-8a9d34dd-403</span></a>\n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-8a9d34dd-4033-4cd9-9315-184865d379f2\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">3-4cd9-9315-184865d379f2'</span></a><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">.</span>                                         \n",
        "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m                              \u001b[0m\u001b[2;36m \u001b[0mView simulation result at                        \n",
-       "\u001b[2;36m                               \u001b[0m\u001b]8;id=637391;https://tidy3d.simulation.cloud/workbench?taskId=fdve-482d8ff4-1de8-4508-8e06-6431135b2c7f\u001b\\\u001b[4;34m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=779214;https://tidy3d.simulation.cloud/workbench?taskId=fdve-482d8ff4-1de8-4508-8e06-6431135b2c7f\u001b\\\u001b[4;34mtaskId\u001b[0m\u001b]8;;\u001b\\\n",
-       "\u001b[2;36m                               \u001b[0m\u001b]8;id=637391;https://tidy3d.simulation.cloud/workbench?taskId=fdve-482d8ff4-1de8-4508-8e06-6431135b2c7f\u001b\\\u001b[4;34m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=274433;https://tidy3d.simulation.cloud/workbench?taskId=fdve-482d8ff4-1de8-4508-8e06-6431135b2c7f\u001b\\\u001b[4;34mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=637391;https://tidy3d.simulation.cloud/workbench?taskId=fdve-482d8ff4-1de8-4508-8e06-6431135b2c7f\u001b\\\u001b[4;34m-482d8ff4-1de8-4508-8e06-6431135b2c7f'\u001b[0m\u001b]8;;\u001b\\\u001b[4;34m.\u001b[0m     \n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "c1226f982dcc4b26970527cf36c7d83f",
-       "version_major": 2,
-       "version_minor": 0
-      },
       "text/plain": [
        "Output()"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
       ],
-      "text/plain": []
+      "application/vnd.jupyter.widget-view+json": {
+       "version_major": 2,
+       "version_minor": 0,
+       "model_id": "8e0134a6b1e94d57bf67a5533942999a"
+      }
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
+      "text/plain": [],
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\n"
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
+      "text/plain": [
+       "\u001B[2;36m15:15:06 CET\u001B[0m\u001B[2;36m \u001B[0mLoading simulation from data/sim.hdf5                              \n"
+      ],
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">11:16:07 Eastern Daylight Time </span>loading simulation from data/sim.hdf5            \n",
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">15:15:06 CET </span>Loading simulation from data/sim.hdf5                              \n",
        "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m11:16:07 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mloading simulation from data/sim.hdf5            \n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     }
    ],
-   "source": [
-    "# upload the simulation to our servers\n",
-    "task_id = web.upload(sim, task_name=\"webAPI\", verbose=verbose)\n",
-    "\n",
-    "# start the simulation running\n",
-    "web.start(task_id)\n",
-    "\n",
-    "# monitor the simulation, don't move on to next line until completed.\n",
-    "web.monitor(task_id, verbose=verbose)\n",
-    "\n",
-    "# download the results and load into a simulation data object for plotting, post processing etc.\n",
-    "sim_data = web.load(task_id, path=\"data/sim.hdf5\", verbose=verbose)"
-   ]
+   "execution_count": 3
   },
   {
    "cell_type": "markdown",
    "id": "78cb3ca3",
    "metadata": {},
    "source": [
-    "While we broke down each of the individual steps above, one can also perform the entire process in one line by calling the [web.run()](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.web.api.webapi.run.html) function as follows.\n",
+    "While we broke down each of the individual steps above, one can also perform the entire process in one line by calling the [web.run()](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.web.api.run.run.html) function as follows.\n",
     "\n",
     "```python\n",
     "sim_data = web.run(sim, task_name='webAPI', path='data/sim.hdf5')\n",
@@ -508,7 +549,6 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
    "id": "148d4559",
    "metadata": {
     "execution": {
@@ -516,107 +556,146 @@
      "iopub.status.busy": "2023-08-19T02:02:21.209738Z",
      "iopub.status.idle": "2023-08-19T02:02:27.321806Z",
      "shell.execute_reply": "2023-08-19T02:02:27.319557Z"
+    },
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:15:11.889453Z",
+     "start_time": "2025-10-29T14:15:06.338483Z"
     }
    },
+   "source": [
+    "# initializes job, puts task on server (but doesn't run it)\n",
+    "job = web.Job(simulation=sim, task_name=\"job\", verbose=verbose)\n",
+    "\n",
+    "# estimate the maximum cost\n",
+    "estimated_cost = web.estimate_cost(job.task_id)"
+   ],
    "outputs": [
     {
      "data": {
+      "text/plain": [
+       "\u001B[2;36m            \u001B[0m\u001B[2;36m \u001B[0mCreated task \u001B[32m'job'\u001B[0m with resource_id                                \n",
+       "\u001B[2;36m             \u001B[0m\u001B[32m'fdve-d6c5317b-6b06-4d8c-8b0b-0cbf102494d6'\u001B[0m and task_type \u001B[32m'FDTD'\u001B[0m.  \n"
+      ],
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'job'</span> with task_id                  \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-7016bdf8-0b42-4abf-ba9d-08195d373f92'</span> and  \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.                                \n",
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'job'</span> with resource_id                                \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-d6c5317b-6b06-4d8c-8b0b-0cbf102494d6'</span> and task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.  \n",
        "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m                              \u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'job'\u001b[0m with task_id                  \n",
-       "\u001b[2;36m                               \u001b[0m\u001b[32m'fdve-7016bdf8-0b42-4abf-ba9d-08195d373f92'\u001b[0m and  \n",
-       "\u001b[2;36m                               \u001b[0mtask_type \u001b[32m'FDTD'\u001b[0m.                                \n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
+      "text/plain": [
+       "\u001B[2;36m            \u001B[0m\u001B[2;36m \u001B[0mView task using web UI at                                          \n",
+       "\u001B[2;36m             \u001B[0m\u001B]8;id=589602;https://tidy3d.simulation.cloud/workbench?taskId=fdve-d6c5317b-6b06-4d8c-8b0b-0cbf102494d6\u001B\\\u001B[32m'https://tidy3d.simulation.cloud/workbench?\u001B[0m\u001B]8;;\u001B\\\u001B]8;id=350894;https://tidy3d.simulation.cloud/workbench?taskId=fdve-d6c5317b-6b06-4d8c-8b0b-0cbf102494d6\u001B\\\u001B[32mtaskId\u001B[0m\u001B]8;;\u001B\\\u001B]8;id=589602;https://tidy3d.simulation.cloud/workbench?taskId=fdve-d6c5317b-6b06-4d8c-8b0b-0cbf102494d6\u001B\\\u001B[32m=\u001B[0m\u001B]8;;\u001B\\\u001B]8;id=335527;https://tidy3d.simulation.cloud/workbench?taskId=fdve-d6c5317b-6b06-4d8c-8b0b-0cbf102494d6\u001B\\\u001B[32mfdve\u001B[0m\u001B]8;;\u001B\\\u001B]8;id=589602;https://tidy3d.simulation.cloud/workbench?taskId=fdve-d6c5317b-6b06-4d8c-8b0b-0cbf102494d6\u001B\\\u001B[32m-d6c5317b-6b0\u001B[0m\u001B]8;;\u001B\\\n",
+       "\u001B[2;36m             \u001B[0m\u001B]8;id=589602;https://tidy3d.simulation.cloud/workbench?taskId=fdve-d6c5317b-6b06-4d8c-8b0b-0cbf102494d6\u001B\\\u001B[32m6-4d8c-8b0b-0cbf102494d6'\u001B[0m\u001B]8;;\u001B\\.                                         \n"
+      ],
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>View task using web UI at                        \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-7016bdf8-0b42-4abf-ba9d-08195d373f92\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId</span></a>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-7016bdf8-0b42-4abf-ba9d-08195d373f92\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">=fdve-7016bdf8-0b42-4abf-ba9d-08195d373f92'</span></a>.     \n",
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>View task using web UI at                                          \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-d6c5317b-6b06-4d8c-8b0b-0cbf102494d6\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-d6c5317b-6b0</span></a>\n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-d6c5317b-6b06-4d8c-8b0b-0cbf102494d6\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">6-4d8c-8b0b-0cbf102494d6'</span></a>.                                         \n",
        "</pre>\n"
-      ],
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
+    },
+    {
+     "data": {
       "text/plain": [
-       "\u001b[2;36m                              \u001b[0m\u001b[2;36m \u001b[0mView task using web UI at                        \n",
-       "\u001b[2;36m                               \u001b[0m\u001b]8;id=588377;https://tidy3d.simulation.cloud/workbench?taskId=fdve-7016bdf8-0b42-4abf-ba9d-08195d373f92\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=667123;https://tidy3d.simulation.cloud/workbench?taskId=fdve-7016bdf8-0b42-4abf-ba9d-08195d373f92\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\n",
-       "\u001b[2;36m                               \u001b[0m\u001b]8;id=588377;https://tidy3d.simulation.cloud/workbench?taskId=fdve-7016bdf8-0b42-4abf-ba9d-08195d373f92\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=6628;https://tidy3d.simulation.cloud/workbench?taskId=fdve-7016bdf8-0b42-4abf-ba9d-08195d373f92\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=588377;https://tidy3d.simulation.cloud/workbench?taskId=fdve-7016bdf8-0b42-4abf-ba9d-08195d373f92\u001b\\\u001b[32m-7016bdf8-0b42-4abf-ba9d-08195d373f92'\u001b[0m\u001b]8;;\u001b\\.     \n"
+       "\u001B[2;36m            \u001B[0m\u001B[2;36m \u001B[0mTask folder: \u001B]8;id=284749;https://tidy3d.simulation.cloud/folders/folder-df61810d-cad6-4474-8ea9-e4f00d5dfcb0\u001B\\\u001B[32m'default'\u001B[0m\u001B]8;;\u001B\\.                                            \n"
+      ],
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>Task folder: <a href=\"https://tidy3d.simulation.cloud/folders/folder-df61810d-cad6-4474-8ea9-e4f00d5dfcb0\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'default'</span></a>.                                            \n",
+       "</pre>\n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "cca724a1ebdc4f1a867b273330457b2d",
-       "version_major": 2,
-       "version_minor": 0
-      },
       "text/plain": [
        "Output()"
-      ]
+      ],
+      "application/vnd.jupyter.widget-view+json": {
+       "version_major": 2,
+       "version_minor": 0,
+       "model_id": "b1fd26cf6eb847edae0c79bf72b3a571"
+      }
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
+      "text/plain": [],
       "text/html": [
        "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
-      ],
-      "text/plain": []
+      ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
+      "text/plain": [
+       "\u001B[2;36m15:15:09 CET\u001B[0m\u001B[2;36m \u001B[0mEstimated FlexCredit cost: \u001B[1;36m0.025\u001B[0m. Minimum cost depends on task     \n",
+       "\u001B[2;36m             \u001B[0mexecution details. Use \u001B[32m'web.real_cost\u001B[0m\u001B[32m(\u001B[0m\u001B[32mtask_id\u001B[0m\u001B[32m)\u001B[0m\u001B[32m'\u001B[0m to get the billed  \n",
+       "\u001B[2;36m             \u001B[0mFlexCredit cost after a simulation run.                            \n"
+      ],
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">15:15:09 CET </span>Estimated FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.025</span>. Minimum cost depends on task     \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>execution details. Use <span style=\"color: #008000; text-decoration-color: #008000\">'web.real_cost(task_id)'</span> to get the billed  \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>FlexCredit cost after a simulation run.                            \n",
        "</pre>\n"
-      ],
-      "text/plain": [
-       "\n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
+      "text/plain": [
+       "\u001B[2;36m15:15:11 CET\u001B[0m\u001B[2;36m \u001B[0mEstimated FlexCredit cost: \u001B[1;36m0.025\u001B[0m. Minimum cost depends on task     \n",
+       "\u001B[2;36m             \u001B[0mexecution details. Use \u001B[32m'web.real_cost\u001B[0m\u001B[32m(\u001B[0m\u001B[32mtask_id\u001B[0m\u001B[32m)\u001B[0m\u001B[32m'\u001B[0m to get the billed  \n",
+       "\u001B[2;36m             \u001B[0mFlexCredit cost after a simulation run.                            \n"
+      ],
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">11:16:08 Eastern Daylight Time </span>Maximum FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.025</span>. Minimum cost     \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>depends on task execution details. Use           \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span><span style=\"color: #008000; text-decoration-color: #008000\">'web.real_cost(task_id)'</span> to get the billed       \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>FlexCredit cost after a simulation run.          \n",
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">15:15:11 CET </span>Estimated FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.025</span>. Minimum cost depends on task     \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>execution details. Use <span style=\"color: #008000; text-decoration-color: #008000\">'web.real_cost(task_id)'</span> to get the billed  \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>FlexCredit cost after a simulation run.                            \n",
        "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m11:16:08 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.025\u001b[0m. Minimum cost     \n",
-       "\u001b[2;36m                               \u001b[0mdepends on task execution details. Use           \n",
-       "\u001b[2;36m                               \u001b[0m\u001b[32m'web.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed       \n",
-       "\u001b[2;36m                               \u001b[0mFlexCredit cost after a simulation run.          \n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     }
    ],
-   "source": [
-    "# initializes job, puts task on server (but doesn't run it)\n",
-    "job = web.Job(simulation=sim, task_name=\"job\", verbose=verbose)\n",
-    "\n",
-    "# estimate the maximum cost\n",
-    "estimated_cost = web.estimate_cost(job.task_id)"
-   ]
+   "execution_count": 4
   },
   {
    "cell_type": "markdown",
@@ -628,7 +707,6 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
    "id": "e9628d1e",
    "metadata": {
     "execution": {
@@ -636,282 +714,81 @@
      "iopub.status.busy": "2023-08-19T02:02:27.336386Z",
      "iopub.status.idle": "2023-08-19T02:03:00.112828Z",
      "shell.execute_reply": "2023-08-19T02:03:00.112033Z"
+    },
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:15:18.452896Z",
+     "start_time": "2025-10-29T14:15:11.937187Z"
     }
    },
+   "source": [
+    "# start job, monitor, and load results\n",
+    "sim_data = job.run(path=\"data/sim.hdf5\")"
+   ],
    "outputs": [
     {
      "data": {
+      "text/plain": [
+       "\u001B[2;36m15:15:15 CET\u001B[0m\u001B[2;36m \u001B[0mstatus = success                                                   \n"
+      ],
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">11:16:09 Eastern Daylight Time </span>status = queued                                  \n",
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">15:15:15 CET </span>status = success                                                   \n",
        "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m11:16:09 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mstatus = queued                                  \n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>To cancel the simulation, use                    \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span><span style=\"color: #008000; text-decoration-color: #008000\">'web.abort(task_id)'</span> or <span style=\"color: #008000; text-decoration-color: #008000\">'web.delete(task_id)'</span> or \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>abort/delete the task in the web UI. Terminating \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>the Python script will not stop the job running  \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>on the cloud.                                    \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m                              \u001b[0m\u001b[2;36m \u001b[0mTo cancel the simulation, use                    \n",
-       "\u001b[2;36m                               \u001b[0m\u001b[32m'web.abort\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m or \u001b[32m'web.delete\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m or \n",
-       "\u001b[2;36m                               \u001b[0mabort/delete the task in the web UI. Terminating \n",
-       "\u001b[2;36m                               \u001b[0mthe Python script will not stop the job running  \n",
-       "\u001b[2;36m                               \u001b[0mon the cloud.                                    \n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "Output()"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">11:16:16 Eastern Daylight Time </span>status = preprocess                              \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m11:16:16 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mstatus = preprocess                              \n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
-      ],
-      "text/plain": []
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">11:16:17 Eastern Daylight Time </span>Maximum FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.025</span>. Use              \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span><span style=\"color: #008000; text-decoration-color: #008000\">'web.real_cost(task_id)'</span> to get the billed       \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>FlexCredit cost after a simulation run.          \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m11:16:17 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.025\u001b[0m. Use              \n",
-       "\u001b[2;36m                               \u001b[0m\u001b[32m'web.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed       \n",
-       "\u001b[2;36m                               \u001b[0mFlexCredit cost after a simulation run.          \n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>starting up solver                               \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m                              \u001b[0m\u001b[2;36m \u001b[0mstarting up solver                               \n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>running solver                                   \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m                              \u001b[0m\u001b[2;36m \u001b[0mrunning solver                                   \n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "8d3b6badd3ec497ca2072f1b1767d63a",
-       "version_major": 2,
-       "version_minor": 0
-      },
       "text/plain": [
        "Output()"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
-      ],
-      "text/plain": []
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
-       "</pre>\n"
       ],
-      "text/plain": [
-       "\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "",
        "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "Output()"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">11:16:21 Eastern Daylight Time </span>status = postprocess                             \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m11:16:21 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mstatus = postprocess                             \n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">11:16:25 Eastern Daylight Time </span>status = success                                 \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m11:16:25 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mstatus = success                                 \n"
-      ]
+       "version_minor": 0,
+       "model_id": "da9e7c2958d44aedba098ecfbe818373"
+      }
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
+      "text/plain": [],
       "text/html": [
        "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
-      ],
-      "text/plain": []
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>View simulation result at                        \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-7016bdf8-0b42-4abf-ba9d-08195d373f92\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">'https://tidy3d.simulation.cloud/workbench?taskId</span></a>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-7016bdf8-0b42-4abf-ba9d-08195d373f92\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">=fdve-7016bdf8-0b42-4abf-ba9d-08195d373f92'</span></a><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">.</span>     \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m                              \u001b[0m\u001b[2;36m \u001b[0mView simulation result at                        \n",
-       "\u001b[2;36m                               \u001b[0m\u001b]8;id=264660;https://tidy3d.simulation.cloud/workbench?taskId=fdve-7016bdf8-0b42-4abf-ba9d-08195d373f92\u001b\\\u001b[4;34m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=631587;https://tidy3d.simulation.cloud/workbench?taskId=fdve-7016bdf8-0b42-4abf-ba9d-08195d373f92\u001b\\\u001b[4;34mtaskId\u001b[0m\u001b]8;;\u001b\\\n",
-       "\u001b[2;36m                               \u001b[0m\u001b]8;id=264660;https://tidy3d.simulation.cloud/workbench?taskId=fdve-7016bdf8-0b42-4abf-ba9d-08195d373f92\u001b\\\u001b[4;34m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=607127;https://tidy3d.simulation.cloud/workbench?taskId=fdve-7016bdf8-0b42-4abf-ba9d-08195d373f92\u001b\\\u001b[4;34mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=264660;https://tidy3d.simulation.cloud/workbench?taskId=fdve-7016bdf8-0b42-4abf-ba9d-08195d373f92\u001b\\\u001b[4;34m-7016bdf8-0b42-4abf-ba9d-08195d373f92'\u001b[0m\u001b]8;;\u001b\\\u001b[4;34m.\u001b[0m     \n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "78350de90c774e36a457e1e60e19a2e8",
-       "version_major": 2,
-       "version_minor": 0
-      },
       "text/plain": [
-       "Output()"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
-      ],
-      "text/plain": []
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
-       "</pre>\n"
+       "\u001B[2;36m15:15:18 CET\u001B[0m\u001B[2;36m \u001B[0mLoading simulation from data/sim.hdf5                              \n"
       ],
-      "text/plain": [
-       "\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">11:16:27 Eastern Daylight Time </span>loading simulation from data/sim.hdf5            \n",
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">15:15:18 CET </span>Loading simulation from data/sim.hdf5                              \n",
        "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m11:16:27 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mloading simulation from data/sim.hdf5            \n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     }
    ],
-   "source": [
-    "# start job, monitor, and load results\n",
-    "sim_data = job.run(path=\"data/sim.hdf5\")"
-   ]
+   "execution_count": 5
   },
   {
    "cell_type": "markdown",
@@ -925,7 +802,6 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
    "id": "55808199",
    "metadata": {
     "execution": {
@@ -933,72 +809,73 @@
      "iopub.status.busy": "2023-08-19T02:03:00.716560Z",
      "iopub.status.idle": "2023-08-19T02:03:01.208721Z",
      "shell.execute_reply": "2023-08-19T02:03:01.207857Z"
+    },
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:15:21.618584Z",
+     "start_time": "2025-10-29T14:15:18.457607Z"
     }
    },
+   "source": [
+    "# saves the job metadata to a single file\n",
+    "job.to_file(\"data/job.json\")\n",
+    "\n",
+    "# can exit session, break here, or continue in new session.\n",
+    "\n",
+    "# load the job metadata from file\n",
+    "job_loaded = web.Job.from_file(\"data/job.json\")\n",
+    "\n",
+    "# download the data from the server and load it into a SimulationData object.\n",
+    "sim_data = job_loaded.load(path=\"data/sim.hdf5\")"
+   ],
    "outputs": [
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "28aaf2de264c42798de57cc881682f9e",
-       "version_major": 2,
-       "version_minor": 0
-      },
       "text/plain": [
        "Output()"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
       ],
-      "text/plain": []
+      "application/vnd.jupyter.widget-view+json": {
+       "version_major": 2,
+       "version_minor": 0,
+       "model_id": "fde051e3429741db86fea073e1b76795"
+      }
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
+      "text/plain": [],
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\n"
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
+      "text/plain": [
+       "\u001B[2;36m15:15:21 CET\u001B[0m\u001B[2;36m \u001B[0mLoading simulation from data/sim.hdf5                              \n"
+      ],
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">11:16:28 Eastern Daylight Time </span>loading simulation from data/sim.hdf5            \n",
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">15:15:21 CET </span>Loading simulation from data/sim.hdf5                              \n",
        "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m11:16:28 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mloading simulation from data/sim.hdf5            \n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     }
    ],
-   "source": [
-    "# saves the job metadata to a single file\n",
-    "job.to_file(\"data/job.json\")\n",
-    "\n",
-    "# can exit session, break here, or continue in new session.\n",
-    "\n",
-    "# load the job metadata from file\n",
-    "job_loaded = web.Job.from_file(\"data/job.json\")\n",
-    "\n",
-    "# download the data from the server and load it into a SimulationData object.\n",
-    "sim_data = job_loaded.load(path=\"data/sim.hdf5\")"
-   ]
+   "execution_count": 6
   },
   {
    "cell_type": "markdown",
@@ -1016,7 +893,6 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
    "id": "b40efc4f",
    "metadata": {
     "execution": {
@@ -1024,1060 +900,495 @@
      "iopub.status.busy": "2023-08-19T02:03:01.220388Z",
      "iopub.status.idle": "2023-08-19T02:03:36.168303Z",
      "shell.execute_reply": "2023-08-19T02:03:36.167357Z"
+    },
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:15:53.383391Z",
+     "start_time": "2025-10-29T14:15:21.624702Z"
     }
    },
+   "source": [
+    "# make a dictionary of  {task name : simulation} for demonstration\n",
+    "sims = {f\"sim_{i}\": sim for i in range(3)}\n",
+    "\n",
+    "# initialize a batch and run them all\n",
+    "batch = web.Batch(simulations=sims, verbose=verbose)\n",
+    "\n",
+    "# run the batch and store all of the data in the `data/` dir.\n",
+    "batch_results = batch.run(path_dir=\"data\")"
+   ],
    "outputs": [
     {
      "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'sim_0'</span> with task_id                \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-2e46f52d-77e8-4bba-87e4-64c648a132f4'</span> and  \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.                                \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m                              \u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'sim_0'\u001b[0m with task_id                \n",
-       "\u001b[2;36m                               \u001b[0m\u001b[32m'fdve-2e46f52d-77e8-4bba-87e4-64c648a132f4'\u001b[0m and  \n",
-       "\u001b[2;36m                               \u001b[0mtask_type \u001b[32m'FDTD'\u001b[0m.                                \n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>View task using web UI at                        \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-2e46f52d-77e8-4bba-87e4-64c648a132f4\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId</span></a>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-2e46f52d-77e8-4bba-87e4-64c648a132f4\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">=fdve-2e46f52d-77e8-4bba-87e4-64c648a132f4'</span></a>.     \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m                              \u001b[0m\u001b[2;36m \u001b[0mView task using web UI at                        \n",
-       "\u001b[2;36m                               \u001b[0m\u001b]8;id=808503;https://tidy3d.simulation.cloud/workbench?taskId=fdve-2e46f52d-77e8-4bba-87e4-64c648a132f4\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=819926;https://tidy3d.simulation.cloud/workbench?taskId=fdve-2e46f52d-77e8-4bba-87e4-64c648a132f4\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\n",
-       "\u001b[2;36m                               \u001b[0m\u001b]8;id=808503;https://tidy3d.simulation.cloud/workbench?taskId=fdve-2e46f52d-77e8-4bba-87e4-64c648a132f4\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=546893;https://tidy3d.simulation.cloud/workbench?taskId=fdve-2e46f52d-77e8-4bba-87e4-64c648a132f4\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=808503;https://tidy3d.simulation.cloud/workbench?taskId=fdve-2e46f52d-77e8-4bba-87e4-64c648a132f4\u001b\\\u001b[32m-2e46f52d-77e8-4bba-87e4-64c648a132f4'\u001b[0m\u001b]8;;\u001b\\.     \n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "f5f4a5471bcb479280716ed37518af55",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "Output()"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
-      ],
-      "text/plain": []
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">11:16:29 Eastern Daylight Time </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'sim_1'</span> with task_id                \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-4f2afb7b-d93b-489c-b5b9-60b312b9b0a8'</span> and  \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.                                \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m11:16:29 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'sim_1'\u001b[0m with task_id                \n",
-       "\u001b[2;36m                               \u001b[0m\u001b[32m'fdve-4f2afb7b-d93b-489c-b5b9-60b312b9b0a8'\u001b[0m and  \n",
-       "\u001b[2;36m                               \u001b[0mtask_type \u001b[32m'FDTD'\u001b[0m.                                \n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>View task using web UI at                        \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-4f2afb7b-d93b-489c-b5b9-60b312b9b0a8\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId</span></a>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-4f2afb7b-d93b-489c-b5b9-60b312b9b0a8\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">=fdve-4f2afb7b-d93b-489c-b5b9-60b312b9b0a8'</span></a>.     \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m                              \u001b[0m\u001b[2;36m \u001b[0mView task using web UI at                        \n",
-       "\u001b[2;36m                               \u001b[0m\u001b]8;id=622947;https://tidy3d.simulation.cloud/workbench?taskId=fdve-4f2afb7b-d93b-489c-b5b9-60b312b9b0a8\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=544162;https://tidy3d.simulation.cloud/workbench?taskId=fdve-4f2afb7b-d93b-489c-b5b9-60b312b9b0a8\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\n",
-       "\u001b[2;36m                               \u001b[0m\u001b]8;id=622947;https://tidy3d.simulation.cloud/workbench?taskId=fdve-4f2afb7b-d93b-489c-b5b9-60b312b9b0a8\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=190861;https://tidy3d.simulation.cloud/workbench?taskId=fdve-4f2afb7b-d93b-489c-b5b9-60b312b9b0a8\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=622947;https://tidy3d.simulation.cloud/workbench?taskId=fdve-4f2afb7b-d93b-489c-b5b9-60b312b9b0a8\u001b\\\u001b[32m-4f2afb7b-d93b-489c-b5b9-60b312b9b0a8'\u001b[0m\u001b]8;;\u001b\\.     \n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "1516208997324f2180146f836305df12",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "Output()"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
-      ],
-      "text/plain": []
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">11:16:30 Eastern Daylight Time </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'sim_2'</span> with task_id                \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-bf9497b0-bbc0-4ebf-a090-92d3805d0380'</span> and  \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.                                \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m11:16:30 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'sim_2'\u001b[0m with task_id                \n",
-       "\u001b[2;36m                               \u001b[0m\u001b[32m'fdve-bf9497b0-bbc0-4ebf-a090-92d3805d0380'\u001b[0m and  \n",
-       "\u001b[2;36m                               \u001b[0mtask_type \u001b[32m'FDTD'\u001b[0m.                                \n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>View task using web UI at                        \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-bf9497b0-bbc0-4ebf-a090-92d3805d0380\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId</span></a>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-bf9497b0-bbc0-4ebf-a090-92d3805d0380\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">=fdve-bf9497b0-bbc0-4ebf-a090-92d3805d0380'</span></a>.     \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m                              \u001b[0m\u001b[2;36m \u001b[0mView task using web UI at                        \n",
-       "\u001b[2;36m                               \u001b[0m\u001b]8;id=423804;https://tidy3d.simulation.cloud/workbench?taskId=fdve-bf9497b0-bbc0-4ebf-a090-92d3805d0380\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=375197;https://tidy3d.simulation.cloud/workbench?taskId=fdve-bf9497b0-bbc0-4ebf-a090-92d3805d0380\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\n",
-       "\u001b[2;36m                               \u001b[0m\u001b]8;id=423804;https://tidy3d.simulation.cloud/workbench?taskId=fdve-bf9497b0-bbc0-4ebf-a090-92d3805d0380\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=940741;https://tidy3d.simulation.cloud/workbench?taskId=fdve-bf9497b0-bbc0-4ebf-a090-92d3805d0380\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=423804;https://tidy3d.simulation.cloud/workbench?taskId=fdve-bf9497b0-bbc0-4ebf-a090-92d3805d0380\u001b\\\u001b[32m-bf9497b0-bbc0-4ebf-a090-92d3805d0380'\u001b[0m\u001b]8;;\u001b\\.     \n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "3f390d59d4b94611984b83a3c4e0a37b",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "Output()"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
-      ],
-      "text/plain": []
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">11:16:33 Eastern Daylight Time </span>Started working on Batch.                        \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m11:16:33 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mStarted working on Batch.                        \n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">11:16:34 Eastern Daylight Time </span>Maximum FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.075</span> for the whole     \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>batch.                                           \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m11:16:34 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.075\u001b[0m for the whole     \n",
-       "\u001b[2;36m                               \u001b[0mbatch.                                           \n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>Use <span style=\"color: #008000; text-decoration-color: #008000\">'Batch.real_cost()'</span> to get the billed        \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>FlexCredit cost after the Batch has completed.   \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m                              \u001b[0m\u001b[2;36m \u001b[0mUse \u001b[32m'Batch.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed        \n",
-       "\u001b[2;36m                               \u001b[0mFlexCredit cost after the Batch has completed.   \n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "2bde9f63a4ce4409898be221a4bcc261",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "Output()"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">11:16:49 Eastern Daylight Time </span>Batch complete.                                  \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m11:16:49 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mBatch complete.                                  \n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
-      ],
-      "text/plain": []
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "# make a dictionary of  {task name : simulation} for demonstration\n",
-    "sims = {f\"sim_{i}\": sim for i in range(3)}\n",
-    "\n",
-    "# initialize a batch and run them all\n",
-    "batch = web.Batch(simulations=sims, verbose=verbose)\n",
-    "\n",
-    "# run the batch and store all of the data in the `data/` dir.\n",
-    "batch_results = batch.run(path_dir=\"data\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "0ae64033",
-   "metadata": {},
-   "source": [
-    "When the batch is completed, the output is not a [SimulationData](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.SimulationData.html) but rather a [BatchData](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.web.api.container.BatchData.html).  The data within this [BatchData](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.web.api.container.BatchData.html) object can either be indexed directly `batch_results[task_name]` or can be looped through `batch_results.items()` to get the [SimulationData](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.SimulationData.html) for each task.\n",
-    "\n",
-    "This was chosen to reduce the memory strain from loading all [SimulationData](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.SimulationData.html) objects at once.\n",
-    "\n",
-    "Alternatively, the batch can be looped through (several times) using the `.items()` method, similar to a dictionary."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "id": "e855fe08",
-   "metadata": {
-    "execution": {
-     "iopub.execute_input": "2023-08-19T02:03:36.530933Z",
-     "iopub.status.busy": "2023-08-19T02:03:36.530695Z",
-     "iopub.status.idle": "2023-08-19T02:03:38.581550Z",
-     "shell.execute_reply": "2023-08-19T02:03:38.580933Z"
-    },
-    "tags": []
-   },
-   "outputs": [
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "fc617c5747a6459e870f76d40ba7a4e0",
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-       "version_minor": 0
-      },
-      "text/plain": [
-       "Output()"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
-      ],
-      "text/plain": []
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">11:16:51 Eastern Daylight Time </span>loading simulation from                          \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>data\\fdve-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">2e46f52d-77e8-4bba-87e4-64c648a132f4</span>.hd\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>f5                                               \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m11:16:51 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mloading simulation from                          \n",
-       "\u001b[2;36m                               \u001b[0mdata\\fdve-\u001b[93m2e46f52d-77e8-4bba-87e4-64c648a132f4\u001b[0m.hd\n",
-       "\u001b[2;36m                               \u001b[0mf5                                               \n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
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-       "version_minor": 0
-      },
-      "text/plain": [
-       "Output()"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
-      ],
-      "text/plain": []
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">11:16:52 Eastern Daylight Time </span>loading simulation from                          \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>data\\fdve-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">4f2afb7b-d93b-489c-b5b9-60b312b9b0a8</span>.hd\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>f5                                               \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m11:16:52 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mloading simulation from                          \n",
-       "\u001b[2;36m                               \u001b[0mdata\\fdve-\u001b[93m4f2afb7b-d93b-489c-b5b9-60b312b9b0a8\u001b[0m.hd\n",
-       "\u001b[2;36m                               \u001b[0mf5                                               \n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
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-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "Output()"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
-      ],
-      "text/plain": []
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">11:16:53 Eastern Daylight Time </span>loading simulation from                          \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>data\\fdve-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">bf9497b0-bbc0-4ebf-a090-92d3805d0380</span>.hd\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>f5                                               \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m11:16:53 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mloading simulation from                          \n",
-       "\u001b[2;36m                               \u001b[0mdata\\fdve-\u001b[93mbf9497b0-bbc0-4ebf-a090-92d3805d0380\u001b[0m.hd\n",
-       "\u001b[2;36m                               \u001b[0mf5                                               \n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "{'sim_0': 6377911.0, 'sim_1': 6377911.0, 'sim_2': 6377911.0}\n"
-     ]
-    }
-   ],
-   "source": [
-    "# grab the sum of intensities in the simulation one by one (to save memory)\n",
-    "intensities = {}\n",
-    "for task_name, sim_data in batch_results.items():\n",
-    "    intensity = sim_data.get_intensity(\"field\").sel(f=freq0)\n",
-    "    sum_intensity = float(intensity.sum((\"x\", \"y\")).values[0])\n",
-    "    intensities[task_name] = sum_intensity\n",
-    "\n",
-    "print(intensities)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "b1e19538-d559-4ea2-b555-0df0135417ff",
-   "metadata": {},
-   "source": [
-    "## Simulation Batching\n",
-    "\n",
-    "Finally, one perform batch processing of several simulations in a single function call.\n",
-    "\n",
-    "For this purpose, a [web.run_async](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.web.api.asynchronous.run_async.html) function is provided, which works like the regular `web.run` but accepts a dictionary of simulations. \n",
-    "\n",
-    "Here is the previous example repeated using this feature."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
-   "id": "0a56613f-78f0-4aad-bb4f-826193a809b0",
-   "metadata": {
-    "execution": {
-     "iopub.execute_input": "2023-08-19T02:03:38.612831Z",
-     "iopub.status.busy": "2023-08-19T02:03:38.612656Z",
-     "iopub.status.idle": "2023-08-19T02:04:17.604868Z",
-     "shell.execute_reply": "2023-08-19T02:04:17.604263Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'sim_0'</span> with task_id                \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-3e163014-4be9-4d47-91b0-490e44a64f19'</span> and  \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.                                \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m                              \u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'sim_0'\u001b[0m with task_id                \n",
-       "\u001b[2;36m                               \u001b[0m\u001b[32m'fdve-3e163014-4be9-4d47-91b0-490e44a64f19'\u001b[0m and  \n",
-       "\u001b[2;36m                               \u001b[0mtask_type \u001b[32m'FDTD'\u001b[0m.                                \n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>View task using web UI at                        \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-3e163014-4be9-4d47-91b0-490e44a64f19\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId</span></a>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-3e163014-4be9-4d47-91b0-490e44a64f19\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">=fdve-3e163014-4be9-4d47-91b0-490e44a64f19'</span></a>.     \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m                              \u001b[0m\u001b[2;36m \u001b[0mView task using web UI at                        \n",
-       "\u001b[2;36m                               \u001b[0m\u001b]8;id=888349;https://tidy3d.simulation.cloud/workbench?taskId=fdve-3e163014-4be9-4d47-91b0-490e44a64f19\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=846180;https://tidy3d.simulation.cloud/workbench?taskId=fdve-3e163014-4be9-4d47-91b0-490e44a64f19\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\n",
-       "\u001b[2;36m                               \u001b[0m\u001b]8;id=888349;https://tidy3d.simulation.cloud/workbench?taskId=fdve-3e163014-4be9-4d47-91b0-490e44a64f19\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=862887;https://tidy3d.simulation.cloud/workbench?taskId=fdve-3e163014-4be9-4d47-91b0-490e44a64f19\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=888349;https://tidy3d.simulation.cloud/workbench?taskId=fdve-3e163014-4be9-4d47-91b0-490e44a64f19\u001b\\\u001b[32m-3e163014-4be9-4d47-91b0-490e44a64f19'\u001b[0m\u001b]8;;\u001b\\.     \n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "cce63644bc0f4cbba65a08b29934c19a",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "Output()"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
-      ],
-      "text/plain": []
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">11:16:54 Eastern Daylight Time </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'sim_1'</span> with task_id                \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-21d2a378-4508-4c6b-b50c-f9181fdfa91c'</span> and  \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.                                \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m11:16:54 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'sim_1'\u001b[0m with task_id                \n",
-       "\u001b[2;36m                               \u001b[0m\u001b[32m'fdve-21d2a378-4508-4c6b-b50c-f9181fdfa91c'\u001b[0m and  \n",
-       "\u001b[2;36m                               \u001b[0mtask_type \u001b[32m'FDTD'\u001b[0m.                                \n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>View task using web UI at                        \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-21d2a378-4508-4c6b-b50c-f9181fdfa91c\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId</span></a>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-21d2a378-4508-4c6b-b50c-f9181fdfa91c\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">=fdve-21d2a378-4508-4c6b-b50c-f9181fdfa91c'</span></a>.     \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m                              \u001b[0m\u001b[2;36m \u001b[0mView task using web UI at                        \n",
-       "\u001b[2;36m                               \u001b[0m\u001b]8;id=127949;https://tidy3d.simulation.cloud/workbench?taskId=fdve-21d2a378-4508-4c6b-b50c-f9181fdfa91c\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=86180;https://tidy3d.simulation.cloud/workbench?taskId=fdve-21d2a378-4508-4c6b-b50c-f9181fdfa91c\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\n",
-       "\u001b[2;36m                               \u001b[0m\u001b]8;id=127949;https://tidy3d.simulation.cloud/workbench?taskId=fdve-21d2a378-4508-4c6b-b50c-f9181fdfa91c\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=960451;https://tidy3d.simulation.cloud/workbench?taskId=fdve-21d2a378-4508-4c6b-b50c-f9181fdfa91c\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=127949;https://tidy3d.simulation.cloud/workbench?taskId=fdve-21d2a378-4508-4c6b-b50c-f9181fdfa91c\u001b\\\u001b[32m-21d2a378-4508-4c6b-b50c-f9181fdfa91c'\u001b[0m\u001b]8;;\u001b\\.     \n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "e3889457a7a047db81bc0f6b34fd55f8",
-       "version_major": 2,
-       "version_minor": 0
-      },
       "text/plain": [
        "Output()"
-      ]
+      ],
+      "application/vnd.jupyter.widget-view+json": {
+       "version_major": 2,
+       "version_minor": 0,
+       "model_id": "5ad4735940514044b1530e88ce152f20"
+      }
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
+      "text/plain": [],
       "text/html": [
        "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
-      ],
-      "text/plain": []
+      ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
+      "text/plain": [
+       "\u001B[2;36m15:15:26 CET\u001B[0m\u001B[2;36m \u001B[0mStarted working on Batch containing \u001B[1;36m3\u001B[0m tasks.                       \n"
+      ],
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">15:15:26 CET </span>Started working on Batch containing <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span> tasks.                       \n",
        "</pre>\n"
-      ],
-      "text/plain": [
-       "\n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
+      "text/plain": [
+       "\u001B[2;36m15:15:33 CET\u001B[0m\u001B[2;36m \u001B[0mMaximum FlexCredit cost: \u001B[1;36m0.075\u001B[0m for the whole batch.                \n"
+      ],
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">11:16:56 Eastern Daylight Time </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'sim_2'</span> with task_id                \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-7cbf20ca-4312-4220-8ff0-deffb7c240ae'</span> and  \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.                                \n",
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">15:15:33 CET </span>Maximum FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.075</span> for the whole batch.                \n",
        "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m11:16:56 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'sim_2'\u001b[0m with task_id                \n",
-       "\u001b[2;36m                               \u001b[0m\u001b[32m'fdve-7cbf20ca-4312-4220-8ff0-deffb7c240ae'\u001b[0m and  \n",
-       "\u001b[2;36m                               \u001b[0mtask_type \u001b[32m'FDTD'\u001b[0m.                                \n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
+      "text/plain": [
+       "\u001B[2;36m            \u001B[0m\u001B[2;36m \u001B[0mUse \u001B[32m'Batch.real_cost\u001B[0m\u001B[32m(\u001B[0m\u001B[32m)\u001B[0m\u001B[32m'\u001B[0m to get the billed FlexCredit cost after    \n",
+       "\u001B[2;36m             \u001B[0mcompletion.                                                        \n"
+      ],
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>View task using web UI at                        \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-7cbf20ca-4312-4220-8ff0-deffb7c240ae\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId</span></a>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-7cbf20ca-4312-4220-8ff0-deffb7c240ae\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">=fdve-7cbf20ca-4312-4220-8ff0-deffb7c240ae'</span></a>.     \n",
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>Use <span style=\"color: #008000; text-decoration-color: #008000\">'Batch.real_cost()'</span> to get the billed FlexCredit cost after    \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>completion.                                                        \n",
        "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m                              \u001b[0m\u001b[2;36m \u001b[0mView task using web UI at                        \n",
-       "\u001b[2;36m                               \u001b[0m\u001b]8;id=751321;https://tidy3d.simulation.cloud/workbench?taskId=fdve-7cbf20ca-4312-4220-8ff0-deffb7c240ae\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=415745;https://tidy3d.simulation.cloud/workbench?taskId=fdve-7cbf20ca-4312-4220-8ff0-deffb7c240ae\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\n",
-       "\u001b[2;36m                               \u001b[0m\u001b]8;id=751321;https://tidy3d.simulation.cloud/workbench?taskId=fdve-7cbf20ca-4312-4220-8ff0-deffb7c240ae\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=985223;https://tidy3d.simulation.cloud/workbench?taskId=fdve-7cbf20ca-4312-4220-8ff0-deffb7c240ae\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=751321;https://tidy3d.simulation.cloud/workbench?taskId=fdve-7cbf20ca-4312-4220-8ff0-deffb7c240ae\u001b\\\u001b[32m-7cbf20ca-4312-4220-8ff0-deffb7c240ae'\u001b[0m\u001b]8;;\u001b\\.     \n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "484c8df2c75c414ca0c0486ceadbbfe7",
-       "version_major": 2,
-       "version_minor": 0
-      },
       "text/plain": [
        "Output()"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
       ],
-      "text/plain": []
+      "application/vnd.jupyter.widget-view+json": {
+       "version_major": 2,
+       "version_minor": 0,
+       "model_id": "ab5df97f5af148d9b080c4e892dcf9ef"
+      }
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
-       "</pre>\n"
-      ],
       "text/plain": [
-       "\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
+       "\u001B[2;36m15:15:48 CET\u001B[0m\u001B[2;36m \u001B[0mBatch complete.                                                    \n"
+      ],
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">11:16:59 Eastern Daylight Time </span>Started working on Batch.                        \n",
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">15:15:48 CET </span>Batch complete.                                                    \n",
        "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m11:16:59 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mStarted working on Batch.                        \n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
+      "text/plain": [],
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">11:17:01 Eastern Daylight Time </span>Maximum FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.075</span> for the whole     \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>batch.                                           \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m11:17:01 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.075\u001b[0m for the whole     \n",
-       "\u001b[2;36m                               \u001b[0mbatch.                                           \n"
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
+    }
+   ],
+   "execution_count": 7
+  },
+  {
+   "cell_type": "markdown",
+   "id": "0ae64033",
+   "metadata": {},
+   "source": [
+    "When the batch is completed, the output is not a [SimulationData](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.SimulationData.html) but rather a [BatchData](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.web.api.container.BatchData.html).  The data within this [BatchData](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.web.api.container.BatchData.html) object can either be indexed directly `batch_results[task_name]` or can be looped through `batch_results.items()` to get the [SimulationData](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.SimulationData.html) for each task.\n",
+    "\n",
+    "This was chosen to reduce the memory strain from loading all [SimulationData](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.SimulationData.html) objects at once.\n",
+    "\n",
+    "Alternatively, the batch can be looped through (several times) using the `.items()` method, similar to a dictionary."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "id": "e855fe08",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-08-19T02:03:36.530933Z",
+     "iopub.status.busy": "2023-08-19T02:03:36.530695Z",
+     "iopub.status.idle": "2023-08-19T02:03:38.581550Z",
+     "shell.execute_reply": "2023-08-19T02:03:38.580933Z"
     },
+    "tags": [],
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:16:00.136519Z",
+     "start_time": "2025-10-29T14:15:53.389178Z"
+    }
+   },
+   "source": [
+    "# grab the sum of intensities in the simulation one by one (to save memory)\n",
+    "intensities = {}\n",
+    "for task_name, sim_data in batch_results.items():\n",
+    "    intensity = sim_data.get_intensity(\"field\").sel(f=freq0)\n",
+    "    sum_intensity = float(intensity.sum((\"x\", \"y\")).values[0])\n",
+    "    intensities[task_name] = sum_intensity\n",
+    "\n",
+    "print(intensities)"
+   ],
+   "outputs": [
     {
      "data": {
+      "text/plain": [
+       "\u001B[2;36m15:15:55 CET\u001B[0m\u001B[2;36m \u001B[0mLoading simulation from                                            \n",
+       "\u001B[2;36m             \u001B[0mdata/fdve-\u001B[93mef73aa96-65f9-4793-9b1d-26ea9b39c6b2\u001B[0m.hdf5                \n"
+      ],
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>Use <span style=\"color: #008000; text-decoration-color: #008000\">'Batch.real_cost()'</span> to get the billed        \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>FlexCredit cost after the Batch has completed.   \n",
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">15:15:55 CET </span>Loading simulation from                                            \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/fdve-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">ef73aa96-65f9-4793-9b1d-26ea9b39c6b2</span>.hdf5                \n",
        "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m                              \u001b[0m\u001b[2;36m \u001b[0mUse \u001b[32m'Batch.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed        \n",
-       "\u001b[2;36m                               \u001b[0mFlexCredit cost after the Batch has completed.   \n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "65727a12fb75474b8bb0f031c6d8386d",
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-       "version_minor": 0
-      },
       "text/plain": [
-       "Output()"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
+       "\u001B[2;36m15:15:56 CET\u001B[0m\u001B[2;36m \u001B[0mLoading simulation from                                            \n",
+       "\u001B[2;36m             \u001B[0mdata/fdve-\u001B[93mc229e1b2-0bb8-44df-a570-df73ab419ba8\u001B[0m.hdf5                \n"
+      ],
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">11:17:14 Eastern Daylight Time </span>Batch complete.                                  \n",
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">15:15:56 CET </span>Loading simulation from                                            \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/fdve-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">c229e1b2-0bb8-44df-a570-df73ab419ba8</span>.hdf5                \n",
        "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m11:17:14 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mBatch complete.                                  \n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
+      "text/plain": [
+       "\u001B[2;36m15:16:00 CET\u001B[0m\u001B[2;36m \u001B[0mLoading simulation from                                            \n",
+       "\u001B[2;36m             \u001B[0mdata/fdve-\u001B[93m2cd0c62f-c207-4191-b057-f2a1c753aed1\u001B[0m.hdf5                \n"
       ],
-      "text/plain": []
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">15:16:00 CET </span>Loading simulation from                                            \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>data/fdve-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">2cd0c62f-c207-4191-b057-f2a1c753aed1</span>.hdf5                \n",
        "</pre>\n"
-      ],
-      "text/plain": [
-       "\n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'sim_0': 6473211.0, 'sim_1': 6473211.0, 'sim_2': 6473211.0}\n"
+     ]
     }
    ],
+   "execution_count": 8
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b1e19538-d559-4ea2-b555-0df0135417ff",
+   "metadata": {},
    "source": [
-    "batch_results = web.run_async(simulations=sims, verbose=verbose)"
+    "## Simulation Batching\n",
+    "\n",
+    "Finally, one perform batch processing of several simulations in a single function call.\n",
+    "\n",
+    "For this purpose, [web.run](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.web.api.run.run.html) function can also be used for any nested combinations of dictionaries, lists or tuples.\n",
+    "\n",
+    "Here is the previous example repeated using this feature."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
-   "id": "4189dce5-6ec8-4bc4-a1a2-946a06bd9de5",
+   "id": "0a56613f-78f0-4aad-bb4f-826193a809b0",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-08-19T02:04:18.077517Z",
-     "iopub.status.busy": "2023-08-19T02:04:18.077354Z",
-     "iopub.status.idle": "2023-08-19T02:04:19.937244Z",
-     "shell.execute_reply": "2023-08-19T02:04:19.936662Z"
+     "iopub.execute_input": "2023-08-19T02:03:38.612831Z",
+     "iopub.status.busy": "2023-08-19T02:03:38.612656Z",
+     "iopub.status.idle": "2023-08-19T02:04:17.604868Z",
+     "shell.execute_reply": "2023-08-19T02:04:17.604263Z"
     },
-    "tags": []
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:16:20.476211Z",
+     "start_time": "2025-10-29T14:16:00.142436Z"
+    }
    },
+   "source": [
+    "batch_results_dict = web.run(sims, verbose=verbose)\n",
+    "# sim_list = list(sims.values())\n",
+    "# batch_results_list = web.run(sim_list, verbose=verbose) # this would return a plain list of SimulationData"
+   ],
    "outputs": [
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "a07f2b2b41be44819fb52df4416d9909",
-       "version_major": 2,
-       "version_minor": 0
-      },
       "text/plain": [
-       "Output()"
+       "\u001B[2;36m15:16:01 CET\u001B[0m\u001B[2;36m \u001B[0mCreated task \u001B[32m'fdtd_2025-10-29_15-16-00'\u001B[0m with resource_id           \n",
+       "\u001B[2;36m             \u001B[0m\u001B[32m'fdve-0e9a1dac-0a3c-431d-af51-3e63bc484aa2'\u001B[0m and task_type \u001B[32m'FDTD'\u001B[0m.  \n"
+      ],
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">15:16:01 CET </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'fdtd_2025-10-29_15-16-00'</span> with resource_id           \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-0e9a1dac-0a3c-431d-af51-3e63bc484aa2'</span> and task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.  \n",
+       "</pre>\n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
+      "text/plain": [
+       "\u001B[2;36m            \u001B[0m\u001B[2;36m \u001B[0mView task using web UI at                                          \n",
+       "\u001B[2;36m             \u001B[0m\u001B]8;id=655135;https://tidy3d.simulation.cloud/workbench?taskId=fdve-0e9a1dac-0a3c-431d-af51-3e63bc484aa2\u001B\\\u001B[32m'https://tidy3d.simulation.cloud/workbench?\u001B[0m\u001B]8;;\u001B\\\u001B]8;id=710211;https://tidy3d.simulation.cloud/workbench?taskId=fdve-0e9a1dac-0a3c-431d-af51-3e63bc484aa2\u001B\\\u001B[32mtaskId\u001B[0m\u001B]8;;\u001B\\\u001B]8;id=655135;https://tidy3d.simulation.cloud/workbench?taskId=fdve-0e9a1dac-0a3c-431d-af51-3e63bc484aa2\u001B\\\u001B[32m=\u001B[0m\u001B]8;;\u001B\\\u001B]8;id=170182;https://tidy3d.simulation.cloud/workbench?taskId=fdve-0e9a1dac-0a3c-431d-af51-3e63bc484aa2\u001B\\\u001B[32mfdve\u001B[0m\u001B]8;;\u001B\\\u001B]8;id=655135;https://tidy3d.simulation.cloud/workbench?taskId=fdve-0e9a1dac-0a3c-431d-af51-3e63bc484aa2\u001B\\\u001B[32m-0e9a1dac-0a3\u001B[0m\u001B]8;;\u001B\\\n",
+       "\u001B[2;36m             \u001B[0m\u001B]8;id=655135;https://tidy3d.simulation.cloud/workbench?taskId=fdve-0e9a1dac-0a3c-431d-af51-3e63bc484aa2\u001B\\\u001B[32mc-431d-af51-3e63bc484aa2'\u001B[0m\u001B]8;;\u001B\\.                                         \n"
       ],
-      "text/plain": []
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>View task using web UI at                                          \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-0e9a1dac-0a3c-431d-af51-3e63bc484aa2\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-0e9a1dac-0a3</span></a>\n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-0e9a1dac-0a3c-431d-af51-3e63bc484aa2\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">c-431d-af51-3e63bc484aa2'</span></a>.                                         \n",
        "</pre>\n"
-      ],
-      "text/plain": [
-       "\n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
+      "text/plain": [
+       "\u001B[2;36m            \u001B[0m\u001B[2;36m \u001B[0mTask folder: \u001B]8;id=515771;https://tidy3d.simulation.cloud/folders/folder-df61810d-cad6-4474-8ea9-e4f00d5dfcb0\u001B\\\u001B[32m'default'\u001B[0m\u001B]8;;\u001B\\.                                            \n"
+      ],
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">11:17:15 Eastern Daylight Time </span>loading simulation from                          \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>.\\fdve-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">3e163014-4be9-4d47-91b0-490e44a64f19</span>.hdf5 \n",
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>Task folder: <a href=\"https://tidy3d.simulation.cloud/folders/folder-df61810d-cad6-4474-8ea9-e4f00d5dfcb0\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'default'</span></a>.                                            \n",
        "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m11:17:15 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mloading simulation from                          \n",
-       "\u001b[2;36m                               \u001b[0m.\\fdve-\u001b[93m3e163014-4be9-4d47-91b0-490e44a64f19\u001b[0m.hdf5 \n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "b6ae513710424a73bbddc052e29f6c40",
-       "version_major": 2,
-       "version_minor": 0
-      },
       "text/plain": [
        "Output()"
-      ]
+      ],
+      "application/vnd.jupyter.widget-view+json": {
+       "version_major": 2,
+       "version_minor": 0,
+       "model_id": "13f2fea2d7ad41dbbaf8fcaeb602f956"
+      }
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
+      "text/plain": [],
       "text/html": [
        "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
-      ],
-      "text/plain": []
+      ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
+      "text/plain": [
+       "\u001B[2;36m15:16:06 CET\u001B[0m\u001B[2;36m \u001B[0mEstimated FlexCredit cost: \u001B[1;36m0.025\u001B[0m. Minimum cost depends on task     \n",
+       "\u001B[2;36m             \u001B[0mexecution details. Use \u001B[32m'web.real_cost\u001B[0m\u001B[32m(\u001B[0m\u001B[32mtask_id\u001B[0m\u001B[32m)\u001B[0m\u001B[32m'\u001B[0m to get the billed  \n",
+       "\u001B[2;36m             \u001B[0mFlexCredit cost after a simulation run.                            \n"
+      ],
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">15:16:06 CET </span>Estimated FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.025</span>. Minimum cost depends on task     \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>execution details. Use <span style=\"color: #008000; text-decoration-color: #008000\">'web.real_cost(task_id)'</span> to get the billed  \n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>FlexCredit cost after a simulation run.                            \n",
        "</pre>\n"
-      ],
-      "text/plain": [
-       "\n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
+      "text/plain": [
+       "\u001B[2;36m15:16:09 CET\u001B[0m\u001B[2;36m \u001B[0mstatus = success                                                   \n"
+      ],
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">11:17:17 Eastern Daylight Time </span>loading simulation from                          \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>.\\fdve-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">21d2a378-4508-4c6b-b50c-f9181fdfa91c</span>.hdf5 \n",
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">15:16:09 CET </span>status = success                                                   \n",
        "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m11:17:17 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mloading simulation from                          \n",
-       "\u001b[2;36m                               \u001b[0m.\\fdve-\u001b[93m21d2a378-4508-4c6b-b50c-f9181fdfa91c\u001b[0m.hdf5 \n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "c5647ac15343459c8cadf2ac1b5ee9dc",
-       "version_major": 2,
-       "version_minor": 0
-      },
       "text/plain": [
        "Output()"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
       ],
-      "text/plain": []
+      "application/vnd.jupyter.widget-view+json": {
+       "version_major": 2,
+       "version_minor": 0,
+       "model_id": "d17b7109c4874aa786e8efcbe2529642"
+      }
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
+      "text/plain": [],
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\n"
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     },
     {
      "data": {
+      "text/plain": [
+       "\u001B[2;36m15:16:20 CET\u001B[0m\u001B[2;36m \u001B[0mLoading simulation from simulation_data.hdf5                       \n"
+      ],
       "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">11:17:18 Eastern Daylight Time </span>loading simulation from                          \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                               </span>.\\fdve-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">7cbf20ca-4312-4220-8ff0-deffb7c240ae</span>.hdf5 \n",
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">15:16:20 CET </span>Loading simulation from simulation_data.hdf5                       \n",
        "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m11:17:18 Eastern Daylight Time\u001b[0m\u001b[2;36m \u001b[0mloading simulation from                          \n",
-       "\u001b[2;36m                               \u001b[0m.\\fdve-\u001b[93m7cbf20ca-4312-4220-8ff0-deffb7c240ae\u001b[0m.hdf5 \n"
       ]
      },
      "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "{'sim_0': 6377911.0, 'sim_1': 6377911.0, 'sim_2': 6377911.0}\n"
-     ]
+     "output_type": "display_data",
+     "jetTransient": {
+      "display_id": null
+     }
     }
    ],
+   "execution_count": 9
+  },
+  {
+   "cell_type": "code",
+   "id": "4189dce5-6ec8-4bc4-a1a2-946a06bd9de5",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-08-19T02:04:18.077517Z",
+     "iopub.status.busy": "2023-08-19T02:04:18.077354Z",
+     "iopub.status.idle": "2023-08-19T02:04:19.937244Z",
+     "shell.execute_reply": "2023-08-19T02:04:19.936662Z"
+    },
+    "tags": [],
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:16:20.505581Z",
+     "start_time": "2025-10-29T14:16:20.482156Z"
+    }
+   },
    "source": [
     "# grab the sum of intensities in the simulation one by one (to save memory)\n",
     "intensities = {}\n",
-    "for task_name, sim_data in batch_results.items():\n",
+    "for task_name, sim_data in batch_results_dict.items():\n",
     "    intensity = sim_data.get_intensity(\"field\").sel(f=freq0)\n",
     "    sum_intensity = float(intensity.sum((\"x\", \"y\")).values[0])\n",
     "    intensities[task_name] = sum_intensity\n",
     "\n",
     "print(intensities)"
-   ]
+   ],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'sim_0': 6473211.0, 'sim_1': 6473211.0, 'sim_2': 6473211.0}\n"
+     ]
+    }
+   ],
+   "execution_count": 10
   },
   {
    "cell_type": "markdown",
@@ -2089,11 +1400,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "eb26adc6",
-   "metadata": {},
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-10-29T14:16:20.537788Z",
+     "start_time": "2025-10-29T14:16:20.535962Z"
+    }
+   },
+   "source": [],
    "outputs": [],
-   "source": []
+   "execution_count": null
   }
  ],
  "metadata": {
@@ -2140,7 +1456,7 @@
         {
          "data": {
           "text/html": "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008000; text-decoration-color: #008000\">🏃 </span> <span style=\"color: #008000; text-decoration-color: #008000; font-weight: bold\">Starting 'job'...</span>\n</pre>\n",
-          "text/plain": "\u001b[32m🏃 \u001b[0m \u001b[1;32mStarting 'job'...\u001b[0m\n"
+          "text/plain": "\u001B[32m🏃 \u001B[0m \u001B[1;32mStarting 'job'...\u001B[0m\n"
          },
          "metadata": {},
          "output_type": "display_data"
@@ -2169,7 +1485,7 @@
         {
          "data": {
           "text/html": "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008000; text-decoration-color: #008000; font-weight: bold\">↓</span> <span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">monitor_data.hdf5</span> <span style=\"color: #729c1f; text-decoration-color: #729c1f\">━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\">100.0%</span> • <span style=\"color: #008000; text-decoration-color: #008000\">302.1/302.1 kB</span> • <span style=\"color: #800000; text-decoration-color: #800000\">12.1 MB/s</span> • <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\n</pre>\n",
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+          "text/plain": "solver progress (field decay = 0.00e+00) \u001B[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━\u001B[0m \u001B[35m100%\u001B[0m \u001B[36m0:00:00\u001B[0m\n"
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+          "text/plain": "solver progress (field decay = 0.00e+00) \u001B[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━\u001B[0m \u001B[35m100%\u001B[0m \u001B[36m0:00:00\u001B[0m\n"
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