diff --git a/EffectiveIndexApproximation.ipynb b/EffectiveIndexApproximation.ipynb
index cffa68c1..6b8c3c4b 100644
--- a/EffectiveIndexApproximation.ipynb
+++ b/EffectiveIndexApproximation.ipynb
@@ -143,7 +143,10 @@
     "    m_values = Mz2(z_coords)\n",
     "\n",
     "    # calculate integrals\n",
-    "    num, denom = np.trapz(y=eps_dif * m_values, x=z_coords), np.trapz(y=m_values, x=z_coords)\n",
+    "    num, denom = (\n",
+    "        np.trapezoid(y=eps_dif * m_values, x=z_coords),\n",
+    "        np.trapezoid(y=m_values, x=z_coords),\n",
+    "    )\n",
     "\n",
     "    if n_eff**2 + num / denom < min_n:\n",
     "        return min_n\n",
@@ -165,7 +168,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "def approximate_material(sim_3D, approx_point, ref_point, spectrum, min_n=1, plot=False):\n",
+    "def approximate_material(\n",
+    "    sim_3D, approx_point, ref_point, spectrum, min_n=1, plot=False, min_num_poles=1\n",
+    "):\n",
     "    eps = []\n",
     "    for wl in spectrum:  # at every [step]th wavelength, calculate the effective permittivity\n",
     "        eps.append(var_eps_eff(approx_point, ref_point, sim_3D, wavelength=wl, min_n=min_n))\n",
@@ -174,7 +179,7 @@
     "    fitter = FastDispersionFitter(wvl_um=spectrum, n_data=np.sqrt(np.real(eps)))\n",
     "\n",
     "    # create the mediums using the material fit\n",
-    "    medium, rms_error = fitter.fit()\n",
+    "    medium, rms_error = fitter.fit(min_num_poles=min_num_poles)\n",
     "\n",
     "    if plot:\n",
     "        # plot the material fit\n",
@@ -278,7 +283,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 2 Axes>"
       ]
@@ -382,13 +387,12 @@
    "outputs": [
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "3d550e5dec994cea9d5f0bf1d485a0f2",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Best weighted RMS error so far: 0.00246 <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": [
-       "Output()"
+       "Best weighted RMS error so far: 0.00246 \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[36m0:00:00\u001b[0m\n"
       ]
      },
      "metadata": {},
@@ -406,20 +410,7 @@
     },
     {
      "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 300x300 with 1 Axes>"
       ]
@@ -442,13 +433,12 @@
    "outputs": [
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "f8fadeceda4f4119a7a5b67b8af3e8da",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Best weighted RMS error: 0 <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": [
-       "Output()"
+       "Best weighted RMS error: 0 \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[36m0:00:00\u001b[0m\n"
       ]
      },
      "metadata": {},
@@ -463,19 +453,6 @@
      },
      "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": [
@@ -545,13 +522,11 @@
     {
      "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\">13:30:09 EST </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'var eps'</span> with task_id                                \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-329f73f4-e53d-4f75-ace2-c6c16f717e99'</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: #008000; text-decoration-color: #008000; font-weight: bold\">↓</span> <span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">simulation_data.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\">5.9/5.9 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[2;36m13:30:09 EST\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'var eps'\u001b[0m with task_id                                \n",
-       "\u001b[2;36m             \u001b[0m\u001b[32m'fdve-329f73f4-e53d-4f75-ace2-c6c16f717e99'\u001b[0m and task_type \u001b[32m'FDTD'\u001b[0m.  \n"
+       "\u001b[1;32m↓\u001b[0m \u001b[1;34msimulation_data.hdf5.gz\u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100.0%\u001b[0m • \u001b[32m5.9/5.9 kB\u001b[0m • \u001b[31m?\u001b[0m • \u001b[36m0:00:00\u001b[0m\n"
       ]
      },
      "metadata": {},
@@ -560,65 +535,254 @@
     {
      "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-329f73f4-e53d-4f75-ace2-c6c16f717e99\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-329f73f4-e53</span></a>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-329f73f4-e53d-4f75-ace2-c6c16f717e99\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">d-4f75-ace2-c6c16f717e99'</span></a>.                                         \n",
-       "</pre>\n"
+       "<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=361464;https://tidy3d.simulation.cloud/workbench?taskId=fdve-329f73f4-e53d-4f75-ace2-c6c16f717e99\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=633718;https://tidy3d.simulation.cloud/workbench?taskId=fdve-329f73f4-e53d-4f75-ace2-c6c16f717e99\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=361464;https://tidy3d.simulation.cloud/workbench?taskId=fdve-329f73f4-e53d-4f75-ace2-c6c16f717e99\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=509360;https://tidy3d.simulation.cloud/workbench?taskId=fdve-329f73f4-e53d-4f75-ace2-c6c16f717e99\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=361464;https://tidy3d.simulation.cloud/workbench?taskId=fdve-329f73f4-e53d-4f75-ace2-c6c16f717e99\u001b\\\u001b[32m-329f73f4-e53\u001b[0m\u001b]8;;\u001b\\\n",
-       "\u001b[2;36m             \u001b[0m\u001b]8;id=361464;https://tidy3d.simulation.cloud/workbench?taskId=fdve-329f73f4-e53d-4f75-ace2-c6c16f717e99\u001b\\\u001b[32md-4f75-ace2-c6c16f717e99'\u001b[0m\u001b]8;;\u001b\\.                                         \n"
-      ]
+      "text/plain": []
      },
      "metadata": {},
      "output_type": "display_data"
     },
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "03235d9d2b5b43ac9449cc7f5596fe66",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "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\">14:34:48 EDT </span>loading simulation from simulation_data.hdf5                       \n",
+       "</pre>\n"
+      ],
       "text/plain": [
-       "Output()"
+       "\u001b[2;36m14:34:48 EDT\u001b[0m\u001b[2;36m \u001b[0mloading simulation from simulation_data.hdf5                       \n"
       ]
      },
      "metadata": {},
      "output_type": "display_data"
-    },
+    }
+   ],
+   "source": [
+    "sim_2d_data = web.run(sim_2d, task_name=\"var eps\")\n",
+    "sim_1d_data = web.run(sim_1d, task_name=\"var eps\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "0d6294c1-5023-4c91-a3ef-b0de0b2297fd",
+   "metadata": {},
+   "source": [
+    "### Example 1 Result Comparison\n",
+    "\n",
+    "Now that both the 2D and 1D simulations have run, we will compare their results to see how representative the 1D simulation is. The results of the 1D approximation retain a reasonable qualitative fidelity to the 2D version."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "0f120c35-9ae2-4a94-8c6c-96c56b1ffc17",
+   "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\"></pre>\n"
-      ],
-      "text/plain": []
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x500 with 2 Axes>"
+      ]
      },
      "metadata": {},
      "output_type": "display_data"
-    },
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots(1, 2, figsize=(12, 5))\n",
+    "\n",
+    "ax[0].plot(\n",
+    "    td.C_0 / sim_1d_data[\"R\"].flux.f,\n",
+    "    sim_1d_data[\"R\"].flux.data,\n",
+    "    label=\"1D\",\n",
+    "    color=\"red\",\n",
+    "    linestyle=\"--\",\n",
+    ")\n",
+    "ax[0].plot(td.C_0 / sim_2d_data[\"R\"].flux.f, sim_2d_data[\"R\"].flux.data, label=\"2D\", color=\"red\")\n",
+    "ax[0].set_title(\"2D vs 1D Reflection\")\n",
+    "ax[0].set_xlabel(\"Wavelength (µm)\")\n",
+    "ax[0].legend()\n",
+    "\n",
+    "ax[1].plot(\n",
+    "    td.C_0 / sim_1d_data[\"R\"].flux.f,\n",
+    "    sim_1d_data[\"T\"].flux.data,\n",
+    "    label=\"1D\",\n",
+    "    color=\"blue\",\n",
+    "    linestyle=\"--\",\n",
+    ")\n",
+    "ax[1].plot(td.C_0 / sim_2d_data[\"R\"].flux.f, sim_2d_data[\"T\"].flux.data, label=\"2D\", color=\"blue\")\n",
+    "ax[1].set_title(\"2D vs 1D Transmission\")\n",
+    "ax[1].set_xlabel(\"Wavelength (µm)\")\n",
+    "ax[1].legend()\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "35762762-3dcb-4f44-9ee6-eee60fff9ec2",
+   "metadata": {},
+   "source": [
+    "## Example 2: Ring Resonator"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "826c2941-9f86-4a72-acf8-11b70ef7bbe7",
+   "metadata": {},
+   "source": [
+    "We will now apply this same method to transform a 3D simulation into its 2D approximation. We will use a ring resonator and check the transmission of the through ports of both setups.<br><br>\n",
+    "First we quickly build the 3D simulation:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "7eb43d86-4e2b-43b4-93ab-ce0ce0be6cc8",
+   "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\">\n",
-       "</pre>\n"
-      ],
+      "image/png": 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",
       "text/plain": [
-       "\n"
+       "<Figure size 640x480 with 1 Axes>"
       ]
      },
      "metadata": {},
      "output_type": "display_data"
-    },
+    }
+   ],
+   "source": [
+    "# Define wavelength/frequency ranges\n",
+    "lambda_beg = 1.5\n",
+    "lambda_end = 1.6\n",
+    "freq_beg = td.C_0 / lambda_end\n",
+    "freq_end = td.C_0 / lambda_beg\n",
+    "freq0 = (freq_beg + freq_end) / 2\n",
+    "fwidth = (freq_end - freq0) / 1.5\n",
+    "lambdas_ring = np.linspace(lambda_beg, lambda_end, 301)\n",
+    "freqs_ring = td.C_0 / lambdas_ring[::-1]\n",
+    "\n",
+    "# Refractive indices\n",
+    "Si_n = 3.4777\n",
+    "SiO2_n = 1.444\n",
+    "\n",
+    "# Materials used\n",
+    "Si = td.Medium(permittivity=Si_n**2)\n",
+    "SiO2 = td.Medium(permittivity=SiO2_n**2)\n",
+    "\n",
+    "# Define geometries and their structures\n",
+    "h_clad = 2.8\n",
+    "h_box = 2\n",
+    "h_wafer = 0.5\n",
+    "\n",
+    "w_wg = 0.5\n",
+    "h_wg = 0.22\n",
+    "couple_gap = 0.1\n",
+    "ring_radius = 5\n",
+    "\n",
+    "z_wafer = -h_box - h_wafer / 2\n",
+    "\n",
+    "y_wg = ring_radius + w_wg / 2 + couple_gap + w_wg / 2\n",
+    "\n",
+    "waveguide_top = td.Structure(\n",
+    "    geometry=td.Box(\n",
+    "        center=[0, y_wg, 0],\n",
+    "        size=[td.inf, w_wg, h_wg],\n",
+    "    ),\n",
+    "    medium=Si,\n",
+    ")\n",
+    "\n",
+    "waveguide_bottom = td.Structure(\n",
+    "    geometry=td.Box(\n",
+    "        center=[0, -y_wg, 0],\n",
+    "        size=[td.inf, w_wg, h_wg],\n",
+    "    ),\n",
+    "    medium=Si,\n",
+    ")\n",
+    "\n",
+    "wg_ring_geo = td.Cylinder(\n",
+    "    center=[0, 0, 0], axis=2, radius=ring_radius + w_wg / 2.0, length=h_wg\n",
+    ") - td.Cylinder(center=[0, 0, 0], axis=2, radius=ring_radius - w_wg / 2.0, length=w_wg * 1.5)\n",
+    "\n",
+    "wg_ring = td.Structure(geometry=wg_ring_geo, medium=Si)\n",
+    "\n",
+    "x_buffer = 2\n",
+    "y_buffer = 1\n",
+    "z_buffer = 1\n",
+    "\n",
+    "z_sim = (h_clad - h_box - h_wafer) / 2\n",
+    "h_sim = 3\n",
+    "l_sim = 2 * ring_radius + 2 * x_buffer\n",
+    "w_sim = 2 * ring_radius + 4 * y_buffer\n",
+    "\n",
+    "# Create Mode Source\n",
+    "wg_insert_x = ring_radius + 0.9 * x_buffer\n",
+    "mode_plane = td.Box(\n",
+    "    center=[-wg_insert_x, y_wg, 0],\n",
+    "    size=[0, 2, 2],\n",
+    ")\n",
+    "mode_source = td.ModeSource(\n",
+    "    size=mode_plane.size,\n",
+    "    center=mode_plane.center,\n",
+    "    source_time=td.GaussianPulse(freq0=freq0, fwidth=fwidth),\n",
+    "    mode_index=0,\n",
+    "    direction=\"+\",\n",
+    "    num_freqs=7,\n",
+    ")\n",
+    "\n",
+    "# Create monitor\n",
+    "through_mode_mnt = td.ModeMonitor(\n",
+    "    size=mode_plane.size,\n",
+    "    center=[wg_insert_x, y_wg, 0],\n",
+    "    freqs=freqs_ring,\n",
+    "    mode_spec=td.ModeSpec(num_modes=2),\n",
+    "    name=\"mode through\",\n",
+    ")\n",
+    "\n",
+    "# Create simulation\n",
+    "min_steps_per_wvl = 15\n",
+    "run_time = 8e-11\n",
+    "\n",
+    "sim_ring_3D = td.Simulation(\n",
+    "    size=[l_sim, w_sim, h_sim],\n",
+    "    center=(0, 0, 0),\n",
+    "    structures=[waveguide_top, waveguide_bottom, wg_ring],\n",
+    "    grid_spec=td.GridSpec.auto(min_steps_per_wvl=min_steps_per_wvl, wavelength=td.C_0 / freq0),\n",
+    "    sources=[mode_source],\n",
+    "    monitors=[through_mode_mnt],\n",
+    "    run_time=run_time,\n",
+    "    medium=SiO2,\n",
+    "    symmetry=(0, 0, 1),  # add symmetry to reduce cost\n",
+    ")\n",
+    "\n",
+    "# Visualize the simulation to check\n",
+    "sim_ring_3D.plot(z=0)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "20af0a05-dd59-49a6-8ae3-272ffdd3d61d",
+   "metadata": {},
+   "source": [
+    "Same as before, we'll calculate the variational effective indices at different input wavelengths, this time downsampled to every 10th wavelength."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "77c3ee34-8395-48db-8808-1f5b36cdf091",
+   "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\">13:30:10 EST </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\">Best weighted RMS error so far: 1.64e-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": [
-       "\u001b[2;36m13:30:10 EST\u001b[0m\u001b[2;36m \u001b[0mstatus = queued                                                    \n"
+       "Best weighted RMS error so far: 1.64e-05 \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[36m0:00:00\u001b[0m\n"
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      },
      "metadata": {},
@@ -627,2354 +791,7 @@
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      "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\"><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"
-    },
-    {
-     "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\">13:30:15 EST </span>status = preprocess                                                \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m13:30:15 EST\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\">13:30:18 EST </span>Maximum FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.025</span>. Use <span style=\"color: #008000; text-decoration-color: #008000\">'web.real_cost(task_id)'</span> to get\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>the billed FlexCredit cost after a simulation run.                 \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m13:30:18 EST\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.025\u001b[0m. 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\n",
-       "\u001b[2;36m             \u001b[0mthe billed FlexCredit 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"
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "deb25da4870f425a963bcaecd29bbc68",
-       "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\">13:30:23 EST </span>early shutoff detected at <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">32</span>%, exiting.                            \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m13:30:23 EST\u001b[0m\u001b[2;36m \u001b[0mearly shutoff detected at \u001b[1;36m32\u001b[0m%, exiting.                            \n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
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-      ],
-      "text/plain": []
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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\">\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\">             </span>status = success                                                   \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mstatus = success                                                   \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>View simulation result at                                          \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-329f73f4-e53d-4f75-ace2-c6c16f717e99\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-329f73f4-e53</span></a>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-329f73f4-e53d-4f75-ace2-c6c16f717e99\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">d-4f75-ace2-c6c16f717e99'</span></a><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">.</span>                                         \n",
-       "</pre>\n"
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-       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mView simulation result at                                          \n",
-       "\u001b[2;36m             \u001b[0m\u001b]8;id=654369;https://tidy3d.simulation.cloud/workbench?taskId=fdve-329f73f4-e53d-4f75-ace2-c6c16f717e99\u001b\\\u001b[4;34m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=151246;https://tidy3d.simulation.cloud/workbench?taskId=fdve-329f73f4-e53d-4f75-ace2-c6c16f717e99\u001b\\\u001b[4;34mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=654369;https://tidy3d.simulation.cloud/workbench?taskId=fdve-329f73f4-e53d-4f75-ace2-c6c16f717e99\u001b\\\u001b[4;34m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=274211;https://tidy3d.simulation.cloud/workbench?taskId=fdve-329f73f4-e53d-4f75-ace2-c6c16f717e99\u001b\\\u001b[4;34mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=654369;https://tidy3d.simulation.cloud/workbench?taskId=fdve-329f73f4-e53d-4f75-ace2-c6c16f717e99\u001b\\\u001b[4;34m-329f73f4-e53\u001b[0m\u001b]8;;\u001b\\\n",
-       "\u001b[2;36m             \u001b[0m\u001b]8;id=654369;https://tidy3d.simulation.cloud/workbench?taskId=fdve-329f73f4-e53d-4f75-ace2-c6c16f717e99\u001b\\\u001b[4;34md-4f75-ace2-c6c16f717e99'\u001b[0m\u001b]8;;\u001b\\\u001b[4;34m.\u001b[0m                                         \n"
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-     "output_type": "display_data"
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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\">\n",
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-      ],
-      "text/plain": [
-       "\n"
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-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
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-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mloading simulation from simulation_data.hdf5                       \n"
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-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "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\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">13:30:24 EST </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'var eps'</span> with task_id                                \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-a22f27be-15ef-47df-9295-9517dd74ed5d'</span> and task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.  \n",
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-       "\u001b[2;36m13:30:24 EST\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'var eps'\u001b[0m with task_id                                \n",
-       "\u001b[2;36m             \u001b[0m\u001b[32m'fdve-a22f27be-15ef-47df-9295-9517dd74ed5d'\u001b[0m and task_type \u001b[32m'FDTD'\u001b[0m.  \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>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-a22f27be-15ef-47df-9295-9517dd74ed5d\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-a22f27be-15e</span></a>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-a22f27be-15ef-47df-9295-9517dd74ed5d\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">f-47df-9295-9517dd74ed5d'</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=952247;https://tidy3d.simulation.cloud/workbench?taskId=fdve-a22f27be-15ef-47df-9295-9517dd74ed5d\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=483630;https://tidy3d.simulation.cloud/workbench?taskId=fdve-a22f27be-15ef-47df-9295-9517dd74ed5d\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=952247;https://tidy3d.simulation.cloud/workbench?taskId=fdve-a22f27be-15ef-47df-9295-9517dd74ed5d\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=261785;https://tidy3d.simulation.cloud/workbench?taskId=fdve-a22f27be-15ef-47df-9295-9517dd74ed5d\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=952247;https://tidy3d.simulation.cloud/workbench?taskId=fdve-a22f27be-15ef-47df-9295-9517dd74ed5d\u001b\\\u001b[32m-a22f27be-15e\u001b[0m\u001b]8;;\u001b\\\n",
-       "\u001b[2;36m             \u001b[0m\u001b]8;id=952247;https://tidy3d.simulation.cloud/workbench?taskId=fdve-a22f27be-15ef-47df-9295-9517dd74ed5d\u001b\\\u001b[32mf-47df-9295-9517dd74ed5d'\u001b[0m\u001b]8;;\u001b\\.                                         \n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "363393fac36e4f7a958c3ba15a6e5694",
-       "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\">13:30:25 EST </span>status = queued                                                    \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m13:30:25 EST\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 <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"
-    },
-    {
-     "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\">13:30:37 EST </span>status = preprocess                                                \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m13:30:37 EST\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\">13:30:38 EST </span>Maximum FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.025</span>. Use <span style=\"color: #008000; text-decoration-color: #008000\">'web.real_cost(task_id)'</span> to get\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>the billed FlexCredit cost after a simulation run.                 \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m13:30:38 EST\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.025\u001b[0m. 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\n",
-       "\u001b[2;36m             \u001b[0mthe billed FlexCredit 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"
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "0d3dd6b319284ac8acc310f87db22870",
-       "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\">13:30:42 EST </span>early shutoff detected at <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">40</span>%, exiting.                            \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m13:30:42 EST\u001b[0m\u001b[2;36m \u001b[0mearly shutoff detected at \u001b[1;36m40\u001b[0m%, exiting.                            \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"
-    },
-    {
-     "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>status = postprocess                                               \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mstatus = postprocess                                               \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\">13:30:43 EST </span>status = success                                                   \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m13:30:43 EST\u001b[0m\u001b[2;36m \u001b[0mstatus = success                                                   \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\">             </span>View simulation result at                                          \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-a22f27be-15ef-47df-9295-9517dd74ed5d\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-a22f27be-15e</span></a>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-a22f27be-15ef-47df-9295-9517dd74ed5d\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">f-47df-9295-9517dd74ed5d'</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=518606;https://tidy3d.simulation.cloud/workbench?taskId=fdve-a22f27be-15ef-47df-9295-9517dd74ed5d\u001b\\\u001b[4;34m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=935109;https://tidy3d.simulation.cloud/workbench?taskId=fdve-a22f27be-15ef-47df-9295-9517dd74ed5d\u001b\\\u001b[4;34mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=518606;https://tidy3d.simulation.cloud/workbench?taskId=fdve-a22f27be-15ef-47df-9295-9517dd74ed5d\u001b\\\u001b[4;34m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=510209;https://tidy3d.simulation.cloud/workbench?taskId=fdve-a22f27be-15ef-47df-9295-9517dd74ed5d\u001b\\\u001b[4;34mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=518606;https://tidy3d.simulation.cloud/workbench?taskId=fdve-a22f27be-15ef-47df-9295-9517dd74ed5d\u001b\\\u001b[4;34m-a22f27be-15e\u001b[0m\u001b]8;;\u001b\\\n",
-       "\u001b[2;36m             \u001b[0m\u001b]8;id=518606;https://tidy3d.simulation.cloud/workbench?taskId=fdve-a22f27be-15ef-47df-9295-9517dd74ed5d\u001b\\\u001b[4;34mf-47df-9295-9517dd74ed5d'\u001b[0m\u001b]8;;\u001b\\\u001b[4;34m.\u001b[0m                                         \n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "40a00be5832141b18555a788f749e5b6",
-       "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\">13:30:44 EST </span>loading simulation from simulation_data.hdf5                       \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m13:30:44 EST\u001b[0m\u001b[2;36m \u001b[0mloading simulation from simulation_data.hdf5                       \n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "sim_2d_data = web.run(sim_2d, task_name=\"var eps\")\n",
-    "sim_1d_data = web.run(sim_1d, task_name=\"var eps\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "0d6294c1-5023-4c91-a3ef-b0de0b2297fd",
-   "metadata": {},
-   "source": [
-    "### Example 1 Result Comparison\n",
-    "\n",
-    "Now that both the 2D and 1D simulations have run, we will compare their results to see how representative the 1D simulation is. The results of the 1D approximation retain a reasonable qualitative fidelity to the 2D version."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 11,
-   "id": "0f120c35-9ae2-4a94-8c6c-96c56b1ffc17",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 1200x500 with 2 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "fig, ax = plt.subplots(1, 2, figsize=(12, 5))\n",
-    "\n",
-    "ax[0].plot(\n",
-    "    td.C_0 / sim_1d_data[\"R\"].flux.f,\n",
-    "    sim_1d_data[\"R\"].flux.data,\n",
-    "    label=\"1D\",\n",
-    "    color=\"red\",\n",
-    "    linestyle=\"--\",\n",
-    ")\n",
-    "ax[0].plot(td.C_0 / sim_2d_data[\"R\"].flux.f, sim_2d_data[\"R\"].flux.data, label=\"2D\", color=\"red\")\n",
-    "ax[0].set_title(\"2D vs 1D Reflection\")\n",
-    "ax[0].set_xlabel(\"Wavelength (µm)\")\n",
-    "ax[0].legend()\n",
-    "\n",
-    "ax[1].plot(\n",
-    "    td.C_0 / sim_1d_data[\"R\"].flux.f,\n",
-    "    sim_1d_data[\"T\"].flux.data,\n",
-    "    label=\"1D\",\n",
-    "    color=\"blue\",\n",
-    "    linestyle=\"--\",\n",
-    ")\n",
-    "ax[1].plot(td.C_0 / sim_2d_data[\"R\"].flux.f, sim_2d_data[\"T\"].flux.data, label=\"2D\", color=\"blue\")\n",
-    "ax[1].set_title(\"2D vs 1D Transmission\")\n",
-    "ax[1].set_xlabel(\"Wavelength (µm)\")\n",
-    "ax[1].legend()\n",
-    "\n",
-    "plt.show()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "35762762-3dcb-4f44-9ee6-eee60fff9ec2",
-   "metadata": {},
-   "source": [
-    "## Example 2: Ring Resonator"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "826c2941-9f86-4a72-acf8-11b70ef7bbe7",
-   "metadata": {},
-   "source": [
-    "We will now apply this same method to transform a 3D simulation into its 2D approximation. We will use a ring resonator and check the transmission of the through ports of both setups.<br><br>\n",
-    "First we quickly build the 3D simulation:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 12,
-   "id": "7eb43d86-4e2b-43b4-93ab-ce0ce0be6cc8",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "# Define wavelength/frequency ranges\n",
-    "lambda_beg = 1.5\n",
-    "lambda_end = 1.6\n",
-    "freq_beg = td.C_0 / lambda_end\n",
-    "freq_end = td.C_0 / lambda_beg\n",
-    "freq0 = (freq_beg + freq_end) / 2\n",
-    "fwidth = (freq_end - freq0) / 1.5\n",
-    "lambdas_ring = np.linspace(lambda_beg, lambda_end, 301)\n",
-    "freqs_ring = td.C_0 / lambdas_ring[::-1]\n",
-    "\n",
-    "# Refractive indices\n",
-    "Si_n = 3.4777\n",
-    "SiO2_n = 1.444\n",
-    "\n",
-    "# Materials used\n",
-    "Si = td.Medium(permittivity=Si_n**2)\n",
-    "SiO2 = td.Medium(permittivity=SiO2_n**2)\n",
-    "\n",
-    "# Define geometries and their structures\n",
-    "h_clad = 2.8\n",
-    "h_box = 2\n",
-    "h_wafer = 0.5\n",
-    "\n",
-    "w_wg = 0.5\n",
-    "h_wg = 0.22\n",
-    "couple_gap = 0.1\n",
-    "ring_radius = 5\n",
-    "\n",
-    "z_wafer = -h_box - h_wafer / 2\n",
-    "\n",
-    "y_wg = ring_radius + w_wg / 2 + couple_gap + w_wg / 2\n",
-    "\n",
-    "waveguide_top = td.Structure(\n",
-    "    geometry=td.Box(\n",
-    "        center=[0, y_wg, 0],\n",
-    "        size=[td.inf, w_wg, h_wg],\n",
-    "    ),\n",
-    "    medium=Si,\n",
-    ")\n",
-    "\n",
-    "waveguide_bottom = td.Structure(\n",
-    "    geometry=td.Box(\n",
-    "        center=[0, -y_wg, 0],\n",
-    "        size=[td.inf, w_wg, h_wg],\n",
-    "    ),\n",
-    "    medium=Si,\n",
-    ")\n",
-    "\n",
-    "wg_ring_geo = td.Cylinder(\n",
-    "    center=[0, 0, 0], axis=2, radius=ring_radius + w_wg / 2.0, length=h_wg\n",
-    ") - td.Cylinder(center=[0, 0, 0], axis=2, radius=ring_radius - w_wg / 2.0, length=w_wg * 1.5)\n",
-    "\n",
-    "wg_ring = td.Structure(geometry=wg_ring_geo, medium=Si)\n",
-    "\n",
-    "x_buffer = 2\n",
-    "y_buffer = 1\n",
-    "z_buffer = 1\n",
-    "\n",
-    "z_sim = (h_clad - h_box - h_wafer) / 2\n",
-    "h_sim = 3\n",
-    "l_sim = 2 * ring_radius + 2 * x_buffer\n",
-    "w_sim = 2 * ring_radius + 4 * y_buffer\n",
-    "\n",
-    "# Create Mode Source\n",
-    "wg_insert_x = ring_radius + 0.9 * x_buffer\n",
-    "mode_plane = td.Box(\n",
-    "    center=[-wg_insert_x, y_wg, 0],\n",
-    "    size=[0, 2, 2],\n",
-    ")\n",
-    "mode_source = td.ModeSource(\n",
-    "    size=mode_plane.size,\n",
-    "    center=mode_plane.center,\n",
-    "    source_time=td.GaussianPulse(freq0=freq0, fwidth=fwidth),\n",
-    "    mode_index=0,\n",
-    "    direction=\"+\",\n",
-    "    num_freqs=7,\n",
-    ")\n",
-    "\n",
-    "# Create monitor\n",
-    "through_mode_mnt = td.ModeMonitor(\n",
-    "    size=mode_plane.size,\n",
-    "    center=[wg_insert_x, y_wg, 0],\n",
-    "    freqs=freqs_ring,\n",
-    "    mode_spec=td.ModeSpec(num_modes=2),\n",
-    "    name=\"mode through\",\n",
-    ")\n",
-    "\n",
-    "# Create simulation\n",
-    "min_steps_per_wvl = 15\n",
-    "run_time = 8e-11\n",
-    "\n",
-    "sim_ring_3D = td.Simulation(\n",
-    "    size=[l_sim, w_sim, h_sim],\n",
-    "    center=(0, 0, 0),\n",
-    "    structures=[waveguide_top, waveguide_bottom, wg_ring],\n",
-    "    grid_spec=td.GridSpec.auto(min_steps_per_wvl=min_steps_per_wvl, wavelength=td.C_0 / freq0),\n",
-    "    sources=[mode_source],\n",
-    "    monitors=[through_mode_mnt],\n",
-    "    run_time=run_time,\n",
-    "    medium=SiO2,\n",
-    "    symmetry=(0, 0, 1),  # add symmetry to reduce cost\n",
-    ")\n",
-    "\n",
-    "# Visualize the simulation to check\n",
-    "sim_ring_3D.plot(z=0)\n",
-    "plt.show()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "20af0a05-dd59-49a6-8ae3-272ffdd3d61d",
-   "metadata": {},
-   "source": [
-    "Same as before, we'll calculate the variational effective indices at different input wavelengths, this time downsampled to every 10th wavelength."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 13,
-   "id": "77c3ee34-8395-48db-8808-1f5b36cdf091",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "03d579067cd74813ad468fbaea1ffb86",
-       "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": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 300x300 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "reference_point = (0, -y_wg)\n",
-    "waveguide_point = (0, -y_wg)\n",
-    "other_point = (0, 0)\n",
-    "\n",
-    "# Downsample wavelengths to speed up the calculation\n",
-    "spectrum = lambdas_ring[::10]\n",
-    "ring_waveguide_medium = approximate_material(\n",
-    "    sim_ring_3D, waveguide_point, reference_point, spectrum, plot=True\n",
-    ")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 14,
-   "id": "4ade732a-6ce6-4847-a5ba-c5923834d667",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "93ca9f9037d9429eb14f7ecea5f776d9",
-       "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"
-    }
-   ],
-   "source": [
-    "ring_background_medium = approximate_material(sim_ring_3D, other_point, reference_point, spectrum)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "bbda4057-4feb-4350-8de7-ac3d9668ba7f",
-   "metadata": {},
-   "source": [
-    "As before, we create a 2D copy of the simulation and replace the mediums with those that we just calculated."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 15,
-   "id": "4a0245f6-7372-4315-a919-1bfd49ea192f",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Note: removed symmetry, as it is incompatible with the variational approximation method.\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 2 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "sim_ring_2D = create_2D_sim(sim_ring_3D, [ring_waveguide_medium, ring_background_medium])\n",
-    "\n",
-    "sim_ring_2D.plot_eps(z=0, freq=freq0)\n",
-    "plt.show()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 16,
-   "id": "71d391f2-3935-44a3-9a8d-1cf4abb4e219",
-   "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\">13:31:11 EST </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'2.5D FDTD ring resonator 2D'</span> with task_id            \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-f748f5dd-5884-4d3e-be98-4eefe1f9df95'</span> and task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.  \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m13:31:11 EST\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'2.5D FDTD ring resonator 2D'\u001b[0m with task_id            \n",
-       "\u001b[2;36m             \u001b[0m\u001b[32m'fdve-f748f5dd-5884-4d3e-be98-4eefe1f9df95'\u001b[0m and task_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-f748f5dd-5884-4d3e-be98-4eefe1f9df95\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-f748f5dd-588</span></a>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-f748f5dd-5884-4d3e-be98-4eefe1f9df95\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">4-4d3e-be98-4eefe1f9df95'</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=114736;https://tidy3d.simulation.cloud/workbench?taskId=fdve-f748f5dd-5884-4d3e-be98-4eefe1f9df95\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=24428;https://tidy3d.simulation.cloud/workbench?taskId=fdve-f748f5dd-5884-4d3e-be98-4eefe1f9df95\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=114736;https://tidy3d.simulation.cloud/workbench?taskId=fdve-f748f5dd-5884-4d3e-be98-4eefe1f9df95\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=201938;https://tidy3d.simulation.cloud/workbench?taskId=fdve-f748f5dd-5884-4d3e-be98-4eefe1f9df95\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=114736;https://tidy3d.simulation.cloud/workbench?taskId=fdve-f748f5dd-5884-4d3e-be98-4eefe1f9df95\u001b\\\u001b[32m-f748f5dd-588\u001b[0m\u001b]8;;\u001b\\\n",
-       "\u001b[2;36m             \u001b[0m\u001b]8;id=114736;https://tidy3d.simulation.cloud/workbench?taskId=fdve-f748f5dd-5884-4d3e-be98-4eefe1f9df95\u001b\\\u001b[32m4-4d3e-be98-4eefe1f9df95'\u001b[0m\u001b]8;;\u001b\\.                                         \n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "7fde33b614374403b37fd1d5478bdaa2",
-       "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\">13:31:13 EST </span>status = queued                                                    \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m13:31:13 EST\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 <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"
-    },
-    {
-     "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\">13:31:26 EST </span>status = preprocess                                                \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m13:31:26 EST\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\">13:31:29 EST </span>Maximum FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.203</span>. Use <span style=\"color: #008000; text-decoration-color: #008000\">'web.real_cost(task_id)'</span> to get\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>the billed FlexCredit cost after a simulation run.                 \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m13:31:29 EST\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.203\u001b[0m. 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\n",
-       "\u001b[2;36m             \u001b[0mthe billed FlexCredit 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\">13:31:30 EST </span>running solver                                                     \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m13:31:30 EST\u001b[0m\u001b[2;36m \u001b[0mrunning solver                                                     \n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "36072bb2e2874ac8b75a30f762b33b7c",
-       "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\">13:32:16 EST </span>early shutoff detected at <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">24</span>%, exiting.                            \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m13:32:16 EST\u001b[0m\u001b[2;36m \u001b[0mearly shutoff detected at \u001b[1;36m24\u001b[0m%, exiting.                            \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"
-    },
-    {
-     "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>status = postprocess                                               \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mstatus = postprocess                                               \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\">             </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"
-    },
-    {
-     "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\">             </span>View simulation result at                                          \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-f748f5dd-5884-4d3e-be98-4eefe1f9df95\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-f748f5dd-588</span></a>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-f748f5dd-5884-4d3e-be98-4eefe1f9df95\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">4-4d3e-be98-4eefe1f9df95'</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=123452;https://tidy3d.simulation.cloud/workbench?taskId=fdve-f748f5dd-5884-4d3e-be98-4eefe1f9df95\u001b\\\u001b[4;34m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=625074;https://tidy3d.simulation.cloud/workbench?taskId=fdve-f748f5dd-5884-4d3e-be98-4eefe1f9df95\u001b\\\u001b[4;34mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=123452;https://tidy3d.simulation.cloud/workbench?taskId=fdve-f748f5dd-5884-4d3e-be98-4eefe1f9df95\u001b\\\u001b[4;34m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=838700;https://tidy3d.simulation.cloud/workbench?taskId=fdve-f748f5dd-5884-4d3e-be98-4eefe1f9df95\u001b\\\u001b[4;34mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=123452;https://tidy3d.simulation.cloud/workbench?taskId=fdve-f748f5dd-5884-4d3e-be98-4eefe1f9df95\u001b\\\u001b[4;34m-f748f5dd-588\u001b[0m\u001b]8;;\u001b\\\n",
-       "\u001b[2;36m             \u001b[0m\u001b]8;id=123452;https://tidy3d.simulation.cloud/workbench?taskId=fdve-f748f5dd-5884-4d3e-be98-4eefe1f9df95\u001b\\\u001b[4;34m4-4d3e-be98-4eefe1f9df95'\u001b[0m\u001b]8;;\u001b\\\u001b[4;34m.\u001b[0m                                         \n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "2d72798360574db685e659afa577bd61",
-       "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\">13:32:17 EST </span>loading simulation from simulation_data.hdf5                       \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m13:32:17 EST\u001b[0m\u001b[2;36m \u001b[0mloading simulation from simulation_data.hdf5                       \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>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'2.5D FDTD ring resonator 3D'</span> with task_id            \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-0f179763-63fa-42ff-9c25-6c48fae8cff1'</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'2.5D FDTD ring resonator 3D'\u001b[0m with task_id            \n",
-       "\u001b[2;36m             \u001b[0m\u001b[32m'fdve-0f179763-63fa-42ff-9c25-6c48fae8cff1'\u001b[0m and task_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-0f179763-63fa-42ff-9c25-6c48fae8cff1\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-0f179763-63f</span></a>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-0f179763-63fa-42ff-9c25-6c48fae8cff1\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">a-42ff-9c25-6c48fae8cff1'</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=166270;https://tidy3d.simulation.cloud/workbench?taskId=fdve-0f179763-63fa-42ff-9c25-6c48fae8cff1\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=636363;https://tidy3d.simulation.cloud/workbench?taskId=fdve-0f179763-63fa-42ff-9c25-6c48fae8cff1\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=166270;https://tidy3d.simulation.cloud/workbench?taskId=fdve-0f179763-63fa-42ff-9c25-6c48fae8cff1\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=964428;https://tidy3d.simulation.cloud/workbench?taskId=fdve-0f179763-63fa-42ff-9c25-6c48fae8cff1\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=166270;https://tidy3d.simulation.cloud/workbench?taskId=fdve-0f179763-63fa-42ff-9c25-6c48fae8cff1\u001b\\\u001b[32m-0f179763-63f\u001b[0m\u001b]8;;\u001b\\\n",
-       "\u001b[2;36m             \u001b[0m\u001b]8;id=166270;https://tidy3d.simulation.cloud/workbench?taskId=fdve-0f179763-63fa-42ff-9c25-6c48fae8cff1\u001b\\\u001b[32ma-42ff-9c25-6c48fae8cff1'\u001b[0m\u001b]8;;\u001b\\.                                         \n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "9f3a2c093e8b4ca9b629d601c528c153",
-       "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\">13:32:19 EST </span>status = queued                                                    \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m13:32:19 EST\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 <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"
-    },
-    {
-     "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\">13:32:47 EST </span>status = preprocess                                                \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m13:32:47 EST\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\">13:32:49 EST </span>Maximum FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">4.011</span>. Use <span style=\"color: #008000; text-decoration-color: #008000\">'web.real_cost(task_id)'</span> to get\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>the billed FlexCredit cost after a simulation run.                 \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m13:32:49 EST\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m4.011\u001b[0m. 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\n",
-       "\u001b[2;36m             \u001b[0mthe billed FlexCredit 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"
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "95ab9cfb962448cd898aa92132f8376a",
-       "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\">14:01:38 EST </span>early shutoff detected at <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">56</span>%, exiting.                            \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m14:01:38 EST\u001b[0m\u001b[2;36m \u001b[0mearly shutoff detected at \u001b[1;36m56\u001b[0m%, exiting.                            \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"
-    },
-    {
-     "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>status = postprocess                                               \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mstatus = postprocess                                               \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\">14:01:40 EST </span>status = success                                                   \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m14:01:40 EST\u001b[0m\u001b[2;36m \u001b[0mstatus = success                                                   \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\">             </span>View simulation result at                                          \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-0f179763-63fa-42ff-9c25-6c48fae8cff1\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-0f179763-63f</span></a>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-0f179763-63fa-42ff-9c25-6c48fae8cff1\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">a-42ff-9c25-6c48fae8cff1'</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=682546;https://tidy3d.simulation.cloud/workbench?taskId=fdve-0f179763-63fa-42ff-9c25-6c48fae8cff1\u001b\\\u001b[4;34m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=367402;https://tidy3d.simulation.cloud/workbench?taskId=fdve-0f179763-63fa-42ff-9c25-6c48fae8cff1\u001b\\\u001b[4;34mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=682546;https://tidy3d.simulation.cloud/workbench?taskId=fdve-0f179763-63fa-42ff-9c25-6c48fae8cff1\u001b\\\u001b[4;34m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=643068;https://tidy3d.simulation.cloud/workbench?taskId=fdve-0f179763-63fa-42ff-9c25-6c48fae8cff1\u001b\\\u001b[4;34mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=682546;https://tidy3d.simulation.cloud/workbench?taskId=fdve-0f179763-63fa-42ff-9c25-6c48fae8cff1\u001b\\\u001b[4;34m-0f179763-63f\u001b[0m\u001b]8;;\u001b\\\n",
-       "\u001b[2;36m             \u001b[0m\u001b]8;id=682546;https://tidy3d.simulation.cloud/workbench?taskId=fdve-0f179763-63fa-42ff-9c25-6c48fae8cff1\u001b\\\u001b[4;34ma-42ff-9c25-6c48fae8cff1'\u001b[0m\u001b]8;;\u001b\\\u001b[4;34m.\u001b[0m                                         \n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "f00c12893afe49e1bde139d45324c8e3",
-       "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\">14:01:41 EST </span>loading simulation from simulation_data.hdf5                       \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m14:01:41 EST\u001b[0m\u001b[2;36m \u001b[0mloading simulation from simulation_data.hdf5                       \n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "sim_data_2D = web.run(sim_ring_2D, task_name=\"2.5D FDTD ring resonator 2D\")\n",
-    "sim_data_3D = web.run(sim_ring_3D, task_name=\"2.5D FDTD ring resonator 3D\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "3dc98bc3-bbcf-4a4b-8d86-7fab1b9bd0a4",
-   "metadata": {},
-   "source": [
-    "### Example 2 Result Comparison\n",
-    "\n",
-    "We will compare the results of our 2D and 3D simulations to see how representative our approximation is. As one can see, the resonant behavior of this setup is well-approximated, especially near the central frequency. The depth of the peaks is lower in the 2D simulation because the 3D simulation takes into account vertical coupling. Toward the ends of the spectrum, there is more error in the free spectral range and resonance frequencies, although this is still well within 1% of the resonant wavelength, as we show for the first resonance. However, the next example will show that this method will not always be a good approximation."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 17,
-   "id": "3e23ed0d-1a5f-4a7a-bfd2-ec7a5e3b975e",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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oOAA2ffp0xTGxD5544gnF8e+++44NGDCAxcTEsMTERDZ27Fi2c+fOoGtqHU+MMfbRRx+xgQMHsri4OBYXF8c6duzIpk+fznbv3l3tbxIJFQrepUuXoHMnT57MWrZsqTh26NAhNm7cOBYbG8saN27MbrvtNrZy5cqgazLG2ObNm9nll1/OGjVqxFwuF2vZsiWbMGECW716NWPMn0rgo48+Unzu8OHDLDExkY0ZM0bz7zKCsrIyNmfOHJaRkcFcLhc777zz2MqVK2u1DUT9hmPMRO86giAInaxYsQKXXHIJtm7diq5du9Z1cwiCiEDqPr0oQRCEjDVr1uDqq68mwYYgiLAhzQ1BEEQtoiUsOjU1laqBE0QNIIdigiCIWkRLWHRNkhoSBEGaG4IgiFolNzdXtYq8nF69eklZgQmC0A8JNwRBEARBWApyKCYIgiAIwlI0OJ8bnudx7NgxJCQkhF2hmSAIgiCI2oUxhqKiIjRt2rTaxKUNTrg5duwYpecmCIIgiAjlyJEjaN68eZXnNDjhJiEhAYDQOfKiawRBEARB1F8KCwuRlZUlreNV0eCEG9EUlZiYSMINQRAEQUQYWlxKyKGYIAiCIAhLQcINQRAEQRCWgoQbgiAIgiAsBQk3BEEQBEFYChJuCIIgCIKwFCTcEARBEARhKUi4IQiCIAjCUpBwQxAEQRCEpSDhhiAIgiAIS0HCDUEQBEEQlqJOhZsff/wRY8eORdOmTcFxHD799NNqP5OTk4Nzzz0XLpcLbdu2xbJly0xvJ0EQBEEQkUOdCjclJSXo3r07XnzxRU3nHzhwABdffDGGDRuGLVu2YNasWbjpppuwatUqk1tKEARBEESkUKeFM0ePHo3Ro0drPn/x4sVo1aoVnnrqKQBAp06d8NNPP+GZZ57BqFGjzGomQRAEQTQseC/grQR4D8BXAl7fM+MBziY8wPn/5jjfww7YogC7Q3jUERFVFXz9+vUYMWKE4tioUaMwa9askJ9xu91wu93S68LCQrOapx3GgLKzQOEx4VF0DCjLBzzlQGWZ8OwpBzxuYXAxr2+Aic8e4RqAMNAYL7zn/wLhfcYLf0sDkPOfz5gwAG1RvuPMP2jtDsDuFI7zXuH77U7AEQNExfgGte+6jhjAGQs44wFnHOBKBGJTgZgUILkFkNhMuI5ZuIuAgr+BgqNA4VGhH92FQHmh0IfeCsDjBvOUg/d6wLwe4fcw4RcwxgBvBTivG5y3Qqg2y9nBOKHPOOaFjfeA4yuF7+PsgM0uPHPw/58AQJQLiIoW3hP/n3iP0K9R0UL/RLlk/48BfeuIARxxvgnB9/9hdwHx6UB8GpCQITzH+56NnDgqy4HTfwn9WF7o68MCf1+6i4SH+HvAwPO89GCMF/pS9gzGwMSxJo5FxoMDfM/+15zvfY4x4RkMjLODs9nB2aNgs9vBweb7fq+v73j/JCqOZfFv3uO/d5zxwriMTgRcCf6/o6KFvo+KFv5fYhsBTXsIY7cmMAaUnhHGY9Fx4V5XPM74//ZUCP0ifs73N894odukPgSY775m0rm+8cuY9J54HSY2BYAwUCG7D/33I8dx4DjAxtl8byvPtdlssHOcvwqz/Bo2G+BKAmKSfY8UoQ/F8RqfLjxiGwn3TDiUngHytgnP4vzorfDNjxWA1y3Mk+L4dPvGqjRmC4HKUgAcmLQI28DZogB7FGB3grdFwYMoVDA7KlgUmC0KNhsHOwfYOQaO8fB6vfDyPHivF4znwYGHnWOwg4eN841XngfjvWCMF8YxxwF2Bzi7E4hygbc54eWiUAEHKhAF3uZAlDMaDmc0nK5ouFzCePRwDng4ByrhgNfmQGJcHGJiYoSx6rsW7E4gqRmQ1gVwROvrU8aAU38BJ/4ATu0FTu8Fio8D5fnCPS8+xHktXJr1Bm5eXbNr1ICIEm7y8vKQnp6uOJaeno7CwkKUlZUJAyCAhQsXYsGCBaa3rcTtwb6TxThdXIHTJRU4U+JGaYUXZZVe2Mry0fHkSmQXbUKGex+SPafgYu7qL2oFHHFA47ZAo3ZAs15Al/FAYlPdl3F7vDiWX44Tx48hevt7SMn9AY2LdyPWW6Tp8xyAMKfX+ktcE6D1UKDHtUCbYfo/z/PArs+AzW8DB34UFg0d2GDRiITsQUCfaUCnsdoFc94LbHkX2P4BcGSDsPjWAEv1K2cXNjnNewNdrwQ6jK6+X0/uBlbeBez73rhmhDhuA+D0PQynUv9HXDrO9XIOHG1xKWxD5iCrdaeqT64oBX7+r3C/FxzW3zDAtxm2SRsWJm5SVPjrVDnahfcthhBRwk04zJ07F7Nnz5ZeFxYWIisry/Dv2Xa0ANe8+oviWBzK8O+oTzHFvhLRXPAoP80SkMdSkctSUYB4lDMnyuFEORwoZ0644YAHUfDABh42eGCHFzZ4mc23t+Ug7CFs8EI4BgAcGHjf++Ix8RMMHBxRdmQkRaNpogtNkxxonuREu4xkuKLsPi2QR9gNAT4thU1Y+CrLhF2QuCthTJjEK0qAimLAXSxI/GVngdJTghagsgTI3So8dnwIrLob6H0DMGI+EJ2k2peMMezKLcL6/afx6/7T2HIkHyeLynCL/XP8O+pTxHDKRbiAxeIYa4xjrBHyEY9CFosixMDt68MKCLslD+zwMmVfAYDHt5tysygwX18JDx48bKiEHR4miEY2Tjhu9/VwJaLgZTbYOAYnKuFCJWzgff9Xdnh8Z8ZwFchOAFqnRKFpagKapyageeMExDgdgoahslTo34oS4bWo4q0sF3ZV0uOE8Mx7gJKTwPb/CY9OY4FLngPiGmkbsCf3wPPBFESd/EM6lM/icIil+/ovFkW+fizyvS5GNDzMDh42Qevle4bNBhsn9JjNxoFxHGySmtrm0w7YABsn9CoPeMGBZxy8DMIYZoCHATwDeGYD79NY8F6Por89sINnNuHzsCEKXkRxXuEZXjjghR1eeGEHz9nRLDUOnRvZ0S4ZaJXgRTJX5tNIFSk0e/C6gfwjwNkDwMG1wqPdSGDcC0BCeohO9FFRAnw8DfjzS+XxuDSwhAwU2RJxtDwa+4odOFzmwhk+DgWIRwGLQ5lvKfNrWjjF2OQgaE9snA12GwfOxsHG+R42G2w2wG6zg+M44X3fs6BxkckQjPk0QTxE/RAHwOPlUeHxwl3phZdnPk2RXztUVukNWrzE11HwIhGlSOaKkYgSpHDFSOWKkG4rQNOoQqRxBYjz5INjXmExLTgM/PEx0PZC4B+vCdoeNQ7/CrxxiV/YTmklbIiion3aY5dM6yZoMfYX2bDpOI9dZxjyyh04w8egmMWgGDEoZUIf+7UsPByy8RIFD5JcQLPEKDSJsSMKlXBXelFcwaO4ggfjbIh3ORAX7UR8tBOx0Q54eA4llQwlvnPcXoa4aBeSYp1IiHaCcTaUV3hQVFqK4pJSVJSXwWnzIsHuRYKTIcnBw8ZXoLy8HO7yMrjd5WCeCjg5D1ycB7E2D6JtXjjhgdfjhgseOOCBE5VwwgMXV4lWXC4aoQgtD32Iwje+wk2pL2LskPMxtltT2GwBotzxP4B3rwIKjgivo6KBjK7CprNRGyCpORCdLMzJ4sMRI8z/NodfI8pxOFFYju92ncC3O/Owbt9pVHiEMSKuMXbf/dq9cRLeq/rOMZWIEm4yMjJw/PhxxbHjx48jMTFRVWsDAC6XCy6XHlk4PJokOJGZFI3UOCdS45xo5ziN6UfnoVHF3wCAk3HtcSDjIhSkdoUnIQssIQNOVyxinHakOGxoYhPUwhw4v+lS5W+eMVR6GCq8XlR6GSq9PCo8PIrKPSgoq0RBWSXySyulvwvL/H8XlFWirNILVAA46XuI/RRlw8C2jTHqnAyM6ZqJeJcBQ8NbCZw9CJzaI+zE/voGOLwe+H0JsD8HuGEVEN9EOn1XbiE+33oMX247hiNnyqTjUfDgFcezuNC+CQBw0NEW25pcjIK0PqhIyEJUTBKiHTZEO+yId9jR2GFHjMOOaIfN92yHy/e3M8om9aWwSEBSuTPG4OGFRcBu48ABqOR5lFfwKK30gJfN8aVuD/LLKlFQWolKLw8Pz1Dh4XG2tAIni904WSQ88ksrcLxQ+Bv5EB4HfL/LxmFYxzRM7Z+N/uc01t6vPC8IkKf2CALj70uBXV8AZw4CU76o0qzi5RnWr/kSPX/6F+JYMQpZLJZ5R+Iz7wDsY02RnhiNlqlxyEyORlqCC00SXGiVEI2UOCfinEJfxjrtiHVGIcZpl/rULBhjcHt4lFZ4UeL2CM8VHpS6fc8VHpwtqcSJIjdOFJYLz0XlyCsoR2G5J2icd85MxITezXFN3xaCMB9I/hFg41Jhh/vXN8Dblwvj1BUfupGiYGN3AkP+A3Qah6KYZljyyzG8t+EwjhcqtbRNElzo0jQRmUnRaBzvkh4psQ4kxjiQFONAQnQU4l1RiLLXrQ7H4+WRX1aJ08UVKKv0osLD++cctwcHT5Vg/8libD9Vgv0nS1Dk9pkyfD/ZDi+u6BiNO3vbkPr3GmDDK8Deb4E1jwBjHg/+QsaAb+4RBJvsQcC454HU1iHbd6akAnd/vB0r/8gLes/GAW2axOPC1qno06oRujRNRHpiNCo8vDSWXFE2JMc6kBxrit5GFxUeHhwHOAL+z4vdHuw/WYx9J4ux63QpTha5hU2Al0dm0VaMO/YMWnv2Y9KpZzBp+V14/acDeGh8V3Rt7ts8etzAhzcKgk1SFjB8PtDxYsGdQCMeL48vtxzDuxsOY8OBM4r3WqTGYVC7xujaLAlNk2OQGONAlI1DnBFrSA3gGGOs+tPMh+M4fPLJJxg/fnzIc+68806sWLEC27dvl45NnDgRZ86cwcqVKzV9T2FhIZKSklBQUIDExMSaNludgr+BJSMFm3tSFjDmCaD9Reb6nmikvNKLo2fLsPeEcLPsPVGMDQfO4O98vzAR67RjUr9s3DKkDZJiDXYI2/8D8OmtQt9k9gCmrsDhIg4PfbUT3+z0C64xDjv6tk5F31aNMLbwPTTf9ARYVDS4i58SzDD1oC/1cKKoHH8cK8SOowXY/ncBdvxdgGMFftPF8I5puH9cF2Slap9wJHK3AW//Ayg5AbToD0xdodo/247m447lv+H1on+iGXcav/Pt8Wyj+Ti/awf0b9sYnTISEeO0jvHuWH4ZNh0+i42HzmLTobPYcawQXp+EmpUag8cu74b+bUMIlSf+BN4YK/Rp50uBK99QH3On9wH/PRcAJ/R7y/5Yv+80Zry7CadLBM1DvCsKF3RMw8gu6ejVMgUZidF+HxYLwRhDSYUXp4rc2JlbiC+2HsOqP/LAMyDBFYX/jO6Ia1P/gu3dfwiC4MzNgsZAzp8rgOXXAI5YYOaWKrVmR8+WYtLrG7D/ZAnsNg7Xn98SI7uko2WjOCRGRyHOGRWswbAip/aCLeoPzuvGf/gZ+KCiP2wcMG1wG/zfyPZwfL8AWPesYMa+9RcgTsdGCkBuQRlmvrcZvx08Kx3rnpWMkZ3TcWHndLRLi6+18axn/a5T4aa4uBh79+4FAPTs2RNPP/00hg0bhtTUVLRo0QJz587F33//jTfffBOAEAp+zjnnYPr06bjhhhvw/fffY+bMmfjqq680R0vVinDz2Qxg81uCym/y52H5mNQmjDHsPl6Eb/44jk83/439p0oACDvM/17TE+e31mjq0MqpvcDrI4HS09jXbQ7Gb+2DIrcHdhuHEZ3SMK57M1zQMU1YaE/tBRb1F8wGl70CdL/K2LbUIXuOF+Gt9Yfw3obD8PAMsU475l3SGVf3aaH/Ysd3Aq+NEMyA138CtLlA8fYnm4/izg+34yqsxIOOZSh2NsbZG35FVoa+iS6SOVtSgc+3HsOLa/biRJEbNg64e0wn3DQohGbg8K/AsouFCJEbvwWy+gSf8829gpan3Ujg2v/h863H8H8fbEGll6F14zjMurA9RnVJV9cSNQB25Rbiro+3Y+uRfABA/9apeMO2AI6j64FeU4Gxzyo/8MpQ4NhmYOBswXQdgr/zy3Dlop9xrKAcTZOi8erk3ujSVN3M3SD4/mHgx8fhbj0SdzjuxudbjwEABma58Nbpq8DxHuDqdwWNjQ5OFJZjzPM/4VSxGwmuKNw0qDUmnNccmUnqlhKz0bN+16nO8/fff0fPnj3Rs2dPAMDs2bPRs2dPzJs3DwCQm5uLw4f9jk+tWrXCV199hW+//Rbdu3fHU089hddee61+hYHnHwG2+iyN41+q94INIGjNOmYkYubwdlj9f0Pw2qTeaNMkDieL3Jj46i/4ZPNRY7+wcVvgwgcBAK6ty1DirkCvlilYedsgvHx9b1zcLdOvQVj3rCDYtLkA6DbB2HbUMe3TE/Dg+HOwctZg9MlORWmFF3d9vB3zPtsBnte550jvDPS8Tvh7vTJv1JrdJzDnf9vAecvxf9FfAADiR9zVoAQbAEiJc2Jy/2zk3DEU/zi3OXgGPPTVLiz56YD6B1r0BTqPE/7e/XXw+5XlwOZ3hL9734Cdxwox539bUellGNu9KVbcNgjjujdtsIINAHTKTMTHt/THgnFdEOu04+f9Z/B/J33pP7b/zx/hBQjm1txtwt+9p4a85uliN65/7VccKyhH6yZx+PCW/g1bsAEEZ20ArtI8PH9NTyy69lwkuKJQeHQnON4DFp+hW7BhjOHuT7bjVLEbbdPi8eXMgbhtRLs6E2z0UqfCzdChQ/0ObLKHmHV42bJlyMnJCfrM5s2b4Xa7sW/fPkyZMqXW210lPz8vOHu2Gqy+06vncByHEZ3T8cW/B2J8j6bgGTDnf9uwckewTbsm/Bw9BGdZPJpzp3Bvu8N47+bz0S49IfjEg2uF5/NvjThTlFbapsVj+bTzMWdkewDAm+sPYdEP+/Rf6PxbAHDA3u+AE7sAAIdPl2LGO5vg5Rlub38Kyd7TQij5uZMM/AWRRawzCk9e2Q2zLxT6+8Evd2Lljlz1k9v7FuI9Kmbv/WuEsO7E5ihteQFmvLsJFR4ewzum4bmreiDa0XCFGjl2G4fJ/bPx6fQBaJEai+8KfKaoimLBsVuk5KQQus/ZgAT1TSFjDHd8uA37T5WgWXIM3rmpL5omR8ZiayoJmcJzkTCOR3fNxIe39EcnhzBvH7E3D/XJkHy65W98t+sEnHYbXpx4Llo2ijOsubWBpSIO6wV/fiU8959Zt+2oIbHOKDw9oQeu6NUcXp5hzv+2KvxyakJheSVmffwn3vcOBQBMdeWoO6UW/C04JHM2IKuvId9dX7HZOMy4oB0evbwrAOCpb3bjt4NnqvlUAKmtBN8uANi9AgCw4Is/UFLhxXnZKbipMy+81+xcIcqkAcNxHP59QVtM7tcSAHDfZ3+g2K2S16PtcCGU+cRO4Owh5Xv5vsiTZj3xzgbBnJuRGI0nruzeMHw9dNI+PQFv3tAH3qhYFDNfbpbiE/4TfAsz4tKEHDQqfLktF9//KSy4r085L2K0CKYjWghKTvpyJwEdMhJwY0chSvfHM8lCUIMOFuUIG6yZw9uiQ4bKxrOeQ8KNkZScBgqF6CgrLMY2G4fH/tENvVumoNjtwZ0fboMRLlpPrNyNE0VubEkYCgDgcreon3honfCc2V1IutYAuOq8LFzWsxl4Btz/+R/6+7tpD+H57EF8t/M4Vv95Ag47h4WXd0PUWZ/5pYrok4YEx3G4++JOyG4Ui5NFbry4Zm/wSbGpQIvzhb8DtTfFwq7YG5eO19cJfXv7he2QGlf3kTf1lezGcbj9wvY4wZIBAJ5CmcZMFG4SMlQ/W1rhwYIvhNQFtw5rE5ELrmnENhJCtgFpXAJAe7vQp3v5pqoRZaHYnVeEPceL4bTbcH2/bCNbWmuQcGMkeVuF59TWllmM7TYOj1/RDa4oG37aewrf7jxe/Yeq4MCpErz9q7ADnjpuuHCw5ISQIycQUbhpOaBG3xlJcByHeZd0hivKhj+OFSoiFDSR7HNGPnsIL/gW6xsHtkbbtHjgjM/U1aiNgS2ObFxRdtx7cWcAwJK1B9R3t+1GCs+iiVSkWLgXdhfHILegHI3jXbi0RzMzm2sJbhzYCmdtQrqCg4dk/k6icBPCT/HHPSdxqrgCzZJjcMtQGsMKOM5vmpILjKf+AgDsY03x1bZjmi/3pe/cwe2bICmm7koo1AQSboxEdIbL6Fa37TCY1k3iMXVAKwDAsp8P1uhaH/x+BIwBQzs0Qd9Orf05Wc6qXPdgwxNuAMHx9fJzhUVy6boQzq6hSBbMLBWnD2HLkXzYbRxuHCj83+G0T7hJpYVBzvBOaejWPAkVXh7f7FTZ3YrhymX5yuNFgnDz/d/CNDp1QDb52WjAYbfB5gvxPnhwv/+Nwqo1N6t3CSasUV0yGrSTdkgSlX438Hqke34f3xS/HjiDE4XVZ85mjOHLbcI1xnbPNKWptQEJN0aS5xNuMq0l3ADA9f1awsYBP+87jT3HtZU8CMTj5fHRRiHy6urzfFmiU3wL79mARdxdLNQ6AvxmgQaEKEyu+iMPeQXVT0gSKYJwYy86Cht4DG3fBE0SXP6EigBpbgLgOA6jzxEmcVXHeZdPC+sOGPc+9f+mM4IZ6rKepLXRSlIToa9O5cnKAEhmqWDNDc8zrNktZGO8oGOa6e2LSAKcipF/SEhj4IhFRlZrMAas2B7CcV7GztxCHDhVAleUDcM7VZOdux5Dwo2RSJqb7nXbDhNolhyDUV2EHdVb6w9Vc7Y6P+w5iRNFbjSKc+KCjr6bJtUn3JwJEG7KfOYYu7PmhQwjkPbpCeiRlQyeAT/+dbL6D4gkZILZHLAzDzJwBlf08mkd8g8LkShR0SEjURoyo7oI43H9vtMoKA0olSJmJw4SbgRNwnE+GS0bxVLUjg4ym/mE8JKTOHKmVDhYhc/NjmMFOFXsRpzTjj6tUmurmZGFaM4r9JmfTu0Rnhu1xYguguCjxcy9xZeTqG/rRsZkqq8jSLgxCnexUF0VsKTmBgAm+LQta3afqOZMdb727Yov7dHMHx0VUnPjq97uSrRsCHh1DGon5KFZt/eU9g/Z7KiIFya59tFncEEn3y5XMkm1Fqo5EwpaN4lHh/QEeHiG1X8G+JW5fI6rcuGG9wqRKQBOsGSc38rgRJcWJyZFGKNNuALkiPNJkU9rlhBsChFNUoPaNTG13EdEE6i5EYWbxu3RpokgoB85W1rtZfaeEPwf26dVUXIkAqBRYhTH/wDAhBwi8dZUm/bJTkWUjcPRs2X+3ZYONh0Sdg3iog0ASMkWngM1N+UFwnOI4poNgf5tROHmtK6oqTMOYZLrl1rs9004IxNuCFVG+rQ3P+wJ0JSJwk2FzOm95BTAePDgcAaJOL8NaRN0ES/0dRMuH7tFM7fkUBws3Gw6LMwdg9s3CXqP8BHoUOxzJkbjdmjhK+uiZd4WhZu2JNwQAIQKt32mWS6Lrpw4VxR6ZCUDENT3ejhbUiGVdejZItn/RmoIzU25T3NjkaizcDi3ZTKiHTacKnZjz3GVaLIQHGHCAtAlJt9/UNTcNGprYAutRbfmyQCAvwL7WvS5qSwVnDQByd/mNEuEF3b0Jc2NPnwbwCZcAQ6fKROKO5b65hQVzY2YYyu7cRi11xoKkkOxzyxV6RNkopOkmnVnSytRVF6p8mE/+0i4IRQ06SAUyBz5YF23xFT6tREm8Z/36TCVANh8RNh5tW4Sp6zAK5ql8o8ITq8ipLmBK8qO87IFjYAe09SfZYKPUku77DP5PsdNUVNGBCFO5vtPFSvLXzhlk3yFT8vg87c5wZLRIpX8bXTj86tphAL8fbrIb5Kyu4J87BhjyM0XnOqbUtK+0EhmqTyhrAXzJe0Eh3hXlJR/6ciZ0MlYS9weqaAvCTdEg0IUbtbv12cq2XQoHwDQq0WAc3BCpjChMS9QcMR/XO5z04ARTVO/H9KWrbjCw2NzkSAQNvHIIn88vgnNGdkTlplkpcTAabehvJJXZuOOcgpjFPD73fgW45MsGR0pmZx+YhuDgYOdYyjJPw5vgU/bkJAR5GNXUFaJskovACAjKbq2Wxo5iA7FlaXC5lCcnzlhmc9KEQTDw1WYpvadFLQ2jeOdyk1oBELCDaGLc1ukwGm34Xihu8odQCAbff4257YMEG5sNn/iuQJZgc7yfOG5AWtuAKBDhk+bcLJE0/l7jhfhkFcQQF3Fsv7khcUhVFp7Aoiy2ySzx96TgaYp0anYd9yXwO8ESyatTTjYo4A4QXBP5c8i/4RPs6iSwO+YT2vTKM5JeYSqwhEDRCcLfxfl+jU3PmFRNE0drcKpWPS3ER2QIxkSbghdRDvs0gJw4LS2BZfnGbYezQcgCEdBOH12dI8sO6zkc9OwhZtsX7G6Q6dLNWnKdvxdgLMQFmJOHt0jmvxskZlttLYQVfGi34FEYDi4KNwgGZmkTQgLTnIqLkChKNyohIHnFgibqMxk6udq8fWpUIRUFG6EZV50Kq5Kc/OXRfxtABJuiDBoKS242oSbE0VulFZ4YbdxaNNEpbKs3af+9Fb4j5HPDQBht2W3cSir9OJ4YfWF7/44VgiPeFvzskKQvE+4sZNwUxVtfTvWvUHCTUA4uMwslUmam/CQnIrzUVyYLxxzBZv4RB8QKpKpAfH+5r0ys5RSc1NVxJRVIqUAEm6IMGjVWBBQDp7SFg4u+i9kJEYjyq4y5NSEG/K5ASCkqm/us5UfOFW9MHksvwxe5lPdy4UbMcrHRmapqmiTFkq4EbMU+8alzKGYNDdh4tMypCEfBWW+e58Lnh9yffNHU+rn6hH9lRgPQOlzo0VzI/rckHBDNEhaNhJukoMaNTfHfJNTs1A7XEm4oWgpNUTTlJb+Plnshgcqwg1pbjQh+hrsC+Vz48t1w3xhy2dYIgk34eIUxrWLq5BlhQ5O2Jkram5IQ1Y9onAoj5aSHIpFn5syZTSgDLFwrBX8yEi4IXSjZ7EF/JqbZinVCDeqPjcNW3MDyDVlGoSbIje84m3NZKppyeeGNDdV0aZJPDhOyAdyulg2Hp1KnxuvTxPm4exITyThJjw4379MprkJFm7EzREJkRqQhBs+SLjJTI6G3cbB7eFxsjjYxM3zDMVuYVwnREf+PEHCDaEbUXNz5EwpvCF2AHLEyalpKIdAUZtAPjeqZPv6uzqzFM8znJJrbgB/lBRPDsVaiHHa0ShOCPvOk1dQDvC58XqFfk2OdcGhZmolqocThRugqNS32KqZpXyaGytoE8xHZpaS5bkBBBN3hk8Qz1UpxltS4ZH2QonRkT9P0F1J6KZpUgycUTZUepkkuFSFX7jRYZYinxuJ7MbaNGUFZZWo9DK/5gbwm6ZEnxsKBa+W5FhhYlcU0Awh3KTEkzYhbHyCDAeGco9XPKg4hecZ8nwLcQZpyKpHoblR+twAQJxL2PiUuj2Bn0RRuXDMYefgskD9rsj/BUStY7NxknPaodPVOxUfPavV54Y0N2qIZqlDp0tD2soBSKrm+BjZIiAKN+IzaW6qJSnGJ9yUyYUb0aFYEG54XtgVN4531WrbrIUgyNjBwEEZ2SNyuqQCFV4eHEcJ/DQhCTLBPjcAEOPLEyQmRZQjCjcJ0Q5wFihWTMINERbZOpyKq3coDjBLedyAx6c2JZ8bNEuOQZTPVn68KFidLCI6AybHy/pZEm7IoVgryarCTYDPjU+4aRRPppKw8S2gzijOr68JMEuJOW6axJP5TxNV+NwAgtkVCCXcCOPdCv42AAk3RJhozXVTVF6JQt+OIKRZKsq3+xXNUqIzMUBmKQiZc8VU6GdLQhe9O+XT3KTGy4oLij43FAquGVFzk18W2izF+/q1MZlKaoBPuLFzsEHpHyJy1mcabEQaMm2oCjf+PhU1N6UVVWlurDFHkHBDhEWTBGGyOVPFYgv4HdeSYx2Ic4W4aSSzlM+pUPS3cSYANkq3DgBJMULfKbQJAYiam8aJMZAWCdLc6CZRVXOjFG6YT3OTSj434cP5hRsu4JhImW8RjnXSPKAJeZ4bFmzqEzU35WqaGzFSymWNOYKEGyIs/H4JFVWe9/dZMQFXFep7ySwlam7yhWfyt5EQF9zC8uqFmyYJLr+GRnIopmgprUgOxXLhRgwF9+W5EXfFqXGkUQgbhXAj+pIphRu3z9E42kFLlSbkmhsEOxTHOIR5QV1zQ2YpglD3S1Dh7+oipYBgh2KqKxWEqpNrACGFG8aEnDcAmaU0IPV1qZpDsTA2xTpfMRbZ5dYNgiDjsiOk5kbUMERHkeZGE5LmJoRDsVP4u6xKs5Q1xjQJN0RYSH4JpVULN2dKBIFFNGOpEiTciJFS5G8jIuadKKxKuPH53DSJDxBu5CH2FApeLaqamwCzFOfzEXE5qD/DhhPzr3BSf4YyS0WTWUobVWQoBoBYpzBeVc1SpLkhCCBJbQFQQVPGy0CzlJs0N4GIwmSVwo1CcyOWYPD6/W0AMktpwO9QLDO5yoUbxsD5NDcupzUWgjrBt+g67TaZMSpAc+MRFmjS3GhEzaFY1qfR5FBMEFUjRu/kl1VKKno1xBsmPpQzMRBac0ORUhKJPodiMfJMjZBmKXmNKXIorhb1PDc+nxveg8qKMim6JybKGgtB3eDT3NhC57kRNTeiOYWoDjWHYr15bqwxpmnEEGEhLgAVHh7llXzI80TNjSbhRqwtVeELL/cV1iOq97mp9PI4UyozASrMUjLhhjQ31ZIUI4xHhc+N6FAMoLw4X9oLu6oa10TVqDkUB+S5ETMXk+ZGI9XkuRGjztR9bkSzlDXmCBJuiLCIc9oRZRMmp6pMU8W+Gya+SrNUQPkF8aYk51eJ6nxuzpZUgDFhvUiJdQZobnyf4WyAjW756pBMgOUef+00m10ScCqKC6TF2EE+TOHjW3QdNg62UNFSvo2TaE4hqqEGGYoLSXNDEADHceq+CQFIPjd6zFIqyacaOtVpbkp8O7E4ZxTsNk7pc0Nh4LoQ+xrw72YB+IWb0nzJLMWRsFgD5A7F1ZmlSLjRRHVJ/Jyiz03o2lKkuSEaPKJTcVURU5LPjSaHYlG4UVdRN2Sqy3MjhcyKO1w1zQ3522jCGWWT1PcKYdInhJdXVITUNBA6EM1Sits80KFYGNdWKORYK6jmuQnOUFym4kpA0VIE4UNLrpuSCj0OxQFmKRJuJKrT3IhqZsnxUs3nhrI9a0Y11YFvkXBXekL6iBB68GtupPILgT43gUI7UTWqGYqDfW7Kq4iWSiThhmjoqCY7C6BYix03pFmKhqeI3+dGPVpKnKwkx0s1zQ2ZpTSjKkz6xmMlCTfGIPrcVJHET9QwxJBwow2FcBM8j4r5gkorlfMIY0yWtsMa8wTdmUTY+MPB1X1u5DdMyLpSABBFPjfVIS62ZZVeVHiCVcqi+l7yTVDzuSGzlGZUi2f6xmN5hcdvliLhJnzEJH42hCy/QJobnVSTxE8yS1Uo55DSCq/kPE9mKaLBU52pxO3hUekVbhhdeW5Ukk81dOQ+S2p+N+Jkpe5zI5ZeIOFGK6pZin2LRIXHKzOj0BgNH6HvomyhHYrLA82tRNUohJtggdEfCq7U3IgmKbuNs4yWjEYMETbVlWAQtTaAEMUTkiDhhnbFgdhtnLSjUhMmy0I5FDNZhmIKW9aMakZoSbjxyMwoNEbDxteJilDwUD43lOdGG9XkuZGHgsuTr8qdiTmLCOx0ZxJhI+5u80Nobopl2YlttipumMDyC6TyV6WqXDeSQ7FDzaGYfG704hfcZSZXyeemEjaOxmiNkfnciPe8NyDZuZgg1GURbYL5VO1zI5qteQZUeP2mKavluAFIuCFqQHX1jjRlJwbIoVgjVZkB3ZJwE+hzQ6Hg4SD6k6mapeTOmDRGa4DPLMUxSRNWGSDdlAWOa6JqqtHcyH2X5FmKJc2Nharc051JhE1yNXluNOW4AUi40UhV9aWCkp1JmhuvLBTcOrsysxF3sHLTql9zEzppJaEDn/nDznGw+271igDhxu9QTHOBJqrJc+Ow2+CwC6/lWYqljShpbgjCX4MnVLSUbs2Nh4SbqqhKcyNOVK4qQ8GtM3GZjdMu+tfIFlvfIuEhzY0xyEoFiP7CFXwo4YY0N5qopvwC4NeClSo0N9bKcQOQcEPUgOry3JTU2CxlDcc2o6jK50b0TQjW3HgoFDwMHD7hplLmlyD3uQk8RoSD6B/CJG2CPIjHyzPJTEVmKY0ozFLqEWgxKsUzrVY0EyDhhqgB8gKDfMCOCwCK9Ao3zCuYUShaSpWqfJyCfBMUPjdkltKLI0pFuPEtxpVeEm4MQZZwziGZpfz9XS4zm5DmRiPVJPEDgFhf5KrcLFXi9tWmc1mnn+nOJMJGbgev8AYnlivW7HMj2y14K0lzEwJxV6Xmc1MeJNzIfG5E4YY0N5px2kVBJlhz4/EEJ/YjwkHsO7/mxi3zuZEvvlRbSiNq5RcC8oVFO4I1N2ICvygLFYK1zi8hah2nbMJxq2TNLXYLi4BmzQ0gmKbI50YVl0P0Awnua3GiiqZQcEMQzVIKB1dRuCGfG2OQJZwTh63cf7tc8iOzVZ1KgvBTTYZiwJ8uQi48enzCjd1C/Ux3JhE2otMloL7gaqorBahobsgspYaqH4gPsfwCVQU3BqmvPcGaG6+HzFKGwMk0N75FVWmWCsi6TVSPBuFGMkvJNDc8EzU3JNwQBDiOk7Q3amYpzT43NjvA+SYwr5vKL4RA1VTiI3QouIdCwcOgKodir4c0N8YQ7HPjlkWnBZlaieqpJs8NIDNLyTU3Pg2llTRkdGcSNcLlWwTcshtFRLPPDQBEuYRnbwUoQ7E6VWpuAtPUUxK/GuGMCu1zw8sdikkADx/OHy0VpeJzQzluwkA1z02g5iY4FNzLC+OcNDcE4UPyA1FzKNaquQGUJRjI50YVVT8QH6FDwWVVwUlzoxm/IKnic0OaG2OQ5WRx2IR+lmtuguqlERpQi5YKCAX39ac8Gs3LyOeGIBT4k53VVLiR5boh4UYVKTxZzaE4VOFMSuIXFn5BUq65ESZ+3usJOkbUAMYkjUGFQnNDPje60WCWipE0N/5xLEZL2S00nmn1IGqEWNBOPVqKhBsjqdLnJmQouMznhsxSmlH3uSHhxlBkYctiL8rTZZFZKgxUk/ipCzdlFf6xLfrc2O3WGc80aogaUZXmRsxQHEdmKUPQ5HMjhYKrJfEj4UYrziqipUThhtH4rCH+hdQGoZ955j9GRTPDQBaBFjJDsYpDsdeC0VKkpyZqhBgt5fYEOxSLAo+mBFxSfSl3SFtxQ8cfmabmc1NF4UyOHIr14pAcioN9bjjmVbwmwkQWtize6V6ZcOMmnxv9qJmlApzeYyXNTbBZymahOZeEG6JGiIKLmuZGXBgcdi3CjSxaKsSOo6ETSnNT6eWDa/DIzVLi5EY+N5qR+9wwxsBxnLRw2EGaRUOQaRlsnDB+5VskcigOA1kEmq5QcN56mhu6O4ka4dfcqAk3vvBCLXZcMktVSyjhRrUGDyXxqxFygVyc+MXxGOVbgjkKA68hKj43sqFNDsVhoMGhWC0UXKwNaNeyEY0QrPNLiDqhKuFGXBS0aW7kDsWU50YNVT8Q+BcBjpOZAOU+N1R+QTfy7NuSMClqbjgySxmCzCwl+tzINTfkUBwGGvLcqIWCeyhaiiCUhDJL8TyT7LjahBtRc0PRUqEQ/UACfW7kCfw4cXKShBuvLBScdsBacci0jZUe5SJBZimDkJml1HxuyKE4DFTLL4QonCl3KLagWYqM8ESNcPoy4gYKN5Uy/bI2s5SouSGzVChCmaXKAp2JAXWfGzJLacZu48BxwhpREai5oQzaBuH3D+F8PjfKUHAyS+lGg1lKTNQnn0a8VDiTIJSI6vtAs5Q8ysSpyyzlhqROJZ8GBc5qfG6i5VFpqkn8SLjRCsdxIYVJu2g8sZAKv06Q5bkRR65cKekms1QYqGUoVhduGPN3Ngk3BBGAVH4hQLjxyBYETarOKNLcVEdIzY3PMTA6lOaGpyR+4RAkTAY4FJNwU0Nk5Rc40eeGzFI1Q9LceIOPiS99XeyVqck8Pk27lYQbMksRNUJK4udV5rkRNTccp/GGoQzF1eKQMhQzf3gyQiwCcp8bcYdGoeC6cARmhPaNRxv53BiEzCzlO6KWodhFwo12xDHJy+dj5fwrOg3zMs2N6EVgJZ8bujuJGiFqbtyVwblXAMBhs/mdXKuChJtqccjMTpUq1ZOVwg2FgtcUKdeNJzAUnManISgcin15bmTCDWluwkBm6gs65sMmmaX8x0TNjY2EG+N48cUXkZ2djejoaPTt2xcbNmyo8vxnn30WHTp0QExMDLKysnD77bejvLy8llpLBOJSKzAIf60STc7EQIg8N9a50YxA7rsk729Vx0tFbSnyuQmHIDOg5FAs7oppfNaM6mpLkUOxbiTNTejK9aL84lXxuSHNjUG8//77mD17NubPn49Nmzahe/fuGDVqFE6cOKF6/rvvvou77roL8+fPx65du7BkyRK8//77uPvuu2u55YSIlOcmQHMjLr6awsCBEHlurHOjGYG8L+W5blQzuar63JBZSg/i2A4WbkhzYwiybLqiqc8j87mRzFJayrcQAmKfVincBJulREHHSj43dTpqnn76adx8882YOnUqOnfujMWLFyM2Nhavv/666vk///wzBgwYgIkTJyI7OxsjR47ENddcU622hzAPlxgKHqi54UXhRqvmRl5bikJt1bDbOGnXJXcqFh2KlaHgMp8bSXNDwo0exLEbGApu40i4MQTZ5kVNc8NbsJij6aj53IQSbmRTtlQV3EJ9XWd3Z0VFBTZu3IgRI0b4G2OzYcSIEVi/fr3qZ/r374+NGzdKwsz+/fuxYsUKjBkzJuT3uN1uFBYWKh6EcThDJPETE5/p19xQtFRVOFTMgOUe0TeBQsGNxG+WIp8bcwjOcyPfI4mCjpX8QExH1SwV4HOjprmxYCh4nW3lTp06Ba/Xi/T0dMXx9PR0/Pnnn6qfmThxIk6dOoWBAweCMQaPx4N//etfVZqlFi5ciAULFhjadsJPqKrgYhI/7T435FCsBafdBreHVzoUV1RjlvKSQ3E4OALLXfgWBcpzYxAy51efbKMov8BbsFK16WjR3IinqJilomzWmXMj6pfk5OTgkUcewUsvvYRNmzbh448/xldffYUHH3ww5Gfmzp2LgoIC6XHkyJFabLH1cYWoLSWqOR1abxYqv6AJR6AfCEKFgss1N17lMUITwXluhEWWNDcGoZbnhvcLMrzkB1LbDYtgNOS5EYVF9QzFprauVtE0233++ee6L3zhhRciJiYm5PuNGzeG3W7H8ePHFcePHz+OjIwM1c/cd999uP7663HTTTcBALp27YqSkhJMmzYN99xzD2wqC6nL5YLL5dLdfkIbIc1SYTsUk1mqKiQ/EFl/i1ElLtU8NxQKHi7+Wl6hHIpJo1Az5HlugkPBpWLs1M86EB2Kqxdu1DMUW2fO1STcjB8/XtdFOY7DX3/9hdatW4c8x+l0olevXli9erV0fZ7nsXr1asyYMUP1M6WlpUECjN0uTOLy/yii9hAdioPLL9TALEXlF0KilqXYoxbGKWluvBQKHiahfG78ZinrLAR1gtws5TskF268ZJbSj5rPTWASPzWzlAVDwTXrqfPy8pCWlqbp3ISEBE3nzZ49G5MnT0bv3r3Rp08fPPvssygpKcHUqVMBAJMmTUKzZs2wcOFCAMDYsWPx9NNPo2fPnujbty/27t2L++67D2PHjpWEHKJ2Ca250etQTGYpLTgDF1z4fRPsqsINhYKHS6g8N1GU58YYFGap4MKZ4obVTsKNdrjqNTecZJaSl1+wniCpababPHlylSamQK677jokJiZWe95VV12FkydPYt68ecjLy0OPHj2wcuVKycn48OHDCk3NvffeC47jcO+99+Lvv/9GkyZNMHbsWDz88MOa20YYizNkEr8wQ8FJuKmSqjQ3IYUb0tyERajaUlR+wSiCyy/I89z4zVK126qIRtXnRj1aSm7sEDdImjXtEYAm4Wbp0qW6Lrpo0SLN586YMSOkGSonJ0fxOioqCvPnz8f8+fN1tYcwD6n8QlC0lE7Njegjoqhma50bzSiC/EAgc7zkQmluKM9NOAT5N0lmKcrDZAiK8gsCCrMUs542wXSCoqW4oHlUrbaU6gYpwqG7k6gRkuYmKM+N6HOjcYhJOw6ekvhVgTMwPBkhclQokvhRVfBwCOlzw5HPjTHIfW6C89wwC2bNNZ3ADMUqgqFUFVzNodhCgqSurVx+fj4++eQTrF27FocOHUJpaSmaNGmCnj17YtSoUejfv79Z7STqKa4QPjdShmKtE5N8x0FmqZAELbgIJdyQ5qamBIfdi6HglOfGEKQNjbrmRkriR92snUCHYpU5VJwn5P5NVkzip2n1OHbsGG666SZkZmbioYceQllZGXr06IHhw4ejefPmWLNmDS688EJ07twZ77//vtltJuoRoaKlKvQ6FKtqbqxzoxlFUL0jyKJKqnUoJs2NHkL53FBtKYOQmaWgorkRxzWFgusg0CylMkarDgW3Tl9r2sr17NkTkydPxsaNG9G5c2fVc8rKyvDpp5/i2WefxZEjRzBnzhxDG0rUT0JFS3n0hoLLdnGkuQmNWvkFr1oNHnIorjHBtaXEDMU0Po0h2KFYqbmx3oJrOoEOxarCjfCsjJbyzdcW6mtNws3OnTvRqFGjKs+JiYnBNddcg2uuuQanT582pHFE/UcUbjw8g5dn0kQk7nadujU3ZJaqCnHBVdPcKB2KfT43HlneINLc6MJffiFUnhvrLAR1gqS4YeB8LxTCjRSeXMvtimS0aG4CzFKMMelvKwmSmlaPRo0awe12a75odYIQYR1EnxtAqb0RfUI0a25Uo6VIuAkkqN4RqjFLecqCjxGaCJ3nRumDQ4SJPM+N7573Mr+5xO9zQ/2snQCHYpUxKu9PxphCg2Ml4UbzbJeUlIR+/fph2LBhGDZsGM4//3w4HLQTbOg4A4SbGKcgpHgk4SYcnxsSbkKhmsSvKrOUHNLc6CLIv4ny3BiM3ywlwoMDzwA75x/XVBVcB5p8bvx/e3kmhYED1hJuNN+dixcvRsuWLfH6669jyJAhSE5OxoUXXoiFCxfil19+gdfrrf4ihOWIsnHSzSLPdRO2WYr3gsovhEbN50YUJFU1N3JIc6OL0HluSLgxBJU8NwycpEmQhBuaBrQjlbSo3iwFCNoxeb6bBlkVfMqUKVi2bBkOHjyIvXv34r///S+aNm2KxYsXY8CAAUhJScHFF19sZluJegjHcdIOVx4xVanXQY0js5QWxCR+lSoOxapJ/OSQcKOLIEFSNEtRnhuD8Oe5ETc0SuFGeNtKuVdMJygUvGqzFM+UmhsLyTb68tyItG7dGq1bt8YNN9yAAwcOYMmSJfjvf/+LlStXGt0+IgJw2m0or+QV2gTRCdMRFY5ZikLBQ6FWfkG9tlRArTVbFPWnToJ9bgKjpag/a4Qiz43Qpwx+YV3UKFAouA6CzFJqwo3/b54xeL3W1NzoFm4OHz6MNWvWICcnBzk5OTh16hTOP/98zJkzB0OGDDGjjUQ9x+WwA+UeuCvl9Y70JvGT7eJIcxMSNZ+bKmtLSa/J30YvQX0dWDiTxmfNUJilfAINbPB6GRhj0h6HzFI60JDET6m5UWYqtlJfaxZubrjhBuTk5ODMmTMYMGAABg0ahGnTpuG8885DVBSpuxsyasUzdVcFp2gpTThUyl3484HITgwUbsiZWDdBJkByKDYYmUOx3MlVFpoMWMvJ1XTkm0SgWuHGyzNFAj8rack0SyXLli1DixYtcM8992D48OHo2bOnpTqCCB+1EgyVUhI/qi1lJGpmKf/kJOuvIM0NbUD0EiRIcoHlF2h81gjZPc8x4W8GDh6eVzi50jqjA02aG//fTOZzYzUhUvOMt2vXLskc9dRTT8HtdmPgwIEYMmQIhg4dinPPPRc2C9nrCO34HYr90VJihmKH3gzFitpS1rrZjECqCq5WOFPeX4GTGmludBMqz42NovmMQV5+wXfPM8aB55XZcy225ppLoHCjMkbtgdFSvEoqCQugWRrp0KED/vWvf2H58uXIy8vDunXrMGbMGGzYsAGXXHIJUlNTcckll5jZVqKeoq650VtbisxSWgiqdwR5Ej/ZiRyn1NbYXbXRPEtRvc+NtRaD2kee50b0uRE0N4zMUuGhIc8NF2CW8qhtjixA2Lrqzp07o1GjRkhJSUFKSgqWL1+Or7/+2si2ERGCWvHMyrBrS5FwUxWqVcGlJH4B/WWL8u/gYpJro3mWIrTmhsanISg0N2IoOMDzytwrlKFYBxpqSwGCNoxnYoZiYTzbtc7VEYIu4ebEiRPIycmRzFN79uyB0+lEnz59cPvtt2PYsGFmtZOox6gVz6yUzFKUodhIVAtn8ioOxYBScxNLJVH0Elw4k6KlDEV+z/u0OAwcvIwpInhIttFDQGeFGKN2GwfeKzhui8PbamYpzcJNp06dsGfPHkRFReG8887DFVdcgaFDh2LAgAGIjo42s41EPUdNuBFVnbp9bsihuEqqKpwZtMOV57qJTTW9bVbDEVh+wbdw2DnKw2QMolkKACdP4sdL+xvAeuYSUwnsqxB9J5imBCFSTNthNQ2ZZuFm/PjxGDZsGAYOHIjY2Fgz20REGC4Vh2LdmhubfBfHqjy1IRNU7whyh0AVs5RIDAk3enGGqAouQcJ3zZDWUrlZioOXD8y9Yq1F11SCxqh634kCIy8LBW+wmpuFCxea2Q4igvGbSvwTklQVXGsEHZmlNOEIXHDh15IFdbXCLEXCjV5C+dxI0PisIfI8N37hJjAUnApn6kDjGBW7lJdVBbeaz42mu/PRRx9FWVmZpgv++uuv+Oqrr2rUKCKyEKMZeFn4pjGh4LR4BKLmc+NP4hdoliKfm5oQyudGgsZnzVAxRQc6FJNcoxPNwo1vzmYhUklYAE13586dO9GiRQvceuut+Prrr3Hy5EnpPY/Hg23btuGll15C//79cdVVVyEhIcG0BhP1D/FGkauSKygU3BTUzFIh1cpynxsyS+kmVG0pP9ZaDGodlWgpHjZBc+PrcjJJ6STI5yaEcCNuSJkyQ7GV0GSWevPNN7F161a88MILmDhxIgoLC2G32+FyuVBaWgoA6NmzJ2666SZMmTKFHIwbGKL84lXR3FAouLGoORR7QjoUyzU3Kaa3zWr4BUnyuTEHNbOUsOBKmhuLLbimEzQm1ftPMkspfG6sNZ41+9x0794dr776Kl5++WVs27YNhw4dQllZGRo3bowePXqgcePGZraTqMeomqV8fzt1h4J7KVqqCtQKZ6pWBQfIobiGiJobsf6OXaOzJqER1Tw3HDxeRmapcAnDLOX32bNWZ+tO4mez2dCjRw/06NHDhOYQkYiqWcqjs7aUVDiTgcovhEatcKY3lM8NJw8FJ58bvcj9xSq9vIpwQ8J3jVDJcwNfnhsyS4WJVuFGbpZiIczaEY7uu9Nut+PEiRNBx0+fPg273a7yCcLqqGtufMKN1htGXs2WzFIhqbpwZkBfeyv8f1O0lG7k/mKVXl5zDhFCK+rlF7y8X3NjNSdX09EZLeXlGbxea/rc6F49mLzohwy32w2n01njBhGRh5rmRjSbiH4L1aKoiUJmqVA4o0In8QtaCNyFsg/Gm942q6EUbhj53BhNCLOUXLgh2UYvgQK4+lninM1kZimrCTeazVLPP/88ACGz4WuvvYb4eP9k6fV68eOPP6Jjx47Gt5Co94g3hWy99deW0qy58Wn9pGq2oMVDhcDaUowJKdQBlcmpXCbc0CqhG7uNg90mLLaC5oaEG0ORm6V8f5NDcQ3RGi3F+c1SIVNJRDiahZtnnnkGgDCZLl68WGGCcjqdyM7OxuLFi41vIVHvscvstyJh15ZSCDfWutmMIDDPjTxCLdgs5a61dlkVh10Qbio8JNwYj8ws5TNF+x2KhbfILKUTzT43wrNQfsGaPjeahZsDBw4AAIYNG4ZPPvkEycnJZrWJiDAks5QiFFxvnhvxPKZyjBCR+9ywgAKDtMs1HofdhvJKXl1zQ3luaoZqnhtOoU3gSLjRh85oKUVVcIvNH7pWj8rKShw+fBi5ublmtYeIQALz3DDZbkBzhmKbmjO6tW42IxBDwZkvsygvMwVabedVH1BoykhzYzCywpmQl19goSvdE1WjcYzaZaHgojtBgxZuHA4HysvLzWoLEaHYOaVZSp6DRXMouNpNSItHEI4oeXiyv6IvUEXYrJ0c/cPFHwkIzf4MhEYUEZL+OcPLM+klhYLrRGMWbfE0IYeTT3Njsb7WfXdOnz4djz32GDweT/UnEw0Cm01plpIvuLprS1V3rIEjN/NVeHiF5ibkzis6yeRWWRd5gUHS3BhMFdFS4lxCwo1OdCfxYxQtJfLbb79h9erV+Oabb9C1a1fExcUp3v/4448NaxwRGQRpbmQVq/X73FRzrIEjNz15A9IyhNx5RSeb2CJroxzb2sJsCa0El18IzHNjsYoA5qPVLCXTSIr5yTSXyokQdAs3ycnJ+Mc//mFGW4gIJVBzUylTJ2gPBSfhRgtyB0ul46WKQ/HoJ4A1DwH/eLU2m2gpOJlvAmluDKbKPDfCO6S50YnGMcqpaG6s1te6hZulS5ea0Q4iggnMc+MPA+e0RzuoCjfWutmMwsYJiy0vS1OvqrXpOw047yba/tYAKWSWJ7OU4aiUX2Bi+QVmzQXXdDTWPxMV6vKq4FYLSKC7k6gxgWYpMQxcV5VZtWgpWjxUkWcXDVlXSjqZ+rAm2GUhsyTcGE1w+QUGwUzCS9qEummZZQgh3Mh9bvyRadYaz7o1Nz179tS8G9+0aZPuBhGRR5BZSqa50QyZpTQjTEzM0nVh6gu2qsxS5HRTM1TNUjZ4yCwVPnrNUry8/IKpLat1dAs3F110EV566SV07twZ/fr1AwD88ssv+OOPP3DLLbcgJibG8EYS9RtRhvEGhIJrdiYGyCylA7Fb5BV9rRbGWV+Qh8yS5sZgJLOU36FYyt9EZqnw0JznRngmzY2MkydPYubMmXjwwQcVx+fPn48jR47g9ddfN6xxRGQQWBVcqiulS3MTYJaihSMkYn+LCwEA2C0W6VBf8Pc1CTfGI89zI/O54am2VNho1C6qmaUavM/N//73P0yaNCno+HXXXYePPvrIkEYRkUVos5QezQ0lSNOKqr2cdrimIDdL8UGh4NTnNSJUtBSTm6XqpmkRi+48N7INksU6W/cKEhMTg3Xr1gUdX7duHaKjow1pFBFZBDkU8+GYpTgodxnWutGMxG+W8k9MtMM1B9E3wcsY+KA3SQCvGcEOxTw4eL1+h2KrLbimo7UquCxaipL4+Zg1axZuueUWbNq0CX369AEA/Prrr3j99ddx3333Gd5Aov5jiEMxIERMiVXBaeEIiVxzIwqUVlMp1xfkIbPBmhsaozVCXiw3SHNDhTPDQqfmRm4CtNocolu4ueuuu9C6dWs899xzePvttwEAnTp1wtKlSzFhwgTDG0jUf+zS7lZ4XRlOKDigvBFp4QiJTdrwWjcBV31BXj2ZD9oVU5/XCHn/MWFDxICAJH6136yIRndVcH/qDqtpf3ULNwAwYcIEEmQIiUCHYk+4mhsSbjTh33VZ115eX5D3NR/Ux9TnNUPef0w6Jq8tRb5kOtGYxE8UZAS/PV8AiMXmEN0ryJEjR3D06FHp9YYNGzBr1iy88sorhjaMiBwMcSgGSLjRCEdmqVpDXjiTZxQtZSgqC69YW4pRKHh4aBVuZCkOqk0EGqHovjsnTpyINWvWAADy8vIwYsQIbNiwAffccw8eeOABwxtI1H/sMqdLQGaW0q25kYWD08IRErkfiFVVyvUFyb+JJ58bw1FZeKWq4LKaaUQN0GCWsqqWTPfduWPHDsmR+IMPPkDXrl3x888/45133sGyZcuMbh8RAUiLre8m4cPdCSg0N0a0zJrIJyapry02MdUX/Op7wBP4Jgk3NURNuIEiFNxq2gTT0etQLE8nYbFcWbrvzsrKSrhcLgDAd999h3HjxgEAOnbsiNzcXGNbR0QEtgDNDQs3dbr8fFo4QqJeF8ZaE1N9QW6WYkFmKerzGlGF5obMUmGiOYmf8CwPBbeaaVv3CtKlSxcsXrwYa9euxbfffouLLroIAHDs2DE0atTI8AYS9Z9Ah2JxwdUdxmkjs5QW1PLckHBjDgpBMvBNGqM1JLTPjX8Oqe02RThayy/INJJei0Zc6r47H3vsMbz88ssYOnQorrnmGnTv3h0A8Pnnn0vmKqJhITkUswCzlN57hRyKNSHPUUFJ/MzFLosq4Rn53BiKav9xilBwEtp1ojdDMW/d8gu6Q8GHDh2KU6dOobCwECkpKdLxadOmITY21tDGEZGB5FDsS+EavlmKhBstyPPceClaylTk1ZNJuDGYKsxSVDgzTDRXBReeFaZti5UFDyvPjd1uVwg2AJCdnW1Ee4gIJMgsFW52UUXxTJrUQmFTUSmTQ7E5SCGzjMEbNCapz2tGCIdi3l9+gWR2nWhMNCk3S3ksOodoEtXOPfdcnD17VvNFBw4ciL///jvsRhGRRaBDsT9aSueFSHOjCTWHYr3JoAltiBM+Uy2/YK3FoNZRucd52AIKZ1If6yIMsxTfkM1SW7ZswdatW5Gamqrpolu2bIHb7a5Rw4jIIVBzE/bERMKNJpSJ5cIsdUFowp8wEcGaGxqjNUPVLCVoEsgsFSYak/jJzVINvnDm8OHDpfC86qBiZw0LUUMjaW7C9b63kXCjhYZQF6a+oMjkypNwYyzqPje8TLix2oJrOlqjpeRCe0MWbg4cOKD7ws2bN9f9GSIykUfvAH6zlO4FV6G5sdaNZiTy8gvecCPTCE2IEz6ZpUygKodiCgUPjyCfm2rMUhbOlaVJuGnZsqXZ7SAimNBmKZ0XIrOUJuTaBF6amKi/zMAm3+EGKq5pjNYMlf5jAaHgZJYKBw7yQqRqiNOFlUPB6e4kakyQQ3G4ZilFbSlr3WhGojBLScJNXbbIusiLwlIouNGE0NwwMkvVCA2bRLnQ7vFVBbeaaZvuTqLG2KUFQHgdtjMgaW40YVMklqNFwEzkztteqgpuLCEciuV5bmiPEwY6hBsvY5JGkjQ3BBGAPIur8CwcJ7OUOfgXXLkzIPWXGSiqJwdqbijPTc1QkVx42HzO28JrMkuFgSbhRnhmjMFLmhtzePHFF5GdnY3o6Gj07dsXGzZsqPL8/Px8TJ8+HZmZmXC5XGjfvj1WrFhRS60l1AjpUEzRUqag6gxorXmp3iDf4QY7FNMYrTnKPg0MBbdaYrlaQUNghtzcKkZcNnjNzZEjR3D06FHp9YYNGzBr1iy88sorur/8/fffx+zZszF//nxs2rQJ3bt3x6hRo3DixAnV8ysqKnDhhRfi4MGD+PDDD7F79268+uqraNasme7vJowjyKE43HpHpLnRhHLXRaHgZqI0SwW8SQtvzeEChRshFFyqCk7TgH7kfarB58aqpm3dQ2fixIlYs2YNACAvLw8XXnghNmzYgHvuuQcPPPCArms9/fTTuPnmmzF16lR07twZixcvRmxsLF5//XXV819//XWcOXMGn376KQYMGIDs7GwMGTJEKt5J1A32QIdiMkuZCidpykC1pUxG4bxNmhsTCDb1eWRmKcqZFgY6zVINuvyCnB07dkjVvz/44AOcc845+Pnnn/HOO+9g2bJlmq9TUVGBjRs3YsSIEf7G2GwYMWIE1q9fr/qZzz//HP369cP06dORnp6Oc845B4888gi8Xq/en0EYiLi7ErUI3rAdiqm2lBYU2gSvNXdd9QW5+j44iR/1eY2R9SGDiqM89bF+dJqlpFBwi9m2dRfOrKyshMvlAgB89913GDduHACgY8eOyM3N1XydU6dOwev1Ij09XXE8PT0df/75p+pn9u/fj++//x7XXnstVqxYgb179+LWW29FZWUl5s+fr/oZt9utKAVRWFiouY2ENgIdiiWVco00N9a60YxE4XNDaepNRSFIBr5Jmpuao3LPe7ws/DmECJg7Qwg3qhmKrTWedf+aLl26YPHixVi7di2+/fZbXHTRRQCAY8eOoVGjRoY3UA7P80hLS8Mrr7yCXr164aqrrsI999yDxYsXh/zMwoULkZSUJD2ysrJMbWNDxB7KoZh8bkzBnzUXli16V19Q+CZQ+QUTCF6IFUI7jWv9aJhH7apBCdbqa91352OPPYaXX34ZQ4cOxTXXXCP5u3z++eeSuUoLjRs3ht1ux/HjxxXHjx8/joyMDNXPZGZmon379rDb/eaLTp06IS8vDxUVFaqfmTt3LgoKCqTHkSNHNLeR0IY/74ro5Oo7rjtaSp7EjxaOUMjLL3jIodhU5M7y5HNjAipmKcpQXFO0OBQLz1Q4U8bQoUNx6tQpFBYWIiUlRTo+bdo0xMbGar6O0+lEr169sHr1aowfPx6AoJlZvXo1ZsyYofqZAQMG4N133wXP87D5VGh79uxBZmYmnE6n6mdcLpdkRiPMQS7xiwIOQA7FZqHIc0O+CaYir54cFC1FfmE1R+Welyfxs9h6WztomEflGyTeoj43Ya0gjDFs3LgRL7/8MoqKigAIwooe4QYAZs+ejVdffRVvvPEGdu3ahVtuuQUlJSWYOnUqAGDSpEmYO3eudP4tt9yCM2fO4LbbbsOePXvw1Vdf4ZFHHsH06dPD+RmEQci1BoqJSbdZilP/m1BgU5mY7BabmOoLCrMUaW5MgAv60ysb16SRDAMNvot2mbZd0v5abM7Vrbk5dOgQLrroIhw+fBhutxsXXnghEhIS8Nhjj8Htdlfp/xLIVVddhZMnT2LevHnIy8tDjx49sHLlSsnJ+PDhw5KGBgCysrKwatUq3H777ejWrRuaNWuG2267DXfeeafen0EYiFydydfELMWRWUoLkuaGt24YZ31B7izv4an8guGoOL96vGSWqhE6QsGtXDhTt3Bz2223oXfv3ti6davCgfiyyy7DzTffrLsBM2bMCGmGysnJCTrWr18//PLLL7q/hzAP+cJaI5UymaU0wSmcXK1pL68vcLJFgKfaUiag7lBMZqkaoNMs5bXoHKJbuFm7di1+/vnnIB+X7Oxs/P3334Y1jIgc5BGEXuYP49StTSDhRhPKrLnWnJjqC/IElZWUodh4ZPc58/3t4WXmVupj/WjIUCw3S1lVuNG9gvA8r5o07+jRo0hISDCkUURkoXAolkU66M4uStFSmvCHgls3jLO+oCycGfAm9XnNUbjZ+SPTwp5DCG1J/ORmKYtmOde9gowcORLPPvus9JrjOBQXF2P+/PkYM2aMkW0jIgR7gENx+BmKKYmfFuRmKaotZS5KLRk5FBuPis9NTeYQQlcSPy+Zpfw89dRTGDVqFDp37ozy8nJMnDgRf/31Fxo3boz33nvPjDYS9RyO48Bx4u5WZpbSO/crFgtr3WhGoqwKLhyz2q6rvqConswHvEnCTc1RiZCUF87UPYcQGh2K/c7bIg1euGnevDm2bt2K5cuXY9u2bSguLsaNN96Ia6+9FjExMWa0kYgA7BwHD2PgeYAPt+idBlsx4dcmCHVhhM622sRUX6gyFJwE8JqjlufGN48AZJYKCx3RUhVev8RutTlEt3ADAFFRUbjuuuuMbgsRwdhsHOBTJxtSOJOEm5Co+YGQ+t4clNWTySxlPFWbpay24NYOGjIU+/q1UibcRFmstpQm4ebzzz/XfEGxkCbRsLArnAENMEvRwhESedZcq2YXrS8oqicHvkljtOaEMEtRKHgN0ORQHCzcWEy20SbciOURRDiOk2yi8mMAVCOpCOtjly0CLFxtAgk3mpCbSjw+/T1pbsxBWThTcCq2c2IoD43RmqOuuQl7DiF0+dxUevzruNU0N5p+Dc/z0uObb75Bjx498PXXXyM/Px/5+fn4+uuvce6552LlypVmt5eop0h+IDLv+5qFgtOkFgq7ikMxqe/NQWmWYuBBEX2GIl98ZYurqFEg4SYMwvS5sdoUotvnZtasWVi8eDEGDhwoHRs1ahRiY2Mxbdo07Nq1y9AGEpGBvHqyZJaiDMWmIK4BjMlNgBabmeoJ8pBZnmdQ6KtpjNacEGHLfuGmlttjBbQIN76OrfCFAEbZOMs5b+u+O/ft24fk5OSg40lJSTh48KABTSIiEcksxWQqZd2FM0m40QKnMEtREj8zkZulvIyBkebGYIJ9bgB/iDLlbwoDHXlu3B7BjcSKPnu6V5DzzjsPs2fPxvHjx6Vjx48fxx133IE+ffoY2jgicpB2uHwNzFKUxE8T8lBwqi1lLookfnxAODgJ4DVH1oecrG8ryCwVPipO2oGIwR5un+bGYcGEQrp/0euvv47c3Fy0aNECbdu2Rdu2bdGiRQv8/fffWLJkiRltJCIAv1kKMrMUaW7MwB8Kbt3sovWFQHMrr+IAS9QA+RxBPjfGoMOhuMLCwo1un5u2bdti27Zt+Pbbb/Hnn38CADp16oQRI0ZYzmZHaEfhmyBFOui8CAk3mlCYSki4MZXA6slKh2IaozUnlM8NhYKHjY6q4G6Zz43VCCuJH8dxGDlyJEaOHGl0e4gIRR4KzoebxE8eLUW74pDI89xQDR5zCayezMgsZSwK2Ubuc+PT3Fhw0TUdDcKNPcDnhjQ3AB544IEq3583b17YjSEiF/8iIBNuyKHYFOykuak15NWTg8xSNEZrToDPjd3GwcszVHhJaA8bHVXB/T431utn3cLNJ598onhdWVmJAwcOICoqCm3atCHhpoGicHIls5SpiEKj3OfGimrl+oDcLCXkuaneWZPQg1JYtHMcvGCSz40FFQq1QPUCOCf57QmvSXMDYPPmzUHHCgsLMWXKFFx22WWGNIqIPBSOlzzVljITTiZIisINqe/NQa4l48ksZTyKyB7fPOIlh+IaocUsFTBfRFlQuDHkFyUmJmLBggW47777jLgcEYEoHYrDNUvRwqEFRUmAcCPTCE2IATx+h2Iao8aidCgWF91Kn7mEglTCQEeGYhErmqUMuzsLCgpQUFBg1OWICEPdoVjnRcgspQl57hUP+dyYik0eLRWUxI/GaI0J8A8Rx7Hoc0NCexgoxmXVSfxEyCwF4Pnnn1e8ZowhNzcXb731FkaPHm1Yw4jIQr4I+Go51ixaiua0kMjz3FASP3ORxjXvM7lSnhtjCdDWihoEMYqHhnUYaNCAB2rVreizp1u4eeaZZxSvbTYbmjRpgsmTJ2Pu3LmGNYyILGyS5gbhh4KT5kYTgSUBAHK8NAu5udXLAjMUW29BqH2UwqKoQaggs1T4aMhQHGyWst4Eolu4OXDggBntICIc0WRLZinzkWvJxBo8dhv1lxnIq4LzlMTPeAIWYnGRFUOUSSMZBjoyFIuQzw2AG264AUVFRUHHS0pKcMMNNxjSKCLykOe58Uqh4BQtZQZ+nxtyKDYbm02mJeMZGCOHYkMJWIgDF1mSbcJAU54bipYK4o033kBZWVnQ8bKyMrz55puGNIqIPOSFM5kULaXzIqS50YRNFnbvDwWvyxZZF0VB2KAkfrTy1hx1s5QIhYKHQRjRUk4LCjeazVKFhYVgTFi4ioqKEB0dLb3n9XqxYsUKpKWlmdJIov6jmqG4Jj435KwZEkX5BSmJn/Ump/qA3CxF5RdMIMAs5YwKEG5IdaOfsPLcWK+fNQs3ycnJ4DgOHMehffv2Qe9zHIcFCxYY2jgicpCHgnvDjpYizY0WyKG49pAc5SnPjTlw1Wluarc51kB7hmIRK26ONAs3a9asAWMMF1xwAT766COkpqZK7zmdTrRs2RJNmzY1pZFE/UfVLEXRUqYQqE0QjtEqYAaKUHBGmhvjUQ8FF6FxHQbhmKWirNfPmoWbIUOGABCipVq0aEEheoQC9cKZOi9Cwo0mFInlyCxlKvaAvlZES5HptOaEiJYSIeEmDDSY94PMUhacPzQJN9u2bcM555wDm82GgoICbN++PeS53bp1M6xxROTg19xAVjizJtFSNKmFQmGWIodiU5FngyazlBmQWcpwtCTxC4qWsl5HaxJuevTogby8PKSlpaFHjx7gOE4yPcjhOA5er9fwRhL1H3FO8rKaFM4kzY0WpArsMi0Z5QMxB04mSPIULWU8ins+ON8Kjesw0DCPBg7dBhstdeDAATRp0kT6myACUVQFD9fJVUN+BsLv5MqotpTpKPI38YG1pajPa0xQ+QVbwNvUx7rRkKGYoqV8tGzZUvVvghCROxSLZindE5ONkvhpgVM4bwvHKImfOUhmKV6t/AKN0ZqjNEsFahBIZg+DMJL4NdjyC59//rnmC44bNy7sxhCRS+AOFwjHLEULhxbECV8svQCQ5sYsOIV/Ew+FMZ7GaM2pxqGYxnUYhBEt1WCFm/Hjx2u6GPncNFzsCm1CmCUByOdGE6LQWCEmFAItAmahFNpBtaWMJiCyxxEQkkzRUmEQRm2pBlsVnOf56k8iGjTyZGd+s5TOi5BwowlRaCTNjfnIzVJ8YIZiCgU3gOp8bmq5OVYgrMKZ1ptvrfeLiDpBygfiq8EDUOFMsxC71SPbdNAO1xwCs0GTz43BBJZfILOUAVQvgFNV8BCsXr0al1xyCdq0aYM2bdrgkksuwXfffWd024gIQtLc8PCbpfROTFRbShN+sxRpbsxGnjCRD0ziR8JNzQk0S1ESv5qjRXMTcJiqggN46aWXcNFFFyEhIQG33XYbbrvtNiQmJmLMmDF48cUXzWgjEQEo8txISfx0XoTMUpoQJ6ZKj19zY0WbeX1A7GueqVUFpzFac5Sam8CQZBrWYUBmKQA6yi+IPPLII3jmmWcwY8YM6djMmTMxYMAAPPLII5g+fbqhDSQiA4VZyifd1CwUnGa1UIgTU6XPodhu4ygfiEkEZoNmlMTPWKrJc0OamzAII0MxmaUA5Ofn46KLLgo6PnLkSBQUFBjSKCLyUDoUG2CWol1xSDgV4YYwh8A6XjyjMWoeanluaGzrJgyzlBU1N7p/0bhx4/DJJ58EHf/ss89wySWXGNIoIvKQa25Y2GYpUvlrQezXSm+YIfeEZqRSF7yQDVqZ54b6vcYEJJyj8gsGoJhH1U+hUHAVOnfujIcffhg5OTno168fAOCXX37BunXr8H//9394/vnnpXNnzpxpXEuJeo1dciiuSRI/MktpwR6gubHixFRfEMc1Y4DHy5PPjdEo7nMOjigKBa8xGjQ3gRsiK2pudAs3S5YsQUpKCnbu3ImdO3dKx5OTk7FkyRLpNcdxJNw0INTMUjYyS5mCaJYSk/jZLWgvry/IzVKewCR+FNFnAFVnKCazVBiQQzGAMIQbKpxJqGGMWYqEGy1IZikPaW7MhpOZpRhDgEMxjdEaQ3lujEdLVfCgUHDr9TPdnYQhyDU3YSfxo8KZmvBHS1FFcLNRmKV4MksZTjV5bkhxEwYa8oUFm6Ws19G6NTeMMXz44YdYs2YNTpw4EVSa4eOPPzascUTk4K8tBb9ZimpLmYIY6SCZpWgFMA1FtBRj4G00Ro0l0CxFtaVqTjih4NYby7qFm1mzZuHll1/GsGHDkJ6eTvk1CAD+JH5kljKfwHuOfG7Mw1/qQhjUPOW5MZZq8tyQ4B4GWsxSAd0aFRgbbgF0CzdvvfUWPv74Y4wZM8aM9hARimiWqqxJvSMSaDQRHMZJ/WYWgYsr+dwYTUC0FDkU1xwNKTUCTdnOKOv1s+67MykpCa1btzajLUQEYw/wAwEoWsosAhdc8rkxj8DFlYQbg6kmzw11cRgE9KkaDWGDpPsX3X///ViwYAHKysrMaA8RoYgLrMcr19zovAgJN5oI7FeKljKPwEWAHIoNppo8N2SWCgNNoeDK11aMltJtlpowYQLee+89pKWlITs7Gw6HQ/H+pk2bDGscETkERvDIj2m/CEVLaSHQ54ZU9+YRuKElnxujUQqLVH7BALjqxyjHceA4SP6Rgf1uBXQLN5MnT8bGjRtx3XXXkUMxISFqbiq9BvnckHATkoaw66ovBI9hcVxSnxtCwEIc5HND04B+NM6jNo6T0nZEkXADfPXVV1i1ahUGDhxoRnuICEX0r/HIHYr13i8abMVEsC8T+dyYR5DPjThGSfg2hkCzFIWC1xzNwg3g9f1txQ2S7js0KysLiYmJZrSFiGBUHYprVFuKFo9QkM9N7REkoItjmsanQVD5BcPRkMQPUPatFc1Sun/RU089hf/85z84ePCgCc0hIhXx3iCzlPkE9istAOYR1LeS5ob63BACwpadUYHCTS23xwroMEuJWHGDpNssdd1116G0tBRt2rRBbGxskEPxmTNnDGscETmIN4pHobnReREN+RkIlTBOC6qU6wuqwg0DjU+jCOhHueaG44Kd5wkN6DBLAUI/W9G0rVu4efbZZ01oBhHpBDoUhzUxUbSUJgIXXDt5XZpG0JzPcSTcGIrSLCUX1EkjGS7aNomi757DZrOkEBlWtBRBBCLlueHDrCsFkEOxRoJTp1NfmUVgyCzIodhYAhyK5b4flOMmTDSEggP+Odqqml/dwo2c8vJyVFRUKI6Rs3HDxJ/npgbFHDU6wjV0gjU31FdmYuc4eETpRhqj1OfGELq2FMk2YaLRLCXOG1YsmgmE4VBcUlKCGTNmIC0tDXFxcUhJSVE8iIaJP0OxsAiENTFRtJQmAq1QtMM1F5uaLxiNT2MI0NbabZxkCiSzVJjo9LkJDL+3Crrv0P/85z/4/vvvsWjRIrhcLrz22mtYsGABmjZtijfffNOMNhIRQKDmpuZmKVo8QhGkubHo5FRfUGr5KVrKUALMUoBfk0AayTDRaN4X/WysWFcKCEO4+eKLL/DSSy/hH//4B6KiojBo0CDce++9eOSRR/DOO++E1YgXX3wR2dnZiI6ORt++fbFhwwZNn1u+fDk4jsP48ePD+l7COAIdisOamEi40URw0TtaBMxEMZZJc2MwwX0r+t2Q/BgmKgKjGqLG12HBiuBAGMLNmTNnpKrgiYmJUuj3wIED8eOPP+puwPvvv4/Zs2dj/vz52LRpE7p3745Ro0bhxIkTVX7u4MGDmDNnDgYNGqT7OwnjEc22NTNLUSi4FgJlGdrhmou6WYr63BBUnF/F4plklgoTvWYp0twItG7dGgcOHAAAdOzYER988AEAQaOTnJysuwFPP/00br75ZkydOhWdO3fG4sWLERsbi9dffz3kZ7xeL6699losWLBAErSIukUyS/E1MEtRKLgmSHNTu6ibpWh8GoJKEIHoA0JCe5hoFG5EsxQ5FPuYOnUqtm7dCgC466678OKLLyI6Ohq333477rjjDl3XqqiowMaNGzFixAh/g2w2jBgxAuvXrw/5uQceeABpaWm48cYbq/0Ot9uNwsJCxYMwHr9Ziile64JCwTVB0VK1i9IsReUXjEVFc2MXNTd10R4LoDNaikLBfdx+++3S3yNGjMCff/6JjRs3om3btujWrZuua506dQperxfp6emK4+np6fjzzz9VP/PTTz9hyZIl2LJli6bvWLhwIRYsWKCrXYR+RPutV8pzE8ZFyOdGE4FyHwk35iIXJjkbaW4MReEeovS5IbNUmOg0S1mxIjhQwzw3ANCyZUu0bNnSiLZUS1FREa6//nq8+uqraNy4sabPzJ07F7Nnz5ZeFxYWIisry6wmNlgCK1WHlfFSEQpOE1soAvvaqtEO9QWbmlmK8twYg4pZStQkkHBjABqS+DlJc2M8jRs3ht1ux/HjxxXHjx8/joyMjKDz9+3bh4MHD2Ls2LHSMd7n4xEVFYXdu3ejTZs2is+4XC64XC4TWk/ICdQe1DiJH+2MQ0IOxbWLYpElzY3BkFnKcLRqbkSzlEU3R3X6q5xOJ3r16oXVq1dLx3iex+rVq9GvX7+g8zt27Ijt27djy5Yt0mPcuHEYNmwYtmzZQhqZOiS4UnUYFyHhRhOBgiMJN+aiMEuJ2kUan8ZQRZ6bQA0loRHdZilr9nOdam4AYPbs2Zg8eTJ69+6NPn364Nlnn0VJSQmmTp0KAJg0aRKaNWuGhQsXIjo6Guecc47i82KEVuBxonYJjNgJyywlj5YitX9IAvuWhBtzUTVLkcnEIII1N+RzU0M0CzfK/rYadS7cXHXVVTh58iTmzZuHvLw89OjRAytXrpScjA8fPgybRdVmViIwnDC8aCnKc6OFwK6lUHBzUWgQbCTcGIpKhKSYVI6GdZhojDqlwpkq7Nu3D0uXLsW+ffvw3HPPIS0tDV9//TVatGiBLl266L7ejBkzMGPGDNX3cnJyqvzssmXLdH8fYTzOgCyXZJYyDwoFr12UZinyuTEUMksZj9SnVfefKKdTnhsfP/zwA7p27Ypff/0VH3/8MYqLiwEAW7duxfz58w1vIBEZBN4g4dWWoiR+WqAkfrWLXHiUFlwanwZRlUMxjeuw0CiA2wP622ro/lV33XUXHnroIXz77bdwOp3S8QsuuAC//PKLoY0jIocg4YZqS5lGYNfQDtdcKEOxiaiYop0ULVUzNI5Rf+FMa3a07jt0+/btuOyyy4KOp6Wl4dSpU4Y0iog8Au22ZJYyD9Lc1C7KJH6idpH63BCqKL9Ampsw0ej0LtWWirLmXKv7VyUnJyM3Nzfo+ObNm9GsWTNDGkVEHoEe9zWvLUUTWyiCQ8GtOTnVF+wK4YY0N8ZCZinD0WqW8kk3DotujnTfoVdffTXuvPNO5OXlgeM48DyPdevWYc6cOZg0aZIZbSQiAGN8bqi2lBYCu4Y0N+aiNEtRnhtDUXEoFssBkKN8DdFqliKfG4FHHnkEHTt2RFZWFoqLi9G5c2cMHjwY/fv3x7333mtGG4kIINjnJoyLkFlKExQtVbvI+9tGmhuDUfO5oVDwGqFRcyOZpSwq3OgOBXc6nXj11Vdx3333YceOHSguLkbPnj3Rrl07M9pHRAiOIJ+bcPPccAAYLR5VQOUXahd5//rNUnXUGKvBhTZLhZUIlJDNnVX3n2SWojw3Slq0aIEWLVoY2RYiguE4Dg47h0ovk16HdyEbwLwk3FQBaW5qF0WGYtLcGItanpsoMkvVCM2aG2uHgmsSbuRVtavj6aefDrsxRGTjsNtQ6fUCAMLeDJBwUy3kc1O7yAV1G4WCGwwVzjQcjdFSfp8ba3a0JuFm8+bNitebNm2Cx+NBhw4dAAB79uyB3W5Hr169jG8hETEIk5Ig3IQd6WCzA3wlSO8fGo7jwHEAE5RktMM1GXWzFAk3hqDiZyf63JBZKkzEfqs2iZ/w7LBotKUm4WbNmjXS308//TQSEhLwxhtvICUlBQBw9uxZTJ06FYMGDTKnlUREILfdhi3c0M5YE3aOg8cn3URZdHKqLyhLS1GeG0NRmSdEzU1gygNCI7rNUtbsZ92z4lNPPYWFCxdKgg0ApKSk4KGHHsJTTz1laOOIyEJuuw17vSXhRhNy4dGiJvN6g1yDQJobo6nCLEVdHB5ak/jZrB0KrtuhuLCwECdPngw6fvLkSRQVFRnSKCIyUQg3NTFLyZ8JVeTdS0n8zMWuECQpz42hVOFQTEn8wkTjBvGSbpk4erYMA9s2roVG1T66hZvLLrsMU6dOxVNPPYU+ffoAAH799VfccccduPzyyw1vIBE5GGKW6nsLcGInkNLKoFZZE3n/kkOxudgUbiGkuTGUKnxuSLgJE40+N5f2aIZLe1i3qoBu4Wbx4sWYM2cOJk6ciMrKSuEiUVG48cYb8cQTTxjeQCJyUJqlwpyYhs01qDXWxqbQ3NAiYCY2VbMU9bkxBJul2qcngOOADhkJddSmSIcq1wNhCDexsbF46aWX8MQTT2Dfvn0AgDZt2iAuLs7wxhGRhTNKbpaqw4Y0AJQ+N9TZZqLoazuZpQxFxSzVs0UKNt17IZJjHXXTpkhHYxI/qxN2Er+4uDikpqZKfxOEIT43hCbkmjESbsxFES2l0VmT0Eqw5gYAUuKcddAWi0BBGQDCiJbieR4PPPAAkpKS0LJlS7Rs2RLJycl48MEHwfO8GW0kIgS57wcJN+YiX3DJ58Zc5MKjzU67YkOhenLGQwI4gDA0N/fccw+WLFmCRx99FAMGDAAA/PTTT7j//vtRXl6Ohx9+2PBGEpEBmaVqDzJL1R6KDMUULWUsKmYpooaQ5gZAGMLNG2+8gddeew3jxo2TjnXr1g3NmjXDrbfeSsJNA4bMUrUHp4iWatiTmNkoaktF+cwldjKbGIO6WYqoAVK0VMPuT93CzZkzZ9CxY8eg4x07dsSZM2cMaRQRmchDwUmbYC7KrLl1146GgHwsFzUfCnS7Cuh+Td01yEqQ5sZ40joBCZlAm+F13ZI6Rfe02L17d7zwwgtBx1944QV0797dkEYRkYlcc9PANw2mYyPNTa2hyFAcmwJc/grQZlgdtshCyCeKBm5GMYyYFOD2ncDFT9Z1S+oU3Zqbxx9/HBdffDG+++479OvXDwCwfv16HDlyBCtWrDC8gUTk4CSzVK1BeW5qD/lYtmqRwbqDzFKmQONUv+ZmyJAh2LNnDy677DLk5+cjPz8fl19+OXbv3k2FMxs4cs0NLbjmIg8Fp2gpc7GTIGkeZJYiTCKsPDdNmzYlx2EiiCjZKkCbMHOhaKnaQ6G5sWgF5TpDEQpOfUsYR1jCTXl5ObZt24YTJ04E5baRR1ERDQuKlqo9yCxVeygi0yxaQbnuILMUYQ66hZuVK1di0qRJOHXqVNB7HMfB6/Ua0jAi8pDnubHTRGUqVDiz9pDLM9TXBkNmKcIkdG9D/v3vf+PKK69Ebm4ueJ5XPEiwadgoqoLTBtdUONLc1BoKQZLMUgZDmhvCHHQvQcePH8fs2bORnp5uRnuICEYZCk4TlZlQKHjtoXTepr42FCq/QJiE7tF0xRVXICcnx4SmEJGOIlqKhBtTUVaqpr42E6rjZSJkliJMQrfPzQsvvIArr7wSa9euRdeuXeFwKMvSz5w507DGEZGFMs9NHTakAaCoCk6CpKmQWcpMyCxFmINu4ea9997DN998g+joaOTk5Cizd3IcCTcNGGUoOE1UZkLRUrWHMhScTCeGQpobwiTCqgq+YMEC3HXXXbCR/ZmQQUn8ag+Klqo9KKeQiZDPDWESukdTRUUFrrrqKhJsiCDILFV7iP3LcUoTFWE85HNTS5C2lzAQ3RLK5MmT8f7775vRFiLCcUTJQsFpojIV0exH/jbmI2promwcmVuNhsxShEnoNkt5vV48/vjjWLVqFbp16xbkUPz0008b1jgisqBQ8NpDVCCQmcR8JEGS+tp4qPwCYRK6hZvt27ejZ8+eAIAdO3Yo3qMFrWGj9Lmpw4Y0AETNGJlJzEfsYnImNgN5tBT1L2EcuoWbNWvWmNEOwgI4qbZUrSH62ZA2wXwksxSFgRsPzROESZCoTBgGhYLXHqJMQ4UczYcjLZmJUJ4bwhxoZiQMgzIU1x6iZow0ZOYjCZIUIWo8ClMUjWXCOOhuJQzDQaHgtQb53NQeoqBOZikT4MjnhjAHGk2EYSh8bmjRNRVxTSCfG/Ox2UiQNA8ySxHmQMINYRiU56b2sJE2odbw9zVNl4ZDeW4Ik6C7lTAMMkvVHpTnpvbw+9xQXxsO5bkhTIKEG8IwKBS89hCFGnLcNh/SkpkJ+dwQ5kCjiTAM+eRPPjfmQllzaw+/zw1Nl4ZDZinCJOhuJQxDUX6hDtvREPDnuaGeNht/hmLqa+Mhh2LCHEi4IQxDLtzwjNVhS6yPTdLc0C1sNjbSkpkHaW4Ik6CZkTAMuc+NlyfhxkykBZfWA9MRzVJUW8oEKM8NYRI0mgjDkKvtvaS5MRVxTSA/EPOhaCkzIbMUYQ40MxKGIVfbe70k3JgJmUpqj6QYBwAgOdZZxy2xIFR+gTAJ3VXBCSIU8mKZpLkxF6pUXXtc2DkdCy/visHtm9R1U6wHR5obwhxIuCFMgXxuzIXKL9Qerig7runToq6bYVFIuCHMgcxShCl4SLgxFb9DMS0IRARD0VKESZBwQ5gCT8KNqVD5BcISUPkFwiRIuCFMgTQ35kIlAQhrQJobwhxIuCFMgXxuzIWjJH6EFaA8N4RJ0GgiTIEyFJuLmE+Ocq8QkQ05FBPmQMINYQpkljIX0SxF1deJiIby3BAmQcINYQqkuDEXyeeGNDdEJEN5bgiTIOGGMJTZF7ZHeqILM4e3reumWBopzw05FBMRDfncEOZASfwIQ5k5vB3+fUFbRbZiwnhIc0NYAi7kC4KoEfVCVH7xxReRnZ2N6Oho9O3bFxs2bAh57quvvopBgwYhJSUFKSkpGDFiRJXnE7UPCTbmQ3luCEtAeW4Ik6hz4eb999/H7NmzMX/+fGzatAndu3fHqFGjcOLECdXzc3JycM0112DNmjVYv349srKyMHLkSPz999+13HKCqDsSoh2KZ4KITMgsRZgDx1jdun727dsX5513Hl544QUAAM/zyMrKwr///W/cdddd1X7e6/UiJSUFL7zwAiZNmlTt+YWFhUhKSkJBQQESExNr3H6CqAvOlFTg401HMb5nMzSOd9V1cwgiPPbnAG9eKvx97UdAuxF12hyifqNn/a5TUbmiogIbN27EiBH+AW2z2TBixAisX79e0zVKS0tRWVmJ1NRU1ffdbjcKCwsVD4KIdFLjnLhpUGsSbIjIRmGWqrtmENajToWbU6dOwev1Ij09XXE8PT0deXl5mq5x5513omnTpgoBSc7ChQuRlJQkPbKysmrcboIgCMIIqPwCYQ4RbeR89NFHsXz5cnzyySeIjo5WPWfu3LkoKCiQHkeOHKnlVhIEQRCqUPkFwiTqNBS8cePGsNvtOH78uOL48ePHkZGRUeVnn3zySTz66KP47rvv0K1bt5DnuVwuuFykuicIgqh/UBI/whzqVFR2Op3o1asXVq9eLR3jeR6rV69Gv379Qn7u8ccfx4MPPoiVK1eid+/etdFUgiAIwmio/AJhEnWexG/27NmYPHkyevfujT59+uDZZ59FSUkJpk6dCgCYNGkSmjVrhoULFwIAHnvsMcybNw/vvvsusrOzJd+c+Ph4xMfH19nvIAiCIHRC5RcIk6hz4eaqq67CyZMnMW/ePOTl5aFHjx5YuXKl5GR8+PBh2Gx+6X7RokWoqKjAFVdcobjO/Pnzcf/999dm0wmCIIgaQT43hDnUeZ6b2oby3BAEQdQTjmwAllwo/D1lBZA9oG7bQ9RrIibPDUEQBNGAofILhEnUuVmqvuL1elFZWVnXzahzHA4H7HZ7XTeDIAhLQnluCHMg4SYAxhjy8vKQn59f102pNyQnJyMjI4MKYhIEYSwK2YYMCYRxkHATgCjYpKWlITY2tkEv6IwxlJaWSkVMMzMz67hFBEFYC4qWIsyBhBsZXq9XEmwaNWpU182pF8TExAAATpw4gbS0NDJREQRhHJTnhjAJ0gPKEH1sYmNj67gl9QuxP8gHiSAIQ6E8N4RJkHCjQkM2RalB/UEQhDmQcEOYAwk3BEEQRN1AZinCJEi4sQgLFy7Eeeedh4SEBKSlpWH8+PHYvXu34pzs7GxwHAeO4xATE4Ps7GxMmDAB33//fR21miCIBg2ZpQiTIOHGIvzwww+YPn06fvnlF3z77beorKzEyJEjUVJSojjvgQceQG5uLnbv3o0333wTycnJGDFiBB5++OE6ajlBEA0XynNDmANFS1mElStXKl4vW7YMaWlp2LhxIwYPHiwdT0hIQEZGBgCgRYsWGDx4MDIzMzFv3jxcccUV6NChQ622myCIBgxHtaUIc6DRVA2MMZRWeOrkUZOyXwUFBQCA1NTUas+97bbbwBjDZ599Fvb3EQRB6IbKLxAmQZqbaiir9KLzvFV18t07HxiFWKf+/yKe5zFr1iwMGDAA55xzTrXnp6amIi0tDQcPHgyjlQRBEOFCZinCHEi4sSDTp0/Hjh078NNPP2n+DGOMQr4JgqhdyKGYMAkSbqohxmHHzgdG1dl362XGjBn48ssv8eOPP6J58+aaPnP69GmcPHkSrVq10v19BEEQ4UM+N4Q5kHBTDRzHhWUaqm0YY/j3v/+NTz75BDk5OboEleeeew42mw3jx483r4EEQRCBcGSWIsyh/q/ahCamT5+Od999F5999hkSEhKQl5cHAEhKSpLqQwFAUVER8vLyUFlZiQMHDuDtt9/Ga6+9hoULF6Jt27Z11XyCIBoiZJYiTIL0gBZh0aJFKCgowNChQ5GZmSk93n//fcV58+bNQ2ZmJtq2bYvrr78eBQUFWL16Ne688846ajlBEA0X0twQ5kCaG4ugJWycoqEIgqhXKELBaa9NGAeNJoIgCKJuILMUYRIk3BAEQRB1BAk0hDmQcEMQBEHUDaS5IUyChBuCIAiibiCfG8IkaDQRBEEQdQRFSxHmQMINQRAEUTeQWYowCRJuCIIgiDqCyi8Q5kCjiSAIgqgbFAINaW4I4yDhhiAIgqgbyCxFmAQJNwRBEEQdQQ7FhDmQcGMRFi1ahG7duiExMRGJiYno168fvv76a+n97OxscBwHjuMQExOD7OxsTJgwAd9//30dtpogiAYNRz43hDnQaLIIzZs3x6OPPoqNGzfi999/xwUXXIBLL70Uf/zxh3TOAw88gNzcXOzevRtvvvkmkpOTMWLECDz88MN12HKCIBosZJYiTIIKZ1qEsWPHKl4//PDDWLRoEX755Rd06dIFAJCQkICMjAwAQIsWLTB48GBkZmZi3rx5uOKKK9ChQ4dabzdBEA0ZMksR5kCam+pgDKgoqZuHhkrfani9XixfvhwlJSXo169flefedtttYIzhs88+C+u7CIIgwoY0N4RJkOamOipLgUea1s13330McMZpPn379u3o168fysvLER8fj08++QSdO3eu8jOpqalIS0vDwYMHa9hYgiAInVD5BcIkaDRZiA4dOmDLli349ddfccstt2Dy5MnYuXNntZ9jjIGjXRNBELUOzTuEOZDmpjocsYIGpa6+WwdOpxNt27YFAPTq1Qu//fYbnnvuObz88sshP3P69GmcPHkSrVq1qlFTCYIgdENmKcIkSLipDo7TZRqqT/A8D7fbXeU5zz33HGw2G8aPH187jSIIgpAgh2LCHEi4sQhz587F6NGj0aJFCxQVFeHdd99FTk4OVq1aJZ1TVFSEvLw8VFZW4sCBA3j77bfx2muvYeHChZLGhyAIotZQ+NyQcEMYBwk3FuHEiROYNGkScnNzkZSUhG7dumHVqlW48MILpXPmzZuHefPmwel0IiMjA+effz5Wr16NYcOG1WHLCYJosDiigY6XALwHcCXWdWsIC0HCjUVYsmRJle9TNBRBEPWSq9+p6xYQFoSipQiCIAiCsBQk3BAEQRAEYSlIuCEIgiAIwlKQcEMQBEEQhKUg4YYgCIIgCEtBwo0KLMyClVaF+oMgCIKIJEi4keFwOAAApaWlddyS+oXYH2L/EARBEER9hvLcyLDb7UhOTsaJEycAALGxsQ26oCRjDKWlpThx4gSSk5Nht9vrukkEQRAEUS0k3ASQkZEBAJKAQwDJyclSvxAEQRBEfYeEmwA4jkNmZibS0tJQWVlZ182pcxwOB2lsCIIgiIiChJsQ2O12WtQJgiAIIgIhh2KCIAiCICwFCTcEQRAEQVgKEm4IgiAIgrAUDc7nRkxIV1hYWMctIQiCIAhCK+K6rSWxbIMTboqKigAAWVlZddwSgiAIgiD0UlRUhKSkpCrP4VgDy63P8zyOHTuGhISEiErQV1hYiKysLBw5cgSJiYl13Zx6B/VP1VD/VA31T9VQ/1QP9VHVGNE/jDEUFRWhadOmsNmq9qppcJobm82G5s2b13UzwiYxMZFunCqg/qka6p+qof6pGuqf6qE+qpqa9k91GhsRcigmCIIgCMJSkHBDEARBEISlIOEmQnC5XJg/fz5cLlddN6VeQv1TNdQ/VUP9UzXUP9VDfVQ1td0/Dc6hmCAIgiAIa0OaG4IgCIIgLAUJNwRBEARBWAoSbgiCIAiCsBQk3BAEQRAEYSlIuKkDfvzxR4wdOxZNmzYFx3H49NNPq/3MO++8g+7duyM2NhaZmZm44YYbcPr0acU5zz77LDp06ICYmBhkZWXh9ttvR3l5uUm/wjzC6Z8XX3wRnTp1QkxMDDp06IA333wz6Jz//e9/6NixI6Kjo9G1a1esWLHChNabjxn98+qrr2LQoEFISUlBSkoKRowYgQ0bNpj0C8zFrPEjsnz5cnAch/HjxxvX6FrErP7Jz8/H9OnTkZmZCZfLhfbt29M9FoAV5uiFCxfivPPOQ0JCAtLS0jB+/Hjs3r272s9VN/8yxjBv3jxkZmYiJiYGI0aMwF9//RV+QxlR66xYsYLdc8897OOPP2YA2CeffFLl+T/99BOz2WzsueeeY/v372dr165lXbp0YZdddpl0zjvvvMNcLhd755132IEDB9iqVatYZmYmu/32203+Ncajt39eeukllpCQwJYvX8727dvH3nvvPRYfH88+//xz6Zx169Yxu93OHn/8cbZz50527733MofDwbZv327yrzEeM/pn4sSJ7MUXX2SbN29mu3btYlOmTGFJSUns6NGjJv8a4zGjf0QOHDjAmjVrxgYNGsQuvfRSc36AyZjRP263m/Xu3ZuNGTOG/fTTT+zAgQMsJyeHbdmyxeRfYw5m9JFV5uhRo0axpUuXsh07drAtW7awMWPGsBYtWrDi4uKQn9Ey/z766KMsKSmJffrpp2zr1q1s3LhxrFWrVqysrCysdpJwU8douXGeeOIJ1rp1a8Wx559/njVr1kx6PX36dHbBBRcozpk9ezYbMGCAYW2tC7T0T79+/dicOXMUxwJ/+4QJE9jFF1+sOKdv377sn//8p2FtrQuM6p9APB4PS0hIYG+88YYRzawzjOwfj8fD+vfvz1577TU2efLkiBVu5BjVP4sWLWKtW7dmFRUVZjSzTjGqj6w6R584cYIBYD/88EPIc6qbf3meZxkZGeyJJ56Q3s/Pz2cul4u99957YbWLzFIRQL9+/XDkyBGsWLECjDEcP34cH374IcaMGSOd079/f2zcuFEyJezfvx8rVqxQnGNV3G43oqOjFcdiYmKwYcMGVFZWAgDWr1+PESNGKM4ZNWoU1q9fX2vtrCu09E8gpaWlqKysRGpqam00sU7R2j8PPPAA0tLScOONN9Z2E+sULf3z+eefo1+/fpg+fTrS09Nxzjnn4JFHHoHX662LJtc6WvrIqnN0QUEBAFQ5V1Q3/x44cAB5eXmKc5KSktC3b9+w52gSbiKAAQMG4J133sFVV10Fp9OJjIwMJCUl4cUXX5TOmThxIh544AEMHDgQDocDbdq0wdChQ3H33XfXYctrh1GjRuG1117Dxo0bwRjD77//jtdeew2VlZU4deoUACAvLw/p6emKz6WnpyMvL68umlyraOmfQO688040bdo0aEKyIlr656effsKSJUvw6quv1nFrax8t/bN//358+OGH8Hq9WLFiBe677z489dRTeOihh+q49bWDlj6y4hzN8zxmzZqFAQMG4Jxzzgl5XnXzr/hs5BxNwk0EsHPnTtx2222YN28eNm7ciJUrV+LgwYP417/+JZ2Tk5ODRx55BC+99BI2bdqEjz/+GF999RUefPDBOmx57XDfffdh9OjROP/88+FwOHDppZdi8uTJAIQq8A0dvf3z6KOPYvny5fjkk0+CdqNWpLr+KSoqwvXXX49XX30VjRs3ruPW1j5axg/P80hLS8Mrr7yCXr164aqrrsI999yDxYsX12XTaw0tfWTFOXr69OnYsWMHli9fXtdNCSYsYxZhGNBgz73uuuvYFVdcoTi2du1aBoAdO3aMMcbYwIEDg2y+b731FouJiWFer9fQNtcmWvpHpKKigh05coR5PB7JwU/87VlZWeyZZ55RnD9v3jzWrVs3g1tcuxjVPyJPPPEES0pKYr/99psJra19jOifzZs3MwDMbrdLD47jGMdxzG63s71795r7I0zEqPEzePBgNnz4cMX5K1asYACY2+02utm1ilF9ZLU5evr06ax58+Zs//791Z5b3fy7b98+BoBt3rxZcc7gwYPZzJkzw2ofbWsjgNLS0qAdtt1uByCEz2k9x+o4HA40b94cdrsdy5cvxyWXXCL1Sb9+/bB69WrF+d9++y369etXF02tE6rqHwB4/PHH8eCDD2LlypXo3bt3Hba0bgjVPx07dsT27duxZcsW6TFu3DgMGzYMW7ZsQVZWVl03vVaoavwMGDAAe/fuBc/z0vl79uxBZmYmnE5nXTW51qmqj6wyRzPGMGPGDHzyySf4/vvv0apVq2o/U93826pVK2RkZCjOKSwsxK+//hr+HB2WSETUiKKiIrZ582ZpR/j000+zzZs3s0OHDjHGGLvrrrvY9ddfL52/dOlSFhUVxV566SW2b98+9tNPP7HevXuzPn36SOfMnz+fJSQksPfee4/t37+fffPNN6xNmzZswoQJtf77aore/tm9ezd766232J49e9ivv/7KrrrqKpaamsoOHDggnbNu3ToWFRXFnnzySbZr1y42f/78iA0FN6N/Hn30UeZ0OtmHH37IcnNzpUdRUVFt/7waY0b/BBLJ0VJm9M/hw4dZQkICmzFjBtu9ezf78ssvWVpaGnvooYdq++cZghl9ZJU5+pZbbmFJSUksJydHMVeUlpZK51x//fXsrrvukl5rmX8fffRRlpyczD777DO2bds2dumll1IoeKSxZs0aBiDoMXnyZMaYMHEOGTJE8Znnn3+ede7cmcXExLDMzEx27bXXKnKQVFZWsvvvv5+1adOGRUdHs6ysLHbrrbeys2fP1t4PMwi9/bNz507Wo0cPFhMTwxITE9mll17K/vzzz6DrfvDBB6x9+/bM6XSyLl26sK+++qqWfpGxmNE/LVu2VL3m/Pnza++HGYRZ40dOJAs3ZvXPzz//zPr27ctcLhdr3bo1e/jhh5nH46mlX2UsZvSRVeZotX4BwJYuXSqdM2TIEKmvRKqbf3meZ/fddx9LT09nLpeLDR8+nO3evTvsdnK+xhIEQRAEQVgC8rkhCIIgCMJSkHBDEARBEISlIOGGIAiCIAhLQcINQRAEQRCWgoQbgiAIgiAsBQk3BEEQBEFYChJuCIIgCIKwFCTcEAQBQEirPm3aNKSmpoLjOGzZsqWum1QvmTJlCjiOA8dx+PTTTw29dk5OjnTt8ePHG3ptgqgpP/74I8aOHYumTZuGNf7Ly8sxZcoUdO3aFVFRUdWO8XXr1iEqKgo9evTQ3VYSbgiCAACsXLkSy5Ytw5dffonc3Fycc845dd2kestFF12E3NxcjB49WjoWarKfMmWKZkGlf//+yM3NxYQJEwxqKUEYR0lJCbp3744XX3wxrM97vV7ExMRg5syZGDFiRJXn5ufnY9KkSRg+fHhY30XCDUEQAIB9+/YhMzMT/fv3R0ZGBqKiooLOqaioqIOW1T9cLhcyMjLgcrkMva7T6URGRgZiYmIMvS5BGMHo0aPx0EMP4bLLLlN93+12Y86cOWjWrBni4uLQt29f5OTkSO/HxcVh0aJFuPnmm5GRkVHld/3rX//CxIkTwy6cScINQRCYMmUK/v3vf+Pw4cPgOA7Z2dkAgKFDh2LGjBmYNWsWGjdujFGjRgEAduzYgdGjRyM+Ph7p6em4/vrrcerUKel6JSUlmDRpEuLj45GZmYmnnnoKQ4cOxaxZs6Rz1DQdycnJWLZsmfT6yJEjmDBhApKTk5GamopLL70UBw8eVLR7/PjxePLJJ5GZmYlGjRph+vTpqKyslM5xu9248847kZWVBZfLhbZt22LJkiVgjKFt27Z48sknFW3YsmULOI7D3r17a9apKhw8eFAyO8kfQ4cONfy7CKK2mTFjBtavX4/ly5dj27ZtuPLKK3HRRRfhr7/+0nWdpUuXYv/+/Zg/f37YbSHhhiAIPPfcc3jggQfQvHlz5Obm4rfffpPee+ONN+B0OrFu3TosXrwY+fn5uOCCC9CzZ0/8/vvvWLlyJY4fP64wpdxxxx344Ycf8Nlnn+Gbb75BTk4ONm3apKtNlZWVGDVqFBISErB27VqsW7cO8fHxuOiiixQapDVr1mDfvn1Ys2YN3njjDSxbtkwhIE2aNAnvvfcenn/+eezatQsvv/wy4uPjwXEcbrjhBixdulTxvUuXLsXgwYPRtm1bnb1YPVlZWcjNzZUemzdvRqNGjTB48GDDv4sgapPDhw9j6dKl+N///odBgwahTZs2mDNnDgYOHBh0j1XFX3/9hbvuugtvv/22qvZYK+F/kiAIy5CUlISEhATY7fYgdXG7du3w+OOPS68feugh9OzZE4888oh07PXXX0dWVhb27NmDpk2bYsmSJXj77bcle/kbb7yB5s2b62rT+++/D57n8dprr4HjOACC4JGcnIycnByMHDkSAJCSkoIXXngBdrsdHTt2xMUXX4zVq1fj5ptvxp49e/DBBx/g22+/lWz8rVu3lr5jypQpmDdvHjZs2IA+ffqgsrIS7777bpA2RyvXXHMN7Ha74pjb7cbFF18MAIr+LS8vx/jx49GvXz/cf//9YX0fQdQXtm/fDq/Xi/bt2yuOu91uNGrUSNM1vF4vJk6ciAULFgRdRy8k3BAEUSW9evVSvN66dSvWrFmD+Pj4oHP37duHsrIyVFRUoG/fvtLx1NRUdOjQQdf3bt26FXv37kVCQoLieHl5Ofbt2ye97tKli0KgyMzMxPbt2wEIJia73Y4hQ4aofkfTpk1x8cUX4/XXX0efPn3wxRdfwO1248orr9TVVpFnnnkmyFHyzjvvhNfrDTr3hhtuQFFREb799lvYbKREJyKb4uJi2O12bNy4MUjAV5sr1CgqKsLvv/+OzZs3Y8aMGQAAnufBGENUVBS++eYbXHDBBZquRcINQRBVEhcXp3hdXFyMsWPH4rHHHgs6NzMzU7OvCsdxYIwpjsl9ZYqLi9GrVy+88847QZ9t0qSJ9LfD4Qi6Ls/zAKDJMfemm27C9ddfj2eeeQZLly7FVVddhdjYWE2/IZCMjIwgc1ZCQgLy8/MVxx566CGsWrUKGzZsCBLeCCIS6dmzJ7xeL06cOIFBgwaFdY3ExERpYyLy0ksv4fvvv8eHH36IVq1aab4WCTcEQeji3HPPxUcffYTs7GxVm3ibNm3gcDjw66+/okWLFgCAs2fPYs+ePQoNSpMmTZCbmyu9/uuvv1BaWqr4nvfffx9paWlITEwMq61du3YFz/P44YcfQoaejhkzRoriWLlyJX788cewvksrH330ER544AF8/fXXaNOmjanfRRBGUlxcrNi8HDhwAFu2bEFqairat2+Pa6+9FpMmTcJTTz2Fnj174uTJk1i9ejW6desmmWZ37tyJiooKnDlzBkVFRVI+rR49esBmswWloEhLS0N0dLTu1BSkCyUIQhfTp0/HmTNncM011+C3337Dvn37sGrVKkydOhVerxfx8fG48cYbcccdd+D777/Hjh07MGXKlCDTywUXXIAXXngBmzdvxu+//45//etfCi3Mtddei8aNG+PSSy/F2rVrceDAAeTk5GDmzJk4evSoprZmZ2dj8uTJuOGGG/Dpp59K1/jggw+kc+x2O6ZMmYK5c+eiXbt2YYeeamHHjh2YNGkS7rzzTnTp0gV5eXnIy8vDmTNnTPtOgjCK33//HT179kTPnj0BALNnz0bPnj0xb948AIJP3KRJk/B///d/6NChA8aPH4/ffvtN2uQAwmaiZ8+e+OKLL5CTk6O4npGQcEMQhC6aNm2KdevWwev1YuTIkejatStmzZqF5ORkSYB54oknMGjQIIwdOxYjRozAwIEDg3x3nnrqKWRlZWHQoEGYOHEi5syZozAHxcbG4scff0SLFi1w+eWXo1OnTrjxxhtRXl6uS5OzaNEiXHHFFbj11lvRsWNH3HzzzSgpKVGcc+ONN6KiogJTp06tQc9Uz++//47S0lI89NBDyMzMlB6XX365qd9LEEYwdOhQMMaCHmJ0osPhwIIFC3DgwAFUVFTg2LFj+Pjjj9G1a1fpGgcPHlS9Rijuv//+sLKlc6yqqxIEQRjE0KFD0aNHDzz77LN13ZQg1q5di+HDh+PIkSNIT0+v8twpU6YgPz/f8NILtf0dBGFlSHNDEESDxe124+jRo7j//vtx5ZVXVivYiHz55ZeIj4/Hl19+aWh71q5di/j4eFUnaoIgtEMOxQRBNFjee+893HjjjejRowfefPNNTZ95/PHHce+99wIQosOMpHfv3pIKXmv4LEEQwZBZiiAIgiAIS0FmKYIgCIIgLAUJNwRBEARBWAoSbgiCIAiCsBQk3BAEQRAEYSlIuCEIgiAIwlKQcEMQBEEQhKUg4YYgCIIgCEtBwg1BEARBEJaChBuCIAiCICzF/wNhsE2sEfUxxwAAAABJRU5ErkJggg==",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Difference in first resonant wavelength: 0.0033333333333331883\n"
-     ]
-    }
-   ],
-   "source": [
-    "sim_data_2D[\"mode through\"].amps.sel(mode_index=0, direction=\"+\").abs.plot(x=\"f\")\n",
-    "sim_data_3D[\"mode through\"].amps.sel(mode_index=0, direction=\"+\").abs.plot(x=\"f\")\n",
-    "plt.legend([\"2D\", \"3D\"])\n",
-    "plt.show()\n",
-    "\n",
-    "res_lda_2d = (\n",
-    "    td.C_0 / sim_data_2D[\"mode through\"].amps.sel(mode_index=0, direction=\"+\").abs.f.data[46]\n",
-    ")\n",
-    "res_lda_3d = (\n",
-    "    td.C_0 / sim_data_3D[\"mode through\"].amps.sel(mode_index=0, direction=\"+\").abs.f.data[56]\n",
-    ")\n",
-    "res_wavelength_dif = np.abs(res_lda_2d - res_lda_3d)\n",
-    "print(f\"Difference in first resonant wavelength: {res_wavelength_dif}\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "59164d1d-6a30-4c1e-8570-69fb76fccc42",
-   "metadata": {},
-   "source": [
-    "## Strip-to-slot Counter-example\n",
-    "\n",
-    "This approximation method is not always applicable, and care must be taken to ensure that a given material's approximation is not too far off from the physical constraints of the original material. If not, this can lead to poor approximations. (One can check this by printing out the $n_{eff}^2 + \\frac{num}{denom}$ value calculated in the variational method function above.)\n",
-    "<br><br>\n",
-    "We will now show an example where this approximation does not work as well. We will use the first design of our [strip to slot converter example](https://www.flexcompute.com/tidy3d/examples/notebooks/StripToSlotConverters/). First we copy the simulation parameters from the notebook, removing the field monitor, as it will be unnecessary for this illustration:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 18,
-   "id": "2b46a885-4127-4b88-b32a-2c8714fe3b93",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 2 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "# Define wavelength/frequency ranges\n",
-    "lda0 = 1.55\n",
-    "ldas = np.linspace(1.5, 1.6, 101)\n",
-    "freq0 = td.C_0 / lda0\n",
-    "freqs = td.C_0 / ldas\n",
-    "fwidth = 0.5 * (np.max(freqs) - np.min(freqs))\n",
-    "\n",
-    "# Create materials\n",
-    "n_si = 3.47\n",
-    "si = td.Medium(permittivity=n_si**2)\n",
-    "n_sio2 = 1.44\n",
-    "sio2 = td.Medium(permittivity=n_sio2**2)\n",
-    "\n",
-    "# Define geometry\n",
-    "L_mmi = 1.38\n",
-    "W_mmi = 1.24\n",
-    "L = 6\n",
-    "buffer = 5\n",
-    "h_si = 0.25\n",
-    "w_strip = 0.4\n",
-    "w_slot = 0.62\n",
-    "g = 0.1\n",
-    "\n",
-    "vertices = [\n",
-    "    (-buffer, w_strip / 2),\n",
-    "    (0, w_strip / 2),\n",
-    "    (0, W_mmi / 2),\n",
-    "    (L_mmi, W_mmi / 2),\n",
-    "    (L, w_slot / 2),\n",
-    "    (L + buffer, w_slot / 2),\n",
-    "    (L + buffer, g / 2),\n",
-    "    (L_mmi, g / 2),\n",
-    "    (L_mmi, -g / 2),\n",
-    "    (L + buffer, -g / 2),\n",
-    "    (L + buffer, -w_slot / 2),\n",
-    "    (L, -w_slot / 2),\n",
-    "    (L_mmi, -W_mmi / 2),\n",
-    "    (0, -W_mmi / 2),\n",
-    "    (0, -w_strip / 2),\n",
-    "    (-buffer, -w_strip / 2),\n",
-    "]\n",
-    "\n",
-    "converter = td.Structure(\n",
-    "    geometry=td.PolySlab(vertices=vertices, axis=2, slab_bounds=(-h_si / 2, h_si / 2)), medium=si\n",
-    ")\n",
-    "\n",
-    "# Define mode source\n",
-    "mode_spec = td.ModeSpec(num_modes=1, target_neff=n_si)\n",
-    "mode_source = td.ModeSource(\n",
-    "    center=(-lda0, 0, 0),\n",
-    "    size=(0, 4 * w_strip, 6 * h_si),\n",
-    "    source_time=td.GaussianPulse(freq0=freq0, fwidth=fwidth),\n",
-    "    direction=\"+\",\n",
-    "    mode_spec=mode_spec,\n",
-    "    mode_index=0,\n",
-    "    num_freqs=7,\n",
-    ")\n",
-    "\n",
-    "# Define mode monitor\n",
-    "mode_monitor = td.ModeMonitor(\n",
-    "    center=(L + lda0, 0, 0),\n",
-    "    size=(0, 4 * w_strip, 6 * h_si),\n",
-    "    freqs=freqs,\n",
-    "    mode_spec=mode_spec,\n",
-    "    name=\"mode\",\n",
-    ")\n",
-    "\n",
-    "# Define misc. simulation parameters\n",
-    "Lx = L + 3 * lda0\n",
-    "Ly = W_mmi + lda0\n",
-    "Lz = 10 * h_si\n",
-    "sim_size = (Lx, Ly, Lz)\n",
-    "\n",
-    "run_time = 1e-12\n",
-    "\n",
-    "# construct simulation\n",
-    "sim_splitter_3D = td.Simulation(\n",
-    "    center=(L / 2, 0, 0),\n",
-    "    size=sim_size,\n",
-    "    grid_spec=td.GridSpec.auto(min_steps_per_wvl=30, wavelength=lda0),\n",
-    "    structures=[converter],\n",
-    "    sources=[mode_source],\n",
-    "    monitors=[mode_monitor],\n",
-    "    run_time=run_time,\n",
-    "    boundary_spec=td.BoundarySpec.all_sides(boundary=td.PML()),\n",
-    "    medium=sio2,\n",
-    "    symmetry=(0, -1, 1),\n",
-    ")\n",
-    "\n",
-    "# plot the simulation\n",
-    "sim_splitter_3D.plot_eps(z=0, freq=freq0)\n",
-    "plt.show()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "68b9ba6d-af75-47bd-9bf7-9341f3693b97",
-   "metadata": {},
-   "source": [
-    "Now we convert the 3D simulation to a 2D simulation, as before."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 19,
-   "id": "dd794575-4213-4a95-9586-b1e1625eb316",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "887318dc121247b3b2f7d133968f3ac5",
-       "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": "ee23f339c40d455a99bb01c7164a708e",
-       "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"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Note: removed symmetry, as it is incompatible with the variational approximation method.\n"
-     ]
-    },
-    {
-     "data": {
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",
-      "text/plain": [
-       "<Figure size 640x480 with 2 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "# Approximate materials by downsampling again\n",
-    "spectrum = ldas[::15]\n",
-    "ref_point = (0, 0)\n",
-    "core_point = (0, 0)\n",
-    "other_point = (2, 0)\n",
-    "\n",
-    "waveguide_splitter_mat = approximate_material(sim_splitter_3D, core_point, ref_point, spectrum)\n",
-    "background_splitter_mat = approximate_material(sim_splitter_3D, other_point, ref_point, spectrum)\n",
-    "\n",
-    "sim_splitter_2D = create_2D_sim(sim_splitter_3D, [waveguide_splitter_mat, background_splitter_mat])\n",
-    "sim_splitter_2D.plot_eps(z=0, freq=freq0)\n",
-    "plt.show()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 20,
-   "id": "f56574ce-a75a-4d93-bab8-8715c24ddbc7",
-   "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\">14:01:49 EST </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'2.5D FDTD splitter 2D'</span> with task_id                  \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-4cb0b3d9-c535-4534-8dc7-04a64653ce14'</span> and task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.  \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m14:01:49 EST\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'2.5D FDTD splitter 2D'\u001b[0m with task_id                  \n",
-       "\u001b[2;36m             \u001b[0m\u001b[32m'fdve-4cb0b3d9-c535-4534-8dc7-04a64653ce14'\u001b[0m and task_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-4cb0b3d9-c535-4534-8dc7-04a64653ce14\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-4cb0b3d9-c53</span></a>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-4cb0b3d9-c535-4534-8dc7-04a64653ce14\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">5-4534-8dc7-04a64653ce14'</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=112189;https://tidy3d.simulation.cloud/workbench?taskId=fdve-4cb0b3d9-c535-4534-8dc7-04a64653ce14\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=746483;https://tidy3d.simulation.cloud/workbench?taskId=fdve-4cb0b3d9-c535-4534-8dc7-04a64653ce14\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=112189;https://tidy3d.simulation.cloud/workbench?taskId=fdve-4cb0b3d9-c535-4534-8dc7-04a64653ce14\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=638851;https://tidy3d.simulation.cloud/workbench?taskId=fdve-4cb0b3d9-c535-4534-8dc7-04a64653ce14\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=112189;https://tidy3d.simulation.cloud/workbench?taskId=fdve-4cb0b3d9-c535-4534-8dc7-04a64653ce14\u001b\\\u001b[32m-4cb0b3d9-c53\u001b[0m\u001b]8;;\u001b\\\n",
-       "\u001b[2;36m             \u001b[0m\u001b]8;id=112189;https://tidy3d.simulation.cloud/workbench?taskId=fdve-4cb0b3d9-c535-4534-8dc7-04a64653ce14\u001b\\\u001b[32m5-4534-8dc7-04a64653ce14'\u001b[0m\u001b]8;;\u001b\\.                                         \n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "011f409911a544e683995eb4f19f7db7",
-       "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\">14:01:50 EST </span>status = queued                                                    \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m14:01:50 EST\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 <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"
-    },
-    {
-     "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\">14:01:55 EST </span>status = preprocess                                                \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m14:01:55 EST\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\">14:01:56 EST </span>Maximum FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.025</span>. Use <span style=\"color: #008000; text-decoration-color: #008000\">'web.real_cost(task_id)'</span> to get\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>the billed FlexCredit cost after a simulation run.                 \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m14:01:56 EST\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.025\u001b[0m. 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\n",
-       "\u001b[2;36m             \u001b[0mthe billed FlexCredit 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"
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "ec978a9210ce4fb5b47e8979b8c5156e",
-       "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\">14:02:04 EST </span>early shutoff detected at <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">48</span>%, exiting.                            \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m14:02:04 EST\u001b[0m\u001b[2;36m \u001b[0mearly shutoff detected at \u001b[1;36m48\u001b[0m%, exiting.                            \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"
-    },
-    {
-     "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>status = postprocess                                               \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mstatus = postprocess                                               \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\">             </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"
-    },
-    {
-     "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\">14:02:05 EST </span>View simulation result at                                          \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-4cb0b3d9-c535-4534-8dc7-04a64653ce14\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-4cb0b3d9-c53</span></a>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-4cb0b3d9-c535-4534-8dc7-04a64653ce14\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">5-4534-8dc7-04a64653ce14'</span></a><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">.</span>                                         \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m14:02:05 EST\u001b[0m\u001b[2;36m \u001b[0mView simulation result at                                          \n",
-       "\u001b[2;36m             \u001b[0m\u001b]8;id=132861;https://tidy3d.simulation.cloud/workbench?taskId=fdve-4cb0b3d9-c535-4534-8dc7-04a64653ce14\u001b\\\u001b[4;34m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=668189;https://tidy3d.simulation.cloud/workbench?taskId=fdve-4cb0b3d9-c535-4534-8dc7-04a64653ce14\u001b\\\u001b[4;34mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=132861;https://tidy3d.simulation.cloud/workbench?taskId=fdve-4cb0b3d9-c535-4534-8dc7-04a64653ce14\u001b\\\u001b[4;34m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=984912;https://tidy3d.simulation.cloud/workbench?taskId=fdve-4cb0b3d9-c535-4534-8dc7-04a64653ce14\u001b\\\u001b[4;34mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=132861;https://tidy3d.simulation.cloud/workbench?taskId=fdve-4cb0b3d9-c535-4534-8dc7-04a64653ce14\u001b\\\u001b[4;34m-4cb0b3d9-c53\u001b[0m\u001b]8;;\u001b\\\n",
-       "\u001b[2;36m             \u001b[0m\u001b]8;id=132861;https://tidy3d.simulation.cloud/workbench?taskId=fdve-4cb0b3d9-c535-4534-8dc7-04a64653ce14\u001b\\\u001b[4;34m5-4534-8dc7-04a64653ce14'\u001b[0m\u001b]8;;\u001b\\\u001b[4;34m.\u001b[0m                                         \n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "c92e1519958146babdda6ab9db74068c",
-       "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\">             </span>loading simulation from simulation_data.hdf5                       \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mloading simulation from simulation_data.hdf5                       \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>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'2.5D FDTD splitter 3D'</span> with task_id                  \n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-6d645823-3048-4598-a4c7-8c0959f8685c'</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'2.5D FDTD splitter 3D'\u001b[0m with task_id                  \n",
-       "\u001b[2;36m             \u001b[0m\u001b[32m'fdve-6d645823-3048-4598-a4c7-8c0959f8685c'\u001b[0m and task_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-6d645823-3048-4598-a4c7-8c0959f8685c\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-6d645823-304</span></a>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-6d645823-3048-4598-a4c7-8c0959f8685c\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">8-4598-a4c7-8c0959f8685c'</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=849190;https://tidy3d.simulation.cloud/workbench?taskId=fdve-6d645823-3048-4598-a4c7-8c0959f8685c\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=771626;https://tidy3d.simulation.cloud/workbench?taskId=fdve-6d645823-3048-4598-a4c7-8c0959f8685c\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=849190;https://tidy3d.simulation.cloud/workbench?taskId=fdve-6d645823-3048-4598-a4c7-8c0959f8685c\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=344104;https://tidy3d.simulation.cloud/workbench?taskId=fdve-6d645823-3048-4598-a4c7-8c0959f8685c\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=849190;https://tidy3d.simulation.cloud/workbench?taskId=fdve-6d645823-3048-4598-a4c7-8c0959f8685c\u001b\\\u001b[32m-6d645823-304\u001b[0m\u001b]8;;\u001b\\\n",
-       "\u001b[2;36m             \u001b[0m\u001b]8;id=849190;https://tidy3d.simulation.cloud/workbench?taskId=fdve-6d645823-3048-4598-a4c7-8c0959f8685c\u001b\\\u001b[32m8-4598-a4c7-8c0959f8685c'\u001b[0m\u001b]8;;\u001b\\.                                         \n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "82b9976a9b8842edab1ec48fc467ef51",
-       "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"
+       "<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": []
      },
@@ -2983,71 +800,41 @@
     },
     {
      "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\">14:02:07 EST </span>status = queued                                                    \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m14:02:07 EST\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 <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"
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-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "",
-       "version_major": 2,
-       "version_minor": 0
-      },
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HiIgIODg4vHOZ7OzsMl+sVv93F4r+/ctYXpu3fcSoaR0adUDEqAgYi4wB64sIedwDmobPuX5QSciq/SyxcKFyHaowNjbG4MGDsX37dsk0XV1dHDhwANevX4eLiwvmz5+PpUuXSi03adIkfPzxx/j888/RqVMnPH/+HFOnTpVqM3HiRDg5OaF9+/YwNTXFmTNn8NFHH2HmzJmYNm0a2rZti7Nnz2KhjB/Wjh07MHHixJoZdE2qdoxWw5QpU8jAwICioqIkp+RTUlKk6oxGjhxJfn5+kucBAQGkp6dHO3bsoMTERDp+/Dg5OjrSkCFDJG1Gjx5NjRo1kpTI7N27l0xMTOirr76qUL9qYk+wxLXUa2T2nVnxHuGUViQ0fCL311A18j47XBfExsaSmZkZZWZmKrorREQUFxdHZmZm9PLlS7mtUyVKZFCqMLPksWnTJkkbNzc3qY8GBQUFFBgYSI6OjqStrU02NjY0depUSk9Pl7TJyMigGTNmkK2traRYev78+ZKap3epyRAkIvpy0U3CbMviIPR+j+Yselwjr6MqVDEEiYo/fl67dk3R3SAiovDwcDp69Khc11lbISggeuPoKgNQfGNnAwMDiMViud93uOQA/IxFd/C7Xnc8zHgIPG+K2SYR+N7fWq6vpSpyc3ORlJQEBweHGr34Jqtdb9uu8nyPKs3ZYVXw5hnIVf5N8deYv2BnYAcY38Hy527o4lX2jFvJcsp0TIqx+oRDsBaVLp9xaOiA6DHRaNywMWCUiHNO3TAzSLpkgctnGKtZHIK1SNYZSDtDO/w15i80M24GGD7AKrEbZgTFA+CrzzBWGzgElUAj/UaIHhONFqYtAP1H+CHDHZqNbnIAMlYLOASVhIWuBSJHR6KVWStALxUFI9yh0egaByBjNYxDUImYNTBDv6eRwOP3gQZP8XqEB6YEXVF0txir1zgElUhwMPBtgDHmNTqJjo06AjovsDa7ByYFXVR01xirtzgElcSbJ0G+8TdE+MhwdLHpAoheYn1uT7QfLPuGOlw+o5oqcqOlmlKVGzi5u7vDx8dH8vyDDz7A77//Lv/OVQGHoJIoXT6jr6WPY18cQze7boBWJi6/1xvjg/6SWobLZ1RXTd1oqbYsWLAAfn5+Cv0+fwkOQSUhq3xGV1MXh4cfRg+HHoBWFn7N64sxQScBcPmMKiMlvNFSZfXt2xeZmZk4cuSIorvCIajsGmg2wIFhB9CnSR9AMxtb8vtD2PwYB+A7EBFe5b9SyKMy30R1d3fH9OnT8dVXX8HIyAgWFhYIfMfxjcuXLyMhIQH9+vWTTCv5iLp79258+OGHEIlE6NChA27fvo1Lly6hffv20NXVRd++ffH06VPJckVFRQgKCoK1tTW0tLTQtm1bHD16VOr1Ll68CBcXF2hra6N9+/aIiYkp06e4uDj07dsXurq6MDc3x8iRI/Hs2bNyx6Curg4vL693Xj+0NmgougPs3URCEfZ/vh+f7fkMB24fwOvPPoLG3t+xcGF/RXdNaWUXZEM3RFchr501LwsNNBtUuP2WLVswa9YsXLhwAefOncOYMWPg6uqKXr16yWx/6tQpNGvWDHp6emXmBQQEYNWqVbC1tcW4ceMwfPhw6OnpITQ0FDo6OhgyZAj8/f2xZs0aAEBoaCiWL1+OdevWwcXFBb/++is++ugj3LhxA02bNkVWVhb69++PXr16Ydu2bUhKSsKMGTOkXvPly5fo3r07JkyYgJUrVyInJwdz587FkCFDEBERUe64O3bsiG+//bbCP6eawnuCdYSWhhZc7vwG3PwY0MjH608+xrCgfYruFpOD1q1bIyAgAE2bNsWoUaPQvn17nDx5stz29+/fh5WVlcx5vr6+6N27N9577z3MmDEDly9fxsKFC+Hq6goXFxeMHz8ekZGRkvbff/895s6di6FDh8LJyQlLly5F27ZtsWrVKgBAWFgYioqKsHHjRrRs2RL9+/fHnDlzpF7zxx9/hIuLC7755hs0b95cEqaRkZGS+/zIYmVlheTkZIUfF+Q9wToiOBgICtBEwKKdiG85CjvjdmJn4WcoCgrDLv8hiu6e0tER6iBrnuz7udTGa1eGPG60JGtd5ubmAIBWrVpJTStZd0ZGBh4/fgxXV1epdbi6uiI2NhZAxW7gFBsbi8jISOjqlt3zTkhIQLNmzWT2VSQSoaioCHl5eRCJROWOt6ZxCNYB0idBhHhdtBVCNSG2XtuK3YXDEDesADd2lL2JVHBw8VlnVSyhEQgElfpIqkhVudHS9evX37kugUAgc5q897yysrIwYMCAMleyBooDvTwvXrxAgwYNFBqAAH8crhNKl89oqGlg08BNGNd2HKBWhJtOI/Fx0GapZbh8pv6SdaOlqtDX14eVlRXOnDkjNf3MmTNo0aIFgIrdwOn999/HjRs3YG9vjyZNmkg9GjQo/w9RXFycUtyUiUOwDpBVPqOupo4NH23ApHaTAAFhH43FwKD1ALh8pr7z8PBAVlYWbty4Ue11zZkzB0uXLsWuXbsQHx8PPz8/XL16VXLyY/jw4RAIBJg4cSJu3ryJw4cP4/vvv5dah7e3N168eIFhw4bh0qVLSEhIwLFjxzB27Ngyd65706lTp+Dp6VntMVQXh2AdpiZQw5p+a/Blxy8BAH/SJGh0+ZEDsJ6TdaOlqpo+fTpmzZqF2bNno1WrVjh69Cj+/PNPNG3aFEDFbuBUsjdZWFgIT09PtGrVCj4+PjA0NCxzw7MSjx49wtmzZzF27Nhqj6G6+PL6MtTk5fVrAhFhTvgcLD+3HACgHr4Cr0/PVHCvao8qXl7/2rVr6NWrFxISEmSekFB2c+fORXp6OtavX19uG768PqswgUAA/fPfAafmAQAKe82CZ1DZg9Ss/mjdujWWLl2KpKQkRXelSszMzBCsJHe05xCsB4KDgYAAARZ1W4IAtwAAQDj5oUeQcvySsZoxZswYqfKXumT27NmSEh5F4xKZOk76JIgAQCCEakIsiFyACPKHw7h8JG4MkpRLvLmcqpbPMPYm3hOs40qXzwDA/G7zsaznMgDAPbvF6BbkJ1VOweUzjP2H9wTruPL25Oa4zoGmuiZ8jvngNJbBNSgfZ/xXYPFiQb09e8zn+OqX2tqeHIL12IwPZkBTXRNTD0/FOayCxsB8FB1cjaAgtXoVgCXfiMjOzlb4tw+Y/GRnZwMo+40aeeMQrOemdJgCTXVNTPhzIora/Qw1tQLMX7AW9elIiLq6OgwNDSXfidXR0SlzDJTVHUSE7OxspKWlwdDQEOo1fNyGQ1AFPD40HtgvBAaORZHLBrQPKsClhb9AXa3+HBS0sLAAgLdeeIDVLYaGhpLtWpM4BOu5/84ej4LjIA2M3DsKMdiM94MLcHnhZmio1Y9fAYFAAEtLS5iZmaGgoEDR3WHVJBQKa3wPsET9eAcwmcp+h3g4hGpCDP1tOK5hOxp9+RoPf9gKobqwzHJ1tXxGXV291t48rH6oPweGWBmyymc+a/kZfv98DwRFQqSZ7ULbxUORX5gvmc/lM0zV8HeHZahr3x2uikO3D2Hgjo9RiHw4YQBi5+/BshCtels+w+oX/u4wq7Z+zfrh0Ig/oQFtxOMARGMHwz8olwOQqRwOQRXWu0lvHB15ECgQgZocgWD4R5jtl63objFWqxQagiEhIejQoQP09PRgZmaGQYMGIT4+/p3LrVq1Ck5OThCJRLCxscHMmTOlrnxrb28PgUBQ5uHt7V2Tw6mTzm7vAWw7CuQ3ADUOh/M3/fEq/5Wiu8VYrVFoCEZHR8Pb2xvnz59HeHg4CgoK4OnpiVevyn8ThoWFwc/PDwEBAbh16xY2btyIXbt24euvv5a0uXTpElJSUiSP8PBwAMBnn31W42OqSyRnj8d3w+lJx6AFPSQhEi1D+iIzL1PR3WOsdpASSUtLIwAUHR1dbhtvb2/q3r271LRZs2aRq6trucvMmDGDHB0dqaioqEL9EIvFBIDEYnHFOl4HBQURAcX/ljiXfI60Aw0IgSCDmV1InFt2/EFBRAEBtddPxmSR53tUqY4JisViAICRkVG5bbp06YLLly/j4sWLAIDExEQcPnwYXl5eMtvn5+dj27ZtGDduXLlfpcrLy0NGRobUo76TVT7zgfUHODXxBDQKGkJscBYtvu2Fl7kvJfO5fIbVS3IIZbkoLCykfv36vXWPrkRoaCgJhULS0NAgADR58uRy2+7atYvU1dXp0aNH5bYJCAggAGUe9XlP8G2uPL5COoHGhECQZeD79Dz7ucw9R8YURZ57gkoTgpMnTyY7OztKTk5+a7vIyEgyNzenDRs20LVr12jv3r1kY2NDQeW8Oz09Pal///5vXWdubi6JxWLJIzk5WaVDkIgoNjWWGgSaEgJBgiltCDpPOQCZ0qh3Iejt7U3W1taUmJj4zrZdu3YlX19fqWlbt24lkUhEhYWFUtPv3btHampqtH///kr1RxWOCVbEjbQbBF/z4iCc6kxPsp4oukuMEVE9OiZIRJg2bRr27duHiIgIODg4vHOZ7OzsMrfxK/muKJX68sumTZtgZmaGfv36ya/TKuT3tS2AzVFApiXILA7O37sjJTNF0d1iTK4UGoLe3t7Ytm0bwsLCoKenh9TUVKSmpiInJ0fSZtSoUZg3b57k+YABA7BmzRrs3LkTSUlJCA8Px8KFCzFgwACpL84XFRVh06ZNGD16NDQ0+DoRlSUpn5neHLfnRUMf1niKW2i1wh2PMh4punuMyU+19yWrATJORgCgTZs2Sdq4ubnR6NGjJc8LCgooMDCQHB0dSVtbm2xsbGjq1KmUnp4ute5jx44RAIqPj690v1T947CskyAJLxLIINCWEAgSzXWk+y/vy1yOy2dYbZDne5QvoCCDKlxA4W0CA4vLYEp/h/j+y/to/q0HckVJMIQ9YmZEwt7QHoCsy3YxVnPk+R7lEJRB1UPwbZLFyWi7qjte4C4MYIvLX0Yg7CdHDkBWq/gqMkxhbAxscH1WNEzgBDEeoMkSN/iH3uYAZHUWhyCrNCs9K1yfHQXB0xaA/iNgjDs+m/KPorvFWJVwCLIq2bDSArQ5EoK0VoBeCtr/5IYbaTcU3S3GKo1DkFWa5CTIXDOkfRcBC7TFK6Sh4xp3XHtyTdHdY6xSOARZpZQ+C2yiY4IbX52EFdohG8/QbrUHYlJiZC5XF2/cxOo/DkFWKbKuPmMkMsKNuSegn9ERr4Uv4Lq+By4/viyZz1efYcqMS2Rk4BKZqhHnitFqaV8k4xy0YYCo8cdwfFMnLp9hcsclMkwpGWgb4IbfMdiiK3Ihxgc/94L/hrMcgEypcQgyudLT0sONeUcguO8OaGUCX/SG+6hTiu4WY+XiEGRyt3KpLmjbIQiSegBaWeixuQ+i7kUpuluMycQhyORKcvZ4oQ5ebTgAR3iiANnw3OKFk4knFd09xsrgEGRyU7p8RiQUIW7+H2gKLxQgB56b++PY3WMyl+PyGaYoHIJMbmSVz2hraOP6/L0wefYRitRz0X/7QBy+c1gyn8tnmKJxiYwMXCIjf/mF+XBZPAw3sRfq0MS+ob/h6u4BXD7DqoRLZFido6muiasLdqIlPkMh8vHR9o/hH7aPA5ApHIcgqzVCdSGuLgyD2o1hgPpr4LMheO+T3xTdLabiOARZrQpZooGi37ZC7fpIQP01Pt8zFDvjdiq6W0yFcQiyWiM5e7xIHfm7N8EFY1CEQgz/fQS2Xdum6O4xFcUhyGpF6fIZdTV1/O2/Ee0wAYQijNw7CluubpG5HJfPsJrEIchqhazyGTWBGi76r0Ojx5MBAWHsH2Ox8cpGyXwun2G1gUtkZOASmdpFROgcNB0X8CMAYG2/tUg7MonLZ1i5uESG1SsCgQDn/H9AZ/gAACYfmgz/Az9xALJawSHIlIJAIMAZ/xVQO+9bPKHfNOj3ClVsp5hK4BBkSmPxYgGKji6D2lk/AIDPMR+sOLdCwb1i9R2HIFMK/509FuD10W/ghgUAgNnHZ2PZmWUK7h2rzzgEmcKVLp8RCASICgiGhyAQADD3xFx8c+obmctx+QyrLg5BpnCyymcAIMI/AA73ggEA8yPmIyg6SDKPy2eYvHCJjAxcIqNcegV9ixM0DwCwsNtCaJxahIAAAZ89VmHyfI9yCMrAIah8egd9j+M0p/jJqXlY1G0J/P0Fiu0UUxiuE2Qq55i/L9TDVxY/+TAErzr7gf9+M3ngEGR1QnAwUHjGB+rHVgMAlp1dBt/jvhyErNo4BJnSe/Ps8euz09Bf8DMAYMX5FZh5bCYHIasWhYZgSEgIOnToAD09PZiZmWHQoEGIj49/53KrVq2Ck5MTRCIRbGxsMHPmTOTm5kq1efToEb744gsYGxtDJBKhVatW+Pvvv2tqKKyGlC6fAYAD/lPwkWAdACD0Qii+PPJlmSDk8hlWUQoNwejoaHh7e+P8+fMIDw9HQUEBPD098erVq3KXCQsLg5+fHwICAnDr1i1s3LgRu3btwtdffy1pk56eDldXVwiFQhw5cgQ3b97E8uXL0bBhw9oYFpOj8spn/vD/H5rHbwRIgJ8u/YSph6aiiIoAcPkMqyRSImlpaQSAoqOjy23j7e1N3bt3l5o2a9YscnV1lTyfO3cude3atcr9EIvFBIDEYnGV18Fqx+BFmwkBAkIgaMIfEyhwUSEBREFBiu4Zq0nyfI8q1TFBsVgMADAyMiq3TZcuXXD58mVcvHgRAJCYmIjDhw/Dy8tL0ubPP/9E+/bt8dlnn8HMzAwuLi7YsGFDuevMy8tDRkaG1IPVDXv9R+MTtf8DitTwS8wvCLwyAYGLCrl+kFWcHEJZLgoLC6lfv35Se3TlCQ0NJaFQSBoaGgSAJk+eLDVfS0uLtLS0aN68eXTlyhVat24daWtr0+bNm2WuLyAggACUefCeYN2h3jaM4K9GCASN2jeKXhe+VnSXWA2S556g0oTg5MmTyc7OjpKTk9/aLjIykszNzWnDhg107do12rt3L9nY2FDQG59/hEIhde7cWWq5L7/8kj744AOZ68zNzSWxWCx5JCcncwjWIUFBRACRepudBH91QiBoxO8jqKCwQNFdYzWk3oWgt7c3WVtbU2Ji4jvbdu3alXx9faWmbd26lUQiERUWFhIRka2tLY0fP16qzc8//0xWVlYV6g8fE6w7SgKw5G/g54v2EBZqEAJBQ38bykFYT9WbY4JEhGnTpmHfvn2IiIiAg4PDO5fJzs6Gmpp0t9X/PQ1I/5ZJuLq6lim1uX37Nuzs7OTUc6YMZJXP7PT/FEM1dgOFGtgZtxMj9o5AQWFBmeW4fIZJVDtGq2HKlClkYGBAUVFRlJKSInlkZ2dL2owcOZL8/PwkzwMCAkhPT4927NhBiYmJdPz4cXJ0dKQhQ4ZI2ly8eJE0NDRoyZIldOfOHdq+fTvp6OjQtm3bKtQv3hOsGwICyj8L3OrTPwgLhYRA0Ce7PqH81/lEVHbPkdVN9ebjMGScjABAmzZtkrRxc3Oj0aNHS54XFBRQYGAgOTo6kra2NtnY2NDUqVMpPT1dat0HDhwgZ2dn0tLSoubNm9P69esr3C8OwfphxKIDhAWahEDQ4J2DyX9RHgdgPSHP92iVryJz8uRJnDx5EmlpaSgqKpKa9+uvv1Zj31Tx+Coy9cfIoCPYVjAY0MgD/vkI/u/txiJ/LUV3i1WTwq8is2jRInh6euLkyZN49uwZ0tPTpR6MKYut/n2hsecPoEAbaP4nrjT9FHmv8xTdLaZENKqy0Nq1a7F582aMHDlS3v1hTK6Cg4HX8b2hsecAXn82AAdvH8THuz/G70N+h7aGtqK7x5RAlfYE8/Pz0aVLF3n3hTG5evPscUF8T4zRPAQUiHD4zmEM3jUYua9z370SVu9VKQQnTJiAsLAwefeFMbmRVT6zyb87xmoeBvJ1cPTuUXy04yPkFOSUWY7LZ1RLlT4O5+bmYv369Thx4gRat24NoVAoNX/FCr5XLFOs8q4+86u/O65+fAQx73khPDEcA3YMwJ/D/oSOUEcqOJnqqNLZYQ8Pj/JXKBAgIiKiWp1SND47XP9NCDqNjbl9Aa0seNh7wPX+ASwOaMA3b6oj+EZLNYxDUDVMDDqLX3L7AFqZwD03zHc4iMX+uoruFqsAhZfIMFYfbPDvAo2dx4BcfcA+Gn/ZeCErP0vR3WK1jEOQqazgYOB1Umdo7DwO5Orj1INT6LOtDzLzMhXdNVaLOASZSpIqn0nqhEmiE0COIc4kn0Hvbb2RkccX1lUVHIJM5cgqn1nr3wGTdU4AOQ1x7uE59N7WG+JccZnluHym/uEQZCqnvPKZNf7t0OFWcRCef3gents88TL3JQC+eVN9xmeHZeCzw6ptatBVrHnVE9B5jvZW7dEr5ThCAhpy+YwS4bPDjNWgn/3bYmqDCOCVCf5+/DdCHvWE36IXHID1FIcgYzL85N8aGmGRwCtTwOoKjpn3xIucF4ruFqsBHIKMyRAcDLx+5AyN7ZFAlhliUmPQ4/964Hn2c0V3jckZhyBjpUiVzzxqiWl6kUCWOa6mXkX3/+uOZ9nPFN1FJkccgoy9QVb5zGr/FvhSLwrItMC1J9fg/F13PH31VOayXEJT93AIMvaG8spnfvBvjun6UdDMs8QTXIfz992R9ipNMp9LaOouLpGRgUtkWHluP7+N9j96IBOPYYoWuD47AutXmpfZe2Q1i0tkGFOQZsbNcHlaFPTRCE9xExbzPOC/LJUDsA7jEGSskpoaN8XlL6OADGvA5BYwxgMTfFIU3S1WRRyCjFXBjp+aAJuiALENYPIPWq1wx+PMx4ruFqsCDkHGKklyBnmmIxIWRsEAtniO22i9wh2PMh4punuskjgEGauE0iU0jRs2Rsz0KBjCDs9xB02/ccfDjIcyl+PyGeXEIchYJcgqoXFo6ICYGVHQzrVHjugu2qx0R7I4WTKfy2eUG5fIyMAlMqwq7r+8D5dQD6QjCQ3RGFd9IrHlB1sun6kBXCLDmBKyM7TDVZ8oNERjpCMRdgHu8F/+gANQyXEIMiZHtga2iPWJAl44Ag2TgDHuGPXlfUV3i70FhyBjcrb5Bxtgc5QkCNuGuuPey3sK7hUrD4cgY3IkOXvsa42HwdEwQhO8xD24hHIQKisOQcbkpHT5TCP9Rrg2MwrGaIqXuI/3lrojKT1J5nJcPqM4HIKMyYms8plG+o1wbVYUdLKbIVf7Plx+cEdieqJkPpfPKB6XyMjAJTJM3h5nPkabFd3xDPEwgA0ufxmJsJ8cuXymiupNiUxISAg6dOgAPT09mJmZYdCgQYiPj3/ncqtWrYKTkxNEIhFsbGwwc+ZM5ObmSuYHBgZCIBBIPZo3b16TQ2Hsraz0rHBtViRM0BxiJKPJEnf4r0zgAFQCCg3B6OhoeHt74/z58wgPD0dBQQE8PT3x6tWrcpcJCwuDn58fAgICcOvWLWzcuBG7du3C119/LdWuZcuWSElJkTxOnz5d08Nh7K0s9SxxfXYk8Kw5oP8QGOuOYd53Fd0tlaehyBc/evSo1PPNmzfDzMwMly9fRrdu3WQuc/bsWbi6umL48OEAAHt7ewwbNgwXLlyQaqehoQELC4ua6ThjVbRhpQWwORIY0x0wuYV2q91x+csoNDFqouiuqSylOjEiFosBAEZGRuW26dKlCy5fvoyLFy8CABITE3H48GF4eXlJtbtz5w6srKzQuHFjjBgxAg8ePCh3nXl5ecjIyJB6MCZvkrPHX1kgNSQSpmiBDDxCu9XuuPP8jqK7p7pISRQWFlK/fv3I1dX1nW1DQ0NJKBSShoYGAaDJkydLzT98+DDt3r2bYmNj6ejRo9S5c2eytbWljIwMmesLCAggAGUeYrFYLmNjLCiICCj+t0RqZiqZBrYgBII051nR7We3ZS4XEFB7/awrxGKx3N6jShOCkydPJjs7O0pOTn5ru8jISDI3N6cNGzbQtWvXaO/evWRjY0NBb/52lZKenk76+vr0yy+/yJyfm5tLYrFY8khOTuYQZHIVECAdgCWeZD2hBnNaEgJBeoFWFP8sXjJPVnCyYvUuBL29vcna2poSExPf2bZr167k6+srNW3r1q0kEomosLCw3OXat29Pfn5+FeqPPH/AjL1LWlYamQU6/xuElvTP0384AN9Bnu9RhR4TJCJMmzYN+/btQ0REBBwcHN65THZ2NtTUpLut/m+lKZVT8piVlYWEhARYWlpWv9OMyZlpA1PE+UbAHK2QiRQ0/9YD/qHxXD5TSxQagt7e3ti2bRvCwsKgp6eH1NRUpKamIicnR9Jm1KhRmDdvnuT5gAEDsGbNGuzcuRNJSUkIDw/HwoULMWDAAEkY+vr6Ijo6Gvfu3cPZs2cxePBgqKurY9iwYbU+RsYqwrSBKa77noQgrRWglwKM8cCQKe+umWXVp9ASmTVr1gAA3N3dpaZv2rQJY8aMAQA8ePBAas9vwYIFEAgEWLBgAR49egRTU1MMGDAAS5YskbR5+PAhhg0bhufPn8PU1BRdu3bF+fPnYWpqWuNjYqyq1q4wBW2OgGBMd5DZdbT/yR2XvCPR3IQL/WsSf21OBv7aHKttb158YcrsZ3D+rgee4Bp0YcFBKEO9+docY6zs1WdMdEwQN+ckLNAGWUhFm5XuuPX0lszl+Ooz1cchyJiCybr6jImOCa7POQHdrDbI13yCjj974ObTm5L5fPUZ+eGPwzLwx2GmLJ5nP4fzdz2Qilg0gBkuTo3E72tbqPzVZ/jjMGMqwljHWPLR+BXS0PI7D/ivvqnSAShvHIKMKbmSIBSktgUapAFjPPDJ5JvvXI5VDIcgY3XAz8uNQVtOSIKw488euJF2Q9Hdqhc4BBlTcpKzx/OM8XT5CVjCBa+Qhk5runMQygGHIGNKrHT5jLGOMeK++i8IXUJl7xFy+UzFcQgypsRklc8YiYwQ99UJ6Ga6oEDzKTqtkQ5CLp+pHC6RkYFLZFhd8CLnBZyX9UIKrqABTHF+SgT2rXNWifIZLpFhjP27RxgOS7yPV3iKVt93h//qG/U+AOWNQ5CxOqwkCAUp7wMNngJjPPDxJD5ZUhkcgozVcT99bwT6v/+CsPQxQvZ2HIKM1WH/lc8Y4dnK/z4acxBWHIcgY3VU6fKZ0scIuXymYjgEGaujyi+fCYde5vtcPlNBXCIjA5fIsLqudPnMhSmR2LuuZb0pn+ESGcbYW5X+aOzM5TPl4hBkrJ6SlM+kuvx79ZnuXD4jA4cgY/XYT98b/Xv1meIg7LSmu9QVqhmHIGP1llT5zIr/LrpQ+lL9qo5DkLF6SHb5zH9B2HaV7CBUxfIZDkHG6qF3X30mDZ1+7s43bwKXyMjEJTKsPisun+mJFMRAF+a4MDWizt28iUtkGGNV9uZH4yw8Qctl3eH/w606E4DyxiHImAoqCUJBaltA9wkwxgOfTi57g3dVwCHImIr6r3ymLaBbfIP3f579o+hu1ToOQcZUUOmbN1mgDbLwBB1+Ur0g5BBkTMXIunnT9TknYI7WyEIq2qzwQPyzeJnL1cfyGQ5BxlSMrPIZEx0TxM05Cd2s1sjXSkWHn6SDsD6Xz3CJjAxcIsNU1bPsZ3D+rjue4Dr0YIm/p0Vh18/NlK58hktkGGM1wkTHBNd9T8IcrZCJFDiFuMM/9LZSBaC8cQgyxqSYNjDFdd+TEKQ5A3opwBgPDJ16R9HdqjEKDcGQkBB06NABenp6MDMzw6BBgxAfX/aAbGmrVq2Ck5MTRCIRbGxsMHPmTOTm5sps++2330IgEMDHx0fOvWes/lq7whS05SQET1sCeo/R/kcP3H1xV9HdqhEKDcHo6Gh4e3vj/PnzCA8PR0FBATw9PfHq1atylwkLC4Ofnx8CAgJw69YtbNy4Ebt27cLXX39dpu2lS5ewbt06tG7duiaHwVi9Ijl7PNcMqUsjYIaWyMAjtPzeHT5BsoOwTp85JiWSlpZGACg6OrrcNt7e3tS9e3epabNmzSJXV1epaZmZmdS0aVMKDw8nNzc3mjFjRoX7IRaLCQCJxeJK9Z+xui4oiAgo/rfEk6wnZBrYghAIwkxr8ll0953L1DR5vkeV6pigWCwGABgZGZXbpkuXLrh8+TIuXrwIAEhMTMThw4fh5eUl1c7b2xv9+vVDz5493/m6eXl5yMjIkHowpopklc+YNTDD9dkRMMV7gMFDrHrpjplBCQDK1hzWSXIIZbkoLCykfv36ldmjkyU0NJSEQiFpaGgQAJo8ebLU/B07dpCzszPl5OQQEb1zTzAgIIAAlHnwniBj/0nJTKHmPzb/d4/QhoRmCbW+B1iiXu4Jent7Iy4uDjt37nxru6ioKHzzzTf4+eefceXKFezduxeHDh1CcHAwACA5ORkzZszA9u3boa2tXaHXnjdvHsRiseSRnJxc7fEwVt9Y6FogcnQkmps0BwySUTDCHUKzxLq7B1hCDqFcbd7e3mRtbU2JiYnvbNu1a1fy9fWVmrZ161YSiURUWFhI+/btIwCkrq4ueQAggUBA6urq9Pr163e+Bh8TZKx8cxY9JkxzKt4j9LGlmYuSar0P9WZPkIgwbdo07Nu3DxEREXBwcHjnMtnZ2VBTk+62+r/f5SEi9OjRA9evX8fVq1clj/bt22PEiBG4evWqpC1jrPKCg4HvAiwxxzQSzYybAYYPsDLdHbOC7im6a1WmocgX9/b2RlhYGP744w/o6ekhNTUVAGBgYACRSAQAGDVqFBo1aoSQkBAAwIABA7BixQq4uLigU6dOuHv3LhYuXIgBAwZAXV0denp6cHZ2lnqdBg0awNjYuMx0xljFSZ8EsYRPZiTcN7vjDu5g5QsPnPeKwtnDdjKXKyxU3hIahe4JrlmzBmKxGO7u7rC0tJQ8du3aJWnz4MEDpKSkSJ4vWLAAs2fPxoIFC9CiRQuMHz8evXv3xrp16xQxBMZURukzx1Z6VogcHYkmRk2AhvdwrpkHZgc9kFqmLlx4gS+gIANfQIGxinuY8RDum92RkJ4AvGiM2cZR+N7fpkbLZ/gCCowxpWGtb42oMVFwbOgIGCVi+XN3aJo8rDP1gxyCjLFqs9a3RuToSDRu2BgwSiwunzF+qPQBCHAIMsbkxMbABoNeRgLpDoBRAgqGd8ecoEeK7tY7cQgyxuQiOBhYEWCLWUaRsDe0B4zv4Pun3fFVUMo7l1UkDkHGWLW9eRJkub8dIkdHwtbAFjC5je+eeqBrn9Ryl1N06QyHIGOs2kqXz9gb2iNqdBRs9G0Ak3icaeKBuUFPpJZRlvIZLpGRgUtkGJOPxPREuG12w8OMh0BaC3xlHoGl/ubVLp/hEhnGWJ3QuGFjRI2OQiO9RoDZTSx70gOaDdOUqnyGQ5AxVqMcjRwRNSYKVnpWgNkNFAzrAaHhU6UIQIBDkDFWC5oYNcFnWVFAhhVgHoeCoT3hF/RM0d0CwCHIGKsFwcFAaEBTTDeIgKWuJWBxDUtTemJe0HNFd41DkDFWs948CRLq74SI0REwb2AOWMTi28e90K33i3KXq43yGQ5BxliNKl0+09ykOSJHR8KsgRlgGYNT9r3wdVC61DK1WT7DJTIycIkMYzXvRtoNeGzxwNPsp8Cj9phnHY5v/A0rVD7DJTKMsTqvpVlLRIyOgImOCdDob4Q89ISmvrjWy2c4BBljCuNs5oyTo07CWGQMNLqEgs97Q6ibUavlMxyCjDGFam3eGp/nngSyjQDLKygw/Rv/3jyyVij0HiOMMRYcDPwc0AZTFp2A19BHiBF2h79/8bza2CPkEGSMKYz0SRAXAC7o/2/w1VYQcggyxhSmdPlMiZLnhYU13wcukZGBS2QYU25cIsMYY3LCIcgYU2kcgowxlcYhyBhTaRyCjDGVxiUyMpScMM/IyFBwTxhjspS8N+VR3MIhKENmZiYAwMbGRsE9YYy9TWZmJgwMDKq1Dq4TlKGoqAiPHz+Gnp4eBALBW9tmZGTAxsYGycnJ9aamsL6Nqb6NB+AxEREyMzNhZWUFNbXqHdXjPUEZ1NTUYG1tXall9PX1680vY4n6Nqb6Nh5AtcdU3T3AEnxihDGm0jgEGWMqjUOwmrS0tBAQEAAtLS1Fd0Vu6tuY6tt4AB6TPPGJEcaYSuM9QcaYSuMQZIypNA5BxphK4xBkjKk0lQ7Bv/76CwMGDICVlRUEAgH279//1vZRUVEQCARlHqmpqVLtfvrpJ9jb20NbWxudOnXCxYsXpebn5ubC29sbxsbG0NXVxSeffIInT54o5XhCQkLQoUMH6OnpwczMDIMGDUJ8fLzUetzd3cusY/LkydUeT02NKTAwsMz85s2bS62nprZRTY3J3t5eZhtvb29JG2XaTgCQl5eH+fPnw87ODlpaWrC3t8evv/4q1WbPnj1o3rw5tLW10apVKxw+fFhqPhHB398flpaWEIlE6NmzJ+7cuVOpvqt0CL569Qpt2rTBTz/9VKnl4uPjkZKSInmYmZlJ5u3atQuzZs1CQEAArly5gjZt2qB3795IS0uTtJk5cyYOHDiAPXv2IDo6Go8fP8bHH3+slOOJjo6Gt7c3zp8/j/DwcBQUFMDT0xOvXr2SWsfEiROl1rFs2bJqj6emxgQALVu2lJp/+vRpqfk1tY2AmhnTpUuXpOaFh4cDAD777DOpdSjTdhoyZAhOnjyJjRs3Ij4+Hjt27ICTk5Nk/tmzZzFs2DCMHz8eMTExGDRoEAYNGoS4uDhJm2XLluGHH37A2rVrceHCBTRo0AC9e/dGbm5uxTtPjIiIANC+ffve2iYyMpIAUHp6erltOnbsSN7e3pLnhYWFZGVlRSEhIURE9PLlSxIKhbRnzx5Jm1u3bhEAOnfuXLXG8CZ5jae0tLQ0AkDR0dGSaW5ubjRjxoyqdbQS5DWmgIAAatOmTbnza2sbEdXcdpoxYwY5OjpSUVGRZJoybacjR46QgYEBPX/+vNw2Q4YMoX79+klN69SpE02aNImIiIqKisjCwoK+++47yfyXL1+SlpYW7dixo8L9Vek9wapq27YtLC0t0atXL5w5c0YyPT8/H5cvX0bPnj0l09TU1NCzZ0+cO3cOAHD58mUUFBRItWnevDlsbW0lbWpbeeORRSwWAwCMjIykpm/fvh0mJiZwdnbGvHnzkJ2dXWP9rYh3jenOnTuwsrJC48aNMWLECDx48EAyTxm3EVDx7ZSfn49t27Zh3LhxZS4Aoizb6c8//0T79u2xbNkyNGrUCM2aNYOvry9ycnIkbc6dOye1DQCgd+/ekm2QlJSE1NRUqTYGBgbo1KlTpbYTX0ChEiwtLbF27Vq0b98eeXl5+OWXX+Du7o4LFy7g/fffx7Nnz1BYWAhzc3Op5czNzfHPP/8AAFJTU6GpqQlDQ8MybUofW6xp7xpPaUVFRfDx8YGrqyucnZ0l04cPHw47OztYWVnh2rVrmDt3LuLj47F3797aHA6Aio2pU6dO2Lx5M5ycnJCSkoJFixbhww8/RFxcHPT09JRqG1V0TG/av38/Xr58iTFjxkhNV6btlJiYiNOnT0NbWxv79u3Ds2fPMHXqVDx//hybNm0CUPxekfVeKtkGJf++rU1FcAhWgpOTk9Qxiy5duiAhIQErV67E1q1bFdizqqnseLy9vREXF1fm+Nn//vc/yf9btWoFS0tL9OjRAwkJCXB0dKy5AchQkTH17dtXMr9169bo1KkT7OzssHv3bowfP75W+1sRld1OGzduRN++fWFlZSU1XZm2U1FREQQCAbZv3y65GsyKFSvw6aef4ueff4ZIJKq1vvDH4Wrq2LEj7t69CwAwMTGBurp6mbOIT548gYWFBQDAwsIC+fn5ePnyZbltFOnN8bxp2rRpOHjwICIjI995mbFOnToBgMz1KEJ5YyphaGiIZs2aSdoo+zYCyh/T/fv3ceLECUyYMOGd61DkdrK0tESjRo2kLof13nvvgYjw8OFDAMXb4V3vpZJp5bWpCA7Barp69SosLS0BAJqammjXrh1OnjwpmV9UVISTJ0+ic+fOAIB27dpBKBRKtYmPj8eDBw8kbRTpzfEAxSUI06ZNw759+xAREQEHB4cKrQOA1HoUqfSYSsvKykJCQoKkjbJvI6D8MW3atAlmZmbo169fhdYBKGY7ubq64vHjx8jKypJMu337ttS1PDt37iy1DQAgPDxcsg0cHBxgYWEh1SYjIwMXLlyo3Haq8CmUeigzM5NiYmIoJiaGANCKFSsoJiaG7t+/T0REfn5+NHLkSEn7lStX0v79++nOnTt0/fp1mjFjBqmpqdGJEyckbXbu3ElaWlq0efNmunnzJv3vf/8jQ0NDSk1NlbSZPHky2draUkREBP3999/UuXNn6ty5s1KOZ8qUKWRgYEBRUVGUkpIieWRnZxMR0d27dykoKIj+/vtvSkpKoj/++IMaN25M3bp1q/Z4ampMs2fPpqioKEpKSqIzZ85Qz549ycTEhNLS0iRtamob1dSYiIorEWxtbWnu3LllXlPZtlNmZiZZW1vTp59+Sjdu3KDo6Ghq2rQpTZgwQdLmzJkzpKGhQd9//z3dunWLAgICSCgU0vXr1yVtvv32WzI0NKQ//viDrl27RgMHDiQHBwfKycmpcN9VOgRLSg9KP0aPHk1ERKNHjyY3NzdJ+6VLl5KjoyNpa2uTkZERubu7U0RERJn1rl69mmxtbUlTU5M6duxI58+fl5qfk5NDU6dOpYYNG5KOjg4NHjyYUlJSlHI8stYHgDZt2kRERA8ePKBu3bqRkZERaWlpUZMmTWjOnDkkFourPZ6aGtPnn39OlpaWpKmpSY0aNaLPP/+c7t69K9WmprZRTY2JiOjYsWMEgOLj48vMU7btRFRcdtSzZ08SiURkbW1Ns2bNkvxxLbF7925q1qwZaWpqUsuWLenQoUNS84uKimjhwoVkbm5OWlpa1KNHD5njfxu+lBZjTKXxMUHGmErjEGSMqTQOQcaYSuMQZIypNA5BxphK4xBkjKk0DkHGmErjEGSMqTQOQcaYSuMQZIypNA5BppTc3d3h4+Oj6G5IVLU/z58/h5mZGe7duyf3PpU2dOhQLF++vMZfp77hEFRha9euhZ6eHl6/fi2ZlpWVBaFQCHd3d6m2JXc8S0hIqOVe1i55h++SJUswcOBA2Nvby22d5VmwYAGWLFkiuQUCqxgOQRXm4eGBrKws/P3335Jpp06dgoWFBS5cuCB1x67IyEjY2trW+hWI67Ls7Gxs3Lix1q5W7ezsDEdHR2zbtq1WXq++4BBUYU5OTrC0tERUVJRkWlRUFAYOHAgHBwecP39earqHhwcA4OjRo+jatSsMDQ1hbGyM/v37S+0hrl+/HlZWVigqKpJ6vYEDB2LcuHEAii82GxISAgcHB4hEIrRp0wa//fZbuX2tSHt3d3dMnz4dX331FYyMjGBhYYHAwECpNpmZmRgxYgQaNGgAS0tLrFy5UrL3N2bMGERHRyM0NFRyX943P8YWFRW9dd2lHT58GFpaWvjggw+kpp8+fRpCoVDqj8y9e/cgEAhw//59yf9///13dOvWDSKRCB06dMCDBw9w6tQpfPDBB9DR0UGPHj3KXP16wIAB2Llz51v7xUqp5GXDWD0zfPhw8vT0lDzv0KED7dmzhyZPnkz+/v5ERJSdnS25UCwR0W+//Ua///473blzh2JiYmjAgAHUqlUrKiwsJCKiFy9ekKamptRFP58/fy41bfHixdS8eXM6evQoJSQk0KZNm0hLS4uioqKIqOztId/VvmQZfX19CgwMpNu3b9OWLVtIIBDQ8ePHJW0mTJhAdnZ2dOLECbp+/ToNHjyY9PT0aMaMGfTy5Uvq3LkzTZw4UXLx2NevX1d43aVNnz6d+vTpU2b66tWrqVWrVlLT9u7dSw0bNiQiov379xMA6tGjB506dYquXLlCNjY29OGHH5KXlxddunSJzp8/T8bGxrRixQqp9Rw5coQ0NTUpNze33H4xaRyCKm7Dhg3UoEEDKigooIyMDNLQ0KC0tDQKCwuTXHX45MmTBEByleDSnj59SgCkrvg7cOBAGjdunOT5unXryMrKigoLCyk3N5d0dHTo7NmzUusZP348DRs2jIikQ7Ai7UuW6dq1q1SbDh06SK60nJGRUeZ+wi9fviQdHR3Ja5V3b953rVuW0j+DEhMmTKBRo0ZJTfP39yd3d3ciIgoMDCQjIyN69uyZZP4XX3xB9vb29OrVK8m0Pn360FdffSW1ntjYWAJA9+7dK7dfTBp/HFZx7u7uePXqFS5duoRTp06hWbNmMDU1hZubm+S4YFRUFBo3bgxbW1sAxffsHTZsGBo3bgx9fX3JQf837907YsQI/P7778jLywNQfL/boUOHQk1NDXfv3kV2djZ69eoFXV1dyeP//u//ZJ54qUz71q1bSz23tLREWloagOLbPBYUFKBjx46S+QYGBlJ3cnubt61blpycHGhra5eZfvXqVbRt21ZqWkxMjGRabGwsBg8eDGNjY8n8Bw8e4PPPP4eOjo7UtNL3fCm5S5ui7/tcl/AtN1VckyZNYG1tjcjISKSnp8PNzQ0AYGVlBRsbG5w9exaRkZHo3r27ZJkBAwbAzs4OGzZskBz7c3Z2Rn5+vlQbIsKhQ4fQoUMHnDp1CitXrgQAyc11Dh06hEaNGkn1R0tLq0wfK9NeKBRKPRcIBGWOTVZVZddtYmKC9PR0qWmFhYWIi4uDi4uL1PQrV67gk08+AVAckvPmzZOaHxsbi5kzZ0qe5+bmIj4+Hm3atJFq9+LFCwCAqalpBUfFOAQZPDw8EBUVhfT0dMyZM0cyvVu3bjhy5AguXryIKVOmACiue4uPj8eGDRvw4YcfAkCZ+xADgLa2Nj7++GNs374dd+/ehZOTk+RG4S1atICWlhYePHggCd23qWz78jRu3BhCoRCXLl2S7NWKxWLcvn0b3bp1A1B8x8DCwsIqv8abXFxcypypjY+PR25urtQ9gc+dO4dHjx6hbdu2yMjIwL1796RCMikpCWKxWGra9evXQURo1aqV1Prj4uJgbW0NExMTuYxBFXAIMnh4eMDb2xsFBQVSIePm5oZp06YhPz9fcma4YcOGMDY2xvr162FpaYkHDx7Az89P5npHjBiB/v3748aNG/jiiy8k0/X09ODr64uZM2eiqKgIXbt2hVgsxpkzZ6Cvr4/Ro0dLraey7cujp6eH0aNHY86cOTAyMoKZmRkCAgKgpqYGgUAAALC3t8eFCxdw79496OrqwsjICGpqVTtq1Lt3b8ybNw/p6elo2LAhgP9uc7l69WpMnz4dd+/exfTp0wEA+fn5iI2Nhbq6OpydnSXruXr1KoyMjGBnZyc1zdHREbq6ulKveerUKXh6elapv6qKjwkyeHh4ICcnB02aNIG5ublkupubGzIzMyWlNACgpqaGnTt34vLly3B2dsbMmTPx3XffyVxv9+7dYWRkhPj4eAwfPlxqXnBwMBYuXIiQkBC899576NOnDw4dOlTufY0r2748K1asQOfOndG/f3/07NkTrq6ueO+99yTH7nx9faGuro4WLVrA1NRU6jhnZbVq1Qrvv/8+du/eLZl29epV9O7dG4mJiWjVqhXmz5+PRYsWQV9fHz/88ANiY2Ph5OQkdSwxNja2zMfn2NjYMh+Fc3NzsX//fkycOLHKfVZFfLc5ptJevXqFRo0aYfny5TVS1Hzo0CHMmTMHcXFxUFNTQ+/evdGhQwcsXrxY7q+1Zs0a7Nu3D8ePH5f7uusz/jjMVEpMTAz++ecfdOzYEWKxGEFBQQCKC7lrQr9+/XDnzh08evQINjY2iI2NlRSMy5tQKMTq1atrZN31Ge8JMpUSExODCRMmID4+HpqammjXrh1WrFhR5gRDTUhNTYWlpSVu3LiBFi1a1PjrsYrhEGSMqTQ+McIYU2kcgowxlcYhyBhTaRyCjDGVxiHIGFNpHIKMMZXGIcgYU2kcgowxlcYhyBhTaRyCjDGV9v8eWm/9W8Wd0AAAAABJRU5ErkJggg==",
       "text/plain": [
-       "Output()"
+       "<Figure size 300x300 with 1 Axes>"
       ]
      },
      "metadata": {},
      "output_type": "display_data"
-    },
+    }
+   ],
+   "source": [
+    "reference_point = (0, -y_wg)\n",
+    "waveguide_point = (0, -y_wg)\n",
+    "other_point = (0, 0)\n",
+    "\n",
+    "# Downsample wavelengths to speed up the calculation\n",
+    "spectrum = lambdas_ring[::10]\n",
+    "ring_waveguide_medium = approximate_material(\n",
+    "    sim_ring_3D, waveguide_point, reference_point, spectrum, plot=True, min_num_poles=4\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "4ade732a-6ce6-4847-a5ba-c5923834d667",
+   "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\">14:02:11 EST </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\">Best weighted RMS error: 0 <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": [
-       "\u001b[2;36m14:02:11 EST\u001b[0m\u001b[2;36m \u001b[0mstatus = preprocess                                                \n"
+       "Best weighted RMS error: 0 \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[36m0:00:00\u001b[0m\n"
       ]
      },
      "metadata": {},
@@ -3062,70 +849,65 @@
      },
      "metadata": {},
      "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ring_background_medium = approximate_material(sim_ring_3D, other_point, reference_point, spectrum)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "bbda4057-4feb-4350-8de7-ac3d9668ba7f",
+   "metadata": {},
+   "source": [
+    "As before, we create a 2D copy of the simulation and replace the mediums with those that we just calculated."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "4a0245f6-7372-4315-a919-1bfd49ea192f",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Note: removed symmetry, as it is incompatible with the variational approximation method.\n"
+     ]
     },
     {
      "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\">14:02:13 EST </span>Maximum FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.055</span>. Use <span style=\"color: #008000; text-decoration-color: #008000\">'web.real_cost(task_id)'</span> to get\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>the billed FlexCredit cost after a simulation run.                 \n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m14:02:13 EST\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.055\u001b[0m. 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\n",
-       "\u001b[2;36m             \u001b[0mthe billed FlexCredit 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"
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "7ced6889c30d4a2292003b03da51cf62",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "image/png": 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",
       "text/plain": [
-       "Output()"
+       "<Figure size 640x480 with 2 Axes>"
       ]
      },
      "metadata": {},
      "output_type": "display_data"
-    },
+    }
+   ],
+   "source": [
+    "sim_ring_2D = create_2D_sim(sim_ring_3D, [ring_waveguide_medium, ring_background_medium])\n",
+    "\n",
+    "sim_ring_2D.plot_eps(z=0, freq=freq0)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "71d391f2-3935-44a3-9a8d-1cf4abb4e219",
+   "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\">14:02:39 EST </span>early shutoff detected at <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">36</span>%, exiting.                            \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: #008000; text-decoration-color: #008000; font-weight: bold\">↓</span> <span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">simulation_data.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\">33.2/33.2 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[2;36m14:02:39 EST\u001b[0m\u001b[2;36m \u001b[0mearly shutoff detected at \u001b[1;36m36\u001b[0m%, exiting.                            \n"
+       "\u001b[1;32m↓\u001b[0m \u001b[1;34msimulation_data.hdf5.gz\u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100.0%\u001b[0m • \u001b[32m33.2/33.2 kB\u001b[0m • \u001b[31m?\u001b[0m • \u001b[36m0:00:00\u001b[0m\n"
       ]
      },
      "metadata": {},
@@ -3144,51 +926,218 @@
     {
      "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\">14:35:14 EDT </span>loading simulation from simulation_data.hdf5                       \n",
        "</pre>\n"
       ],
       "text/plain": [
-       "\n"
+       "\u001b[2;36m14:35:14 EDT\u001b[0m\u001b[2;36m \u001b[0mloading simulation from simulation_data.hdf5                       \n"
       ]
      },
      "metadata": {},
      "output_type": "display_data"
-    },
+    }
+   ],
+   "source": [
+    "sim_data_2D = web.run(sim_ring_2D, task_name=\"2.5D FDTD ring resonator 2D\")\n",
+    "sim_data_3D = web.run(sim_ring_3D, task_name=\"2.5D FDTD ring resonator 3D\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "3dc98bc3-bbcf-4a4b-8d86-7fab1b9bd0a4",
+   "metadata": {},
+   "source": [
+    "### Example 2 Result Comparison\n",
+    "\n",
+    "We will compare the results of our 2D and 3D simulations to see how representative our approximation is. As one can see, the resonant behavior of this setup is well-approximated, especially near the central frequency. The depth of the peaks is lower in the 2D simulation because the 3D simulation takes into account vertical coupling. Toward the ends of the spectrum, there is more error in the free spectral range and resonance frequencies, although this is still well within 1% of the resonant wavelength, as we show for the first resonance. However, the next example will show that this method will not always be a good approximation."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "3e23ed0d-1a5f-4a7a-bfd2-ec7a5e3b975e",
+   "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\">             </span>status = postprocess                                               \n",
-       "</pre>\n"
-      ],
+      "image/png": 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",
       "text/plain": [
-       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mstatus = postprocess                                               \n"
+       "<Figure size 640x480 with 1 Axes>"
       ]
      },
      "metadata": {},
      "output_type": "display_data"
     },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Difference in first resonant wavelength: 0.0033333333333331883\n"
+     ]
+    }
+   ],
+   "source": [
+    "sim_data_2D[\"mode through\"].amps.sel(mode_index=0, direction=\"+\").abs.plot(x=\"f\")\n",
+    "sim_data_3D[\"mode through\"].amps.sel(mode_index=0, direction=\"+\").abs.plot(x=\"f\")\n",
+    "plt.legend([\"2D\", \"3D\"])\n",
+    "plt.show()\n",
+    "\n",
+    "res_lda_2d = (\n",
+    "    td.C_0 / sim_data_2D[\"mode through\"].amps.sel(mode_index=0, direction=\"+\").abs.f.data[46]\n",
+    ")\n",
+    "res_lda_3d = (\n",
+    "    td.C_0 / sim_data_3D[\"mode through\"].amps.sel(mode_index=0, direction=\"+\").abs.f.data[56]\n",
+    ")\n",
+    "res_wavelength_dif = np.abs(res_lda_2d - res_lda_3d)\n",
+    "print(f\"Difference in first resonant wavelength: {res_wavelength_dif}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "59164d1d-6a30-4c1e-8570-69fb76fccc42",
+   "metadata": {},
+   "source": [
+    "## Strip-to-slot Counter-example\n",
+    "\n",
+    "This approximation method is not always applicable, and care must be taken to ensure that a given material's approximation is not too far off from the physical constraints of the original material. If not, this can lead to poor approximations. (One can check this by printing out the $n_{eff}^2 + \\frac{num}{denom}$ value calculated in the variational method function above.)\n",
+    "<br><br>\n",
+    "We will now show an example where this approximation does not work as well. We will use the first design of our [strip to slot converter example](https://www.flexcompute.com/tidy3d/examples/notebooks/StripToSlotConverters/). First we copy the simulation parameters from the notebook, removing the field monitor, as it will be unnecessary for this illustration:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "2b46a885-4127-4b88-b32a-2c8714fe3b93",
+   "metadata": {},
+   "outputs": [
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "image/png": 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",
       "text/plain": [
-       "Output()"
+       "<Figure size 640x480 with 2 Axes>"
       ]
      },
      "metadata": {},
      "output_type": "display_data"
-    },
+    }
+   ],
+   "source": [
+    "# Define wavelength/frequency ranges\n",
+    "lda0 = 1.55\n",
+    "ldas = np.linspace(1.5, 1.6, 101)\n",
+    "freq0 = td.C_0 / lda0\n",
+    "freqs = td.C_0 / ldas\n",
+    "fwidth = 0.5 * (np.max(freqs) - np.min(freqs))\n",
+    "\n",
+    "# Create materials\n",
+    "n_si = 3.47\n",
+    "si = td.Medium(permittivity=n_si**2)\n",
+    "n_sio2 = 1.44\n",
+    "sio2 = td.Medium(permittivity=n_sio2**2)\n",
+    "\n",
+    "# Define geometry\n",
+    "L_mmi = 1.38\n",
+    "W_mmi = 1.24\n",
+    "L = 6\n",
+    "buffer = 5\n",
+    "h_si = 0.25\n",
+    "w_strip = 0.4\n",
+    "w_slot = 0.62\n",
+    "g = 0.1\n",
+    "\n",
+    "vertices = [\n",
+    "    (-buffer, w_strip / 2),\n",
+    "    (0, w_strip / 2),\n",
+    "    (0, W_mmi / 2),\n",
+    "    (L_mmi, W_mmi / 2),\n",
+    "    (L, w_slot / 2),\n",
+    "    (L + buffer, w_slot / 2),\n",
+    "    (L + buffer, g / 2),\n",
+    "    (L_mmi, g / 2),\n",
+    "    (L_mmi, -g / 2),\n",
+    "    (L + buffer, -g / 2),\n",
+    "    (L + buffer, -w_slot / 2),\n",
+    "    (L, -w_slot / 2),\n",
+    "    (L_mmi, -W_mmi / 2),\n",
+    "    (0, -W_mmi / 2),\n",
+    "    (0, -w_strip / 2),\n",
+    "    (-buffer, -w_strip / 2),\n",
+    "]\n",
+    "\n",
+    "converter = td.Structure(\n",
+    "    geometry=td.PolySlab(vertices=vertices, axis=2, slab_bounds=(-h_si / 2, h_si / 2)), medium=si\n",
+    ")\n",
+    "\n",
+    "# Define mode source\n",
+    "mode_spec = td.ModeSpec(num_modes=1, target_neff=n_si)\n",
+    "mode_source = td.ModeSource(\n",
+    "    center=(-lda0, 0, 0),\n",
+    "    size=(0, 4 * w_strip, 6 * h_si),\n",
+    "    source_time=td.GaussianPulse(freq0=freq0, fwidth=fwidth),\n",
+    "    direction=\"+\",\n",
+    "    mode_spec=mode_spec,\n",
+    "    mode_index=0,\n",
+    "    num_freqs=7,\n",
+    ")\n",
+    "\n",
+    "# Define mode monitor\n",
+    "mode_monitor = td.ModeMonitor(\n",
+    "    center=(L + lda0, 0, 0),\n",
+    "    size=(0, 4 * w_strip, 6 * h_si),\n",
+    "    freqs=freqs,\n",
+    "    mode_spec=mode_spec,\n",
+    "    name=\"mode\",\n",
+    ")\n",
+    "\n",
+    "# Define misc. simulation parameters\n",
+    "Lx = L + 3 * lda0\n",
+    "Ly = W_mmi + lda0\n",
+    "Lz = 10 * h_si\n",
+    "sim_size = (Lx, Ly, Lz)\n",
+    "\n",
+    "run_time = 1e-12\n",
+    "\n",
+    "# construct simulation\n",
+    "sim_splitter_3D = td.Simulation(\n",
+    "    center=(L / 2, 0, 0),\n",
+    "    size=sim_size,\n",
+    "    grid_spec=td.GridSpec.auto(min_steps_per_wvl=30, wavelength=lda0),\n",
+    "    structures=[converter],\n",
+    "    sources=[mode_source],\n",
+    "    monitors=[mode_monitor],\n",
+    "    run_time=run_time,\n",
+    "    boundary_spec=td.BoundarySpec.all_sides(boundary=td.PML()),\n",
+    "    medium=sio2,\n",
+    "    symmetry=(0, -1, 1),\n",
+    ")\n",
+    "\n",
+    "# plot the simulation\n",
+    "sim_splitter_3D.plot_eps(z=0, freq=freq0)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "68b9ba6d-af75-47bd-9bf7-9341f3693b97",
+   "metadata": {},
+   "source": [
+    "Now we convert the 3D simulation to a 2D simulation, as before."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "dd794575-4213-4a95-9586-b1e1625eb316",
+   "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\">14:02:43 EST </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\">Best weighted RMS error: 0 <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": [
-       "\u001b[2;36m14:02:43 EST\u001b[0m\u001b[2;36m \u001b[0mstatus = success                                                   \n"
+       "Best weighted RMS error: 0 \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100%\u001b[0m \u001b[36m0:00:00\u001b[0m\n"
       ]
      },
      "metadata": {},
@@ -3205,42 +1154,53 @@
      "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-6d645823-3048-4598-a4c7-8c0959f8685c\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-6d645823-304</span></a>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-6d645823-3048-4598-a4c7-8c0959f8685c\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">8-4598-a4c7-8c0959f8685c'</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=963963;https://tidy3d.simulation.cloud/workbench?taskId=fdve-6d645823-3048-4598-a4c7-8c0959f8685c\u001b\\\u001b[4;34m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=427813;https://tidy3d.simulation.cloud/workbench?taskId=fdve-6d645823-3048-4598-a4c7-8c0959f8685c\u001b\\\u001b[4;34mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=963963;https://tidy3d.simulation.cloud/workbench?taskId=fdve-6d645823-3048-4598-a4c7-8c0959f8685c\u001b\\\u001b[4;34m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=904508;https://tidy3d.simulation.cloud/workbench?taskId=fdve-6d645823-3048-4598-a4c7-8c0959f8685c\u001b\\\u001b[4;34mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=963963;https://tidy3d.simulation.cloud/workbench?taskId=fdve-6d645823-3048-4598-a4c7-8c0959f8685c\u001b\\\u001b[4;34m-6d645823-304\u001b[0m\u001b]8;;\u001b\\\n",
-       "\u001b[2;36m             \u001b[0m\u001b]8;id=963963;https://tidy3d.simulation.cloud/workbench?taskId=fdve-6d645823-3048-4598-a4c7-8c0959f8685c\u001b\\\u001b[4;34m8-4598-a4c7-8c0959f8685c'\u001b[0m\u001b]8;;\u001b\\\u001b[4;34m.\u001b[0m                                         \n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Note: removed symmetry, as it is incompatible with the variational approximation method.\n"
+     ]
     },
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "fccf4d62df404997a2948473019a69c0",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "image/png": 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",
       "text/plain": [
-       "Output()"
+       "<Figure size 640x480 with 2 Axes>"
       ]
      },
      "metadata": {},
      "output_type": "display_data"
-    },
+    }
+   ],
+   "source": [
+    "# Approximate materials by downsampling again\n",
+    "spectrum = ldas[::15]\n",
+    "ref_point = (0, 0)\n",
+    "core_point = (0, 0)\n",
+    "other_point = (2, 0)\n",
+    "\n",
+    "waveguide_splitter_mat = approximate_material(sim_splitter_3D, core_point, ref_point, spectrum)\n",
+    "background_splitter_mat = approximate_material(sim_splitter_3D, other_point, ref_point, spectrum)\n",
+    "\n",
+    "sim_splitter_2D = create_2D_sim(sim_splitter_3D, [waveguide_splitter_mat, background_splitter_mat])\n",
+    "sim_splitter_2D.plot_eps(z=0, freq=freq0)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "f56574ce-a75a-4d93-bab8-8715c24ddbc7",
+   "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\"></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: #008000; text-decoration-color: #008000; font-weight: bold\">↓</span> <span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">simulation_data.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\">9.9/9.9 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": []
+      "text/plain": [
+       "\u001b[1;32m↓\u001b[0m \u001b[1;34msimulation_data.hdf5.gz\u001b[0m \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[35m100.0%\u001b[0m • \u001b[32m9.9/9.9 kB\u001b[0m • \u001b[31m?\u001b[0m • \u001b[36m0:00:00\u001b[0m\n"
+      ]
      },
      "metadata": {},
      "output_type": "display_data"
@@ -3248,12 +1208,9 @@
     {
      "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"
+       "<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": [
-       "\n"
-      ]
+      "text/plain": []
      },
      "metadata": {},
      "output_type": "display_data"
@@ -3261,11 +1218,11 @@
     {
      "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\">14:02:44 EST </span>loading simulation from simulation_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\">14:36:33 EDT </span>loading simulation from simulation_data.hdf5                       \n",
        "</pre>\n"
       ],
       "text/plain": [
-       "\u001b[2;36m14:02:44 EST\u001b[0m\u001b[2;36m \u001b[0mloading simulation from simulation_data.hdf5                       \n"
+       "\u001b[2;36m14:36:33 EDT\u001b[0m\u001b[2;36m \u001b[0mloading simulation from simulation_data.hdf5                       \n"
       ]
      },
      "metadata": {},
@@ -3295,7 +1252,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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G0qVLkZ6eDr1ej3vuucfmflHW7rrrLqxcuRJPP/002rRpY3Pn6127duGbb77B4sWLAcCuY58yZQreeOMNTJkyBd26dcMvv/yC06dPl3l858+fx9ChQ3Hfffdh//79WL9+PcaOHYtOnTqV+35W1pNPPon33nsPY8aMwcyZMxEYGIgNGzYowbiiLW/ff/+90mJm7a677rLpKF9ZKpUKq1atwpAhQ9C5c2dMmjQJgYGBOHnyJP744w/88MMPpa7XvHlzLF68GHPnzkViYiKGDx8ODw8PnD9/Htu2bcM///lPPPfcc3bVZcKECVi3bh2ioqJw8OBB3H333cjOzsZPP/2Ep59+2ub+RYMHD0aDBg2wZcsW3H///WX+/0dUYc4YCkdUVb7//nsxefJk0aZNG+Hu7i50Op1o0aKFeOaZZ0RKSorNsidPnhR9+/YVLi4uAoAyPNsyHPnKlSsltl/WcP1p06aJ9evXi5YtWwq9Xi+6dOlSoWHsQpiHST/zzDOiUaNGQpIkm+1nZmaK2bNni8aNGwutVitatmwp/vWvf1VoKPKRI0fEmDFjRHBwsNDr9cLPz088+OCDNrcVsNTfeli7Zd3IyEjh7u4uXF1dxYABA8S+fftK7GPNmjWiWbNmQq1WV3jo/uHDh8XYsWOVY/Lx8RH33nuv+Oyzz4TRaLT72HNycsTjjz8uvLy8hIeHhxg1apRITU0tc7j+iRMnxIgRI4SHh4fw8fER06dPF7m5uTbbrOhw/TvuuKPE8U2cOFGEhITYlJ07d04MHjxYuLi4iEaNGolnn31WbN26VQAQBw4cKPf9Km+4PordquB2hutb7N27VwwcOFB4eHgINzc30bFjR/Huu+8q80v7DAghxNatW0WfPn2Em5ubcHNzE23atBHTpk0Tp06dUpax5z3LyckR8+bNE2FhYUKr1YqAgAAxYsQIm9tIWFhuubBx48YS84jsxd9KI7pNkiRh2rRppTb7U83x6quvYuHChbhy5Yry22LOtGLFCsyePRt///03mjRp4uzq1GqzZ8/Gxx9/jOTkZLi6ujq7OlTLsY8REVEVy83NtZnOy8vDBx98gJYtWzIU3aa8vDysX78ejzzyCEMROQT7GBERVbGHH34YwcHB6Ny5M9LT07F+/XqcPHnS5uaEZJ/U1FT89NNP+PLLL3H16tVyf7KEyB4MRkREVSwyMhIfffQRNmzYAKPRiHbt2mHTpk0YPXq0s6tWa504cQLjxo2Dn58f3nnnHWXEJdHtcmofo19++QX/+te/cPjwYVy+fBnbtm3D8OHDy11n165diIqKwh9//IGgoCC8/PLLNr/ITURERFRZTu1jlJ2djU6dOpW4r0hZzp8/j8GDB2PAgAGIj4/HrFmzMGXKlDKHkRIRERHZo8aMSpMk6ZYtRi+88AJ27NiB48ePK2WPPvoobty4gZ07d1ZDLYmIiKguq1V9jPbv31/iVvWRkZGYNWtWmevk5+fb3OXXZDLh2rVraNCgAX99mYiIqJYQQiAzMxONGzeGSlV1F7xqVTBKTk6Gv7+/TZm/vz8yMjKQm5tb6o9+RkdHV+juw0RERFTzJSUloWnTplW2/VoVjCpj7ty5iIqKUqbT09MRHByMpKQk5TefiIiIqGbLyMhAUFCQzQ9LV4VaFYwCAgKQkpJiU5aSkgJPT89SW4sAQK/XQ6/Xlyj39PRkMCIiIqplqrobTK2683V4eDhiY2NtymJiYhAeHu6kGhEREVFd4tRglJWVhfj4eMTHxwMwD8ePj4/HxYsXAZgvg02YMEFZfurUqTh37hyef/55nDx5Eu+//z6++OILzJ492xnVJyIiojrGqcHo0KFD6NKlC7p06QIAiIqKQpcuXTB//nwAwOXLl5WQBABhYWHYsWMHYmJi0KlTJ7z55pv46KOPEBkZ6ZT6ExERUd1SY+5jVF0yMjLg5eWF9PR09jEiIiKqJarr+7tW9TEiIiIiqkq1alQaEVUBkwkQRkCYAJOx2GthnjbJZTavRbFlTVYPq3nWD5t1i81D8TJRcjllGWE1bXmNcubJr0t9BuT/3CxTXsNq2eLLFVfRxvdSRtQoo2wkq+lir5VnFJu2epZUZb+2KVOV8rBeTl1yvkptO0+lLva6tDK1+VmlBlQa22lJLlPmqazeByLnYTCiusnyhWgqsnoYS5kuViasy4o9C2PZ65a2Xlnbsi5XXhcvN5WyX+tgYv1sst2WpazEsqUFH6OzzxTRTUpY0tiGpuLTaq38WltyWq29ubxaK5dpbOeptYBad3Oe8louV1u/1pXz2qpMo5e3o2HAq+UYjOo6U/FwUMrDWLystABRWM78srZRbB1jedtw0LR1eCHHsfylr7QgqAGV1WtLS4KyjGQ1r3jLQ7HpUlswrFs6ii9XvDVEsp1X4nVpZSg2r5QWGuW19bIoZZ7NG3WLN9KqVal4K1RpZWW2chVr7bIuL7W1zLqVTl7WZLSaZ9WiB5TRymcJ1GW1MN4ijFs+p+W1rAkjYDQCxvyyl6nxpJshSa27+drmWQ9odIDGcLNMo7eaNsgPy2t9Gc+Gm9NaF9uyKvzJjLqu/gaj3BuAuhAlvuDLCgHKl/qtvqCLbaNEYCjtcat9lBdAbhFqLJcY6CZLk77yV6bGqpnf8lepVdO/2npesfnKeirbv2yLl1mHBuvt3PJSg9p2e9Z1LLOsvMsaKqtl1MXKi82zDjJEjmKyBK4i28BUvAXWWLyVtvi/f4VWf3BZv5bnGS3PBVavC4vNs/w7XWB+bZSXN1m9NhYARQVW2yr2XJQP27AngKI888OZ1DpA4yKHJoP5tdYAaF3NwUnrIocp+VlZxsW8jGVZrXVZKc8alzr3b0T9DUYr2gP6etzcadM8bfmy18Kmudqmibr48tYPVckmbSV4WPchKCWMlPVQF5uWVOZ1bQKK1X5tAovWdtq6LuzHQORcKhUAlfkzXhcIufXNmG8OScZC+XWBVVlBsXmWcnm5ojzb10X5clmx6eLPhXlAUa68Xq5tS7kl1FVH45vGBdC5ymFJDkw6N6tQ5Waer3O7+VorT1uX6dwAnbtcJk+r1NVwAMUOp9r3WBOVuE5t9Ve+zRe0tuSXsVpzixBwiy98my9yeVpd/Mteg5Khxfr6elkBQ211DFbHyHBAROQYkiT3U9KYv8idyVh0s7XKOjiV9lyYIy+Ta34U5d58XZgrz8uRp3NurmMps24RK5LXx1XHH5PG5WaAMhocv/3Sdlkte6mJ5pwDvH3rXBMgERHVU2oNoHYH9O5Vvy+TyRyGCnJuBqYCq+BUmG1+Lsi2mpdtnlZeW9bLsiqXpy3dQCyhKycNyK+e2y7W32Ck0TEUERERVYZKdbMlx9GE3E+rINv2cTUFeGOI4/dXTP0NRkRERFTzSNLN/kluDW+We2VUy+7ZZEJEREQkYzAiIiIikjEYEREREckYjIiIiIhkDEZEREREMgYjIiIiIhmDEREREZGMwYiIiIhIxmBEREREJGMwIiIiIpIxGBERERHJGIyIiIiIZAxGRERERDIGIyIiIiIZgxERERGRjMGIiIiISMZgRERERCRjMCIiIiKSMRgRERERyRiMiIiIiGQMRkREREQyBiMiIiIiGYMRERERkYzBiIiIiEjGYEREREQk0zi7AlQ7CSGQX2RCVn4RsvOLkJ1vRG6h+TmnoAg5BUbkFhqRW2BEfpEJufJ0QZEJ+UXmMvNrEwqN5keRUaDQJFBkNMFoEuaHEDDJz0IAQpSsi0oFqCQJKkmCJAEalQS1SiU/S9CqJWjVKmjVKug0KujkZ4NWBb1GDb1WBYNGDYNWDRetCq46DQw6NVy1arjq1HDTa+Cmtzxr4KbTQK2Sqv9NJyKiKsdgVE/lFRqRkVuIjLxCpOcWIiO3CBl5hcjIK0JGbiEy88zTmXlFyMwrRFZeETLzipCVb57OLjDCaColpdQTrjo13PUauBs08NBr4GHQwsOggafl2UULT4MGXq5aeBq08HK5+fB00cKgVTv7EIiIqBQMRrVYfpFRDjXmcGN53Mi5+VxinvxcUGRyWD3cdGq46jVw06nhorM8q+GiNT8bNOZnvaWFRqNSHpZWHI1aBZ1agkalgkZtbulRqySoJfOzSiXB0kYjSebXAuaWK+VZQGllMpoEikwCRqNAodGEAqMJhUaBArmFKr/IiPxCc4tVXqHcqlV4s5Urp6AIuYUm5OSbW78sLWNFchjMKTAip8CI1Mz8Sr1nBq0KXi5aeLvo4OWqhbeLFt6uWni76szPLpZnqzJXLVy0akgSW6uIiKoKg5ETFRpNyLJqmcnIM7fcZMotN5bQYy63DTjpuYXIK7y9cCNJgKdBC08XjdKqYWn18JRfW1pCLK0i7gaNuaVEbi1x1aqhqkeXlfKLjMjKM18yzMw3t6Rl5Vu3rhVZnbMipUXO8sjILYRJAHmFJuQV5iMlw75gpdOobEOU1Wsv+bWlZcrbRae89jBo6tV5IiKqLAajWzCZBAqMJrl1waplwdKHRmlhMCJX7luTI7c4ZOUb5f435i/P7IIi5Ys0M68I+Q5otbGEG+tLNV6uttPexS7jWJ499PyytJdeo4beXY0G7pVb32QSyCooQrrcqnc9p6BYK18BrudYpgtwI6cQ1+XXlhav1Mx8u1uqJAnw0Fsu8VmFYKsA7GnQwMOggbv+ZgD2MGiUy4Zueg20ao7XIKLqIYTAlax8nL+SjfNp2fjzYkq17LfeBqMxHx6ApHdBkVG+5GK6eZml0OqyS4HRcZecyuKqUyt9UyxfUubwcrP1xqvYw9NgDkAMN7WLSiWZz6lBiyA71hNCIKfAiOs5BUqIsn59Q35tuVRqCV7puYXILTRCCJj7j+UVAcitdP11GpX50qlOAxeduXO6i9xJ3XLZVK9Vw6BVwUWrhk5jvnyqky+dWjq/mzvDS9BqVNDKl08tneU1KhVUKiiXUiXL5VQJkGDuYA+Yw15plxWFVUd9AQGTMJeZBGASwvwwmV/bdPBXXgNFJhNMQqDIaF7e8m9E8TKTyXae0Wq7RSYh79dq3yZLfcx1E+Lm5WBz3W2PRZIACfLlY8k8yECtMr9WywMOLAMMbAYcaMyXprXKe33z8rXlnCiDDnQqeeCBmsGXqp0QAtdzCnE+LRuJadlIvGoOQYlXs5GYloOs/CJlWVN+TrXUqd4Go2OX0qHSF9q1jiRB6S/jYvnHX+lLo1FGMblYRjLpzKOZ3PUauOo1cNerzZej5EtRngYt3PRqaPiPEd2CJEnKqLimPvatm19ktLmsZ7ksa7n0Z750a57OyitCZr51y6a5o72lT1qBPJrweo59nx2qHTQqyRx09XL41arhJr92txqd6WEZeCD/Qeeut/xBd/OPOQ4wIAuTydzyc+FqDi5czcbFazlIlF+fT8tGZl5RmetKEtDUxwVhDd3R2MWEpdVQX0mI0gZA110ZGRnw8vLCtt/+gpeXJzSqmx1+dcqQbsn2ryytucOwRiWx4yvVS4VGE3LyjcgqKFI6pGcXFFldRjYir8iIvEIjcgtMymvLLRkst2kwt8qaL08XyS2zhUaT0upSKN+qwdLaYpRbWExyi4y5oz2U1xCApVe+9SdTZdXCIskzza1OlsfN1heVSm59sersb3morKY1qpKDAtTFylTWz1bbtd7nzdafmy1gpf67YnW8ltYlS+uX8r4IgSKT/J4Z5fdQvuWFedCBQKHc8m19DvKLbg48sLQoOppOo5Iv22puXtZ3vdnvzcfSN85qkIGPPIqTreC1T3puIS5dz0XS9RwkXcvB39dzkXQtBxflx626jgR6GRDawA2hDd0Q1tAVoQ3cENbQDcENXKHXmEO25fs7PT0dnp6eVXYs9bbF6J42flX6xhLVJVq1Cl6uKni5ap1dFXIwIcxBNa/AhJzCm2HX0lcyp8B4s59k/s2+k5l5hfLAg5stj5ZBJEKYWxfTsvKRlmVffziVBDk4mUdj+rrplNDk7aqDr5vta8soTp2GLe9VJb/IiJT0fFxOz8Xl9Dz5kYtL13Nx6Yb5OTO/7FYfwPyHSWNvA0J8zWEntIErQizhx9e1RrUw1ttgRERE5tYq82001PDC7Qdfk0kgu8AcmKz7umXkFuJGrlW/OLkvnKWv3I2cAmQXGGESwHV50IE93PUaeLveDFSWUZs+rlp4ya+tB6d41/N7ihlNAum5hbialY8rWflIyyrAVTnIpmbkIyUzH6kZeUjNzMe17IIKbdPHVYsgX1cE+biiqa8LgnxcEeTrihBfVzTxcak1fdgYjIiIyGFUKknue6RFE28Xu9bNLzLKYckSmMyjNK9lF1iN2CyQp+Vlcs0tVFlyq9bf1+0bXGC55GcZ7OKhjM40j9C0vHbVq+Gm0yh3w7e+R5uL3HldrzUPLqjKS4GWXx3IKzTKt/0wX9bOzrc8F8ktekVKf0LLjXuvy++hZTSsPZdQ9RoVGnu7IMDTgEBvAwK9DGji7YrG3gY09XFBoJcL3PR1I1LUjaMgIqJaT69Rw89TDT9PQ4XXMZqE8qV/w3LLi+xC5bVltOaNnAK51cr2nmKVveRXHo1KMo/AlG9iqynWT83SB856lCWAmyMY5T51hUZzH7JCq75ijrjNizVvVy0auOnQ0F0vP3Tw8zTAz0MPf08D/Dz18PMwwMdVW2/62DIYERFRraVWSfBx08HHTWfXepZ7iik3ZbVqWckuKFJGbWbJN3K19LuytMrkWlpsCozIKbT9iaQik0CRvHxVUqskGDQqedSzPGpQZx696mm4ed8yS2uYpa+Wpd+Wt6u21lzeqk4MRkREVO9Y31PM3kt+pbGM+lPugVdkQoHRPK38RJHc+mMyDzW0GXVoPZLSMopRI9/vyzJiWqM29wczaM33nmKoqRoMRkRERLfJcumMaj+eRSIiIiIZgxERERGRjMGIiIiISMZgRERERCRjMCIiIiKSMRgRERERyRiMiIiIiGQMRkREREQyBiMiIiIiGYMRERERkYzBiIiIiEjGYEREREQkYzAiIiIikjk9GK1cuRKhoaEwGAzo2bMnDh48WO7yK1asQOvWreHi4oKgoCDMnj0beXl51VRbIiIiqsucGow2b96MqKgoLFiwAEeOHEGnTp0QGRmJ1NTUUpffuHEjXnzxRSxYsAB//vknPv74Y2zevBkvvfRSNdeciIiI6iKnBqPly5fjiSeewKRJk9CuXTusXr0arq6u+OSTT0pdft++fejduzfGjh2L0NBQDBo0CGPGjLllKxMRERFRRTgtGBUUFODw4cOIiIi4WRmVChEREdi/f3+p69x11104fPiwEoTOnTuH7777Dg888ECZ+8nPz0dGRobNg4iIiKg0GmftOC0tDUajEf7+/jbl/v7+OHnyZKnrjB07FmlpaejTpw+EECgqKsLUqVPLvZQWHR2NhQsXOrTuREREVDc5vfO1PXbt2oXXX38d77//Po4cOYKvvvoKO3bswGuvvVbmOnPnzkV6errySEpKqsYaExERUW3itBajhg0bQq1WIyUlxaY8JSUFAQEBpa7zyiuv4LHHHsOUKVMAAB06dEB2djb++c9/Yt68eVCpSuY8vV4PvV7v+AMgIiKiOsdpLUY6nQ5du3ZFbGysUmYymRAbG4vw8PBS18nJySkRftRqNQBACFF1lSUiIqJ6wWktRgAQFRWFiRMnolu3bujRowdWrFiB7OxsTJo0CQAwYcIENGnSBNHR0QCAIUOGYPny5ejSpQt69uyJM2fO4JVXXsGQIUOUgERERERUWU4NRqNHj8aVK1cwf/58JCcno3Pnzti5c6fSIfvixYs2LUQvv/wyJEnCyy+/jEuXLqFRo0YYMmQIlixZ4qxDICIiojpEEvXsGlRGRga8vLyQnp4OT09PZ1eHiIiIKqC6vr9r1ag0IiIioqrEYEREREQkYzAiIiIikjEYEREREckYjIiIiIhkDEZEREREMgYjIiIiIhmDEREREZGMwYiIiIhIxmBEREREJGMwIiIiIpIxGBERERHJGIyIiIiIZAxGRERERDIGIyIiIiIZgxERERGRjMGIiIiISMZgRERERCRjMCIiIiKSMRgRERERyRiMiIiIiGQMRkREREQyBiMiIiIiGYMRERERkYzBiIiIiEjGYEREREQkYzAiIiIikjEYEREREckYjIiIiIhkDEZEREREMgYjIiIiIhmDEREREZGMwYiIiIhIxmBEREREJGMwIiIiIpIxGBERERHJGIyIiIiIZAxGRERERDIGIyIiIiIZgxERERGRjMGIiIiISMZgRERERCRjMCIiIiKSMRgRERERyRiMiIiIiGQMRkREREQyBiMiIiIiGYMRERERkYzBiIiIiEjGYEREREQkYzAiIiIikjEYEREREckYjIiIiIhkDEZEREREMgYjIiIiIhmDEREREZGMwYiIiIhIxmBEREREJGMwIiIiIpIxGBERERHJGIyIiIiIZJrKrHTjxg0cPHgQqampMJlMNvMmTJjgkIoRERERVTe7g9F///tfjBs3DllZWfD09IQkSco8SZIYjIiIiKjWsvtS2rPPPovJkycjKysLN27cwPXr15XHtWvX7K7AypUrERoaCoPBgJ49e+LgwYPlLn/jxg1MmzYNgYGB0Ov1aNWqFb777ju790tERERUnN0tRpcuXcKMGTPg6up62zvfvHkzoqKisHr1avTs2RMrVqxAZGQkTp06BT8/vxLLFxQUYODAgfDz88OXX36JJk2a4MKFC/D29r7tuhARERHZHYwiIyNx6NAhNGvW7LZ3vnz5cjzxxBOYNGkSAGD16tXYsWMHPvnkE7z44osllv/kk09w7do17Nu3D1qtFgAQGhp62/UgIiIiAioRjAYPHow5c+bgxIkT6NChgxJQLIYOHVqh7RQUFODw4cOYO3euUqZSqRAREYH9+/eXus4333yD8PBwTJs2Ddu3b0ejRo0wduxYvPDCC1Cr1aWuk5+fj/z8fGU6IyOjQvUjIiKi+sfuYPTEE08AABYtWlRiniRJMBqNFdpOWloajEYj/P39bcr9/f1x8uTJUtc5d+4cfv75Z4wbNw7fffcdzpw5g6effhqFhYVYsGBBqetER0dj4cKFFaoTERER1W92d742mUxlPioaiirLZDLBz88PH374Ibp27YrRo0dj3rx5WL16dZnrzJ07F+np6cojKSmpSutIREREtVel7mPkCA0bNoRarUZKSopNeUpKCgICAkpdJzAwEFqt1uayWdu2bZGcnIyCggLodLoS6+j1euj1esdWnoiIiOqkSt35evfu3RgyZAhatGiBFi1aYOjQodizZ49d29DpdOjatStiY2OVMpPJhNjYWISHh5e6Tu/evXHmzBmbm0qePn0agYGBpYYiIiIiInvYHYzWr1+PiIgIuLq6YsaMGZgxYwZcXFxw7733YuPGjXZtKyoqCmvWrMFnn32GP//8E0899RSys7OVUWoTJkyw6Zz91FNP4dq1a5g5cyZOnz6NHTt24PXXX8e0adPsPQwiIiKiEuy+lLZkyRIsW7YMs2fPVspmzJiB5cuX47XXXsPYsWMrvK3Ro0fjypUrmD9/PpKTk9G5c2fs3LlT6ZB98eJFqFQ3s1tQUBB++OEHzJ49Gx07dkSTJk0wc+ZMvPDCC/YeBhEREVEJkhBC2LOCXq/HH3/8gRYtWtiUnzlzBu3bt0deXp5DK+hoGRkZ8PLyQnp6Ojw9PZ1dHSIiIqqA6vr+tvtSWlBQkE2/IIuffvoJQUFBDqkUERERkTPYfSnt2WefxYwZMxAfH4+77roLAPDrr79i7dq1ePvttx1eQSIiIqLqYncweuqppxAQEIA333wTX3zxBQDzkPnNmzdj2LBhDq8gERERUXWxu49Rbcc+RkRERLVPje1jRERERFRXVehSmq+vL06fPo2GDRvCx8cHkiSVuey1a9ccVjkiIiKi6lShYPTWW2/Bw8NDeV1eMCIiIiKqrdjHiIiIiGq8GtvH6MiRIzh27JgyvX37dgwfPhwvvfQSCgoKHFo5IiIioupkdzB68skncfr0aQDAuXPnMHr0aLi6umLLli14/vnnHV5BIiIioupidzA6ffo0OnfuDADYsmUL+vXrh40bN2Lt2rXYunWro+tHREREVG3sDkZCCJhMJgDmnwF54IEHAJh/KiQtLc2xtSMiIiKqRnYHo27dumHx4sX4/PPPsXv3bgwePBgAcP78efj7+zu8gkRERETVxe5gtGLFChw5cgTTp0/HvHnz0KJFCwDAl19+qfx2GhEREVFt5LDh+nl5eVCr1dBqtY7YXJXhcH0iIqLap8YO109KSsLff/+tTB88eBCzZs3CunXranwoIiIiIiqP3cFo7NixiIuLAwAkJydj4MCBOHjwIObNm4dFixY5vIJERERE1cXuYHT8+HH06NEDAPDFF1+gffv22LdvHzZs2IC1a9c6un5ERERE1cbuYFRYWAi9Xg/APFx/6NChAIA2bdrg8uXLjq0dERERUTWyOxjdcccdWL16Nfbs2YOYmBjcd999AID//e9/aNCggcMrSERERFRd7A5GS5cuxQcffID+/ftjzJgx6NSpEwDgm2++US6xEREREdVGlRqubzQakZGRAR8fH6UsMTERrq6u8PPzc2gFHY3D9YmIiGqf6vr+1lRmJbVabROKACA0NNQR9SEiIiJymgoFozvvvBOxsbHw8fFBly5dIElSmcseOXLEYZUjIiIiqk4VCkbDhg1TRqINHz68KutDRERE5DQO+0mQ2oJ9jIiIiGqfGt3HyCIrKwsmk8mmjGGDiIiIaiu7h+ufP38egwcPhpubG7y8vODj4wMfHx94e3uX6JBNREREVJvY3WI0fvx4CCHwySefwN/fv9yO2ERERES1id3BKCEhAYcPH0br1q2roj5ERERETmP3pbTu3bsjKSmpKupCRERE5FR2txh99NFHmDp1Ki5duoT27dtDq9XazO/YsaPDKkdERERUnewORleuXMHZs2cxadIkpUySJAghIEkSjEajQytIREREVF3sDkaTJ09Gly5d8J///Iedr4mIiKhOsTsYXbhwAd988w1atGhRFfUhIiIichq7O1/fc889SEhIqIq6EBERETmV3S1GQ4YMwezZs3Hs2DF06NChROfroUOHOqxyRERERNXJ7t9KU6nKbmSqDZ2v+VtpREREtU+N/a204r+NRkRERFRX2N3HqDQ3btxwxGaIiIiInMruYLR06VJs3rxZmR45ciR8fX3RpEkTdsomIiKiWs3uYLR69WoEBQUBAGJiYvDTTz9h586duP/++zFnzhyHV5CIiIioutjdxyg5OVkJRt9++y1GjRqFQYMGITQ0FD179nR4BYmIiIiqi90tRj4+PsqPyO7cuRMREREAACFEjR+RRkRERFQeu1uMHn74YYwdOxYtW7bE1atXcf/99wMAjh49yrthExERUa1mdzB66623EBoaiqSkJCxbtgzu7u4AgMuXL+Ppp592eAWJiIiIqovdN3is7XiDRyIiotqnxt7gEQD++usvxMXFITU1tcQNH+fPn++QihERERFVN7uD0Zo1a/DUU0+hYcOGCAgIgCRJyjxJkhiMiIiIqNayOxgtXrwYS5YswQsvvFAV9SEiIiJyGruH61+/fh0jR46siroQEREROZXdwWjkyJH48ccfq6IuRERERE5l96W0Fi1a4JVXXsGBAwfQoUMHaLVam/kzZsxwWOWIiIiIqpPdw/XDwsLK3pgk4dy5c7ddqarE4fpERES1T40drn/+/PmqqAcRERGR09ndx4iIiIiorqrUDR7//vtvfPPNN7h48SIKCgps5i1fvtwhFSMiIiKqbnYHo9jYWAwdOhTNmjXDyZMn0b59eyQmJkIIgTvvvLMq6khERERULey+lDZ37lw899xzOHbsGAwGA7Zu3YqkpCT069eP9zciIiKiWs3uYPTnn39iwoQJAACNRoPc3Fy4u7tj0aJFWLp0qcMrSERERFRd7A5Gbm5uSr+iwMBAnD17VpmXlpbmuJoRERERVTO7+xj16tULe/fuRdu2bfHAAw/g2WefxbFjx/DVV1+hV69eVVFHIiIiomphdzBavnw5srKyAAALFy5EVlYWNm/ejJYtW3JEGhEREdVqdl1KMxqN+PvvvxEcHAzAfFlt9erV+L//+z9s3boVISEhlarEypUrERoaCoPBgJ49e+LgwYMVWm/Tpk2QJAnDhw+v1H6JiIiIrNkVjNRqNQYNGoTr1687rAKbN29GVFQUFixYgCNHjqBTp06IjIxEampqueslJibiueeew9133+2wuhAREVH9Znfn6/bt2zv099CWL1+OJ554ApMmTUK7du2wevVquLq64pNPPilzHaPRiHHjxmHhwoVo1qyZw+pCRERE9ZvdwWjx4sV47rnn8O233+Ly5cvIyMiwedijoKAAhw8fRkRExM0KqVSIiIjA/v37y1xv0aJF8PPzw+OPP37LfeTn599WHYmIiKj+qHDn60WLFuHZZ5/FAw88AAAYOnQoJElS5gshIEkSjEZjhXeelpYGo9EIf39/m3J/f3+cPHmy1HX27t2Ljz/+GPHx8RXaR3R0NBYuXFjhOhEREVH9VeFgtHDhQkydOhVxcXFVWZ9yZWZm4rHHHsOaNWvQsGHDCq0zd+5cREVFKdMZGRkICgqqqioSERFRLVbhYCSEAAD069fPYTtv2LAh1Go1UlJSbMpTUlIQEBBQYvmzZ88iMTERQ4YMUcpMJhMA8124T506hebNm9uso9frodfrHVZnIiIiqrvs6mNkfenMEXQ6Hbp27YrY2FilzGQyITY2FuHh4SWWb9OmDY4dO4b4+HjlMXToUAwYMADx8fFsCSIiIqLbYtcNHlu1anXLcHTt2jW7KhAVFYWJEyeiW7du6NGjB1asWIHs7GxMmjQJADBhwgQ0adIE0dHRMBgMaN++vc363t7eAFCinIiIiMhedgWjhQsXwsvLy6EVGD16NK5cuYL58+cjOTkZnTt3xs6dO5UO2RcvXoRKZffgOSIiIiK7ScLSeegWVCoVkpOT4efnV9V1qlIZGRnw8vJCeno6PD09nV0dIiIiqoDq+v6ucFOMo/sXEREREdU0FQ5GFWxYIiIiIqq1KtzHyDIsnoiIiKiuYq9mIiIiIhmDEREREZGMwYiIiIhIxmBEREREJGMwIiIiIpIxGBERERHJGIyIiIiIZAxGRERERDIGIyIiIiIZgxERERGRjMGIiIiISMZgRERERCRjMCIiIiKSMRgRERERyRiMiIiIiGQMRkREREQyBiMiIiIiGYMRERERkYzBiIiIiEjGYEREREQkYzAiIiIikjEYEREREckYjIiIiIhkDEZEREREMgYjIiIiIhmDEREREZGMwYiIiIhIxmBEREREJGMwIiIiIpIxGBERERHJGIyIiIiIZAxGRERERDIGIyIiIiIZgxERERGRjMGIiIiISMZgRERERCRjMCIiIiKSMRgRERERyRiMiIiIiGQMRkREREQyBiMiIiIiGYMRERERkYzBiIiIiEjGYEREREQkYzAiIiIikjEYEREREckYjIiIiIhkDEZEREREMgYjIiIiIhmDEREREZGMwYiIiIhIxmBEREREJGMwIiIiIpIxGBERERHJGIyIiIiIZAxGRERERDIGIyIiIiIZgxERERGRjMGIiIiISMZgRERERCSrEcFo5cqVCA0NhcFgQM+ePXHw4MEyl12zZg3uvvtu+Pj4wMfHBxEREeUuT0RERFRRTg9GmzdvRlRUFBYsWIAjR46gU6dOiIyMRGpqaqnL79q1C2PGjEFcXBz279+PoKAgDBo0CJcuXarmmhMREVFdIwkhhDMr0LNnT3Tv3h3vvfceAMBkMiEoKAjPPPMMXnzxxVuubzQa4ePjg/feew8TJky45fIZGRnw8vJCeno6PD09b7v+REREVPWq6/vbqS1GBQUFOHz4MCIiIpQylUqFiIgI7N+/v0LbyMnJQWFhIXx9fUudn5+fj4yMDJsHERERUWmcGozS0tJgNBrh7+9vU+7v74/k5OQKbeOFF15A48aNbcKVtejoaHh5eSmPoKCg2643ERER1U1O72N0O9544w1s2rQJ27Ztg8FgKHWZuXPnIj09XXkkJSVVcy2JiIiottA4c+cNGzaEWq1GSkqKTXlKSgoCAgLKXfff//433njjDfz000/o2LFjmcvp9Xro9XqH1JeIiIjqNqe2GOl0OnTt2hWxsbFKmclkQmxsLMLDw8tcb9myZXjttdewc+dOdOvWrTqqSkRERPWAU1uMACAqKgoTJ05Et27d0KNHD6xYsQLZ2dmYNGkSAGDChAlo0qQJoqOjAQBLly7F/PnzsXHjRoSGhip9kdzd3eHu7u604yAiIqLaz+nBaPTo0bhy5Qrmz5+P5ORkdO7cGTt37lQ6ZF+8eBEq1c2GrVWrVqGgoAAjRoyw2c6CBQvw6quvVmfViYiIqI5x+n2MqhvvY0RERFT71Iv7GBERERHVJAxGRERERDIGIyIiIiIZgxERERGRjMGIiIiISMZgRERERCRjMCIiIiKSMRgRERERyRiMiIiIiGQMRkREREQyBiMiIiIiGYMRERERkYzBiIiIiEimcXYFaiqj0YjCwkJnV8PptFot1Gq1s6tBRERULRiMihFCIDk5GTdu3HB2VWoMb29vBAQEQJIkZ1eFiIioSjEYFWMJRX5+fnB1da3XYUAIgZycHKSmpgIAAgMDnVwjIiKiqsVgZMVoNCqhqEGDBs6uTo3g4uICAEhNTYWfnx8vqxERUZ3GztdWLH2KXF1dnVyTmsXyfrDPFRER1XUMRqWoz5fPSsP3g4iI6gsGIyIiIiIZg1EdER0dje7du8PDwwN+fn4YPnw4Tp06ZbNMaGgoJEmCJElwcXFBaGgoRo0ahZ9//tlJtSYiIqpZGIzqiN27d2PatGk4cOAAYmJiUFhYiEGDBiE7O9tmuUWLFuHy5cs4deoU1q1bB29vb0RERGDJkiVOqjkREVHNwVFpdcTOnTttpteuXQs/Pz8cPnwYffv2Vco9PDwQEBAAAAgODkbfvn0RGBiI+fPnY8SIEWjdunW11puIiKgmYYvRLQghkFNQ5JSHEKLS9U5PTwcA+Pr63nLZmTNnQgiB7du3V3p/REREdQFbjG4ht9CIdvN/cMq+TyyKhKvO/lNkMpkwa9Ys9O7dG+3bt7/l8r6+vvDz80NiYmIlaklERFR3MBjVQdOmTcPx48exd+/eCq8jhOCwfCIiqvcYjG7BRavGiUWRTtu3vaZPn45vv/0Wv/zyC5o2bVqhda5evYorV64gLCzM7v0RERHVJQxGtyBJUqUuZ1U3IQSeeeYZbNu2Dbt27bIr5Lz99ttQqVQYPnx41VWQiIioFqj53/hUIdOmTcPGjRuxfft2eHh4IDk5GQDg5eWl/N4ZAGRmZiI5ORmFhYU4f/481q9fj48++gjR0dFo0aKFs6pPRERUI0jidoY+1UIZGRnw8vJCeno6PD09bebl5eXh/PnzCAsLg8FgcFINK6es/kGffvop/vGPfwAw3+DxwoULAACdToeAgAD06tULU6dOxYABA8rcdm1+X4iIqG4o7/vbkdhiVEdUJN9y1BkREVH5eB8jIiIiIhmDEREREZGMwYiIiIhIxmBEREREJGMwIiIiIpIxGBERERHJGIyIiIiIZAxGRERERDIGIyIiIiIZgxERERGRjMGojli1ahU6duwIT09PeHp6Ijw8HN9//70yPzQ0FJIkQZIkuLi4IDQ0FKNGjcLPP//sxFoTERHVLAxGdUTTpk3xxhtv4PDhwzh06BDuueceDBs2DH/88YeyzKJFi3D58mWcOnUK69atg7e3NyIiIrBkyRIn1pyIiKjm4I/I1hFDhgyxmV6yZAlWrVqFAwcO4I477gAAeHh4ICAgAAAQHByMvn37IjAwEPPnz8eIESPQunXraq83ERFRTcIWo1sRAijIds5DiEpV2Wg0YtOmTcjOzkZ4eHi5y86cORNCCGzfvr1S+yIiIqpL2GJ0K4U5wOuNnbPvl/4H6NwqvPixY8cQHh6OvLw8uLu7Y9u2bWjXrl256/j6+sLPzw+JiYm3WVkiIqLajy1GdUjr1q0RHx+P3377DU899RQmTpyIEydO3HI9IQQkSaqGGhIREdVsbDG6Fa2rueXGWfu2g06nQ4sWLQAAXbt2xe+//463334bH3zwQZnrXL16FVeuXEFYWNhtVZWIiKguYDC6FUmy63JWTWIymZCfn1/uMm+//TZUKhWGDx9ePZUiIiKqwRiM6oi5c+fi/vvvR3BwMDIzM7Fx40bs2rULP/zwg7JMZmYmkpOTUVhYiPPnz2P9+vX46KOPEB0drbQ0ERER1WcMRnVEamoqJkyYgMuXL8PLywsdO3bEDz/8gIEDByrLzJ8/H/Pnz4dOp0NAQAB69eqF2NhYDBgwwIk1JyIiqjkYjOqIjz/+uNz5HHVGRER0axyVRkRERCRjMCIiIiKSMRgRERERyRiMiIiIiGQMRkREREQyBqNSiEr+eGtdxfeDiIjqCwYjK1qtFgCQk5Pj5JrULJb3w/L+EBER1VW8j5EVtVoNb29vpKamAgBcXV3r9Y+rCiGQk5OD1NRUeHt7Q61WO7tKREREVYrBqJiAgAAAUMIRAd7e3sr7QkREVJcxGBUjSRICAwPh5+eHwsJCZ1fH6bRaLVuKiIio3qgRwWjlypX417/+heTkZHTq1AnvvvsuevToUebyW7ZswSuvvILExES0bNkSS5cuxQMPPODQOqnVagYCIiKiesbpna83b96MqKgoLFiwAEeOHEGnTp0QGRlZ5qWsffv2YcyYMXj88cdx9OhRDB8+HMOHD8fx48erueZERERU10jCyWOxe/bsie7du+O9994DAJhMJgQFBeGZZ57Biy++WGL50aNHIzs7G99++61S1qtXL3Tu3BmrV6++5f4yMjLg5eWF9PR0eHp6Ou5AiIiIqMpU1/e3U1uMCgoKcPjwYURERChlKpUKERER2L9/f6nr7N+/32Z5AIiMjCxzeSIiIqKKcmofo7S0NBiNRvj7+9uU+/v74+TJk6Wuk5ycXOryycnJpS6fn5+P/Px8ZTo9PR2AOXkSERFR7WD53q7qC101ovN1VYqOjsbChQtLlAcFBTmhNkRERHQ7rl69Ci8vryrbvlODUcOGDaFWq5GSkmJTnpKSUuZ9cwICAuxafu7cuYiKilKmb9y4gZCQEFy8eLFK31i6tYyMDAQFBSEpKYn9vWoAno+ag+ei5uC5qDnS09MRHBwMX1/fKt2PU4ORTqdD165dERsbi+HDhwMwd76OjY3F9OnTS10nPDwcsbGxmDVrllIWExOD8PDwUpfX6/XQ6/Ulyr28vPg/eQ3h6enJc1GD8HzUHDwXNQfPRc2hUlVt92inX0qLiorCxIkT0a1bN/To0QMrVqxAdnY2Jk2aBACYMGECmjRpgujoaADAzJkz0a9fP7z55psYPHgwNm3ahEOHDuHDDz905mEQERFRHeD0YDR69GhcuXIF8+fPR3JyMjp37oydO3cqHawvXrxokw7vuusubNy4ES+//DJeeukltGzZEl9//TXat2/vrEMgIiKiOsLpwQgApk+fXuals127dpUoGzlyJEaOHFmpfen1eixYsKDUy2tUvXguahaej5qD56Lm4LmoOarrXDj9Bo9ERERENYXTfxKEiIiIqKZgMCIiIiKSMRgRERERyRiMiIiIiGS1Ohj98ssvGDJkCBo3bgxJkvD111+Xu/yuXbsgSVKJR/HfWVu5ciVCQ0NhMBjQs2dPHDx4sAqPou6oivMRHR2N7t27w8PDA35+fhg+fDhOnTpVxUdS+1XVZ8PijTfegCRJNjdapdJV1bm4dOkSxo8fjwYNGsDFxQUdOnTAoUOHqvBIar+qOBdGoxGvvPIKwsLC4OLigubNm+O1116r8t/zqu3sPReA+bdP582bh5CQEOj1eoSGhuKTTz6xWWbLli1o06YNDAYDOnTogO+++87uutXqYJSdnY1OnTph5cqVdq136tQpXL58WXn4+fkp8zZv3oyoqCgsWLAAR44cQadOnRAZGYnU1FRHV7/OqYrzsXv3bkybNg0HDhxATEwMCgsLMWjQIGRnZzu6+nVKVZwLi99//x0ffPABOnbs6Kjq1mlVcS6uX7+O3r17Q6vV4vvvv8eJEyfw5ptvwsfHx9HVr1Oq4lwsXboUq1atwnvvvYc///wTS5cuxbJly/Duu+86uvp1SmXOxahRoxAbG4uPP/4Yp06dwn/+8x+0bt1amb9v3z6MGTMGjz/+OI4ePYrhw4dj+PDhOH78uH2VE3UEALFt27Zyl4mLixMAxPXr18tcpkePHmLatGnKtNFoFI0bNxbR0dEOqmn94KjzUVxqaqoAIHbv3n17FaxHHHkuMjMzRcuWLUVMTIzo16+fmDlzpsPqWR846ly88MILok+fPo6tXD3jqHMxePBgMXnyZJuyhx9+WIwbN84BtawfKnIuvv/+e+Hl5SWuXr1a5jKjRo0SgwcPtinr2bOnePLJJ+2qT61uMaqszp07IzAwEAMHDsSvv/6qlBcUFODw4cOIiIhQylQqFSIiIrB//35nVLVeKOt8lCY9PR0AqvxHBOurW52LadOmYfDgwTafEaoa5Z2Lb775Bt26dcPIkSPh5+eHLl26YM2aNU6qad1X3rm46667EBsbi9OnTwMAEhISsHfvXtx///3OqGqdZfl/ftmyZWjSpAlatWqF5557Drm5ucoy+/fvL/FvU2RkpN3f3zXiztfVJTAwEKtXr0a3bt2Qn5+Pjz76CP3798dvv/2GO++8E2lpaTAajcrPkVj4+/vj5MmTTqp13XWr81GcyWTCrFmz0Lt3b/4EjINV5Fxs2rQJR44cwe+//+7k2tZtFTkX586dw6pVqxAVFYWXXnoJv//+O2bMmAGdToeJEyc6+QjqjoqcixdffBEZGRlo06YN1Go1jEYjlixZgnHjxjm59nXLuXPnsHfvXhgMBmzbtg1paWl4+umncfXqVXz66acAgOTk5FK/v8vqK1kmu9qXajBUoCmuNH379hXjx48XQghx6dIlAUDs27fPZpk5c+aIHj16OKKa9YYjzkdxU6dOFSEhISIpKek2a1e/OOJcXLx4Ufj5+YmEhARlPi+l2c9RnwutVivCw8NtlnnmmWdEr169breK9YajzsV//vMf0bRpU/Gf//xH/N///Z9Yt26d8PX1FWvXrnVgbeu2ipyLgQMHCoPBIG7cuKGUbd26VUiSJHJycoQQ5s/Fxo0bbdZbuXKl8PPzs6s+9fJSmrUePXrgzJkzAICGDRtCrVYjJSXFZpmUlBQEBAQ4o3r1jvX5sDZ9+nR8++23iIuLQ9OmTZ1Qs/rH+lwcPnwYqampuPPOO6HRaKDRaLB7926888470Gg0MBqNTq5t3Vb8cxEYGIh27drZLNO2bVtcvHixuqtW7xQ/F3PmzMGLL76IRx99FB06dMBjjz2G2bNnIzo62om1rHsCAwPRpEkTeHl5KWVt27aFEAJ///03ACAgIMAh39/1PhjFx8cjMDAQAKDT6dC1a1fExsYq800mE2JjYxEeHu6sKtYr1ucDAIQQmD59OrZt24aff/4ZYWFhTqxd/WJ9Lu69914cO3YM8fHxyqNbt24YN24c4uPjoVarnVzbuq3456J3794lbltx+vRphISEVHfV6p3i5yInJwcqle1XqVqthslkqu6q1Wm9e/fG//73P2RlZSllp0+fhkqlUv5YDg8Pt/n+BoCYmBi7v79rdR+jrKwsm+R+/vx5xMfHw9fXF8HBwZg7dy4uXbqEdevWAQBWrFiBsLAw3HHHHcjLy8NHH32En3/+GT/++KOyjaioKEycOBHdunVDjx49sGLFCmRnZ2PSpEnVfny1TVWcj2nTpmHjxo3Yvn07PDw8lGvFXl5ecHFxqd4DrEUcfS48PDxK9Otyc3NDgwYN2N/rFqriczF79mzcddddeP311zFq1CgcPHgQH374IT788MNqP77apCrOxZAhQ7BkyRIEBwfjjjvuwNGjR7F8+XJMnjy52o+vNrH3XIwdOxavvfYaJk2ahIULFyItLQ1z5szB5MmTle+CmTNnol+/fnjzzTcxePBgbNq0CYcOHbL/c2HXhbcaxjKUsvhj4sSJQgghJk6cKPr166csv3TpUtG8eXNhMBiEr6+v6N+/v/j5559LbPfdd98VwcHBQqfTiR49eogDBw5U0xHVblVxPkrbHgDx6aefVt+B1UJV9dmwxj5GFVNV5+K///2vaN++vdDr9aJNmzbiww8/rKYjqr2q4lxkZGSImTNniuDgYGEwGESzZs3EvHnzRH5+fjUeWe1j77kQQog///xTRERECBcXF9G0aVMRFRWl9C+y+OKLL0SrVq2ETqcTd9xxh9ixY4fddZOE4O05iYiIiAD2MSIiIiJSMBgRERERyRiMiIiIiGQMRkREREQyBiMiIiIiGYMRERERkYzBiIiIiEjGYEREREQkYzAiIiIikjEYEZFT9e/fH7NmzXJ2NRSVrc/Vq1fh5+eHxMREh9epuEcffRRvvvlmle+HqD5iMCKqB1avXg0PDw8UFRUpZVlZWdBqtejfv7/Nsrt27YIkSTh79mw117J6OTqQLVmyBMOGDUNoaKjDtlmWl19+GUuWLEF6enqV74uovmEwIqoHBgwYgKysLBw6dEgp27NnDwICAvDbb78hLy9PKY+Li0NwcDCaN2/ujKrWSjk5Ofj444/x+OOPV8v+2rdvj+bNm2P9+vXVsj+i+oTBiKgeaN26NQIDA7Fr1y6lbNeuXRg2bBjCwsJw4MABm/IBAwYAAHbu3Ik+ffrA29sbDRo0wIMPPmjTkvThhx+icePGMJlMNvsbNmwYJk+eDAAwmUyIjo5GWFgYXFxc0KlTJ3z55Zdl1rUiy/fv3x8zZszA888/D19fXwQEBODVV1+1WSYzMxPjxo2Dm5sbAgMD8dZbbymtRP/4xz+we/duvP3225AkCZIk2VwCM5lM5W67uO+++w56vR69evWyKd+7dy+0Wq1N8ExMTIQkSbhw4YLyeuvWrejbty9cXFzQvXt3XLx4EXv27EGvXr3g6uqKe++9Fzdu3LDZ9pAhQ7Bp06Zy60VE9mMwIqonBgwYgLi4OGU6Li4O/fv3R79+/ZTy3Nxc/Pbbb0owys7ORlRUFA4dOoTY2FioVCo89NBDShAaOXIkrl69arPda9euYefOnRg3bhwAIDo6GuvWrcPq1avxxx9/YPbs2Rg/fjx2795daj0ruvxnn30GNzc3/Pbbb1i2bBkWLVqEmJgYZX5UVBR+/fVXfPPNN4iJicGePXtw5MgRAMDbb7+N8PBwPPHEE7h8+TIuX76MoKCgCm+7uD179qBr164lyuPj49G2bVsYDAal7OjRo/Dx8UFISAgSEhIAAKtWrcLrr7+Offv2ISUlBePHj8cbb7yB9957D3FxcUhISMCnn35qs+0ePXrg4MGDyM/PL7NeRFQJgojqhTVr1gg3NzdRWFgoMjIyhEajEampqWLjxo2ib9++QgghYmNjBQBx4cKFUrdx5coVAUAcO3ZMKRs2bJiYPHmyMv3BBx+Ixo0bC6PRKPLy8oSrq6vYt2+fzXYef/xxMWbMGCGEEP369RMzZ84UQogKLW9Zp0+fPjbLdO/eXbzwwgtCCCEyMjKEVqsVW7ZsUebfuHFDuLq6Kvuy3q+1W227NMXfA4spU6aICRMm2JTNnz9f9O/fXwghxKuvvip8fX1FWlqaMn/8+PEiNDRUZGdnK2X33XefeP755222k5CQIACIxMTEMutFRPZjixFRPdG/f39kZ2fj999/x549e9CqVSs0atQI/fr1U/oZ7dq1C82aNUNwcDAA4K+//sKYMWPQrFkzeHp6Kh2LL168qGx33Lhx2Lp1q9JysWHDBjz66KNQqVQ4c+YMcnJyMHDgQLi7uyuPdevWldq5257lO3bsaDMdGBiI1NRUAMC5c+dQWFiIHj16KPO9vLzQunXrCr1X5W27NLm5uTatQhbx8fHo3LmzTdnRo0eVsoSEBDz00ENo0KCBMv/ixYsYPXo0XF1dbcrCwsJstuPi4gLA3L+JiBxH4+wKEFH1aNGiBZo2bYq4uDhcv34d/fr1AwA0btwYQUFB2LdvH+Li4nDPPfco6wwZMgQhISFYs2aN0peoffv2KCgosFlGCIEdO3age/fu2LNnD9566y0A5pFvALBjxw40adLEpj56vb5EHe1ZXqvV2kxLklSir1Nl2bvthg0b4vr16zZlRqMRx48fR5cuXWzKjxw5gkceeQSAOTjNnTvXZn5CQgJmz56tTOfl5eHUqVPo1KmTzXLXrl0DADRq1KiCR0VEFcFgRFSPDBgwALt27cL169cxZ84cpbxv3774/vvvcfDgQTz11FMAzPflOXXqFNasWYO7774bgLkzcXEGgwEPP/wwNmzYgDNnzqB169a48847AQDt2rWDXq/HxYsXlSBWHnuXL0uzZs2g1Wrx+++/K61f6enpOH36NPr27QsA0Ol0MBqNld6HtS5dupQYIXbq1Cnk5eWhcePGStn+/ftx6dIldO7cGRkZGUhMTLQJTufPn0d6erpN2bFjxyCEQIcOHWy2f/z4cTRt2hQNGzZ0yDEQkRmDEVE9MmDAAEybNg2FhYU2waNfv36YPn06CgoKlI7XPj4+aNCgAT788EMEBgbi4sWLePHFF0vd7rhx4/Dggw/ijz/+wPjx45VyDw8PPPfcc5g9ezZMJhP69OmD9PR0/Prrr/D09MTEiRNttmPv8mXx8PDAxIkTMWfOHPj6+sLPzw8LFiyASqWCJEkAgNDQUPz2229ITEyEu7s7fH19oVJVrndBZGQk5s6di+vXr8PHxweAuTUIAN59913MmDEDZ86cwYwZMwAABQUFSEhIgFqtRvv27ZXtxMfHw9fXFyEhITZlzZs3h7u7u80+9+zZg0GDBlWqvkRUNvYxIqpHBgwYgNzcXLRo0QL+/v5Keb9+/ZCZmakM6wcAlUqFTZs24fDhw2jfvj1mz56Nf/3rX6Vu95577oGvry9OnTqFsWPH2sx77bXX8MorryA6Ohpt27bFfffdhx07dpToM1PZ5cuyfPlyhIeH48EHH0RERAR69+5tM0Lsueeeg1qtRrt27dCoUSObflP26tChA+6880588cUXSll8fDwiIyNx7tw5dOjQAfPmzcPChQvh6emJd955BwkJCWjdurVN36SEhIQSl94SEhJKXEbLy8vD119/jSeeeKLSdSai0klCCOHsShARVbXs7Gw0adIEb775ZpXciHHHjh2YM2cOjh8/DpVKhcjISHTv3h2LFy92+L5WrVqFbdu24ccff3T4tonqO15KI6I66ejRozh58iR69OiB9PR0LFq0CID55pNVYfDgwfjrr79w6dIlBAUFISEhQbnJpaNptVq8++67VbJtovqOLUZEVCcdPXoUU6ZMwalTp6DT6dC1a1csX768RCfmqpCcnIzAwED88ccfaNeuXZXvj4gch8GIiIiISMbO10REREQyBiMiIiIiGYMRERERkYzBiIiIiEjGYEREREQkYzAiIiIikjEYEREREckYjIiIiIhkDEZEREREMgYjIiIiIhmDEREREZHs/wHL+RUNYZrv8AAAAABJRU5ErkJggg==",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -3364,7 +1321,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.8"
+   "version": "3.9.20"
   },
   "title": "How to approximate 3D simulations with effective permittivity in Tidy3D FDTD"
  },