diff --git a/qiskit/advanced/aqua/chemistry/programmatic_approach.ipynb b/qiskit/advanced/aqua/chemistry/programmatic_approach.ipynb
index 865e75cd0..ca9fb708e 100644
--- a/qiskit/advanced/aqua/chemistry/programmatic_approach.ipynb
+++ b/qiskit/advanced/aqua/chemistry/programmatic_approach.ipynb
@@ -49,6 +49,7 @@
     "\n",
     "# lib from Qiskit Aqua\n",
     "from qiskit.aqua import Operator, QuantumInstance\n",
+    "from qiskit.aqua.operators import Z2Symmetries\n",
     "from qiskit.aqua.algorithms import VQE, ExactEigensolver\n",
     "from qiskit.aqua.components.optimizers import COBYLA\n",
     "\n",
@@ -99,7 +100,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "HF energy: -8.854072040283643\n",
+      "HF energy: -8.854072040283647\n",
       "# of electrons: 4\n",
       "# of spin orbitals: 12\n"
      ]
@@ -131,106 +132,106 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "IIII\t(-0.20765933501970843+0j)\n",
-      "IIIZ\t(-0.0937633748462618+0j)\n",
-      "IIZX\t(-0.003177581454819807+0j)\n",
-      "IIIX\t(0.003177581454819807+0j)\n",
-      "IIXX\t(-0.0012513965999782634+0j)\n",
-      "IIYY\t(0.0012513965999782634+0j)\n",
-      "IIZZ\t(-0.21162509515110325+0j)\n",
-      "IIXZ\t(0.019200533863114204+0j)\n",
-      "IIXI\t(0.019200533863114204+0j)\n",
-      "IIZI\t(0.35810269945770123+0j)\n",
-      "IZII\t(0.09376337484626177+0j)\n",
-      "ZXII\t(0.0031775814548198056+0j)\n",
-      "IXII\t(0.0031775814548198056+0j)\n",
-      "XXII\t(-0.0012513965999782738+0j)\n",
-      "YYII\t(0.0012513965999782738+0j)\n",
-      "ZZII\t(-0.21162509515110328+0j)\n",
-      "XZII\t(-0.01920053386311419+0j)\n",
-      "XIII\t(0.01920053386311419+0j)\n",
-      "ZIII\t(-0.3581026994577012+0j)\n",
-      "IZIZ\t(-0.12182774215822034+0j)\n",
-      "IZZX\t(0.012144897228053009+0j)\n",
-      "IZIX\t(-0.012144897228053009+0j)\n",
-      "IZXX\t(0.0316987459873487+0j)\n",
-      "IZYY\t(-0.0316987459873487+0j)\n",
-      "IXIZ\t(0.012144897228053009+0j)\n",
-      "ZXIZ\t(0.012144897228053009+0j)\n",
-      "IXZX\t(-0.003265995499652904+0j)\n",
-      "ZXZX\t(-0.003265995499652904+0j)\n",
-      "IXIX\t(0.003265995499652904+0j)\n",
-      "ZXIX\t(0.003265995499652904+0j)\n",
-      "IXXX\t(-0.008650156860603548+0j)\n",
-      "ZXXX\t(-0.008650156860603548+0j)\n",
-      "IXYY\t(0.008650156860603548+0j)\n",
-      "ZXYY\t(0.008650156860603548+0j)\n",
-      "YYIZ\t(0.0316987459873487+0j)\n",
-      "XXIZ\t(-0.0316987459873487+0j)\n",
-      "YYZX\t(-0.00865015686060355+0j)\n",
-      "XXZX\t(0.00865015686060355+0j)\n",
-      "YYIX\t(0.00865015686060355+0j)\n",
-      "XXIX\t(-0.00865015686060355+0j)\n",
-      "YYXX\t(-0.030981613344632574+0j)\n",
-      "XXXX\t(0.030981613344632574+0j)\n",
-      "YYYY\t(0.030981613344632574+0j)\n",
-      "XXYY\t(-0.030981613344632574+0j)\n",
-      "ZZIZ\t(0.05590251078515368+0j)\n",
-      "ZZZX\t(0.0018710427514123198+0j)\n",
-      "ZZIX\t(-0.0018710427514123198+0j)\n",
-      "ZZXX\t(0.003104004116078267+0j)\n",
-      "ZZYY\t(-0.003104004116078267+0j)\n",
-      "XIIZ\t(0.012841723180750613+0j)\n",
-      "XZIZ\t(-0.012841723180750613+0j)\n",
-      "XIZX\t(-0.002352152173238769+0j)\n",
-      "XZZX\t(0.002352152173238769+0j)\n",
-      "XIIX\t(0.002352152173238769+0j)\n",
-      "XZIX\t(-0.002352152173238769+0j)\n",
-      "XIXX\t(-0.007975908750559497+0j)\n",
-      "XZXX\t(0.007975908750559497+0j)\n",
-      "XIYY\t(0.007975908750559497+0j)\n",
-      "XZYY\t(-0.007975908750559497+0j)\n",
-      "ZIIZ\t(0.11346110712685867+0j)\n",
-      "ZIZX\t(-0.010838363828730848+0j)\n",
-      "ZIIX\t(0.010838363828730848+0j)\n",
-      "ZIXX\t(-0.03355135311124219+0j)\n",
-      "ZIYY\t(0.03355135311124219+0j)\n",
-      "IZZZ\t(-0.05590251078515368+0j)\n",
-      "IZXZ\t(-0.012841723180750615+0j)\n",
-      "IZXI\t(-0.012841723180750615+0j)\n",
-      "IXZZ\t(-0.0018710427514123196+0j)\n",
-      "ZXZZ\t(-0.0018710427514123196+0j)\n",
-      "IXXZ\t(0.0023521521732387685+0j)\n",
-      "ZXXZ\t(0.0023521521732387685+0j)\n",
-      "IXXI\t(0.0023521521732387685+0j)\n",
-      "ZXXI\t(0.0023521521732387685+0j)\n",
-      "YYZZ\t(-0.0031040041160782664+0j)\n",
-      "XXZZ\t(0.0031040041160782664+0j)\n",
-      "YYXZ\t(0.007975908750559497+0j)\n",
-      "XXXZ\t(-0.007975908750559497+0j)\n",
-      "YYXI\t(0.007975908750559497+0j)\n",
-      "XXXI\t(-0.007975908750559497+0j)\n",
-      "ZZZZ\t(0.08447056807294816+0j)\n",
-      "ZZXZ\t(-0.008994911953942152+0j)\n",
-      "ZZXI\t(-0.008994911953942152+0j)\n",
-      "XIZZ\t(-0.008994911953942152+0j)\n",
-      "XZZZ\t(0.008994911953942152+0j)\n",
-      "XIXZ\t(0.006612047066148212+0j)\n",
-      "XZXZ\t(-0.006612047066148212+0j)\n",
-      "XIXI\t(0.006612047066148212+0j)\n",
-      "XZXI\t(-0.006612047066148212+0j)\n",
-      "ZIZZ\t(0.06035891281077614+0j)\n",
-      "ZIXZ\t(0.011019231644706083+0j)\n",
-      "ZIXI\t(0.011019231644706083+0j)\n",
-      "IZZI\t(0.11346110712685867+0j)\n",
-      "IXZI\t(-0.01083836382873085+0j)\n",
-      "ZXZI\t(-0.01083836382873085+0j)\n",
-      "YYZI\t(-0.03355135311124219+0j)\n",
-      "XXZI\t(0.03355135311124219+0j)\n",
-      "ZZZI\t(-0.06035891281077614+0j)\n",
-      "XIZI\t(-0.011019231644706081+0j)\n",
-      "XZZI\t(0.011019231644706081+0j)\n",
-      "ZIZI\t(-0.11344680300367628+0j)\n",
+      "IIII\t(-0.2076593350197074+0j)\n",
+      "IIIZ\t(-0.09376337484626278+0j)\n",
+      "IIZX\t(-0.0031775814548399956+0j)\n",
+      "IIIX\t(0.0031775814548399956+0j)\n",
+      "IIXX\t(-0.001251396599969751+0j)\n",
+      "IIYY\t(0.001251396599969751+0j)\n",
+      "IIZZ\t(-0.21162509515110128+0j)\n",
+      "IIXZ\t(0.019200533863109957+0j)\n",
+      "IIXI\t(0.019200533863109957+0j)\n",
+      "IIZI\t(0.3581026994577025+0j)\n",
+      "IZII\t(0.09376337484626282+0j)\n",
+      "ZXII\t(0.0031775814548399973+0j)\n",
+      "IXII\t(0.0031775814548399973+0j)\n",
+      "XXII\t(-0.0012513965999697415+0j)\n",
+      "YYII\t(0.0012513965999697415+0j)\n",
+      "ZZII\t(-0.21162509515110128+0j)\n",
+      "XZII\t(-0.019200533863109957+0j)\n",
+      "XIII\t(0.019200533863109957+0j)\n",
+      "ZIII\t(-0.3581026994577025+0j)\n",
+      "IZIZ\t(-0.12182774215821467+0j)\n",
+      "IZZX\t(0.012144897228064444+0j)\n",
+      "IZIX\t(-0.012144897228064444+0j)\n",
+      "IZXX\t(0.03169874598734439+0j)\n",
+      "IZYY\t(-0.03169874598734439+0j)\n",
+      "IXIZ\t(0.012144897228064444+0j)\n",
+      "ZXIZ\t(0.012144897228064444+0j)\n",
+      "IXZX\t(-0.0032659954996582014+0j)\n",
+      "ZXZX\t(-0.0032659954996582014+0j)\n",
+      "IXIX\t(0.0032659954996582014+0j)\n",
+      "ZXIX\t(0.0032659954996582014+0j)\n",
+      "IXXX\t(-0.008650156860609944+0j)\n",
+      "ZXXX\t(-0.008650156860609944+0j)\n",
+      "IXYY\t(0.008650156860609944+0j)\n",
+      "ZXYY\t(0.008650156860609944+0j)\n",
+      "YYIZ\t(0.03169874598734438+0j)\n",
+      "XXIZ\t(-0.03169874598734438+0j)\n",
+      "YYZX\t(-0.008650156860609944+0j)\n",
+      "XXZX\t(0.008650156860609944+0j)\n",
+      "YYIX\t(0.008650156860609944+0j)\n",
+      "XXIX\t(-0.008650156860609944+0j)\n",
+      "YYXX\t(-0.030981613344629504+0j)\n",
+      "XXXX\t(0.030981613344629504+0j)\n",
+      "YYYY\t(0.030981613344629504+0j)\n",
+      "XXYY\t(-0.030981613344629504+0j)\n",
+      "ZZIZ\t(0.055902510785159+0j)\n",
+      "ZZZX\t(0.0018710427514161882+0j)\n",
+      "ZZIX\t(-0.0018710427514161882+0j)\n",
+      "ZZXX\t(0.003104004116073226+0j)\n",
+      "ZZYY\t(-0.003104004116073226+0j)\n",
+      "XIIZ\t(0.012841723180756926+0j)\n",
+      "XZIZ\t(-0.012841723180756926+0j)\n",
+      "XIZX\t(-0.0023521521732445616+0j)\n",
+      "XZZX\t(0.0023521521732445616+0j)\n",
+      "XIIX\t(0.0023521521732445616+0j)\n",
+      "XZIX\t(-0.0023521521732445616+0j)\n",
+      "XIXX\t(-0.00797590875056439+0j)\n",
+      "XZXX\t(0.00797590875056439+0j)\n",
+      "XIYY\t(0.00797590875056439+0j)\n",
+      "XZYY\t(-0.00797590875056439+0j)\n",
+      "ZIIZ\t(0.1134611071268544+0j)\n",
+      "ZIZX\t(-0.010838363828740441+0j)\n",
+      "ZIIX\t(0.010838363828740441+0j)\n",
+      "ZIXX\t(-0.03355135311123841+0j)\n",
+      "ZIYY\t(0.03355135311123841+0j)\n",
+      "IZZZ\t(-0.055902510785159+0j)\n",
+      "IZXZ\t(-0.012841723180756926+0j)\n",
+      "IZXI\t(-0.012841723180756926+0j)\n",
+      "IXZZ\t(-0.001871042751416188+0j)\n",
+      "ZXZZ\t(-0.001871042751416188+0j)\n",
+      "IXXZ\t(0.002352152173244561+0j)\n",
+      "ZXXZ\t(0.002352152173244561+0j)\n",
+      "IXXI\t(0.002352152173244561+0j)\n",
+      "ZXXI\t(0.002352152173244561+0j)\n",
+      "YYZZ\t(-0.003104004116073226+0j)\n",
+      "XXZZ\t(0.003104004116073226+0j)\n",
+      "YYXZ\t(0.00797590875056439+0j)\n",
+      "XXXZ\t(-0.00797590875056439+0j)\n",
+      "YYXI\t(0.00797590875056439+0j)\n",
+      "XXXI\t(-0.00797590875056439+0j)\n",
+      "ZZZZ\t(0.08447056807294587+0j)\n",
+      "ZZXZ\t(-0.008994911953942185+0j)\n",
+      "ZZXI\t(-0.008994911953942185+0j)\n",
+      "XIZZ\t(-0.008994911953942183+0j)\n",
+      "XZZZ\t(0.008994911953942183+0j)\n",
+      "XIXZ\t(0.006612047066151987+0j)\n",
+      "XZXZ\t(-0.006612047066151987+0j)\n",
+      "XIXI\t(0.006612047066151987+0j)\n",
+      "XZXI\t(-0.006612047066151987+0j)\n",
+      "ZIZZ\t(0.060358912810781123+0j)\n",
+      "ZIXZ\t(0.011019231644712395+0j)\n",
+      "ZIXI\t(0.011019231644712395+0j)\n",
+      "IZZI\t(0.1134611071268544+0j)\n",
+      "IXZI\t(-0.01083836382874044+0j)\n",
+      "ZXZI\t(-0.01083836382874044+0j)\n",
+      "YYZI\t(-0.03355135311123841+0j)\n",
+      "XXZI\t(0.03355135311123841+0j)\n",
+      "ZZZI\t(-0.060358912810781123+0j)\n",
+      "XIZI\t(-0.011019231644712394+0j)\n",
+      "XZZI\t(0.011019231644712394+0j)\n",
+      "ZIZI\t(-0.11344680300367244+0j)\n",
       "\n",
       "Representation: paulis, qubits: 4, size: 100\n"
      ]
@@ -261,10 +262,10 @@
     "    num_spin_orbitals -= len(remove_list)\n",
     "\n",
     "qubitOp = ferOp.mapping(map_type=map_type, threshold=0.00000001)\n",
-    "qubitOp = qubitOp.two_qubit_reduced_operator(num_particles) if qubit_reduction else qubitOp\n",
+    "qubitOp = Z2Symmetries.two_qubit_reduction(qubitOp, num_particles) if qubit_reduction else qubitOp\n",
     "qubitOp.chop(10**-10)\n",
     "\n",
-    "print(qubitOp.print_operators())\n",
+    "print(qubitOp.print_details())\n",
     "print(qubitOp)"
    ]
   },
@@ -316,7 +317,7 @@
     "### [Optional] Setup token to run the experiment on a real device\n",
     "If you would like to run the experiement on a real device, you need to setup your account first.\n",
     "\n",
-    "Note: If you do not store your token yet, use `IBMQ.save_accounts()` to store it first."
+    "Note: If you do not store your token yet, use `IBMQ.save_account()` to store it first."
    ]
   },
   {
@@ -326,7 +327,7 @@
    "outputs": [],
    "source": [
     "# from qiskit import IBMQ\n",
-    "# IBMQ.load_accounts()"
+    "# IBMQ.load_account()"
    ]
   },
   {
@@ -340,7 +341,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 10,
    "metadata": {
     "scrolled": true
    },
@@ -396,13 +397,6 @@
     "print('The total ground state energy is: {:.12f}'.format(results['eigvals'][0] + energy_shift + nuclear_repulsion_energy))\n",
     "print(\"Parameters: {}\".format(results['opt_params']))"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {
diff --git a/qiskit/advanced/terra/using_the_transpiler.ipynb b/qiskit/advanced/terra/using_the_transpiler.ipynb
index 5be970627..7651f6409 100644
--- a/qiskit/advanced/terra/using_the_transpiler.ipynb
+++ b/qiskit/advanced/terra/using_the_transpiler.ipynb
@@ -55,10 +55,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 58,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 1,
+   "metadata": {},
    "outputs": [],
    "source": [
     "from qiskit.compiler import transpile\n",
@@ -74,13 +72,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 60,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
-       "<pre style=\"word-wrap: normal;white-space: pre;line-height: 15px;\">             \n",
+       "<pre style=\"word-wrap: normal;white-space: pre;background: #fff0;line-height: 1.1;font-family: &quot;Courier New&quot;,Courier,monospace\">             \n",
        "q_0: |0>──■──\n",
        "          │  \n",
        "q_1: |0>──■──\n",
@@ -89,10 +87,10 @@
        "        └───┘</pre>"
       ],
       "text/plain": [
-       "<qiskit.visualization.text.TextDrawing at 0x1272e0518>"
+       "<qiskit.visualization.text.TextDrawing at 0x1321f83c8>"
       ]
      },
-     "execution_count": 60,
+     "execution_count": 2,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -121,17 +119,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 65,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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U2p52vxgtfc7i6u0igSKrX2QyGVavXo3WrV/A6NGjse/AYRQbtkaH10YDchma2LjgZFQs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\nO0kNM9eadGwU83ERqJtxXp8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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x126810160>"
+       "<Figure size 939.12x204.68 with 1 Axes>"
       ]
      },
-     "execution_count": 65,
+     "execution_count": 3,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -157,17 +155,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 66,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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U2p52vxgtfc7i6u0igSKrX2QyGVavXo3WrV/A6NGjse/AYRQbtkaH10YDchma2LjgZFQs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\nO0kNM9eadGwU83ERqJtxXp8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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x1264c49e8>"
+       "<Figure size 939.12x204.68 with 1 Axes>"
       ]
      },
-     "execution_count": 66,
+     "execution_count": 4,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -189,13 +187,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 56,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "['BarrierBeforeFinalMeasurements',\n",
+       "['ApplyLayout',\n",
+       " 'BarrierBeforeFinalMeasurements',\n",
        " 'BasicSwap',\n",
        " 'CXCancellation',\n",
        " 'CXDirection',\n",
@@ -206,14 +205,15 @@
        " 'CommutativeCancellation',\n",
        " 'ConsolidateBlocks',\n",
        " 'CountOps',\n",
+       " 'CountOpsLongestPath',\n",
        " 'DAGFixedPoint',\n",
+       " 'DAGLongestPath',\n",
        " 'Decompose',\n",
        " 'DenseLayout',\n",
        " 'Depth',\n",
        " 'EnlargeWithAncilla',\n",
        " 'FixedPoint',\n",
        " 'FullAncillaAllocation',\n",
-       " 'LegacySwap',\n",
        " 'LookaheadSwap',\n",
        " 'MergeAdjacentBarriers',\n",
        " 'NoiseAdaptiveLayout',\n",
@@ -232,7 +232,7 @@
        " 'Width']"
       ]
      },
-     "execution_count": 56,
+     "execution_count": 5,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -260,7 +260,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -279,34 +279,33 @@
     "circuit.cx(qr[3], qr[0])\n",
     "\n",
     "coupling_map = CouplingMap(couplinglist=coupling)\n",
-    "layout = Layout({qr[i]: i for i in range(coupling_map.size())})\n",
     "\n",
-    "bs = BasicSwap(coupling_map=coupling_map, initial_layout=layout)\n",
+    "bs = BasicSwap(coupling_map=coupling_map)\n",
     "pass_manager = PassManager(bs)\n",
     "basic_circ = pass_manager.run(circuit)\n",
     "\n",
-    "ls = LookaheadSwap(coupling_map=coupling_map, initial_layout=layout)\n",
+    "ls = LookaheadSwap(coupling_map=coupling_map)\n",
     "pass_manager = PassManager(ls)\n",
     "lookahead_circ = pass_manager.run(circuit)\n",
     "\n",
-    "ss = StochasticSwap(coupling_map=coupling_map, initial_layout=layout)\n",
+    "ss = StochasticSwap(coupling_map=coupling_map)\n",
     "pass_manager = PassManager(ss)\n",
     "stochastic_circ = pass_manager.run(circuit)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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2qZCIiOh6GFxERCQUBhcREQmFwUVEREJhcBERkVAYXEREJBQGFxERCYXBRURE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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x1265b92b0>"
+       "<Figure size 517.72x445.48 with 1 Axes>"
       ]
      },
-     "execution_count": 22,
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -317,17 +316,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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xx1xQ6X81bNhQGzZs0D333FNqQLIGo27dumnNmjWqW7eukyutfIwxevvtmQpo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\nu+7JDJuzmtzcHObPn3+HqpQkqe6qt+Hoh8rKynj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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x126724978>"
+       "<Figure size 1059.52x445.48 with 1 Axes>"
       ]
      },
-     "execution_count": 23,
+     "execution_count": 8,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -338,17 +337,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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XvU+ePInRo0cjLy+vUUaaJyUlISkpCTNnztT7uUlafv75ZwwaNEinKd0qlQq+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\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x12660d2e8>"
+       "<Figure size 698.32x445.48 with 1 Axes>"
       ]
      },
-     "execution_count": 24,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -359,17 +358,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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UlIQxY8YYtB4nJyeD7Ncgddrsg8CgcO+QyWR48803cOlkAX7b8Z9m9bU/eQGuV1Vi5syZ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\nYXU/AAAAAElFTkSuQmCC\n",
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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x125f9c2b0>"
+       "<Figure size 878.92x445.48 with 1 Axes>"
       ]
      },
-     "execution_count": 25,
+     "execution_count": 10,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -404,10 +403,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 11,
+   "metadata": {},
    "outputs": [],
    "source": [
     "import math\n",
@@ -422,17 +419,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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Rl8sFn8+Xtr1uFW+88QZ/asgWpFrgN27cQHd3NwYGBmCz2aDRaNDV1QVZlpMK/L/+67/w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\n8Bs3bqC7uxsDAwOw2WzQaDT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       "text/plain": [
-       "<matplotlib.figure.Figure at 0x110ad24a8>"
+       "<Figure size 1491.76x626.08 with 1 Axes>"
       ]
      },
-     "execution_count": 30,
+     "execution_count": 12,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -469,15 +466,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 46,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "gates =  {'u3': 15, 'u1': 15, 'cx': 107}\n",
-      "depth =  125\n"
+      "gates =  OrderedDict([('cx', 86), ('u3', 15), ('u1', 15)])\n",
+      "depth =  102\n"
      ]
     }
    ],
@@ -489,15 +486,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 47,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "gates =  {'u3': 15, 'cx': 95, 'u1': 10}\n",
-      "depth =  108\n"
+      "gates =  OrderedDict([('cx', 80), ('u3', 15), ('u1', 10)])\n",
+      "depth =  91\n"
      ]
     }
    ],
@@ -509,15 +506,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 48,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "gates =  {'u3': 15, 'cx': 40, 'u1': 6}\n",
-      "depth =  49\n"
+      "gates =  OrderedDict([('cx', 74), ('u3', 15), ('u1', 6), ('u2', 4)])\n",
+      "depth =  81\n"
      ]
     }
    ],
@@ -529,15 +526,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 49,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "gates =  {'u3': 50, 'cx': 26, 'u2': 8}\n",
-      "depth =  45\n"
+      "gates =  OrderedDict([('cx', 70), ('u3', 35), ('u2', 8), ('u1', 4)])\n",
+      "depth =  84\n"
      ]
     }
    ],
@@ -553,6 +550,13 @@
    "source": [
     "You can see that the circuit gets progressively better (both in terms of depth and the number of expensive cx gates)."
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {