qiskit/fundamentals/5_using_the_transpiler.ipynb

{
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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![qiskit_header.png](attachment:qiskit_header.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Circuit Rewriting using the Transpiler\n",
    "\n",
    "Previously we have performed basic operations on circuits, and ran those circuits on real quantum devices using the `execute` function.  `execute` is a helper function that performs three tasks for the user:\n",
    "\n",
    "1) Circuits are rewritten to match the constraints of a given backend and optimized.\n",
    "\n",
    "2) The rewritten circuits are packaged for submission.\n",
    "\n",
    "3) The packaged circuits are submitted to the device.\n",
    "\n",
    "The first step is called transpilation, and is the fundamental step required for running circuits on real quantum devices.  The qiskit function that does this is `transpile`, which takes a single or list of input circuits, as well as a collection of parameters, and returns a modified list of circuits.  Using this `transpile` function is the goal of this tutorial.\n",
    "\n",
    "For those wishing to bypass this in-depth discussion of what happens during the transpilation process, we note that the standard way of calling the `transpile` function is:\n",
    "\n",
    "```python\n",
    "new_circuits = transpile(circuits, backend, optimization_level=1)\n",
    "```\n",
    "\n",
    "where `circuits` is a single or list of input circuits, `backend` is the target device, and `optimization_level` selects between four different `[0,1,2,3]` preset methods of circuit rewriting and optimization.  By default, `optimization_level=1`."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-09T14:50:04.434271Z",
     "start_time": "2019-08-09T14:50:04.429464Z"
    }
   },
   "source": [
    "# Table of contents\n",
    "\n",
    "1) [Introduction](#introduction)\n",
    "\n",
    "\n",
    "2) [Basis Gates](#basis)\n",
    "\n",
    "\n",
    "3) [Initial Layout](#layout)\n",
    "\n",
    "\n",
    "4) [Mapping Circuits to Hardware](#mapping)\n",
    "\n",
    "\n",
    "5) [Optimizing Gates](#optimizing)\n",
    "\n",
    "\n",
    "6) [User Defined Topologies](#topology)\n",
    "\n",
    "\n",
    "7) [Passing Transpiled Circuits to Devices](#passing)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-09T13:47:51.084814Z",
     "start_time": "2019-08-09T13:47:48.486326Z"
    }
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from qiskit import *\n",
    "from qiskit.visualization import plot_histogram, plot_gate_map, plot_circuit_layout\n",
    "from qiskit.tools.monitor import job_monitor\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-09T13:47:53.454349Z",
     "start_time": "2019-08-09T13:47:51.092457Z"
    }
   },
   "outputs": [],
   "source": [
    "IBMQ.load_account()\n",
    "provider = IBMQ.get_provider(group='open')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Introduction <a name='introduction'></a>\n",
    "\n",
    "Consider the following circuit that creates a five-qubit GHZ state:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-09T13:47:53.996090Z",
     "start_time": "2019-08-09T13:47:53.463668Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 818.72x385.28 with 1 Axes>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ghz = QuantumCircuit(5, 5)\n",
    "ghz.h(0)\n",
    "for idx in range(1,5):\n",
    "    ghz.cx(0,idx)\n",
    "ghz.barrier(range(5))\n",
    "ghz.measure(range(5), range(5))\n",
    "ghz.draw(output='mpl')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We would like to take this circuit and run it on an IBM Q quantum device.  However, in its original form, this circuit cannot be run.  This circuit, as is the case with most circuits, must undergo a series of transformations that make it compatible with a given target device, and optimize it to reduce the effects of noise on the resulting outcomes.\n",
    "\n",
    "As we will see, rewriting quantum circuits to match hardware constraints and optimizing for performance can be far from trivial.  The flow of logic in the rewriting tool chain need not be linear, and can often have iterative sub-loops, conditional branches, and other complex behaviors.  That being said, the basic building blocks follow the structure given below."
   ]
  },
  {
   "attachments": {
    "transpiling_core_steps.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-06T09:28:13.270334Z",
     "start_time": "2019-08-06T09:28:13.266618Z"
    }
   },
   "source": [
    "![transpiling_core_steps.png](attachment:transpiling_core_steps.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In what follows, we highlight the key steps in this workflow, and show how they modify circuits based on the value of keyword arguments passed to the `transpile` function.  The `transpile` function has many input arguments:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-09T13:47:54.015108Z",
     "start_time": "2019-08-09T13:47:54.011066Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Signature (circuits, backend=None, basis_gates=None, coupling_map=None, backend_properties=None, initial_layout=None, seed_transpiler=None, optimization_level=None, pass_manager=None, callback=None, output_name=None)>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import inspect\n",
    "inspect.signature(transpile)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here we focus only on the most important ones: `basis_gates`, `initial_layout` `optimization_level` and `coupling_map`."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Basis Gates <a name='basis'></a>\n",
    "\n",
    "When writing a quantum circuit you are free to use any quantum gate (unitary operator) that you like, along with a collection of non-gate operations such as qubit measurements and reset operations.  However, when running a circuit on a real quantum device one no longer has this flexibility.  Due to limitations in, for example, the physical interactions between qubits, difficulty in implementing multi-qubit gates, control electronics etc, a quantum computing device can only natively support a handful of quantum gates and non-gate operations. In the present case of IBM Q devices, the native gate set can be found by querying the devices themselves, and looking for the corresponding attribute in their configuration:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-09T13:47:54.451253Z",
     "start_time": "2019-08-09T13:47:54.037172Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<IBMQBackend('ibmqx2') from IBMQ(hub='ibm-q', group='open', project='main')>,\n",
       " <IBMQBackend('ibmq_16_melbourne') from IBMQ(hub='ibm-q', group='open', project='main')>,\n",
       " <IBMQBackend('ibmq_vigo') from IBMQ(hub='ibm-q', group='open', project='main')>,\n",
       " <IBMQBackend('ibmq_ourense') from IBMQ(hub='ibm-q', group='open', project='main')>,\n",
       " <IBMQBackend('ibmq_london') from IBMQ(hub='ibm-q', group='open', project='main')>,\n",
       " <IBMQBackend('ibmq_burlington') from IBMQ(hub='ibm-q', group='open', project='main')>,\n",
       " <IBMQBackend('ibmq_essex') from IBMQ(hub='ibm-q', group='open', project='main')>]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "provider = IBMQ.get_provider(group='open')\n",
    "provider.backends(simulator=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-09T13:47:54.470643Z",
     "start_time": "2019-08-09T13:47:54.466317Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['u1', 'u2', 'u3', 'cx', 'id']"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "backend = provider.get_backend('ibmqx2')\n",
    "backend.configuration().basis_gates"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-05T18:44:17.399097Z",
     "start_time": "2019-08-05T18:44:17.383113Z"
    }
   },
   "source": [
    "We see that the `ibmqx2` device supports five native gates: four single-qubit gates (`u1`, `u2`, `u3`, and `id`) and one two-qubit entangling gate `cx`.  In addition, the device supports qubit measurements (otherwise we can not read out an answer!).  Although we have queried only a single device, let us note that all IBM Q devices support this gate set.\n",
    "\n",
    "The `u*` gates represent arbitrary single-qubit rotations of one, two, and three angles.  The `u1` gates are single-parameter rotations that represent generalized phase gates of the form\n",
    "\n",
    "$$\n",
    "U_{1}(\\lambda) = \\begin{bmatrix}\n",
    "1 & 0 \\\\\n",
    "0 & e^{i\\lambda}\n",
    "\\end{bmatrix}\n",
    "$$\n",
    "\n",
    "This set includes common gates such as $Z$, $T$, $T^{\\dagger}$, $S$, and $S^{\\dagger}$.  It turns out that these gates do not actually need to be performed on hardware, but instead, can be implemented in software as \"virtual gates\".  These virtual gates are called \"frame changes\" and take zero time, and have no associated error; they are free gates on hardware.\n",
    "\n",
    "Two-angle rotations, $U_{2}(\\phi,\\lambda)$, are actually two frame changes with a single $X_{\\pi/2}$ gate in between them, and can be used to synthesize gates like the Hadamard ($U_{2}(0,\\pi)$) gate.  As the only actual gate performed is the $X_{\\pi/2}$ gate, the error and gate time associated with any $U_{2}$ gate is the same as an $X_{\\pi/2}$ gate.  Similarly, $U_{3}(\\theta,\\phi,\\lambda)$ gates are formed from three frame changes with two $X_{\\pi/2}$ gates in between them.  The errors and gate times are twice those of a single $X_{\\pi/2}$.  The identity gate, $id$, is straightforward, and is a placeholder gate with a fixed time-interval. \n",
    "\n",
    "The only entangling gate supported by the IBM Q devices is the CNOT gate (`cx`) which, in the computational basis, can be written as:\n",
    "\n",
    "$$\n",
    "\\mathrm{CNOT}(0,1) = \\begin{bmatrix}\n",
    "1 & 0 & 0 & 0 \\\\\n",
    "0 & 0 & 0 & 1 \\\\\n",
    "0 & 0 & 1 & 0 \\\\\n",
    "0 & 1 & 0 & 0\n",
    "\\end{bmatrix}\n",
    "$$\n",
    "\n",
    "where the matrix form above follows from the specific bit-ordering convention used in Qiskit. (This was discussed in [Part 1: Getting Started with Qiskit](1_getting_started_with_qiskit.ipynb#Statevector-backend).)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Every quantum circuit run on an IBM Q device must be expressed using only these basis gates.  For example, suppose one wants to run a simple phase estimation circuit:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-09T13:47:54.684874Z",
     "start_time": "2019-08-09T13:47:54.491476Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 397.32x204.68 with 1 Axes>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "qc = QuantumCircuit(2, 1)\n",
    "\n",
    "qc.h(0)\n",
    "qc.x(1)\n",
    "qc.cu1(np.pi/4, 0, 1)\n",
    "qc.h(0)\n",
    "qc.measure([0], [0])\n",
    "qc.draw(output='mpl')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We have $H$, $X$, and controlled-$U_{1}$ gates, all of which are not in our devices basis gate set, and must be expanded.  This expansion is taken care of for us in the `execute` function.  However, we can decompose the circuit to show what it would look like in the native gate set of the IBM Q devices"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-09T13:47:54.920353Z",
     "start_time": "2019-08-09T13:47:54.699157Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 698.32x204.68 with 1 Axes>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "qc_basis = qc.decompose()\n",
    "qc_basis.draw(output='mpl')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A few things to highlight.  One, as mentioned in [Part 4: Quantum Circuit Properties](4_quantum_circuit_properties.ipynb), the circuit has gotten longer with respect to the initial one.  This can be verified by checking the depth of the circuits:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-09T13:47:54.941745Z",
     "start_time": "2019-08-09T13:47:54.937994Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "4 , 7\n"
     ]
    }
   ],
   "source": [
    "print(qc.depth(), ',', qc_basis.depth())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Two, although we had a single controlled gate, the fact that it was not in the basis set means that, when expanded, it requires more than a single `cx` gate to implement. All said, unrolling to the basis set of gates leads to an increase in the depth of a quantum circuit and the number of gates.\n",
    "\n",
    "It is important to highlight two special cases:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### SWAP Gate Decomposition\n",
    "\n",
    "A SWAP gate is not a native gate on the IBM Q devices, and must be decomposed into three CNOT gates:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-09T13:47:57.053386Z",
     "start_time": "2019-08-09T13:47:56.919376Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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48wTp5H+6AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 337.12x144.48 with 1 Axes>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "swap_circ = QuantumCircuit(2)\n",
    "swap_circ.swap(0, 1)\n",
    "swap_circ.decompose().draw(output='mpl')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As a product of three CNOT gates, SWAP gates are expensive operations to perform on a noisy quantum devices.  However, such operations are usually necessary for embedding a circuit into the limited entangling gate connectivities of actual devices.  Thus, minimizing the number of SWAP gates in a circuit is a primary goal in the transpilation process."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Toffoli Gate Decomposition\n",
    "\n",
    "A Toffoli, or controlled-controlled-not gate, is a three-qubit gate.  Given that our basis gate set includes only single- and two-qubit gates, it is obvious that this gate must be decomposed.  This decomposition is quite costly."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-09T01:00:00.098589Z",
     "start_time": "2019-08-09T00:59:59.884584Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAngAAACoCAYAAABzNpM8AAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjEsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy8QZhcZAAAfPUlEQVR4nO3de3xU1b338c/kQkgISQjhmhAukoQQEzBRishFlHqQ56kXXnhBxSNUUURPlWN76mOxPe0RfaiPL8Wqlfa0YpVjBaH6UqqCBUQQJKDcccI1F0OEcA3kPvP8sQtkIJch2bP3ZM/3/XrNC2bPnjW/rKzM/u211l7b5fV6vYiIiIiIY4TZHYCIiIiImEsJnoiIiIjDKMETERERcRgleCIiIiIOowRPRERExGGU4ImIiIg4jBI8EREREYdRgiciIiLiMErwRERERBxGCZ6IiIiIwyjBExEREXEYJXgiIiIiDqMET0RERMRhlOCJiIiIOIwSPBERERGHUYInIiIi4jBK8EREREQcRgmeiIiIiMMowRMRERFxGCV4IiIiIg6jBE9ERETEYZTgiYiIiDiMEjwRERERh1GCJyIiIuIwSvBEREREHEYJnoiIiIjDKMETERERcZgIuwMQERERe6143p7PHfeEPZ8bCtSDJyIiIuIwSvBEREREHEYJnoiIiIjDKMETERERcRgleCIiIiIOowRPRERExGGU4ImIiIg4jBI8EREREYfRQsciIcjrhQNHYNd3UO+BHvEwNBU66BtB2rF6D+wsMdq2ywX9u0FmLwgL8q6MI6fgm0I4Uw1x0ZDXDzpH2x2VMx06AVsKoboWEmMhty/ERNkdVWCE3Ne5x+PhhRde4PXXX6eoqIiMjAzmzZvH9OnTGTNmDPPnz7c7RJGAKq+AP38Oxcd8ty/Jh9uGGQcXkfZm3/ew4As4Uem7vUsM3DcK+ibZE1dzaurgrxtg0wHf7R98DWMGwY+GBl9yumbbEua+c6/xxOulqvYMUZHRuFxGoCOybubJu962McLGnamBt9bCzu98t/9tE4zPgesHGycFThJyCd60adNYunQps2fPJi8vj3Xr1jF58mQOHz7MrFmz7A5PJKBOV8PLy+HEmYtfq6qFv6yFyHDI6WN9bCKtVXwUXv2H0YN3oeOV8MpnMGs89Iy3PrameL3w5hewveTi1zxeWLnL+PfWPOtja86o7ImMyp4IwLdFG3lk3jD+8uR+unTuYXNkTav3wOsr4eCRi1+r88CH34ALuD7L8tACKsjODQJr4cKFLFiwgA8++IAnnniCsWPH8tRTT3H11VdTV1dHXp7xl1RWVsYNN9xATEwMQ4YM4euvv7Y5chFzfOGG42fA28TrLozeA29TO4gEoU+2GQfxxtqt1wu1dfDpNuvjas7+w40ndw19vhuOnbYmntZwF2+iW3xKUCd3ANuKGk/uGvp4m3GS6yQhleA9++yzjB8/njFjxvhsHzhwIJGRkWRnZwMwY8YMBg0aRHl5OTNnzmTSpEnU19fbEbKIqb7c0/zrXoz5QPsPWxKOSJtVVMH24uZPSrwYc9wqaywLq0Xr9xonVM3xAhv3WRFN67iL80lLCbIuxkas39vy8GttPXxz0Jp4rBIyCV5xcTHbt2/ntttuu+i1wsJCsrKyiIqK4tSpU3z00Uc8/fTTREdHM336dOrr61m/fn3AYnO5XHroYcnjaIV/Jyo33jLZ9lj10MOfR/+MIU32SDfk8ULvfhm2x3v2sfj95Xi8jYwpN4y5vo7/++J8S+JpDXdRPukpV7bqvWdZ8bOty9/l16jE4//xn7a3CzN/VyGV4AH07NnTZ3tlZSWrV68+NzxbUFBA165dSUo6PyM3OzubnTt3WhesSIDUVp3ya7+aMycCHImIOaovoa0GU7uuqTyJ19N8gudyhVFTGTwxN1RTW8XBsh1tTvCsUH3meIt1DVAdpHXdWiFzkcXZhM3tdjNhwoRz2+fOnUtpaSm5ubkAnD59mri4OJ/3xsXFUVFREbDYvJrwJBZ5d4MxTNtci4vuAO5Ny4gMtywskTb5f383LrRobm5p/25w+vghK8Nq1uYD8Oba5vdxhYXx9ss/JXXhTwMez4rnL23/vaVbqPfUtXmI1orj36rdxtWyzXEBK959gcTYFwIej1VCJsEbMGAAOTk5zJkzh8TERJKTk1m8eDHLli0DONeD16lTJ06d8u3lOHnyJLGxsZbHLGK20YNgwz7weJo+GI7NRMmdtCvjsuDPa5p+3fvPfYJJTh9IioXy043PH3QBA3tAalfLQ/OLuyif7gmpJMR2szuUFg3rDyu2w+mapudq5vYz1sVzkpAZog0LC2PRokVkZWUxY8YMpk6dSlJSEjNnziQiIoKcnBwA0tLSOHLkCOXl5efeu337dgYPHmxX6CKm6RkPPx4NERckcGdndYxIC74DoUhLhqTCLblNvz7pKhicbF08/ogIhxnXQ2KM7/azU6z6JBrr9wWrgpJN7WJ4FoyFjGdcD50uWND47PfeoF5wxw8sDyvgXN4QHx+cMmUKW7ZsYevWree2TZw4kdTUVJ577jneeust5syZQ0FBAeHh6tYQZzhVaVxZ9tEW4/mwAUZy17er8xb7lNBRdhLWuuHzb43n1w6Ca9KhW2d742pOTZ1xhe/CL43nWcnG3+PlKRBuYRfMpQ7RmmXcE9Z9VlUt5O+HxRuN50NSYfhlkNELwhz4vRcyPXhNyc/PPzc8e9Zrr73Gjh076NKlC/PmzeO9995TcieO0jkafnj5+ed3XQ39kpTcSfvWIw4mNuhUuiUvuJM7MG4POGzA+ecPXGskHlYmd6GiYySMTD//fOooyOztzOQOQmgOXmMqKipwu908/PDDPtt79OjB8uXLbYpKREREpG1COsGLjY3VAsYiIiLiOOoEFhEREXEYJXgiIiIiDqMET0RERMRhlOCJiIiIOIwSPBERERGHUYInIiIi4jAhvUyKiIiIWHtHCbGGevBEREREHEYJnoiIiIjDKMETERERcRgleCIiIiIOowRPRERExGGU4ImIiIg4jBI8EREREYdRgiciIiLiMErwRERERBxGCZ6IiIiIwyjBExEREXEYJXgiIiIiDqMET0RERMRhlOCJiIiIOIwSPBERERGHibA7ABERCbwVz1v/meOesP4zpXXsaB+gNhJI6sETERERcRgleCIiIiIOowRPRETERqerz///wBGoqrUvFqc7VXX+/4XlUFNnXyyBpjl4IiIiFiuvgLUFsKXQ+P9ZL34CLqB7HOT1h6svg87RtoXpCIdOwFo3bC2CE5Xnt7/wMYS5oFcCXDUAhvWHmCj74jSbEjwRERGL1NTBR1vg893gbWIfL1B2EpZtgU+2wfhsuG4whGvM7ZKcqYG/bYKv9jW9j8cLJcegZBP8fQvcdAWMSAOXy7o4A0UJnoiIiAXKK+D1lfD9Sf/fU+8xEsKdJXD/tdDJQT1MgfTdMaOuG/bYtaS6DhZthB0l8K+jIKqdZ0g6HxAREQmwY6fh5eWXltw1tP8IvPqZ0SslzSs9Dr9bcWnJXUM7v4M/roLaelPDspwSPBERkQDyeODNtXD8TNP7vHi38WhOyTFYstHc2Mx26OgB5r5zn22fX1sPf17TfCLsT10XlBlDtu2ZEjwJOlW1cKrSGJoQcQKv17hSsqLKmPMjoeWLAth/2Jyy8g/AjmJzynKiT7a1vpf0Qit3wcEj5pRlh3Y+wnzpPB4PL7zwAq+//jpFRUVkZGQwb948pk+fzpgxY5g/f77dIYasnSXGH1RBmfG8YyQMv8yYXBynq8ikHfJ4YcNeWL3buJIPICEGRqbD6AzoEHLfwKGn3gOf7TC3zOU7ICvF3DLN8Or7j7GrcD1lRw/w769dy4ybXmRg8lDLPr+qFj7/1rzyvMBnO2HaaPPKtFLIfb1MmzaNpUuXMnv2bPLy8li3bh2TJ0/m8OHDzJo1y+7wQtbKXfD+Zt8rl6pqYdVu+Pog/OQGSIy1Lz6RS+XxwsJ1Ro9Lwwvyjp+BD78xemEeuj74JnKv2baEue/cazzxeqmqPUNUZDQulzHgMyLrZp68620bI2xfdpS0fi5YUw4cgeKjkJJobrlN8bdNPHzzixw6eoA3P/0VP7vzDWuCayB/v/nr2m0vNv5mE2LMLdcKQfbVElgLFy5kwYIFrFq1ijFjxgAwduxYNm/ezJIlS8jLywPgl7/8JYsWLWL37t28++67TJo0yc6wHa+o3EjuwBjKutDJSnhrHfzbDdbGJdIWG/YayR00vhzG/iPGMhi35lkZVctGZU9kVPZEAL4t2sgj84bxlyf306VzD5sja5/cpYEpt6DMugSvvbQJ9yHzy/R4YW+ZsSZhexNSc/CeffZZxo8ffy65O2vgwIFERkaSnZ0NQFpaGi+99BLDhg2zI8yQs8bt28NxIS+w77Bx2btIe+D1GsOyLS2ltX6PsTRDsHIXb6JbfErQHcjbk6KjgSm3sDww5bYkmNtEUYDqpDBAv8NAC5kevOLiYrZv387jjz9+0WuFhYVkZWURFWUsMHTPPfcA8Mwzz1gSm8sJKyq2wbSXDtK5a2qL+914xyNsXf6KBRGFjp+8ZfQthXobNFtUTAIPzW/5jKS6DvoPHkFpwZcBj2n5by/96g53cT5pKa3vYrSrXQVTu542r4jOib4T5pq7grOp1x67YFT8w08+575RYxrfuRX8bR9tbRMXMvN39OibdYSFhZ973tKVsv7W9R/e+CsTr7yzjdGZx9vYUFcjQqYHr7jYuOyoZ8+ePtsrKytZvXr1ueFZsZ6rwR9kc8L83E/Ebv626Uvd12ruonzSU660O4x2zdViP25rC7YneW2pTXSI6Ehq90EWRnSe0+q6rUKmBy8pKQkAt9vNhAkTzm2fO3cupaWl5Obm2hWa39m4U/33amMia0u18N6bLzGg+0uWxBQqzp6phnobNJvHC7/+W/PrnoFx6yn3ljWW3J1gxfOXtn9NbRUHy3aQnvJcqz/TrnYVTO36t8uM9esaurCHCM73JjX2WmNuHDeKRb827+fzp3340yYS43py53U/9/tzzfwdzX4PTlWdf95UXV5qXU+753aWzbu9bcHZIGQSvAEDBpCTk8OcOXNITEwkOTmZxYsXs2zZMgD14NloZDpsa2ZdJxfQPR76d7MsJJE2CXMZ7frDb5rexwXk9g3eW0/tLd1CvafO1OG4UJSSeHGCZ1a5Vgv2NpGSCLu+C0C5Xc0v0wohM0QbFhbGokWLyMrKYsaMGUydOpWkpCRmzpxJREQEOTk5docYstJ7Gjd3bozLBRHhcPfV7baXXELUmEFNn5S4gIRO8KMrLA3pkriL8umekEpCrM6s2uKy7gEq14ZfS7C3CSfVtRlCpgcPID09nZUrV/psmzJlCpmZmURHn19Jt7a2lvr6ejweD7W1tVRVVREVFRUUE3adyOWC266C7nGwcqfvmlGZveB/D4XeXeyLT6Q1IsNhxnXw962wbg9U1xrbw8Mgtx/cNBQ6B/EC3gUlmzT/zgRDU2FJvrGup1m6x8GAACUzzQn2NjFsgLH0kJl3i0nrAd3izCvPSiGV4DUmPz+f4cOH+2x74IEHWLBgAQBr1qwBYP/+/fTr18/q8EKGywXXDoLR6TDrf4xtv7wFunSyNy6RtugQATfnwo058LO/Gtt+PTF4h2UbeuL2P9kdgiN0iIBR6cbdJ8xyXaY9IxrB3ibiouHK/vDVPvPKHJtpXllWC5kh2sZUVFTgdrsvusDijTfewOv1+jyU3FkjrEGLVHInTtHwlmTtIbkTc/3wcqPXzQxpPWDYZeaU5UQ350LnjuaUldcPBiebU5YdQroHLzY2lvr6ervDEBERB+sQAfdeAy8vb3pha3+u6IyPhruuNi7ikcZ1ioIp18DrK437ADfGn7ruHgcTg3c02i8h3YMnIiJihZREeOg6iO7Quvd36QSPjNPIhj/Se8KPRxvzYFujVzzMvL7997YrwRMREbFA/27wH/8LMntf2vuGDYCf3th+J/vbYXAy/HQC9E/y/z0ujKvfHx8P8TEBC80yIT1EKyIiYqWEGJh+LXx7CNa6YUdJ41d9RoTB0L7Geor9LiFJkfO6x8GjP4TtJUZduw81vqB+VATk9YeRac5asUEJnoiIiIVcLhjUy3jU1BkLIZedhLp6Y75erwRjmDAieO9i126EhUFOH+NRVQslR+H7U8b8vI6R0DsBesQbyxc5jRI8ERERm3SIMIZudaeewOsYCZf1MB6hwIE5q4iIiEhoU4InIiIi4jAaohURCQHjnrA7Aglmah/Oox48EREREYdRgiciIiLiMErwRERERBxGCZ6IiIiIwyjBExEREXEYJXgiIiIiDqMET0RERMRhlOCJiIiIOIwSPBERERGHUYInIiIi4jBK8EREREQcRgmeiIiIiMMowRMRERFxGCV4IiIiIg6jBE9ERETEYSLsDkD889jb9nzui3fb87l2WvG8PZ877gl7PtdOdtR1KNYzqK6t1B7rWscY51EPnoiIiIjDKMETERERcRgN0UpQKDsJO0ugqPz8tt+tgOQu0LcrXJ4CHdRaTVFyDHZ9B0VHz2979TNI6QL9usHg3hARbl98TuH1woEj4D7kW9e//wf0SYQB3SGjJ4TpNLvNPF7YU2Y8ihvU9R9WQUoipPWAy7qDy2VbiCKW0yFTbHXgCCzbYhwEL3T2CxsgugOMGAg3XA5RkdbG6BS7S+HjrUadX8h96J+/g10Q1xFGZsB1mUr0WsPrhS2F8OkO+O7Yxa/vLjUe7IDETnBtJoxMU6LXGl4vbNgLn+2Ew6cufn1HifH4ZBt0j4NxWXBVfyV6EhqU4Ikt6j3w4Tewahd4/di/ssb4Ev/6INw9wjgbF/9U18HSfFi/17/9T1YZSffXB+Cea4xeVPHP6Wr46wbYWuTf/kdPw5J82HwA7hkBSZ0DGp6jHD8Db6+DgjL/9v/+JCz80qjryVdDfHRAwxOxnc4ZxXJ19fCnz2Gln8ldQ0dPG8OJ24sDEprjVNUaQ4L+JncNlZ6AeZ/Cvu/Nj8uJTlXBy8v9T+4aOnAEXvwESo+bH5cTHTll1Je/yV1Du0uNdn3stPlxiQQTJXhiucUbjWGT1qr3wBtrfOfrBaNDRw8w9537bPt8rxfe/AL2H259GdV1MH+VcUCVptV7jPleh060voyKanjtH1BRZVpYAWF3u66qhd+vNHrwWqu8wjjxqakzLy6RYKMETyy1vbjl3qQX7255baQ6jzHcUldvXmxOs34v7Pyu+X38qeuqWnhngzGRXRq3fAcUtnDC4U9dn6yE9/LNi8uJPvi65RMOf+q67CR8tMW8uESCTcgleB6Ph+eff560tDQ6duzIkCFDWL16NRkZGUyfPt3u8BzN44Glm8wrr/QErC0wrzwzvfr+Yzzz9p3kf/sx//7atewp+cbSz6+ugw82m1fenjLYWmheeU5yohKWbzevvK8PBu+wuN3t+rtjsM7Ev/nPd8Phk+aVJxJMQu4ii2nTprF06VJmz55NXl4e69atY/LkyRw+fJhZs2bZHZ5p/vhIb4ZP+g2XX/vjc9u8Xi+/fyCeHz64gIFX3Wp5TLtKjaERM60tgNEZ1l0Vt2bbEua+c6/xxOulqvYMUZHRuFzGudKIrJt58q63efjmFzl09ABvfvorfnbnG9YE18DmA1BZa26ZXxTA0L7mlukvf+vdDuv3GEO0ZvrCbSyjYpX20q7NPqHz/rPMW/LMLddfwdyuWxKMxxjxFVIJ3sKFC1mwYAGrVq1izJgxAIwdO5bNmzezZMkS8vLyqK6u5sEHH2T58uWcPn2a3NxcXnnlFTIzM22O3n8VR0s4fbyUbqlDfLaf+H4fNVWn6DHgSlvi2nzA/DK/P2mse9Wnq/llN2ZU9kRGZU8E4NuijTwybxh/eXI/XTr3sCYAPwWirveUwYkzEB9jftktCeZ633TA/DK3FEFtPURatExNMNfvWR4vbD5ofrmbDsDNufYsndIe6r0xwXqMEV8hNUT77LPPMn78+HPJ3VkDBw4kMjKS7Oxs6urqGDhwIF999RXl5eWMGzeOO+64w6aIW6ds30ZcYeF0Tcny2X6kcAsx8T3o3LWPLXG1NEep1eUebXmfQHAXb6JbfErQfRl7vIGr6yKb6rqhYKr3qlrjJMNs9R77rqgNpvptqPyUsVyS2U5VGcPsdgvWem9MsB5jxFfIJHjFxcVs376d22677aLXCgsLycrKIioqik6dOvGLX/yC5ORkwsPDefTRR9m2bRtVVUF+aVsDZfs20qVnOhEdfBd6Oly4he797TmzqqtvfCFSMxyy7UCYT1qKTWM7zThxxpiDFwjBsIxHMNV7W66abYl9CV7w1G9DpQ6s64aCtd4bE4zHGLlYyAzRFhcbC6f17NnTZ3tlZSWrV69mwoQJjb5v3bp19OvXj44dOwYsNpcfYwM/ecv/SxjL9m3keNkeXn8oyWd7bXUFV/7oSdNj80eH6M7M+INvV0dLV7k19fpjF0xJ+f38/2bSsPvbEJ2v5b/1r67dRfmMzpnU5OsdIjqS2n2Q359rVl0n9ErnX3/7rc82s+r66f/8DTcsfroN0fnyt64baqneW2JWPQMkZ45h0lOrfLaZVdfTH3qYrStea31wF7CjXZtZ1+lX38mNM//HZ5tZdf2jm29lb/7f2hCdr/bYrtv7MSaUeL3+/a5CJsFLSjIaotvt9knm5s6dS2lpKbm5uRe959ixY8ycOZNnnnnGsjjNULY/nx9M/BWZI+/12f72k9n0sOnsqr62GjAaptl/0HU11o+v1NRWcbBsB+kpzzW5T2JcT+687ucWRmWorwlcb3Mgy/aHP/VupUDWR50NdR3U7brWWXXdULC165YE4zFGLhYyCd6AAQPIyclhzpw5JCYmkpyczOLFi1m2bBkAeXm+XeOVlZXcdNNN3HHHHdx1110Bjc2fbPzCM86mHD+0h+rTx+ib8y907priu/3Mcbpf4uRXf88U/PFf78ORivPJXVM/09mzbn9/5t889QgjFzzSxujOW/F8y/vsLd1CvafO1CEVs+ra44GfL/JdxNWsuv7j754h533zTnj8qeuGzKh3M9v0mRr4P4t8t5lV1x+99yf6Jf2p9cFdwI52bWZdl52AZz/03WZWXW9e+3cSY1sf24XaY7t2wjFGfIXMHLywsDAWLVpEVlYWM2bMYOrUqSQlJTFz5kwiIiLIyck5t29dXR233347aWlp7a/3bt9GIqJiLrq6qbRgHbFd+9Ap3r4JvIG60rVPYmDKbY67KJ/uCakkxHaz/sNbEBYGKQG6f6wddd1QsNV7TIfA3D82zAW9E8wvtyXBVr8NdYuDqAB0SXSKgi6dzC/3UgRzvV8omI8x4itkevAA0tPTWblypc+2KVOmkJmZSXT0+cmi999/Px6Ph/nz51sdYpuV7dtIj/5XERbu+6st3fOl7V3nV/Q1FnE1U9dY65ZIaaigZBPpKcE7FHFFX9jXhluUNaZfkv0HwmCs9ytSjTtZmOnyFOhgw7dzMNbvWWEuYx3GDa24r3JzruhrzxIpDQVzvV8omI8x4iukErzG5OfnM3z48HPPDx48yIIFC+jYsSMJCedPoXfu3ElqaqodIV6S0fe80Oj266aaN1m7tbKSISGmbfeQvNA1acYXv9WeuN28obNAuGoAfPiNuVfTjkw3r6zWCsZ6H5EGn+0091ZudtV1MNZvQyPTzE/wrkkzt7zWCPZ6byiYjzHiK2SGaBtTUVGB2+32ucCib9++eL1eKisrqaioOPdoD8ldsAsPMxYUNUu3zsGRdASjjpEwYUjL+/mrbxLk2nQXi2DXpROMNXEd9MtTIE2jXI3q0xWu6m9eeSMGQi8bhsJFrBDSPXixsbHU1+tu9Va6oi9sLWp+qNafyb5hLpg83J5hrPZiVAZsKzbuQNEUf+o6MhzuGm7M7ZPGjc+Bnd81v56aP3XdKQpuG2b/kGEwuzUPCsqaHwnwp667xsJNJp5wigQbfWWL5SYPb1sPRZgL7hlh7b0626MwF0wb1bYLLiLC4f4x0CPevLicKDIcHhxrJA2tFR1plBEf3fK+oSwmCh66Djq3YWnS+Gh4aKzR0y3iVErwxHIdImD6WLh64KW/t3NHI+HI7Wd6WI4UEwUPj4OhrZhh0DUWZl4PGb3Mj8uJEmLg326AjJ4t73uh3gnGe1NtuGCoPeoZ3/r66t/NeG+3OPPjEgkmGuASW0SGwx0/MBKPj7a0fO/UyHAYNsCYV9YpypoYnSKmA9w3Cr4phI+3tnx7rY6RxoUD/5IdmGUpnCw+2uhd2rDXuLK2vKL5/WOjYHQGXDfY6C0V/3XrDD+5AT7/Flbtavl+sgkxxlzJUemabiChQV/fYquMXsajsBx2lEBRORypMG62Ht0BkrtA367G8ggxHeyOtn0bmgpD+sC+72FXKRQdhaMV4PUaPX0pXaBfNxiSqsSuLVwuGD4Qhl0G35aC+xAUHzXmjHkxkro+icYUg+wUJXZtER5mJG2jM4zvjz1lRl2frAIXRo9/n67GlJDM3sb+IqFCX+MSFFK7anjKCi4XXNbDeEhghbmMpCKzt92ROF94GOT0MR4iYtD5jIiIiIjDKMETERERcRiXV3f6FREREXEU9eCJiIiIOIwSPBERERGHUYInIiIi4jBK8EREREQcRgmeiIiIiMMowRMRERFxGCV4IiIiIg6jBE9ERETEYZTgiYiIiDiMEjwRERERh1GCJyIiIuIwSvBEREREHEYJnoiIiIjDKMETERERcRgleCIiIiIOowRPRERExGGU4ImIiIg4jBI8EREREYdRgiciIiLiMP8fSDaqv5nf1n8AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 818.72x204.68 with 1 Axes>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ccx_circ = QuantumCircuit(3)\n",
    "ccx_circ.ccx(0, 1, 2)\n",
    "ccx_circ.decompose().draw(output='mpl')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For every Toffoli gate in a quantum circuit, the IBM Q hardware may execute up to six CNOT gates, and a handful of single-qubit gates.  From this example, it should be clear that any algorithm that makes use of multiple Toffoli gates will end up as a circuit with large depth and will therefore be appreciably affected by noise and gate errors."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Initial Layout <a name='layout'></a>\n",
    "\n",
    "Quantum circuits are abstract entities whose qubits are \"virtual\" representations of actual qubits used in computations.  We need to be able to map these virtual qubits in a one-to-one manner to the \"physical\" qubits in an actual quantum device."
   ]
  },
  {
   "attachments": {
    "mapping.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![mapping.png](attachment:mapping.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "By default, qiskit will do this mapping for you.  The choice of mapping depends on the properties of the circuit, the particular device you are targeting, and the optimization level that is chosen.  The basic mapping strategies are the following:\n",
    "\n",
    "- **Trivial layout**: Map virtual qubits to the same numbered physical qubit on the device, i.e. `[0,1,2,3,4]` -> `[0,1,2,3,4]` (default in `optimization_level=0`).\n",
    "\n",
    "\n",
    "- **Dense layout**: Find the sub-graph of the device with same number of qubits as the circuit with the greatest connectivity (default in `optimization_level=1`).\n",
    "\n",
    "\n",
    "- **Noise adaptive layout**: Uses the noise properties of the device, in concert with the circuit properties, to generate the layout with the best noise properties (default in `optimization_level=2` and `optimization_level=3`).\n",
    "\n",
    "The choice of initial layout is extremely important when:\n",
    "\n",
    "1) Computing the number of SWAP operations needed to map the input circuit onto the device topology.\n",
    "\n",
    "2) Taking into account the noise properties of the device.\n",
    "\n",
    "As we will see, the choice of `initial_layout` can mean the difference between getting a result, and getting nothing but noise.\n",
    "\n",
    "To begin, lets see what layouts are automatically picked at various optimization levels.  The modified circuits returned by `transpile` have this initial layout information in them, and we can view this layout selection graphically using `plot_circuit_layout`.  Let us pick the `ibmq_16_melbourne` device:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-09T13:50:51.640655Z",
     "start_time": "2019-08-09T13:50:51.520404Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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ecDy+ic31HWlqFt+l1fG4Gvge6c2F364nMab3xcbjL/Tdok3rsfgu7zke92Hj4tOeu/59IGoK2AScBtyb8pr1jwAfkP652YLNVhf+UCFEkNT9O/DvwYyacZKCa4Erk5Yhj0bgmhIng+oiWG74B8APginDd4/x9mqJLb8DLvZdXkurAFUWW6SCamYeAtj2/PAhrIk+7jrehWwBHsXWL6/oHyuYevUfQJpdsBoAz3e5IsV9lsTx2B27m0szKDUCZ1bDMrrB0rJzSb9++/our6S4z5I4Hj/EZqVLs37vApNTTs5iU2wpSdXEFommpoaCBB+qc4DCE2nG1wycU+kPLEAQFM+AyLP/hWnFAu73UtpfIsFF7duQWvDfhE3nWvFkACAoxz2kd342AN+uhmQg8G/AO5D8bj7QCJxR6WQAFFtKUFWxRaKpqYQAtjV7ngSpdGJpBE5K4fl4anyXR4ErSF6/VqwJ+7gqm1L0V8DdJK9fM/AK1bf86hzsTizphaUR+zv9KnGJUhKcR8dh51XSpKAR+E5wvlcFxZbIqjW2SIiaSwgAfJeHsYVaGqCkVfi2Bu/9TLCvquK7XANchmXzpdxdbAJWAR/zXcKnFOlGwbPis7EOU6UGpgZsmNOhSVcATFtQnkOx8pV659uAdSI8O41n62kKzqeDsPOreN/6/Nqw8/qy4DyvKootoao2tki4mupDkMvxmAD8CetRHHVN7o3YnAZn+y7FRw9XmONxIHZhGEm0+rVgd6bzgAuq7WKZy/GYjXVI6ku03uubsYD7PeDnMRYe6naORy/gm1jP/F5EW4CnCavjHN/l1jIWL7FgOetfAadjw9mi3Hw0YHNAnOa7LC5j8RJTbNlOpmKL5FfTCQFs6wx0PHAJdueyCTvB20dYtGfsdcAi4KdYD/NM/GGC5WvPxNYz3wXrqJQ7gcp6bOndO7ALZVUH284cj+FYs/+FdASm3J7e9dgF51rgl8FQukwI5gG4AKtjK9sfu43B9wZseKDvu7zfbQVMyPE4ALgYu6tuBobmbFKPddJ7A5scZ67vpvqcvmwKxJbc+q1HsUUyouYTgs4cjx2xmdn2p6M37bvAM9isXomHblWS4zEJq1vumPSZwDNZztodj57AXlj9bsz59QxsQpZMXEjyCYLvNLYfb/8F7Px8sdoeD8QRtBjsz/bDP0/Dzs3Xu79U6ekUW/6c86tPodgiGfGhSgg+LByv6x2I7xZf9Clrarl+tVw3UP2yrtbr92FXk50KRUREJB4lBCIiIqKEQERERJQQiIiICEoIREREBCUEIiIighICERERQfMQ1BzHoy85C+fU0lhhx2MK8FLn12qsfrkfyCm+y/KKFCYFjscOwPhOLz2Xs8m0Tj83+C6vlb9U6XE8dsKm921XrH5rfJd3y1+q9Dgeu9J16uJi9XvLd/mg/KWSclELQe05JveFYJa/WnFGpQvQzbJe39HYRaT9K1fn353fjeVKy0yi1++I7itWar5G9Prt2I3lkjKopQuFmDPzvHZIt5eiDIK548/K8/oOFShO6hyPYXlePiuodyb5Li8DSyNuPq+cZSmTO7FFp8I0AXeVuSzlEPWYLMlyS5YYJQQ1xPHoj63Xnivrd5ntPgLsmef1fHXOonz12AvYp7sLkrK5EbZ5DbK3MI7vshG4O8KmdwXbZs3TEGmdiSjHWKqcEoLacjzbrwQIcFqw3G7WFUps8rWKZFGhemQ9obspwjbzsrIKYB5R7qKz2PpBcEyilD3KMZYqp4SgthS6oIwGDu/OgqQtaDYvVL+jHa9Lx67McTxGAUcV+PWZGX9s8DrwZMhmWb7DvAeK3v1vAO7tprKUQ9ixWZSlJcelMCUENcLxGAScWGSTrN9F7w/sWuB3vYDZ3ViWcpgNBVtxdgM+2o1lKYdid5kvAs93V0HS5rs0AXcU2eSOYJuseo6ckT05Mtn6IdtTQlA7ZgH9i/x+tuPRp7sKUwZhCU3Wm9XDyp/1hO4mKPhIIMuPC9oVu4vOcutH2GODNuDmbiyOlJESgtoRdsEYDhzdHQVJWzBsMuyCeUQwJjxzHI+xhD/SOSPLw0d9l7eBvxX4dS3cYT4Aecfgvw882M1lKYdCx+jR4NhKDchsgJEOwbC74yJsmtW76IOBcSHb9ABO7YaylMOpENpHYDxwUDeUpZzy3Skv9d2izdGZ4LtsBm7N86tbg99lmu/yIrAsz68y3fohXSkhqA0nAX0jbHey41FX7sKUQdTm8qw2q9d6/drdkue1WmgdaJfv4lhLF8x8x2p+t5dCykYJQW0YjU160v6Vq/31hcCUbixXWvoRrX5rHI/B3VmwpILyria8bndBJpO5bXyXVXlerqWE4C95XlvQ3YUoo+2OVYFjKhmltQxqUO58+LU01z/Udv1quW6g+mVdrdfvw04tBCIiIqKEQERERJQQiIiICEoIREREBCUEIiIighICERERQQmBiIiIAL0rXQAREZFq4Hj0xSYA2+y7bKp0ebqbJiaqAcGiN0cB52Lz/k/K2eRp4D7gWt/lze4tXXKORz9seeCzsGWQcxcxWgDcDtzou3kXmKlqwVoUX8CmoD4i59fvAouxKXDn+y7N3Vu65ByPCcCXsPU2Dsz59evAE8D1wCO+S2s3Fy8xx2M/wMEWqNo759d/x2YI9X2Xpd1dtqQ+hLFlNNCCLUVeDywlw7ElLiUEGeZ49ABOA34BDAEGUniRnGZsqdK/Av/iu7zRHWVMwvHoDXwTuCx4qdi0xI3YI7A/Ahf5LvVlLl5ijscQ4Grgc0ArMKDI5huC7z8Gfua7bC1z8RJzPCYCvwMOw87LfgU2bQMasAD8DeDmLCyH7HgcBPwXsBtWt14FNm3BPn+vYJ+9Rd1TwtIptnSRudhSKiUEGeV4jAD+gAXbgTHeuhX7AF/ou/xXOcqWBsdjCrZ63C7Eq98mYCNwpu/ycDnKlgbH4yjsrn8Q8dYoaABWAKf4Li+Xo2xpcDy+DFyDXSjjPJpsxO6oz/Fd1pajbEk5Hn2AnwFfBvrHfHsTlkR803fZknbZ0qDYUlAmYksSSggyyPEYgzWzjiXaKof5NAK/BS6ptrsxx2N/4BHsYllqx9cmYI7vVt9qc47HWcDviX8xadeKBaYjfZdnUitYCoI7y58BXyFesO1sM/AOcLDv8s+0ypaGoIn5Hmwp6mItOsU0YZ/fE6rtEZBiSyRVG1uS0iiDjHE8BgCPAjtT+gcWLJidD1ySRrnS4nhMwj6wQ0h2fvYHrnM8jk6lYClxPI4hWTIA9ncZAjwc/L2qyaXAVyk9GQA7r3cGHnW8RH+nVAXJzjySJQNgx/5gYG6wz6qg2BJZVcaWNCghyJ6rsA9snxT2NQC40vGYlsK+Egs6MM0j2cWks/7AvKDTXsUF5ZhLsmSgs0FY/aricxycR98l2cWyXR/sPP9pCvtKy1nA0aRTv/7AMcE+q4ViS3RVFVvSUhWBRKJxPA4A5pDeBQXs+XW13Kl8EZhK4c5ZpRiAdYyqBh7pXEza9cL+Xl9McZ8lCc6fucTrDxGmP/DF4LyvKMdjOPCfpHdBIdjXfzoew1LcZ0kUW0pSTbElFZqHIFu+TU7APWo6HDoVxo6Anj3hzkVwV9CH+YDJMOsgGD4YevSAtfXwl2Ww4Lku++wBjAc+gfUSDuV4LMSGws0HFqUxVCwIGleSE3CL1W/GFDhiGowZBn37wJr18OCz8NgLXXZdB5zpeFycVic1x2MqNlRpNnC077ImwntGAmfQ6fgVq9u4kXD6YTBpDNT1hTX1cNl1eXc9EPiu43FtlOe1wSOLy7Fjd6vv8k7YeyI6DDuPtgX/YvUD2H8yfPogGDUU1jfCgmVw//Y9IvoF5T0ljUIGfQCOxo5di+/iRHzreYRcTHYaDrMPhV13gj694MW3YO4CWLeh2LvoFez7miiFcDz84D23AA+n2Adhu9iSa/woq98uO0Kf3gXjSWexY0sYx2Nn4GTs+P3Id3kwwnvyxpbO9hgH3zw1/++ufwAefyHvr1KPLZWmhCAjHI9R2DjuLq06u+wIDc2wbiOMHNL1PcOHwNoNsPxtGD4Ipu0KZx8J766Dl1d22XQgcDHRP7QTsQvAhcA7jsdt2AXm0QTD4Y7Anu11Uax+e+8CI4fC31fA4AH273OPhQ1N8NzrXTZtxe4QSmp+DgLKvnQkAXuVsJs5QTm2KXrsBsPQgfDmKgtWIXbA/n5/iVCOXsG2RwC/djwepyM5eCPC+wu5mJyAW6x+u+4EXz4BNm+Bp5fDXuPh1E9A02b46/NdNu0JHO94jPJdVpdSsODZ+CexYzeLjvPstojv74Gd6wVbd/r3g2+cAsMGwbLXYGuLJTw7DoV/+yPFMrUBwEWOxy8idsAbgV0QzwPqHY+7sON3v+/SGKU+uQrFllznz7LjuHI1vPcBTN+9YDzpLG5syVe+iXR89g7u9KurIu7iCPLEls7e3wAPLen4d78+8Il97OdVxWcfSBRbqo0Sguw4DOt93SWLv+5++97+Ye3sgWfsq92VZ8O4UbZdzni1HsBMx6NHCb2CxwJfC75WOx63YwHqkZjDqo4jTwZfrH6PLIX/fghagsvsxafClHEwdcJ2CcEAbNKfyB/a4CIwg45AtGvU9xZwMjkXlGJ1e+51+9pvt0gJQfsFL0pCkOuQ4Otqx+MZ7NjN912WR91B8LeaSc449WL1O+4A6NnDWg0efBb2HA8XzYbjD9wuIQA77z+BDRWLWqbBwKewY3cCyR7VTIDiz4p338mSgTXr4Td32mvfPdvuqqfvDs++UnT/w7A76bgT+wwBzg6+Gh2Pe7Dj92ffpXi7RFd5Y0tnvXraTQWAfx+8sxa+fRZMHA0jil5qS4stjscedHz29o/6vgLyxpbOVq+HeQs7/n3kvvZ9xSp4pXgbWuzYUs2UEGTHDEp4fjlxNHxsT7tTGTfKPshLX8u76SCg1fESlXEUNmObA5BwX6FWrOr6717B/c37G/NufrDjlWUI1Opy1zOCnsCljselCfezf/D1o3LXacIo+77iva7fRw6xu+2mrg3hQ4D5ZSjTyWmdE1ta7PvAOqtDS6u18IA9/glJCPoDKxLWbwBwavCV+mevpRUeXgrHfBS+dJzdNU/YEd5aDUteDX17GrEln3vLdZ4euZ99f+jZSJtPK/FmquooIciOfSmhQ8zYEXD0dPu5tdWa1zdtTrlkVeCY6bD7WHjvfVi4/R2mVJkhwf36pqANqblTW9LQAdslBFVv+Ur4x9sweWf48ZyuvxuaZjfEClryKkzfzVo9xo+yxyJLXq29eDJtEoweBh802OOsCPpgLUjvl7Vg3UAJQXaU1Hv78RfgiRfsWfu/nGAZ/sYmuOfptItXObM+Bp8+2O5arrm19gJULapvtKbmumCAW79Oo97Xl/QkvLJa2+Dq+daRd6cR1pFwj52tdW5DU6VLl9zAOrjgJHu2ftVN1tLonmydQjc0Fu1YmDntN1ALlnU8jgzRQuFpuTNFww6zI3aY7BcE2zbsGdkbQRP76IoPckpHD+CzMy0ZWLHKAlVIj26pEm8F3QMnjgm+j7bva+uz1zrQ2ZMvw+2P2yOCqRPstRczt+TP9kYOsXiytQXeeA8am60zIdjoilqx8wjYawJs3hqrpbE3Nnth5qmFIDsWYxOZdDlmh+5tzZTtz2Sn72Yf3iWvwqmH2nC11ethh4HWFAb22CCPZmCS7/JuWEEcjxVYR6ti/k7QQQ14Puz5WjCU8bDc14vVb+JomLmvPQp5a5V1SANrKfjLsu3+iw98N3y8t+OxCzbEbTbW2S5sDPWoiMMOPwCGRq3bP9dZfYYHS64MqoPzghEUtzya979Y6LvbrZSYrxzHAfeGbLYZeAA7dnf6LutC9jkWeJWcVqxi9btvsY16mfWxjiAMcO/ivP/FVmyI2ZUh5egFHIodu1OwSXaKuc13w4czOh4nAv+PkJ7q3zjFWt+ammGfiTby5bnXivbAb7ceONt3+XOEstyKdVAt5m2sA+Z84G++S0vIPr+HLfJT8Hrw7jqr26D+cOEpFlNmTLHf/SN84Gqk2BLM9fBp7PgdS/hsicf7LveF/eeFYks+7a0DT75k9Y2owXdZH3nrKqaEIDuexloJusO29wAAAAbLSURBVASlyTvDIVM7/t3+fG9NPbzwJnxkkjVdbt5qLQQLlsFT+ZfEaYqSDIRYQkcv9ZdivnchdgHuck4Wq9+woNdzz55w6D4d27y8Mm9CsP0refguK7DJRn7heOxEx5jnI0jWoraMnKBUrG6NzV1/V9fX/r2mPm9CsBX7+yXRBF16qUde0c13ecfxaCYnIShWv7sWgX+vJQQzpsD6Bpj/N1iYv+m5ATv/w8rRgv0dFjoeLh2jRE7FhsqW6hkiTOW7cjUcuAcMqLP63Pu0jaKIoC74P5J4nY4E/KmYc4PkjS2dbd4Kv7oDTjrYOhNO2NES778+D4vDn7NHii1B4nkDcEOwEuiJ2PE7nmQTJuWNLbkG1cGMPe3nzkMQI4gUW7JACUF2LCTPlKLXP2BfBUUbiNYC4XcnBSyiYxx7/vEL0dyNjfXuck6G1a9o3Ts0YNOWxhIEsd8Cvw3Gan8GC1BHEX9617lYD/5tXczC6hajB3UzpR2/Ddjf/RbgvlLHsQfuBs6kU8fXsPotXh7pYgJ2MY41jj24IC4CFjkelwDT6RjGNiXmvt51PN7GljkuaO5C+yrBWyUu4vQyduzmA0sT9HLPG1tyvf5P+EWkmRu6KCm2BAnpn4A/OR4DsaGDs7EkodhSxfnkjS25Nm6Cr/0mbklLiy3VSglBRvgu9Y7HTdiY47SPWzMRZ0oL/A0Ltrf5LuENotE8jTV17pHS/jprX8u8ZMGkONcC1wbzl8/CAlTUO7E/AlcnKUMRK32XpyJuuxG7C5sPPOS7bEqpDNeQZ66FFGwF5iVZgz64UD4LPOt4XAHbZpqM0xHsKqyOg0otRwEbiT7BDsCLwFLs+L2QxlC3Kost2/FdGghaPxyPOjpmmsw/wHh7VR1bqomWP86QYB3vJaQ73/hW4Enf5dAU91kSx2M2cCPpzhffCPyH73JxivssieNxNbYscJoXzQbg874bfdKecnE8HsOa6dO8qDQB0303dy6t7hXcpb4BjEx512uAicFFr2IUW0pSNbElLRplkCFBUPwRpBo8mrE7g2pwK9Y0nObAwbXAFSnuL4krINU5zzcDC6ohGQicDanNrQ92nv+w0skAbLtL/RwljPYpohHrTFjRZAAUW0pUTbElFUoIsucnwPOQSlNvE/CVoCNdxQXNn+diE3wkXjAJC24np9gsnojv0oQ1q6cRdFuBddic9lUhWAvhq6QzBGsT8BzxmtPLyne5H7iedI5fA3C97xKtF0z3UGyJrqpiS1qUEGRMsHjQsdgHN0ngbQQu8t3qev7lu6zCegSvpvRsvg37wJ7ou4l7b6cqKM+JWPlKfV63Gfv7HFLqgj/l4rv8AVvMJsmddBN2fn8ywWJZ5fJ14GaSJQUNwE3BvqqGYkskVRtb0qCEIIOChUsOA35P/A/uJuzO8lTf5T/SLlsagtEK+2K9n+MG3gZgOXCQ77Ig5aKlIijXQVg5S6nfQmBf3+X1sI0rwXf5LTbUbx3x7zabsPP6sJgL9HSLYPTCHGzcfiMUH+OfoyV4z2XAF9NYNjxtii1FVX1sSUqdCjPO8fg41nt9GtaZq9DwoY1YAngjcLnvUnxRzyoQrKJ3OvZsc0esM16+JLYNq98WbNWxa2KutFgRjkcfbDjUJdhxG0T+iZBasQvJKuBy4KYsLKQSjMb4EfAFrA6FeuhvwTqgLQMu9l0e654SJuN47Ir1oP8kdg4W6pDXhB3X+4ELEw7P7TaKLUBGY0uplBDUCMdjT+wEPwLYB+tN24pdRBYBDwI3V0MHpriCD+8h2DwAh2PDh/phF5E3gUeB+7AJdaqtiTmU49EbW6r3OGyZ3wlYAG7G7kgWAncAj2chEcjleAzCWgyOwVpGdsSCbwPwP8ACbGhhxTsPlsLxGA2cBRyJzTXRvlTyB9iEQ48A/993ea8yJUxGsSW7sSUuJQQiIiKiPgQiIiKihEBERERQQiAiIiIoIRARERGUEIiIiAhKCERERAQlBCIiIoISAhEREUEJgYiIiKCEQERERFBCICIiIighEBEREZQQiIiICEoIREREBCUEIiIighICERERQQmBiIiIoIRAREREUEIgIiIiKCEQERERlBCIiIgISghEREQEJQQiIiKCEgIRERFBCYGIiIighEBERERQQiAiIiIoIRARERGUEIiIiAhKCERERAQlBCIiIoISAhEREUEJgYiIiKCEQERERFBCICIiIighEBEREZQQiIiICEoIREREBCUEIiIighICERERQQmBiIiIoIRAREREUEIgIiIiKCEQERERlBCIiIgISghEREQEJQQiIiKCEgIREREB/hdKLAY7r3E2yAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 648x216 with 1 Axes>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "backend = provider.get_backend('ibmq_16_melbourne')\n",
    "plot_gate_map(backend, plot_directed=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Layout using `optimization_level=0`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-09T13:50:53.338042Z",
     "start_time": "2019-08-09T13:50:52.836642Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x216 with 1 Axes>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "backend = provider.get_backend('ibmq_16_melbourne')\n",
    "new_circ_lv0 = transpile(ghz, backend=backend, optimization_level=0)\n",
    "\n",
    "plot_circuit_layout(new_circ_lv0, backend)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Layout using `optimization_level=3`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-09T13:50:54.050445Z",
     "start_time": "2019-08-09T13:50:53.775606Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Depth: 13\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 648x216 with 1 Axes>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from qiskit.visualization import plot_circuit_layout\n",
    "\n",
    "backend = provider.get_backend('ibmq_16_melbourne')\n",
    "new_circ_lv3 = transpile(ghz, backend=backend, optimization_level=3)\n",
    "\n",
    "print('Depth:', new_circ_lv3.depth())\n",
    "plot_circuit_layout(new_circ_lv3, backend)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let us now execute this level 3 circuit, and get the counts.  Note that the circuit has already been rewritten to match the target backend.  Therefore, the circuit will go unmodified by `execute` and be directly packaged and sent to the device."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-09T13:51:39.195545Z",
     "start_time": "2019-08-09T13:50:54.994602Z"
    }
   },
   "outputs": [],
   "source": [
    "job1 = execute(new_circ_lv3, backend)\n",
    "job_monitor(job1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Specifying an Initial Layout\n",
    "\n",
    "It is completely possible to specify your own initial layout.  To do so we can pass a list of integers to `transpile` via the `initial_layout` keyword argument, where the index labels the virtual qubit in the circuit and the corresponding value is the label for the physical qubit to map onto.  For example, lets map our GHZ circuit onto `ibmq_16_melbourne` in two different ways:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Good choice"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-09T13:51:53.183029Z",
     "start_time": "2019-08-09T13:51:53.011406Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Depth: 10\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 648x216 with 1 Axes>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Virtual -> physical\n",
    "#    0    ->    11\n",
    "#    1    ->    12\n",
    "#    2    ->    10\n",
    "#    3    ->    2\n",
    "#    4    ->    4\n",
    "\n",
    "good_ghz = transpile(ghz, backend, initial_layout=[11,12,10,2,4])\n",
    "print('Depth:', good_ghz.depth())\n",
    "plot_circuit_layout(good_ghz, backend)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-09T13:52:57.307300Z",
     "start_time": "2019-08-09T13:51:53.267947Z"
    }
   },
   "outputs": [],
   "source": [
    "job2 = execute(good_ghz, backend)\n",
    "job_monitor(job2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Bad choice"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-09T13:52:57.671042Z",
     "start_time": "2019-08-09T13:52:57.391975Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Depth: 38\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAgQAAACxCAYAAAC7mqV5AAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjEsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy8QZhcZAAAcH0lEQVR4nO3de5gdRZ3G8W/NTCb3REUSlmgwqKiBxbiRS2IgDIhGdAUFITECSbBRAU0LCIIKD+xKvAVbfERJI5ddhXDTILJcXLMEdYlc1kQRdxGFGAyEEAJJ5pqZqf2jejAOzLl1dbrP4f08j488kzl1qs/U+fXb1dXdxlqLiIiIvLI15d0BERERyZ8CgYiIiCgQiIiIiAKBiIiIoEAgIiIiKBCIiIgICgQiIiKCAoGIiIigQCAiIiIoEIiIiAgKBCIiIoICgYiIiKBAICIiIigQiIiICAoEIiIiggKBiIiIoEAgIiIiKBCIiIgICgQiIiKCAoGIiIigQCAiIiIoEIiIiAgKBCIiIoICgYiIiKBAICIiIigQiIiICAoEIiIiggKBiIiIoEAgIiIiKBCIiIgICgQiIiKCAoGIiIigQCAiIiIoEIiIiAgKBCIiIoICgYiIiKBAICIiIigQiIiICAoEIiIiggKBiIiIoEAgIiIiKBCIiIgICgQiIiKCAoGIiIigQCAiIiIoEIiIiAgKBCIiIgK05N2BXckYY4ApwDuA3ZMfbwJ+AzxurbV59c2HIKIFeCvwdmAc0Af8FXgoDnk6z775EESMAPYHpgKjgB7gMeA3ccgLefbNhyBiPPBPwBuBVqADeAT4bRzSlWfffAgi9gCmA5OAZmArsBb43zikN8++pRVElKwtcUhd1xZjzJC1xVpb97VFHFPn+8CKGGPeBHwaWIgrRL38LQwN/HcfcDXwbWvtY3n0sxZJIToQOAv4IG4nCW6bLLADGAFsAS4DroxDNuXQ1ZoEEc3A+4BzgIOBTtzMVjPQj/v7jQL+DHwNWB6HdOTT2+oFEaOAubjt2xsXAlpw29iH28aRwGrc9t0Rh/Tl09vqBRG7Ax8HPgO8GugChgEGXgwBrcBPgKXA/fW08wwiqqotcUjd1JbkAKqq2mKtrZvaIi/V0IHAGDMa+AawAFdgW8u8pAdXgK8BzrbWtmfZv7SCiD2Bf8PtKEdS/hRQJ+6L/EXgW3FIf7Y9TCeImAbcCOwBjK3gJdtxf8OT45CfZtk3H4KIDwDX4sblmApesg14Gjg+DlmTZd/SCiKagMXAv+J2/iPLvKQfNz5XAyfFIRuy7WE6QUSq2hKHFLq2GGNS1RZrbaFri7y8hg0Expi3Af+JOyopV4wG68Sl3ndba//gu28+BBHvw+0sh+OOuKrRjpuKnhOHPOe7bz4EEWcB/4I7AjFVvrwDuAVYVMSp6CBiGPB94Fjc7EY1LO4o+0txyFLfffMhiHgNcBfwNmB0lS/fAXQDH4lD7vTdNx+CCC+1JQ4pZG0xxnipLdbaQtYWGVpDBgJjzFTgv3HnuqrdmQywuHOcM621j/jqmw9BxD8DN1B9MdpZD/AX4MA4ZIuXjnkSRFyIm0Kvdme5sw5gJXBMkabYk3UeK4A20m/fV+OQi710zJMg4tXA/cBkyh81l9IJnBCH3OalY54EEV5rSxxSqNpijPFaW6y1haotUlrDXWVgjBmL2xGk+cKSvHYcsDJpsxCSo5PlpPvCgivWrwduTdYhFEIQcSzpwwDJ6w8HlqTulF9LSB8GSF5/bhDx4fRd8iMZRz/Bjas0YQDc+F4eRLw1dcc8CSK815akzUJIZlW91pZkHYLUiYYLBLjFLeNJ94UdMPDF/ZaHtlJLFtjdiJtG92E4blX7xz21l0qyAO37pN9ZDhgFnBFEHOCpvVSCiAOB0/G7fVcFEa/11F5aAW6V/XBP7Y0AbkzGfRE0bG0xxjR0bZHKNFQgMMbsDxyPv0ENLi2fkLSdtxNxlzb5/LuNBr6ZLJLK25dJf3Qy2AhcyCiCK/E7NsF9Xpd4brNqyfi5lOrXDJTShLvy4kSPbdYkiMistiRt5y2z2pIs7pY60FCBADiTMlOVw4cP57LLLmPjxo10dHTwy1/+kgMPPLBcu61A6KuTKXwevwV3gAXmZdBuxZKp04+Rfqp5MAO8MYh4h+d2qxJEL95fwPcUaivwsQJMPX8UMrlccDRwbgbtVqtsbalR3dSWxYsXs3btWnp7e7HWcuGFF1bSbu61RSrXMIHAGNMKnECZmy1FUcSnP/1pNm7cyIoVK5gxYwY/+9nP2G233Uq9rAWYl7xHLoKIfwRel1HzY8i/KB0LmS3+Gw58KqO2K/VJ/E2lD9aH+/zytJjKLp2sxeuDiP0yarusIKKi2lKjFmBe8h65MMZUVFumT5/Oc889x/r166tpvgi1RSrUMIEA2A93ydKQdt99dxYtWkRfXx9HHHEEH/3oR/nhD3/IuHHjOOOMM8q1vwPY11dnazAj4/b3ybMo4RbaZbVDaQZmZ9R2pQ5L+pGFMUn7uUjGzT4Zv03W47+UsrUlpbqoLSeddBJtbW2sWVP1LTD2yfNgSirXSLcu/ifKBJx9992X1tZWHn/8cTZtcjfUevDBBznxxBOZNm1aycZbWkeNPfhD3/qfIPLW36IZBnQ38PbtE0T1cwe8GpwcRJycdycyMhpYFkQsy7sjGRkL5FZb3nTASTz2wL9l+RZduMDzmyzfRNJrpBmCPSizIG3ixIkAbN++/cWftbe7G4btscceJRvv3dFF57aNKbsoIlIs7VuqOgVQi35gYtZvIuk1UiAwlFmwtXGj26GPGfO3memB/3766TLP57AWdDdOEWk4u2TirJH2NQ2rkf5Iz0HpJ8I98sgj9PT0MHnyZCZMmADAAQe4S9TXrl1bsvHmYSMYPqrkwkMRkbozYkzmB+8G2Jz1m0h6DXPrYmPMTOAO3M0+hnTFFVdw6qmn8vDDD/Pwww9z/PHH097ezt57782zzz5b6qVbcffnvs9jtysWRHwG+Cr+r2Mf0AuMz+tJgUHETcBxGb7FujjkDRm2X1IQsQ53O9+s3BSHHJ9h+0NKntj4AtmtSeoEzo1Dvp1R+yUFERXVlhS24p4rkkttMcZUVFtOOeUUZs2axeGHH87kyZNZs2YNa9asYcWKFdx6662lXtoLjLfW1s1TSF+pGmmGYA0V7CwXL17Md77zHSZOnMgxxxzD6tWrec973lMuDJC0XXoaIVv3k+1K5/U5PzZ4FWT2/hbyKbY7uY/s5mY7cJ9fLpJx82SGb9ELPJBh++VUVFtSqIvaMmvWLBYsWMDkyS7XTps2jQULFpRdkA2sVxioDw0TCJIBdzdlim5XVxdnnHEGEyZMYOTIkbzrXe9i9erVZZsH7sp5UN+Pe7xvFjqAKzJqu1I3kd14bAfijNquVJz0IwtNuM8vT1fgjuSzsA03/nORBJ6ytaVGFrgr5zBeUW1ZuHAhxpiX/O+iiy4q9bIi1BapUMMEgsQ3yKbodkC+j5qNQ/qTPmRROJrI+fa+cchG4E6yuTnRFuC/Mmi3GiuB5zNotw+4Mw55JoO2q3El/u/CCG68X5qM/zw1bG2x1jZ0bZHKNVoguBf/U+s7gF8nbefte7hztT61A0vjkLLnTHaBzwHdntvsAE6Pw3zvQZC8/2n4L7rduM8tV8n4uRT/2/cCbtznTbWleu3AUmttEWqLVKChAoF1KyRPxO9OpRs40RZg9WUc0o67haqvqdl+4CngYk/tpRKHPAZ8AX9HYl3AT+OQ2zy1l0rSj//A3/hsB76QfG5FcBGwAbwdzXcAJyTjPldJoMuktuQdVgGstQ1dW6QyDRUIAKy1G4Bj8HOk0gEck7RZCHHIL4Avkn77+nFT2HPikJ7UHfPnMuCnpN++buAxivf41UXAH0m/Y+nAfU6Xpe6RJ8k4moMbV2lDQQfwpWS8F0Ic4r22JG0WgrXWe22x1haptkgZDRcIAKy1PweOxh1B9dbQRG/y2qOTtgolDrkUOA+X5ms5uugCngEOikP+5LNvaSXniucDN1N7YWoHfgfMikO2+eqbD0l/ZuH6V+uRbztuEeH8Apxb/zvJeDoYN75K3hdkCBY3rs9LxnmhxCHeakvSVqFYa73VFmttoWqLlNcw9yF4OcaYycB1wDQqf2zwdtw9t+dbazO/p2caQcQBuB3Da6ls+/pwR6Y3AIuLtrMcLIg4FrcgqZUyt6VO9OAK7sXAN+Iws6cnphZENOPO/V+Ae+hRJQ9/6cRt46I45EcZdi+15HHMlwHH4y6rq+Tgox3YBHwkDnkww+6lFkSkqi1xSKFrizEmVW2x1ha6tsjLa+hAAGCMMcD7gHNwRy5duAE+cBOVgcQ+AlgNfA24owhrBioRRAwH5uKeZ74XbqHS4BuovIB79O6tuB1loYvtzoKI1+Cm/c/kb4Vp8FMRt+J2OFcC34pDnthlHUwpiHgD7tHBH8dNtQ7+2w1cDtaOW7QXxyFbdlkHUwoi3gmcjTuq7gbGD/qVrbgHaz2BuznO8jj0vrA0E0HEy9WWwdv3AoNqSxHWDFTCGPMytcWMG5g4aGoZTn9v99/VFmtt3dQWeamGDwQ7M8ZMAN4JTAf+IfnxU8BDwIPW2rwv3UoliJiC27bB16S3AQ8VfUaglCCiCXgbbvuuHfTPBwK/rZcdyctJgt3+vPR6+5Nx4/MPRTs9UI1kxmA6L7388yO4sfn4ru+VP0HEQG25fdA/vR94sACXhaZijJkCTH/7u8+7qat9M01Nwxi72xTu/8nZbcBDmhFoDK+oQPBKMfgxv3GYyfXhuWnk7WvkbQNtX71r9O17pWvIRYUiIiJSHQUCERERUSAQERERBQIRERFBgUBERERQIBAREREUCERERAQFAhEREUGBQERERFAgEBERERQIREREBAUCERERQYFAREREUCAQERERFAhEREQEBQIRERFBgUBERERQIBAREREUCERERAQFAhEREUGBQERERFAgEBERERQIREREBAUCERERQYFAREREUCAQERERFAhEREQEaMm7A+Jff18vvTs6aWpqpnnYSMDk3SURAKy19O3opL+/j5ZhI1EJkiIxxrQCI4Aea21X3v3Z1Yy1Nu8+SErGmCbgCGABMMM0tUwxGCyW5uZWend0PADcCVxprf1Lnn2tRRAxHDgWmAdMB/5h0K/cA6wAro1Dnt+1vUsviHgVcDJwDHDYoH9+CngQWA7cEod079repWeMmQx8HJjTMmzUAX19PQyMT9vf+zhwH3A1sNJa259rZ2sQREwDAmA2sO+gf/49sAqI45A1u7pvaQURf1dbgCmDfuXF2hKH1F1tMcYMri0TgT6gGdgKrCGpLdbauqst1VIgqGPGGAN8BPgmMA4YzdDTAd2ABe4FPmGtfWJX9DGNIKIF+BxwXvKjsSV+vQN3CuwHwFlxyNaMu5daEDEOWAp8DOgHRpX49W3J/y8Bvh6H9GbcvdSMMW8ArgAOxY3L4UP8qgXacQX4s8BNtg4KUxBxMLAMeCNu25qH+NU+3PfvMeATccjqXdPD2gURNdeWOOSJXdHHNIwxNdcWa23ha0utFAjqlDFmN+DfccV2dBUv7cV9gc+01i7Lom8+BBFvAX4E7EV129cFbAfmxiE/z6JvPgQRR+CO+sfgpigr1Q6sAz4ch/xfFn3zwRhzKnApbkdZzXmBDtwR9YnW2s1Z9C2tIGIY8HXgVGBklS/vxIWIz8UhO3z3zYcgInVtiUMKW1uMMalri7W2sLUlDQWCOmSM2QM3zbon0FpjMx3A5cA5RTsaCyKmAytxO8taF752AovikOXeOuZJEDEP+D7V70wG9OMK0+FxyEPeOuZBMmv1deCTVFdsd9YDbABmWGuf9tU3H5LTV/8BHEzpGZ1SOnHf36OKdgooiPBaW+KQQtUWY4y32mKtLVxtSUtXGdQZY8wo4BfAJGr/woIrZqcB5/joly9BxBTcF3Yc6cbnSOCqIOLdXjrmSRBxJOnCALjPZRzw8+TzKpJzgU9RexgAN64nAb8wxqT5nLxKptFvIF0YAPe3nwEsT9oshCCioWuLMcZrbTHGFKq2+KBAUH++ivvCDvPQ1ijgQmPM/h7aSi1ZwHQD6XYmOxsJ3JAs2std0o/lpAsDOxuD275CfI+TcXQB6XaWA4bhxvnXPLTlyzzg3fjZvpHAkUmbReG9tgQRhagtycJr77XFGFOI2uJLIQqJVMYY805gEf52KODOXy9PpnrzdgowlaEXZ9ViFG5hVBFE+NmZDGjGfV6neGyzJsn4WU516yHKGQmckoz7XAURrwG+h78dCklb3wsiXu2xzZoEEZnVloLMgjR6bfFCgaC+fIEyBfeaa67hySefpKuri02bNnHHHXcwbdq0Ui8xwOuBQzz2s2pJ0bgQvwUX3Oc1N1kolZsg4rXACfjdYYL7vC4oQNE9FDeOhuzHsmXL+P3vf8+2bdt49tlnuf3225k6dWq5docD53vsZ60W4ndnMqA5aTtvZWtLDQpRW5KwWnFtmTt3LtZarLV885sl9/cjgLnJAu+GoEBQJ4wxuwNzKPM322uvvVi1ahVXXXUVmzdvZs6cOaxYsaJc86OBsz11tVaH4c7tZaGf/I+iFyX9yMKreOn9C3a1sylTcIMgYOvWrVx//fVs3bqVo446irvuuovhw4e6GhFw4/19yfjPRRK2zsTv7M6AUcBZeQa6IKKi2lKjuqotkyZN4vLLL2fHjoovAClCbfFGgaB+HIpbfV1SW1sb8+fP57TTTmPePHd68nWvex0tLSWv/DJAW86nDebgf3ZgwCjcTX/y9CGy2aGQtPvejNouKxk3bZS5JebMmTOZMWMGp556Km1tbYAbmxXMEvSQ71HmZMh0HcqrcUfSeamottTIAG05z2BVXFuuvfZaNmzYwC233FJp20WoLd7ovqH140AqHNSnn346U6dO5YgjjgBg6dKl9PaWvo9N87CRY477/B/6gyh1P4tqRhAV6xIoj5qAc4OIc/N48xO+9AQ3f+Vt9O3oLPl7991334v/3drqFrH39fXx1FNPlX4D0zRu/7azbmngsTkSWNfA2zcGyK227D75IDb95ddlfy8MQ2bNmsVBBx1EGIbVvMX+xhhTtMu3a6FAUD/eToXnMI877jgOO+wwANavX8+vfvWrsq9pam7lhU2PMvY1e6Xpo7wCvbDpUZqbW8sGggGjR4/mmmuuAVxYffrpMrcasP1s/uvalL2UV6ptm/9c9nf23XdflixZwgUXXMDatVWPtWG4GaQtNXSvUHTKoH5UvOCnra2NESNGcPTRR7Pnnnty8803s9depXf0BujvzWrWUBpZf293xVMvu+22GytXrmTmzJksW7aMc8+tbFKjr7dQ9++ROtLfX349wLHHHktrayuzZ8/mtttue3F29YMf/CCXXHJJuZf3MfRtueuKZgjqR0e5XxgxYgQ9PT309/fT3d3NnXfeyfbt2xk/fjxTpkxh3bp1Q77WAi2thbkHjNQR90TN8iZPnszdd9/NW97yFpYsWcL551d+8UBLa1bLL6TRNTWX31cbY2hqauKoo476u5/vvffezJgxo9zLW3B3L6x7unVxnTDGXIx7EMeQIW727Nlcd9113HvvvWzZsoVDDjmE/fbbj2eeeYY3v/nNbN1a8pkc3cAUa22ZE7rZCCJW4RY3ZeX5OMzveu8g4nlgfIZvsSoO87nSwBizJ/AnysxiPfnkk0yaNIl169bx4x//+MWfX3fddTzwwAOlXtoLXGKtvdBHf6sVRHwA+CHZXQXzAjA/Drk9o/ZLCiLK1paUuoEpcUgutcUYU3Vtufrqq1mwYAFRFPHZz3623K8/b63N/V4SPmiGoH48gJslGLIobdiwgUcffZQjjzySsWPHsmnTJm688UYuvvjicmEAoDOvMJBYBcwkuzGZ90notWQXeHpxn18urLUbjDHdlAkEkyZNAtylsTsv2lqzZk25QNCOG/95eYh0t/ItZ0TyHnkpW1tS6swrDCQavbZ4o0BQP1ZR5paif/zjH1+8nKtKfZDP0clOfoq71juLMdmOu21pnpbjnreexaWV3RTj7zeXEgtfU1zV2op7tG4u4pCngoi/4h5znIX1cUieD3EqW1tSqMvasnDhQhYurOh+UUWoLd5oUWGdSJ7BfSPuaNC3btyjavP0APDXjNoeeJZ5nn5Adt+3J+OQ+zNqu1KXQiZP7usFbijAM+i/invCpG/bk7ZzE4eottSuCLXFGwWC+rIEvD9DvRf4jbX2fzy3W5XkMann4xK3Tx3A5XHINs/tViV5/+9SweLQKrVTgFv7JuNnDf53KjuAr3husxbXAV0ZtNsFXJ9Bu9XKrLbEIbnWluT+AJnVFmttrrXFJwWCOmKt/T/gEvwO7G5gvsf20vgRbmrY5/WPm4EvemwvjS/i+uNLD3BPHPIjj22mMR+/swTtwJeTcZ+rOKQd+Bh+A10HbjGh7x1V1eIQ1ZbqFam2eKFAUH++AvwOP0crncAnrbVDX4+4CyWzBAtwN/jwcd//duBDcZjJkV3V4pBO3C2MfRTdfuA5ivFgHACstU8An8LPJVhdwG/JeTp9Z3HIXcDV+Pn7tQNXxyF3e2jLF++1JQ4pRG1JZgkW4Lm2WGsLUVt8USCoM9baXuA9uC9umsLbAZxlrS3U+a845BnciuBN1J7mLe4L+4E4zHX19ksk/fkArn+1XvPbg/t8ZsYhm3z1zQdr7b/jHmaT5ki6Eze+35uM9yL5DHAT6UJBO+6c/We89MiTOMRrbYnDYp1bt9Z6rS3W2kLVFh8UCOpQcs7qUOD7VP/F7cIdWR5nrf2u7775EIf8GXer5lVUX3jbgUeBg+OQezx3zYukXwfj+lnL9q0C3h6HPO65a15Yay8HjsONs2qPoDpx4/rQIp6bjUP6cU+uPA+34+ur4uV9yWvOA05J2iqUZK1L6toShxSytlhrvdQWa+09nrtWCLoxUZ0zxrwLWArsj7usZqjLh7bjAuC1wPnW2ud3TQ9rlzwh7Xjcuc0JuCeLvVyItbjt2wF8Dbg0Dr0vkPIuiBiGuxzqHNzfbQwv/8TAftyO5Bnc4qgbk9MrhWaMeRXub3cybhvGDPGrO3AL0NYCZ1tryz98owCCiL1xK+jfixuDQ92ysRP3d70LODMJvIUXRNRUW+KQwteW5AmdNdUWa23ha0utFAgahDHmrbgBfhiwH+56937cTmQ18DPgJmtt7guYqpUEg5nA0cBsYB/cvcN7gb8AvwDuBG5Ppj3rShDRArwf95jWQ3CP223BLcp6FHc0cyvw3/UQBAYzxozBzRgciZsZmYArvu3Aw8A9uEsLc188WIsgYiIwDzgcd6+JgUclP4+74dBK4Po4ZGM+PUwniKiothRhcWS1kmBQUW0p4Okr7xQIRERERGsIRERERIFAREREUCAQERERFAhEREQEBQIRERFBgUBERERQIBAREREUCERERAQFAhEREUGBQERERFAgEBERERQIREREBAUCERERQYFAREREUCAQERERFAhEREQEBQIRERFBgUBERERQIBAREREUCERERAQFAhEREUGBQERERFAgEBERERQIREREBAUCERERQYFAREREUCAQERERFAhEREQEBQIRERFBgUBERERQIBAREREUCERERAQFAhEREUGBQERERFAgEBERERQIREREBAUCERERQYFAREREUCAQERERFAhEREQEBQIRERFBgUBERERQIBAREREUCERERAQFAhEREUGBQERERFAgEBERERQIREREBPh/UDg+eAd/LYkAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 648x216 with 1 Axes>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Virtual -> physical\n",
    "#    0    ->    0\n",
    "#    1    ->    6\n",
    "#    2    ->    10\n",
    "#    3    ->    13\n",
    "#    4    ->    7\n",
    "\n",
    "bad_ghz = transpile(ghz, backend, initial_layout=[0,6,10,13,7])\n",
    "print('Depth:', bad_ghz.depth())\n",
    "plot_circuit_layout(bad_ghz, backend)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-09T13:54:13.845012Z",
     "start_time": "2019-08-09T13:52:57.815605Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Job Status: job has successfully run\n"
     ]
    }
   ],
   "source": [
    "job3 = execute(bad_ghz, backend)\n",
    "job_monitor(job3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-09T13:54:14.254191Z",
     "start_time": "2019-08-09T13:54:13.969361Z"
    }
   },
   "outputs": [],
   "source": [
    "counts1 = job1.result().get_counts()\n",
    "counts2 = job2.result().get_counts()\n",
    "counts3 = job3.result().get_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-09T13:54:15.151337Z",
     "start_time": "2019-08-09T13:54:14.380235Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x432 with 1 Axes>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plot_histogram([counts1, counts2, counts3],\n",
    "               figsize=(15,6),\n",
    "               legend=['level3', 'good', 'bad'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "From the figure it is clear that the choice of initial layout is an extremely important step, and can mean the difference between a good answer and one dominated by noise.  Although the 'good' circuit has a smaller depth, the results generated by the \"level 3\"-circuit are more in line with the expected answer.  This is because our manual layout selection did not take into account the noise properties of the device.  Noise affects each qubit differently, and qubit measurement errors can also corrupt the answer.  The noise adaptive layout in `optimization_level=2` and `optimization_level=3` takes this into account, and the benefits are obvious."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Being a bit Smarter\n",
    "\n",
    "Picking a good `initial_layout` is critical, but it is not the only step in optimizing a circuit on a quantum device.  Often it is beneficial to rewrite a circuit, with the goal of targeting a specific device.  Our GHZ circuit can be perfectly mapped to the `ibmq_16_melbourne` device provided that we reformulate the gate sequence as:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-09T01:31:29.549091Z",
     "start_time": "2019-08-09T01:31:29.281965Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 758.52x385.28 with 1 Axes>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ghz2 = QuantumCircuit(5, 5)\n",
    "ghz2.h(2)\n",
    "ghz2.cx(2, 1)\n",
    "ghz2.cx(1, 0)\n",
    "ghz2.cx(2, 3)\n",
    "ghz2.cx(3, 4)\n",
    "ghz2.barrier(range(5))\n",
    "ghz2.measure(range(5), range(5))\n",
    "ghz2.draw(output='mpl')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This circuit can now be mapped exactly onto the device topology using `initial_layout=[10,4,5,6,8]`.  This can be verified by once again computing the depth."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-09T01:31:29.646031Z",
     "start_time": "2019-08-09T01:31:29.552835Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Depth: 5\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x216 with 1 Axes>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "exact_ghz = transpile(ghz2, backend, initial_layout=[10,4,5,6,8])\n",
    "print('Depth:', exact_ghz.depth())\n",
    "plot_circuit_layout(exact_ghz, backend)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-09T01:41:09.732117Z",
     "start_time": "2019-08-09T01:31:29.648616Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Job Status: job has successfully run\n"
     ]
    }
   ],
   "source": [
    "job4 = execute(exact_ghz, backend)\n",
    "job_monitor(job4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-09T01:41:10.408469Z",
     "start_time": "2019-08-09T01:41:09.734297Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x432 with 1 Axes>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "counts4 = job4.result().get_counts()\n",
    "plot_histogram([counts1, counts4],\n",
    "               figsize=(15,6),\n",
    "               legend=['level3', 'exact'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Mapping Circuits to Hardware Topology <a name='mapping'></a>\n",
    "\n",
    "Our original GHZ circuit consists of a single qubit (`0`) coupled to the others via CNOT gates.  If implemented directly, this would require hardware that has a single qubit coupled to four other qubits.  Looking at the gate maps of the public IBM Q hardware we see that there is one device that fits this description."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-09T01:41:10.472262Z",
     "start_time": "2019-08-09T01:41:10.410598Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAASUAAAEeCAYAAADM2gMZAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjEsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy8QZhcZAAAXJ0lEQVR4nO3de5xWVb3H8c9wv4sgFuANFU0SQ6V64a0Q8prHwBSPlwxrFWXZTiwt02O3U54oVmnX7UGPWUqiJpYpmYmmknfTYx3TUvGOolxmgIGZOX+sTcB+5rnMzH72Xns/3/frNS+HWc+z+Dk8z/fZe+2112rq6OhARMQXvbIuQERkawolEfGKQklEvKJQEhGvKJRExCsKJRHxikJJRLyiUBIRryiURMQrCiUR8YpCSUS8olASEa8olETEKwolEfGKQklEvKJQEhGvKJRExCsKJRHxikJJRLyiUBIRryiURMQrCiUR8YpCSUS8olASEa8olETEKwolEfGKQklEvKJQEhGvKJRExCsKJRHxikJJRLyiUBIRryiURMQrCiUR8YpCSUS8olASEa8olETEKwolEfGKQklEvKJQEhGvKJRExCsKJRHxikJJRLyiUBIRryiURMQrCiUR8YpCSUS8olASEa8olETEKwolEfGKQklEvKJQEhGvKJRExCsKJRHxikJJRLyiUBIRryiURMQrCiUR8YpCSUS8olASEa8olETEK32yLkDyyViagF2AA4H9gOHABuAfwIPA42FAa3YVSl41dXR0ZF2D5IixDAROBc4DxgIbgSFsOepuATYBvYErARsGPJ1+pZJXCiWpmbEcCiwEhuKCqJpWoA34LvB1HTlJLRRKUlV0qnYxcC4wqBtdNAPPAVPDgNcSLE0KSAPdUotvAnPpXiABDAbGA382lpGJVSWFpCMlqchYZgBX0/1A2lorcB/uiEkvPOmUjpSkrOioZgHJBBJAP2AyMDuh/qSAFEpSyQXAwIT7HAzMN5Z+CfcrBaF5StIpYxkAfBzoX+lx0/aHQybAmJHQqxcsXgY3L6vafRMwE7g2kWKlUHSkJOUcCdXHfXbdEZo3wMq1Xep7KHBWN+uSglMoSTlTqGEu0oLbYN4iWL6iy/1PiqYaiGxDoSTlHEp9Xx+9gZ3q2L/klEJJytmhzv1vBM1ZklIKJSknjXlE7Sn8HZIzCiUp55U6998P6PpIlBSepgRIOXcBh+DGfso65J0wfizsMsr9ef89YIdh8Mgz8OgzFfvfEAa8nFCtUiAKJSnnXtyNtMMqPWj8WDhowpY/7zzKfb2+umoo3Z9AjVJACiUp53bcsiMVXbHEfXXRGuDSbtQkDUBjStKpMGATLjjW1aH79cAtdehXCkChJJV8B+jaXO3qWgATBtWPwqQxKZSkkiG4caWkrAduCwNuSrBPKRiFknTKWMYCdwK7JdTleuCvwOkJ9ScFpVCSEsayC7AU2DvW1E73Jjw2A8uAw8Ig0SMvKSCFkmzDWMbhAmmPWNMtwAG4o51ax5lacIF0DnB4GCQ+PiUFpOVw5V+MZTxwB6U3yt4EzAoDNhhLL9yyJl/A3bTbQulcpvXAm8B8YEEY8EZdC5dCUSgJAMbyDlwgjY41XQecGgZs7OQ5g3AbUd4XaxobBrxUl0Kl8BRKgrHsC/wB2DHW9EvgjGjOUqXnb/MiCgOtkyTdpzGlBmcsk3BX2eKBdCXwkWqBJJI0hVIDM5bJuFO2+LpGPwM+pgmOkgWFUoMylim4U7btY02XAXPCQGsdSTYUSg3IWA4FllB61ex7wNnaKFKypFBqMMZyOHArpZsCfAs4V4EkWVMoNRBjORL4LaU73l4MXKBAEh9oPaUGYSwfBK6Hkp1pvxwGfCuDkkQ6pVBqAMYyA1gI9I01zQ0DvpdBSSJlKZQKzlhmAb+gdK3tz4YBl2VQkkhFCqUCM5bTgP+hdOzwk2HAzzIoSaQqDXQXlLGcCVzFtv/GHcCZCiTxmUKpgIxlDvDfsM09aO3A6WHAFdlUJVIbhVLBGMvZwI9jP24DTg4DfpFBSSJdolAqEGM5F/h+7McbgQ+HAddlUJJIlymUCsJYLsDtPrK1DcCMMODXGZQk0i26+pZzxtKEm5F9UaxpPXB8GND1rSJFMqRQyrEokL4FnBdragE+GAb8Mf2qRHpGoZRTUSDdD0yONa0Fjg4D/pR+VSI9p1DKIWPpDTwCTIw1rQKOCgOWpV+VSDIUSjkT7SbyOLBPrGkNMC0MeCj9qkSSo6tvORIdIS2gNJA6cMvXKpAk93SklBPG0gd3H9spsaZ23GX/xelXJZI8HSnlgLH0Ba6hNJBWAccqkKRIdKTkOWPpj1sL6fhY03LcVthPp1+VSP0olDxmLANwq0UeE2v6Jy6Qnk29KJE6Uyh5KtoS+yZgeqzpaVwgLU+/KpH6Uyh5yFiGADcD7481/Q132f+l1IsSSYlCyTPGMgy4BTg41vQEMD0MeDX9qkTSo1DyiLEMB24D3hNrehT4QBjwevpViaRLUwI8YSwjcdtoxwPpQdwpmwJJGoJCyQPGsiNwB3BArGkZ7pRtZfpViWRDoZQxYxkN/BHYL9Z0N3BEGLAq/apEsqNQypCxjAXuBCbEmu7ALT+yJvWiRDKmUMqIsewK3AXsFWu6DbdAW3P6VYlkT6GUAWPZHVgK7B5r+g3woTBgXfpVifhBoZQyYxmPC6RdY003AieEAevTr0rEHwqlFBnLPrhTtp1iTQuBWWFAa/pVifhFoZQSY5mIO0J6e6zp58BpYcDG9KsS8Y9CKQXGsj/usv+oWNMCYHYYsCn9qkT8pFCqM2N5N+4S/8hY008AEwa0pV+ViL8USnVkLAcBtwPDY00/AD4dBrSnX5WI35o6OjqyrsF7xrIz8G7cHmtjcOtiL8fdl/ZAGPBKJ885DHe3/+BY03eA88KAXP/io11VJgAHAlfGmqcCD4YBa9OuK2vRSqEH4H4v78T9+6/G7UDzEPCYxg8rUyiVEe0cMhM4H/fmawWGsOXochPQDPTHbQp5CfC7MKDDWKbh1kMaGOv2G8BFeQ6kaGmVjwHnAtvhdlIZEnvYKqAfsAiYFwb8JdUiM2AsuwEB7nfTDvRl23//FqAt+vohcFlnH2aiUOqUsewN/Ao3uTH+hitnLe6T8HIgBAbE2i8KA76eWJEZMJajcVcLBwKDanhKGy7ML8cdHRZuUmj04TUXuBjojQvjatbjfjdnA1fk+UOqHhRKMcYyE/fGG0DXx9zacC/MuPPDgEt6WltWoi3Cvwt8ktrCKK4FeAU4LAx4McnasmQsQ3G3Be1H6Wl6LZpxy9WcFAZsSLK2PFMobcVYZgBX0703XjnnhAHzE+wvVVEg/QCYTffeeJttAlYABxThtCVaQ/1u3LhR/x501QL8CbdVlqaGoKtv/2Ise5J8IJ2X50CKnEzPAwncKqejgF9Hg+R592PcTsU9CSRwr7dDgIt6XFFBFOHF0WPRm2QhPX+BbW0T7sWWW8byNuCn9DyQNusD7AvMSai/TBjLdODDlF7I6K5BwLnG8q6E+ss1hZLzQdwSIp2NB3VXH2CasUxOsM+0XUiyQQ0u4C6J9rTLneh09kcke0QNbgzz+wn3mUvaOMD5IlWusvXpDSceCpP3ggH94PnX4Fd3wT8rj470B86hdLtt70VjJh+lytWk06fBnmNgxFDY1OZ+H4vuhpeqL+B7Iu6CQt68FzdXraLZR8A+u8CQAbB+Izz3KtxwDyxfUfYpTcB7jWW3Rt9ktOGPlIxlFFQ/mjn5fXD4JFjdAo8+A7uPhs/PcC+6CnoDM43NZfgfDdVvgTlsIqxvhfv/z/134jgIZrgQr2AI8OmE6kzbmdRw2jZyGDz1AtzzJDSvg313g7OOq9p3L3L4AZa0PL5ZknYgbt5I2dOUoQPh4HdCezt873pYsw7a2mHKPjB1Ety8rGL/rbjJl3mbQDiFGuZofXshPPOy+37kMPj2mbD9UBgzAp4vf1QAsJ+xNOVwjs6h1PBhPm/Rlu93GQUXngrbD4Hevdxrp4x+uNnw/9nzMvNLoQSTqDKQO2ak++R/fZULJHCH41P2gZ3j9/2XGgo8ZmwClXpocyAB9Inequ3tsKr6Yr6DgPai/l4Apr4LRo+AfXZ2f17ycMVA2qzhB7sVSrAjVX4Pw6IhzfVb3bG0Ifp+u6SHO3Oqf1/46BHu+yUPw6qWbOvxwYHjYe9oOb+Va+Dp2jZbr/UOgsJq+DElqH6n/uroDTag75af9Y+Gf/Xmc+Nqc09wA953PQ7X/ynrivwwbxF86lK4bDEMHwxzjnWnuFXk7XQ2cQoleAEqT/F/aaW7sjRiKAyNjozGvS16cuVxk8IbMRTOOwnGvR1ueQB+/oesK8pe397Q1OS+39QG//ucO8ru0xt2qB5Kb9a5PO/p9A0epspA95oWuPdJd6Vp7kx48Q03NWB9K9zxWNX+m4FJYcDTyZVcf8ZyMXABVV4j589yA7hvrIZ+fWDW+9zP//w3ePbVin/Fm2HAiGSqTY+xPETpTsbbGDcazFHw1IvQsgHGj4FB/d0R9/OvVf0rHkiq1rxSKLlQqjqR79o73SDl5PGw43D4x8tw3d2wtvp97+3AMz0vM3X34O7LqvjZvn00AjJyGEzff8vPl6+oGkqVr1n663ZgIm5pkk6tWguvvgUTdnFz2tasgwefgpv/DOsqbw3REvXf0HRDLmAsi4AZJH8624pbN2duwv3WXbQkxyvADnXofg3uzvhb69B3XUVbZP2FGj7IumE9MDYMqD71tMA0puTMg7qs9dMOXFaHfusuWjt8Pu7TO2lrgSV16LfuwoC/41YcTXop443AjY0eSKBQAiAMWAb8FhLdCLIF+GEY8M8E+0zbfEj8TdKC28Elz+uTfwISX9J2A+TviLoeFEpbzMENSidxPtsGvIYbKM6taKXIWSR3FLkOuCEMuC2h/rIylmTfOy3AnDDg5aqPbAAKpUgY8CYwDTfe0ZNgasNd1p1ahNUEw4B7cfep9fQ0bh3wCGB6XFSGjOUo4DdUGOjuombg0jDgFwn1l3sKpa2EAY/h1kB6je4dHbQAzwKTi3SndxhwJW5B/M2L33dVM/B7YFoYJHqKnCpjOQ64idLpI905levAvca+CXyph6UViq6+dcJYhuDGU07D3elf7VNxA+5FZoH/CAMqX/jNKWMZB1yDW6htINU/1JpxIfYJ4Fc5vPn2X4zlBOBaSqfRfB54FPd7GYy717GaNbilgU8MAx5Oss4iUChVEC2R+1ncukJ9cZ+Imxfl2IT7xGzG7Xb7kzDghQzKTFW0yNnBuC2WjmbL1lNb2wg8h9vj7pd53//NWP4dt/ZTfEGWs8KAH0WP6YebVvJF3EYCLbjQbsJdqevABfky4L9w23Fpd+ROKJRqEL0Rd8bN5B2Je5GtAB4OA2q7zbKAorlM7wCeiDUNDwNWZVBS4ozlI8AVbHtU2AF8Igy4vMxzBuLu9t8LtxzJeuCvwBNFGGesN4WS9Jix256WhQFNWdWSJGP5GG4Pv63/f9pxUxquyqaq4tNAt0gnjOXTuE00tw6kNuBUBVJ9KZREYowlwG2tvbVNwKww4NoMSmooCiWRrRjLF6Fkr75W4IQw4PoMSmo4CiWRiLFcCCXbq28Ajg8DFmdQUkPS0iXS8KKrq18DvhJrWgccFwZo6boUKZSkoUWBdAnwhVhTM3BsGLA0/aoam0JJGlYUSPOBz8Wa1gBHhwH3pF+VKJSkIRlLL9xaV5+KNb0FHBkG3J9+VQIKJWlA0Uz0n+JuMt7aSuADuh8tWwolaSjRFuoLgNNjTSuA6WGQu52MC0ehJA3DWPribqydFWt6BbesypPpVyVxCiVpCNFd/NcAM2NNLwKHhwFPpV+VdEahJIVnLP2B64DjYk3P4wIpj1tgFZZCSQotWkbkRuDIWNM/cIH0XPpVSSUKJSksYxkMLAYOjzX9HRdIhV+UL48USlJIxjIUt23WobGmv+IGtbVziKcUSlI4xrId8DtgSqzpcdxl/9fSr0pqpVCSQjGW3XBbOQ2PNT2Cmxj5RupFSZdo6RIpDGPZC3iS0kB6AHfKpkDKAR0pSSEYy3jgL5TuyfYg7gipEBsZNAIdKUnuGcto3FW2eCCtwq2HpEDKER0pSa4Zy07AHcD4WNNKYO8w4PX0q5Ke0JGS5FY0qH0XpYH0N2APBVI+KZQkl4xlD2ApMC7WtBiYFAa8lX5VkgSFkuSOseyNO0LaJdZ0PXCidqHNN4WS5IqxTMAdIY2JNV0DnBwGtKZflSRJoSS5YSz7AXcCb4s1XQWcHgZsSr0oSZxCSXLBWA4A/giMijVdDswOA9rSr0rqQaEk3jOW9+Iu+4+INf0I+GQY0J5+VVIvCiXxmrEcAvwe2C7WNB/4jAKpeBRK4i1jeT9wKzA01nQJMDcM6Ei9KKk7hZJ4yVimA7cAg2NNXwO+pEAqLt1mIt4xlmOAGyi9l+0rYcA3MyhJUqRQEq8Yy/G4Rf77xpq+EAbMy6AkSZlCSbxhLCcCv6T0dfm5MOAHGZQkGVAoiReM5RTcRpHxcc5PhQE/yaAkyYhCSTJnLGcAVwBNW/24A/h4GLAgm6okK7r6JpkyFkNpILUDH1EgNSaFkmTGWM4Cfsa2gdQGnBIGXJ1NVZI1hZJkwljOAS6L/XgjcFIYsDCDksQTCiVJnbGcD3w39uNWYGYYcEMGJYlHmjo6NDFWus5Y+gDvBg4ELo01/xtwX3w5WmNpAi4Evhp7/HrgQ2HAbXUqV3JEoSRdYiw7AJ8BzsZdve0DDIw9bDXQD1gCfDsMuC8KpG8AX449dh1ux5E/1LVwyQ2FktQsmtx4OS5wBtTwlA5c6FyH2+7o7Fj7WuDYMOCuJOuUfFMoSVXG0gt3lexkSm+QrUUb0Dv2s9XAUWHAfT0sTwpGoSQVRaddVwIfBgYl1O1bwBFhwAMJ9ScFohndUs1s4ASSC6Q2YHoY8FBC/UnBaEqAlBXtPvt9unfKVk4rMDXB/qRgFEpSyUWUrmnUUwOBrxqb2JGXFIxO36RTxjIEOI3SdY069Z69wRztvr/9EVi4tOLD23GD5rq3TUroSEnKOQZq20dt+yFwylTYVPsmR0OAOd2sSwpOoSTlTKHGsaTZR8CqZnj46S71v290ZU9kGwolKecganh9TN8f9hwDl9/apSMlcBMrd+1mbVJgCiUpZ/tqDxgzEmYeDIuXwfIVXe5/EzC8O4VJsWmgW8qpetxz4J7QuzfsNRbGj4Gdog2137U7tG6CG+/p+d8hjUehJOW8ALyj4iOaoFcTTBy37Y9HbQd7jK7a/wDgle6XJ0WlUJJylgLvo8KUgJuXua/NZh8BB02oaUoAwJowoOsnfVJ4GlOScu7BrXNUDx3AvXXqW3JOR0pSzlKgBRha6xOuWOK+atCMu31FpISOlKRTYUA7MA8XTElbCdxRh36lABRKUsmlwKu4062ktABnhEGifUqBKJSkrDBgA3AibvXIJLQAV4cBdybUnxSQQkkqitY9OoOeB1MLbnD7Mz0uSgpNoSRVhQGLgJNwa2pv7EYXLcCNwDFh0K3nSwPRcrhSM2MZDVyFuy+uH9Wv3q7BLep2Rhjw2zqXJwWhUJIuM5ZJwOeBmbgNAVpxR92bX0wDgSeA7wA3RGNTIjVRKEm3RUuP7AxMxM1n2gg8CzyhIJLuUiiJiFc00C0iXlEoiYhXFEoi4hWFkoh4RaEkIl5RKImIVxRKIuIVhZKIeEWhJCJeUSiJiFcUSiLiFYWSiHhFoSQiXlEoiYhXFEoi4hWFkoh4RaEkIl5RKImIVxRKIuIVhZKIeEWhJCJeUSiJiFcUSiLiFYWSiHhFoSQiXlEoiYhXFEoi4hWFkoh4RaEkIl5RKImIVxRKIuIVhZKIeEWhJCJeUSiJiFcUSiLiFYWSiHhFoSQiXlEoiYhXFEoi4hWFkoh4RaEkIl5RKImIVxRKIuIVhZKIeEWhJCJeUSiJiFcUSiLiFYWSiHhFoSQiXlEoiYhXFEoi4hWFkoh4RaEkIl5RKImIVxRKIuIVhZKIeEWhJCJeUSiJiFcUSiLiFYWSiHhFoSQiXvl/XBosxKWsW7gAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "backend = provider.get_backend('ibmqx2')\n",
    "plot_gate_map(backend)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "and five that do not.  Four that have the following topology:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-09T01:41:10.537942Z",
     "start_time": "2019-08-09T01:41:10.473878Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "backend = provider.get_backend('ibmq_ourense')\n",
    "plot_gate_map(backend)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "and one ladder-type configuration:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-09T01:41:10.645877Z",
     "start_time": "2019-08-09T01:41:10.539381Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 648x216 with 1 Axes>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "backend = provider.get_backend('ibmq_16_melbourne')\n",
    "plot_gate_map(backend)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It seems our circuit is a good match to the `ibmqx2` topology provided that we map virtual qubit `0` to physical qubit `2`.  The arrows on the graphs above indicate that CNOT gates are only allowed in one direction.  However, flipping the direction of a CNOT gate is relatively trivial, and does not greatly affect the fidelity of the computation."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`ibmq_ourense`, `ibmq_vigo`, and `ibmq_16_melbourne` represent a problem.  There is no qubit anywhere that is connected to four others via CNOT gates.  In order to implement a CNOT gate between qubits that are not directly connected, one or more SWAP gates must be inserted into the circuit to move the qubit states around until they are adjacent on the device gate map.  Our choice of `initial_layout` in `job3` above was purposely designed to take many SWAP gates to make adjacent. As we have seen previously, each SWAP gate is decomposed into three CNOT gates on the IBM Q devices, and represents an expensive and noisy operation to perform.  Thus, finding the minimum number of SWAP gates needed to map a circuit onto a given device, is an important step (if not the most important) in the whole execution process.\n",
    "\n",
    "As with many important things in life, finding the optimal SWAP mapping is hard.  In fact it is in a class of problems called NP-Hard, and is thus prohibitively expensive to compute for all but the smallest quantum devices and input circuits.  To get around this, by default Qiskit uses a stochastic heuristic algorithm called `StochasticSwap` to compute a good, but not necessarily minimal SWAP count.  The use of a stochastic method means the circuits generated by `transpile` (or `execute` that calls `transpile` internally) are not guaranteed to be the same over repeated runs.  Indeed, running the same circuit repeatedly will in general result in a distribution of circuit depths and gate counts at the output.\n",
    "\n",
    "In order to highlight this, we run the GHZ circuit 100 times, using the \"bad\" (disconnected) `initial_layout` from the previous section:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-09T13:56:02.418909Z",
     "start_time": "2019-08-09T13:55:55.996117Z"
    }
   },
   "outputs": [],
   "source": [
    "bad_circs = transpile([ghz]*100, backend, initial_layout=[0,6,10,13,7])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-09T13:56:12.152254Z",
     "start_time": "2019-08-09T13:56:11.936337Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "depths = [circ.depth() for circ in bad_circs]\n",
    "plt.figure(figsize=(8,6))\n",
    "plt.hist(depths, bins=list(range(34,50)), align='left', color='#648fff')\n",
    "plt.xlabel('Depth', fontsize=14)\n",
    "plt.ylabel('Counts', fontsize=14);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This distribution is quite wide, signaling the difficultly the SWAP mapper is having in computing the best mapping.  Most circuits will have a distribution of depths, perhaps not as wide as this one, due to the stochastic nature of the default SWAP mapper.  Of course, we want the best circuit we can get, especially in cases where the depth is critical to success or failure.  In cases like this, it is best to `transpile` a circuit several times, e.g. 10, and take the one with the lowest depth.  The `transpile` function will automatically run in parallel mode, making this procedure relatively speedy in most cases.\n",
    "\n",
    "Just to highlight the difference when running on a different device, we show the same distribution when using the `ibmqx2` backend with the default settings:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-09T13:56:19.396948Z",
     "start_time": "2019-08-09T13:56:16.884565Z"
    }
   },
   "outputs": [],
   "source": [
    "backend = provider.get_backend('ibmqx2')\n",
    "qx2_circs = transpile([ghz]*100, backend)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-09T13:56:24.008482Z",
     "start_time": "2019-08-09T13:56:23.828800Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "depths = [circ.depth() for circ in qx2_circs]\n",
    "plt.figure(figsize=(8,6))\n",
    "plt.hist(depths, bins=list(range(6,15)), align='left', color='#648fff')\n",
    "plt.xlabel('Depth', fontsize=14)\n",
    "plt.ylabel('Counts', fontsize=14);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Optimizing Single- and Multi-Qubit Gates <a name='optimizing'></a>\n",
    "\n",
    "Decomposing quantum circuits into the basis gate set of the IBM Q devices, and the addition of SWAP gates needed to match hardware topology, conspire to increase the depth and gate count of quantum circuits.  Fortunately many routines for optimizing circuits by combining or eliminating gates exist.  In some cases these methods are so effective the output circuits have lower depth than the inputs.  In other cases, not much can be done, and the computation may be difficult to perform on noisy devices.  Different gate optimizations are turned on with different `optimization_level` values.  Below we show the benefits gained from setting the optimization level higher:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-success\">\n",
    "    <b>Remember:</b> The output from <code>transpile</code> varies due to the stochastic swap mapper.  So the numbers below will likely change each time you run the code.\n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-09T13:56:26.038494Z",
     "start_time": "2019-08-09T13:56:26.035734Z"
    }
   },
   "outputs": [],
   "source": [
    "backend = provider.get_backend('ibmq_16_melbourne')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-09T13:56:26.353081Z",
     "start_time": "2019-08-09T13:56:26.248097Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Depth: 23\n",
      "Gate counts: OrderedDict([('u2', 17), ('cx', 13), ('measure', 5), ('barrier', 1)])\n"
     ]
    }
   ],
   "source": [
    "circ0 = transpile(ghz, backend, optimization_level=0)\n",
    "print('Depth:', circ0.depth())\n",
    "print('Gate counts:', circ0.count_ops())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-09T13:56:26.649019Z",
     "start_time": "2019-08-09T13:56:26.509400Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Depth: 22\n",
      "Gate counts: OrderedDict([('u2', 25), ('cx', 17), ('measure', 5), ('barrier', 1)])\n"
     ]
    }
   ],
   "source": [
    "circ1 = transpile(ghz, backend, optimization_level=1)\n",
    "print('Depth:', circ1.depth())\n",
    "print('Gate counts:', circ1.count_ops())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-09T13:56:26.948413Z",
     "start_time": "2019-08-09T13:56:26.829380Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Depth: 14\n",
      "Gate counts: OrderedDict([('u2', 13), ('cx', 7), ('measure', 5), ('barrier', 1)])\n"
     ]
    }
   ],
   "source": [
    "circ2 = transpile(ghz, backend, optimization_level=2)\n",
    "print('Depth:', circ2.depth())\n",
    "print('Gate counts:', circ2.count_ops())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-09T13:56:27.479648Z",
     "start_time": "2019-08-09T13:56:27.271226Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Depth: 13\n",
      "Gate counts: OrderedDict([('u2', 11), ('cx', 7), ('measure', 5), ('barrier', 1)])\n"
     ]
    }
   ],
   "source": [
    "circ3 = transpile(ghz, backend, optimization_level=3)\n",
    "print('Depth:', circ3.depth())\n",
    "print('Gate counts:', circ3.count_ops())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Transpiling for User Defined Topologies <a name='topology'></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Up to now, we have focused on rewriting and optimizing circuits for the IBM Q set of devices.  However, `transpile` is much more general than that, and can be used to map circuits onto user defined device topologies.  The topology is encoded in what qiskit calls the `coupling_map`, and the coupling map for a device can be obtained from its `configuration`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-09T13:56:31.152071Z",
     "start_time": "2019-08-09T13:56:31.148319Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[[0, 1],\n",
       " [0, 2],\n",
       " [1, 0],\n",
       " [1, 2],\n",
       " [2, 0],\n",
       " [2, 1],\n",
       " [2, 3],\n",
       " [2, 4],\n",
       " [3, 2],\n",
       " [3, 4],\n",
       " [4, 2],\n",
       " [4, 3]]"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "backend = provider.get_backend('ibmqx2')\n",
    "backend.configuration().coupling_map"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The elements of this list are `[control, target]` pairs that indicate that a CNOT gate can be performed using those qubits.  The coupling map is in essence an adjacency matrix characterizing the entangling gate coupling of the device:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-09T13:56:31.604159Z",
     "start_time": "2019-08-09T13:56:31.509046Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from scipy.sparse import coo_matrix\n",
    "cmap = backend.configuration().coupling_map\n",
    "rows = [c[0] for c in cmap]\n",
    "cols = [c[1] for c in cmap]\n",
    "data = np.ones_like(rows)\n",
    "adj_matrix = coo_matrix((data,(rows,cols)),shape=(5,5))\n",
    "plt.spy(adj_matrix);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If it is possible to perform CNOT gates in both directions on all pairs of qubits, then this matrix is symmetric.\n",
    "\n",
    "We are free to construct our own device topology by defining our own `coupling_map` and using it in `transpile`.  For example, a five-qubit linear nearest-neighbor (LNN) topology supporting bi-directional CNOT gates is written as:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-09T13:56:31.854550Z",
     "start_time": "2019-08-09T13:56:31.851114Z"
    }
   },
   "outputs": [],
   "source": [
    "lnn5 = [[0,1], [1,0], [1,2], [2,1], [2,3], [3,2], [3,4], [4,3]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-09T13:56:32.182267Z",
     "start_time": "2019-08-09T13:56:32.092850Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "rows = [c[0] for c in lnn5]\n",
    "cols = [c[1] for c in lnn5]\n",
    "data = np.ones_like(rows)\n",
    "adj_matrix = coo_matrix((data,(rows,cols)),shape=(5,5))\n",
    "plt.spy(adj_matrix);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can then use this `coupling_map` in place of an actual backend as follows:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-09T13:56:32.784373Z",
     "start_time": "2019-08-09T13:56:32.392714Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1337.64x385.28 with 1 Axes>"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lnn5_circ = transpile(ghz, backend=None, coupling_map=lnn5)\n",
    "lnn5_circ.draw(output='mpl')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Or we can write a directional five-qubit '+' shaped topology, with all directional CNOT gates pointing to the center as:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-09T13:56:35.162158Z",
     "start_time": "2019-08-09T13:56:35.159222Z"
    }
   },
   "outputs": [],
   "source": [
    "plus = [[0,2], [1,2], [3,2], [4,2]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-09T13:56:35.578426Z",
     "start_time": "2019-08-09T13:56:35.484158Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "rows = [c[0] for c in plus]\n",
    "cols = [c[1] for c in plus]\n",
    "data = np.ones_like(rows)\n",
    "adj_matrix = coo_matrix((data,(rows,cols)),shape=(5,5))\n",
    "plt.spy(adj_matrix);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-09T13:56:37.342535Z",
     "start_time": "2019-08-09T13:56:36.761977Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1759.04x806.68 with 1 Axes>"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plus_circ = transpile(ghz, backend=None, coupling_map=plus)\n",
    "plus_circ.draw(output='mpl')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the above examples we can see that a Hadamard gate is still in the circuit.  This is because with `backend=None` we also need to specify the `basis_gates` if we want a specific gate set at the end."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Passing Transpiled Circuits to a Backend <a name='passing'></a>\n",
    "\n",
    "Now that we have transpiled circuits, the final step is to pass them to a backend for execution.  There are two ways of doing this:\n",
    "\n",
    "1) Pass the circuits to `execute` as done before.\n",
    "\n",
    "2) Use the `assemble` function to package them, and then call the backend directly."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Using `execute` with transpiled circuits\n",
    "\n",
    "Typically one is interested in transpiling circuits for the same backend that they intend to run their circuits on.  In this case, the circuits have already been mapped to the backend and optimized, so calling:\n",
    "\n",
    "```\n",
    "job = execute(transpiled_circuits, backend, **kwargs)\n",
    "```\n",
    "will simply package the circuits up, and send them to the target backend.  The exception to this rule is if the level of optimization is different than what the circuits were originally transpiled with.  That is to say setting `optimization_level=3` in `execute` while passing circuits transpiled under `optimization_level=1` (the default) will undergo further optimization before being sent to the device."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Packaging Circuits with `assemble`\n",
    "\n",
    "It is also possible to skip the `execute` function and bundle the transpiled circuits using the `assemble` function.  The `assemble` function is designed to take both, circuits and pulse schedules, and has lots of input arguments:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-09T14:06:50.694252Z",
     "start_time": "2019-08-09T14:06:50.690385Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Signature (experiments, backend=None, qobj_id=None, qobj_header=None, shots=1024, memory=False, max_credits=None, seed_simulator=None, qubit_lo_freq=None, meas_lo_freq=None, qubit_lo_range=None, meas_lo_range=None, schedule_los=None, meas_level=2, meas_return='avg', meas_map=None, memory_slot_size=100, rep_time=None, parameter_binds=None, **run_config)>"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "inspect.signature(assemble)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "many of which overlap with those in `execute`.  Here `experiments` is the circuit or list of circuits to be run, and `backend` is of course the backend you are targeting.  The other important ones are:\n",
    "\n",
    "- **shots** - Number of times to execute each circuit.\n",
    "\n",
    "- **memory** - Return the resulting bitstring for each shot rather than collecting counts.\n",
    "\n",
    "A standard call to `assemble` would look like:\n",
    "\n",
    "```\n",
    "qobj = assemble(transpiled_circuits, backend, shots=2048)\n",
    "```\n",
    "\n",
    "where `qobj` is the container format used in sending circuits (and pulse experiments) to the devices.  This `qobj` can be run by calling the `backend` directly:\n",
    "\n",
    "```\n",
    "job = backend.run(qobj)\n",
    "```\n",
    "\n",
    "which will return a `job` just like `execute`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-09T01:41:22.751335Z",
     "start_time": "2019-08-09T01:41:22.745919Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<h3>Version Information</h3><table><tr><th>Qiskit Software</th><th>Version</th></tr><tr><td>Qiskit</td><td>0.12.1</td></tr><tr><td>Terra</td><td>0.9.0</td></tr><tr><td>Aer</td><td>0.3.0</td></tr><tr><td>Ignis</td><td>0.2.0</td></tr><tr><td>Aqua</td><td>0.5.5</td></tr><tr><td>IBM Q Provider</td><td>0.3.3</td></tr><tr><th>System information</th></tr><tr><td>Python</td><td>3.7.4 (default, Sep  7 2019, 18:27:02) \n",
       "[Clang 10.0.1 (clang-1001.0.46.4)]</td></tr><tr><td>OS</td><td>Darwin</td></tr><tr><td>CPUs</td><td>4</td></tr><tr><td>Memory (Gb)</td><td>16.0</td></tr><tr><td colspan='2'>Sun Oct 06 19:57:04 2019 CDT</td></tr></table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
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     "metadata": {},
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     "data": {
      "text/html": [
       "<div style='width: 100%; background-color:#d5d9e0;padding-left: 10px; padding-bottom: 10px; padding-right: 10px; padding-top: 5px'><h3>This code is a part of Qiskit</h3><p>&copy; Copyright IBM 2017, 2019.</p><p>This code is licensed under the Apache License, Version 2.0. You may<br>obtain a copy of this license in the LICENSE.txt file in the root directory<br> of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.<p>Any modifications or derivative works of this code must retain this<br>copyright notice, and modified files need to carry a notice indicating<br>that they have been altered from the originals.</p></div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
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   ],
   "source": [
    "import qiskit.tools.jupyter\n",
    "%qiskit_version_table\n",
    "%qiskit_copyright"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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