qiskit/advanced/aer/2_device_noise_simulation.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src=\"../../../images/qiskit_header.png\" alt=\"Note: In order for images to show up in this jupyter notebook you need to select File => Trusted Notebook\" align=\"middle\">"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Qiskit Aer: Device noise model simulations\n",
    "\n",
    "The latest version of this notebook is available on https://github.com/Qiskit/qiskit-tutorials."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Introduction\n",
    "\n",
    "This notebook shows how to use the Qiskit Aer `noise.device` module to automatically generate a noise model for an IBMQ hardware device, and use this model to do noisy simulation of `QuantumCircuits` to study the effects of errors which occur on real devices.\n",
    "\n",
    "Note that these automatic models are only a highly simplified approximation of the real errors that occur on actual devices. The study of quantum errors on real devices is an active area of research and we discuss the Qiskit Aer tools for configuring more detailed noise models in another notebook."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-19T16:57:28.062507Z",
     "start_time": "2019-08-19T16:57:24.202560Z"
    }
   },
   "outputs": [],
   "source": [
    "from qiskit import Aer, IBMQ, execute\n",
    "from qiskit.providers.aer import noise\n",
    "from qiskit import QuantumCircuit, QuantumRegister, ClassicalRegister\n",
    "from qiskit.tools.visualization import plot_histogram\n",
    "from qiskit.tools.monitor import job_monitor"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Device noise module\n",
    "\n",
    "The *Qiskit Aer* device noise module contains two functions to automatically generate a simplified noise model for a real device. This model is generated using the calibration information reported in the `BackendProperties` of a device.\n",
    "\n",
    "### IBMQ Provider\n",
    "\n",
    "We will use a real hardware device in the `IBMQ` provider as an example. First we must load our account credentials, and then select a backend from the provider."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-19T16:57:31.724630Z",
     "start_time": "2019-08-19T16:57:28.076074Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<IBMQSimulator('ibmq_qasm_simulator') from IBMQ(hub='ibm-q', group='open', project='main')>,\n",
       " <IBMQBackend('ibmqx4') from IBMQ(hub='ibm-q', group='open', project='main')>,\n",
       " <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')>]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Load IBMQ account\n",
    "provider = IBMQ.load_account()\n",
    "provider.backends()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We will use the `ibmq_16_melbourne` device for this tutorial. We may get the properties of the backend using the `properties` method, the information in the returned `BackendProperties` object will be used to automatically generate a noise model for the device that can be used by the Qiskit Aer `QasmSimulator`. We will also want to get the `coupling_map` for the device from its `configuration` to use when compiling circuits for simulation to most closely mimic the gates that will be executed on a real device"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-19T16:57:32.162207Z",
     "start_time": "2019-08-19T16:57:32.159466Z"
    }
   },
   "outputs": [],
   "source": [
    "device = provider.get_backend('ibmq_16_melbourne')\n",
    "properties = device.properties()\n",
    "coupling_map = device.configuration().coupling_map"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Test circuit for device and simulation comparison\n",
    "\n",
    "Now we construct a test circuit to compare the output of the real device with the noisy output simulated on the Qiskit Aer `QasmSimulator`. We will prepare a 3-qubit GHZ state $\\frac{1}{2}(|0,0,0\\rangle + |1,1,1\\rangle)$ on qubits 0, 1 and 2. Before running with noise or on the device we show the ideal expected output with no noise."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-19T16:57:32.330124Z",
     "start_time": "2019-08-19T16:57:32.175615Z"
    }
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Construct quantum circuit\n",
    "circ = QuantumCircuit(3, 3)\n",
    "circ.h(0)\n",
    "circ.cx(0, 1)\n",
    "circ.cx(1, 2)\n",
    "circ.measure([0,1,2], range(3))  # Can use list or generator like `range`.\n",
    "\n",
    "# Select the QasmSimulator from the Aer provider\n",
    "simulator = Aer.get_backend('qasm_simulator')\n",
    "\n",
    "# Execute and get counts\n",
    "result = execute(circ, simulator).result()\n",
    "counts = result.get_counts(circ)\n",
    "plot_histogram(counts, title='Ideal counts for 3-qubit GHZ state')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Generating a device noise model\n",
    "\n",
    "Noise models in Qiskit Aer are presented using the `NoiseModel` object from the `aer.noise` module. The function we will use is the `basic_device_noise_model` function from `aer.noise.device` module which will return a basic approximate `NoiseModel` object configured from a device `BackendProperties`.\n",
    "\n",
    "### Basic device noise model\n",
    "\n",
    "The `basic_device_noise_model` constructs an approximate noise model consisting of:\n",
    "\n",
    "* **Single-qubit gate errors** consisting of a single qubit depolarizing error followed by a single qubit thermal relaxation error.\n",
    "* **Two-qubit gate errors** consisting of a two-qubit depolarizing error followed by single-qubit thermal relaxation errors on both qubits in the gate.\n",
    "* **Single-qubit readout errors** on the classical bit value obtained from measurements on individual qubits\n",
    "\n",
    "For the gate errors the error parameter of the thermal relaxation errors is derived using the `thermal_relaxation_error` function from `aer.noise.errors` module, along with the individual qubit $T_1$ and $T_2$ parameters, and the `gate_time` parameter from the device backend properties. The probability of the depolarizing error is then set so that the combined average gate infidelity from the depolarizing error followed by the thermal relaxation is equal to the `gate_error` value from the backend properties.\n",
    "\n",
    "For the readout errors the probability that the recorded classical bit value will be flipped from the true outcome after a measurement is given by the qubit `readout_errors`.\n",
    "\n",
    "Let us construct the device noise model.\n",
    "\n",
    "**Note:** *Since the devices don't currently provide the gate times for gates we will manually provide them for the gates we are interested in using the optional `gate_times` argument for `basic_device_noise_model`.*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-19T16:57:34.232936Z",
     "start_time": "2019-08-19T16:57:34.125212Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NoiseModel:\n",
      "  Basis gates: ['cx', 'id', 'u2', 'u3']\n",
      "  Instructions with noise: ['cx', 'u2', 'measure', 'u3']\n",
      "  Qubits with noise: [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]\n",
      "  Specific qubit errors: [('u2', [0]), ('u2', [1]), ('u2', [2]), ('u2', [3]), ('u2', [4]), ('u2', [5]), ('u2', [6]), ('u2', [7]), ('u2', [8]), ('u2', [9]), ('u2', [10]), ('u2', [11]), ('u2', [12]), ('u2', [13]), ('u3', [0]), ('u3', [1]), ('u3', [2]), ('u3', [3]), ('u3', [4]), ('u3', [5]), ('u3', [6]), ('u3', [7]), ('u3', [8]), ('u3', [9]), ('u3', [10]), ('u3', [11]), ('u3', [12]), ('u3', [13]), ('cx', [1, 0]), ('cx', [1, 2]), ('cx', [2, 3]), ('cx', [4, 3]), ('cx', [4, 10]), ('cx', [5, 4]), ('cx', [5, 6]), ('cx', [5, 9]), ('cx', [6, 8]), ('cx', [7, 8]), ('cx', [9, 8]), ('cx', [9, 10]), ('cx', [11, 3]), ('cx', [11, 10]), ('cx', [11, 12]), ('cx', [12, 2]), ('cx', [13, 1]), ('cx', [13, 12]), ('measure', [0]), ('measure', [1]), ('measure', [2]), ('measure', [3]), ('measure', [4]), ('measure', [5]), ('measure', [6]), ('measure', [7]), ('measure', [8]), ('measure', [9]), ('measure', [10]), ('measure', [11]), ('measure', [12]), ('measure', [13])]\n"
     ]
    }
   ],
   "source": [
    "# List of gate times for ibmq_14_melbourne device\n",
    "# Note that the None parameter for u1, u2, u3 is because gate\n",
    "# times are the same for all qubits\n",
    "gate_times = [\n",
    "    ('u1', None, 0), ('u2', None, 100), ('u3', None, 200),\n",
    "    ('cx', [1, 0], 678), ('cx', [1, 2], 547), ('cx', [2, 3], 721),\n",
    "    ('cx', [4, 3], 733), ('cx', [4, 10], 721), ('cx', [5, 4], 800),\n",
    "    ('cx', [5, 6], 800), ('cx', [5, 9], 895), ('cx', [6, 8], 895),\n",
    "    ('cx', [7, 8], 640), ('cx', [9, 8], 895), ('cx', [9, 10], 800),\n",
    "    ('cx', [11, 10], 721), ('cx', [11, 3], 634), ('cx', [12, 2], 773),\n",
    "    ('cx', [13, 1], 2286), ('cx', [13, 12], 1504), ('cx', [], 800)\n",
    "]\n",
    "\n",
    "# Construct the noise model from backend properties\n",
    "# and custom gate times\n",
    "noise_model = noise.device.basic_device_noise_model(properties, gate_times=gate_times)\n",
    "print(noise_model)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Simulating a quantum circuit with noise\n",
    "\n",
    "To use this noise model we must make use of several keyword arguments in the `execute` function. These are:\n",
    "\n",
    "* `noise_model`: This passes the noise model to the `QasmSimulator.run` method for noisy simulation.\n",
    "* `basis_gates`: A noise model is defined with respect to specific gates, we must pass these basis gates to the Qiskit compiler so that it compiles the circuit to the correct gates for the noise model. The basis gates of a noise model may be obtained from the `NoiseModel.basis_gates` property.\n",
    "* `coupling_map`: We also must make sure we provide the `coupling_map` for the real device so that the compiler will produce a Qobj for the simulator that will match the compiled experiment that can be executed on the real device.\n",
    "\n",
    "### Local Simulator"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-19T16:57:36.864987Z",
     "start_time": "2019-08-19T16:57:36.672055Z"
    }
   },
   "outputs": [
    {
     "data": {
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uzFtvvcWyZcs48cQTd3j/G2+8waBBgxg8eDC33XZbbRIVEZHCpKTZAO6+w7TEM8bPPvuM//3f/+Xmm29O+f4jjjiC6dOnM2XKFMaPH8/mzZtzFquIiDSckmYDlJaWsmzZstrXy5cvp1OnTrWvN27cSGVlJcOHD6esrIw33niDkSNH1nYGqtG7d29atWpFZWVlo8UuIiKZU9JsgMMPP5yFCxeyaNEitm7dyqRJkzjppJNq57dt25YFCxZQUVFBRUUFRxxxBH/6058oLy9n0aJFtR1/lixZwoIFC+jatWu+VkVERGJo9KRpZt82s/fMbLOZzTSzITHfN9jMtpnZnKTpF5uZp3i0TLesbGnatCnjxo1jxIgRDBw4kNNPP50+ffowduzYlB2CEs2YMYMhQ4YwdOhQLrjgAn75y1/SoUMHAC699FJOPPFEFixYQL9+/XjooYdyvSoiIhKDpWqXy9k/MzsHeBj4NvDP6O8lQF93X1zH+9oBM4H5QGd3758w72Lg98AXEt/j7h/UF095eblPnTo18xUREZFdVvv27We6+xGp5jX2meYo4H53v9vdK939u8AK4Ip63ncv8AAwPc18d/cPEh9ZjFlERARoxKRpZs2BAcDzSbOeB9IOfWNm3wY6Aam7oAZ7mtkiM1tqZk+bWXmDAxYRkaza2RHU1q5dy6mnnkqXLl247rrrtis7YsQIhgwZwqBBgxg1ahTV1dU5XYfGvDBwX6AJsDJp+krguFRvMLNDgBuBge5enXg5R4J5wNeBCqANcDXwipmVufv8FMu8DLgMoKSkhFmzZgGhJ2yrVq1YsGABAHvvvTc9evSo/dKaNGlCWVkZ8+bN45NPPgHCqD5r165l5cqwSgcccADNmzdn4cKFALRr146uXbtSUVEBQLNmzTjkkEOorKzk008/BaBv376sWrWKVatWAdCtWzfMjPfffx+ADh06UFJSwpw5oSm3RYsW9OvXj7lz57JlyxYA+vfvz4oVK1izZg0A3bt3x91ZtGgRAB07dqRjx4688847AOy555706dOHt99+m6qqKgDKyspYvHgxH330EQA9evRg69atLF26FID999+f9u3b1/bwbd26Nb1796aioqJ2Iy0vL2fhwoWsW7cOgJ49e7Jp0yaWL19Ozefdtm1b5s2bB0CbNm046KCDmD17Nu6OmVFeXs78+fPZsGEDEHoWr1+/vvb6V31P+p70PRXn9zRnzhyuvvpqbrnlFoYOHcoJJ5xAt27dah8139OmTZv4zW9+w+GHH867776Lu/PZZ58xevRo/v73v7NgwQJmzZpV+z1dffXVtG7dmm7duvGd73yH8ePHM2zYsAZ9T3VptDZNMysFlgFD3f3lhOk3Aue5+8FJ5VsAs4BfuPtD0bQxwIjENs0U/6cJ8CbwortfVVdMatMUEWkcr7/+OrfccgsTJ04E4Fe/+hUA11xzzXblbrjhBo499lh+97vf8ZOf/ITy8s8rDh955BHefPNNxo0bt8Pyq6qquPDCCznrrLM444wzGhRrobRprgaqCVWtifZjx7NPgBKgL/DHqNfsNuDHQL/o9Qmp/om7VwNvAAdlLXIREWmQho6gVpczzzyTXr16sddee3HaaadlJd50Gi1puvtWQg/Y45NmHQ+8muIty4BDgMMSHncCC6Lnqd6DhTrcQwkdjEREpAA0dAS1ukycOJHKykq2bNnCtGnTGhRnfRp7sNPbgYfM7HXgFeByoJSQDDGzBwHc/UJ3rwKSr8n8ENji7nMSpt0IzCBcjtIWuIqQNOvrkSsiIo0kkxHUAD788ENGjhxZOyBMfVq2bMnJJ5/M5MmTGTZsWPZXINKoSdPdHzWzDsAPCdWvc4BT3H1RVGRnhsTZB7iLUO27DphNaDd9PQshi4hIFiSOoFZSUsKkSZO46667aufXjKBWY/jw4Tu0aSbbuHEjGzdupFOnTmzbto0XXniBQYMG5XQ9Gv22Gu5+B3BHmnnH1vPeMcCYpGnXANekKi8iIoUhcQS16upqRo4cWTuCWnl5OSeffHKd7y8rK2PDhg1UVVXxzDPPMHHiRNq3b8/IkSPZsmUL1dXVDB06lEsuuSSn69GoIwIVGvWeFRGRZIXSe1ZERKSoKWmKiIjE1Ohtmrui6x5ol9Plj7voo5wuX0RE4tGZpoiISExKmiIiIjEpaYqIiMSkpCkiIhKTkqaIiEhMSpoiIiIxKWmKiIjEpKQpIiISk5KmiIhITBoRSEREGsWuMHqazjRFRERiUtIUERGJSUlTREQkJiVNERGRmJQ0RUREYlLSFBERiUlJU0REJCYlTRERkZiUNEVERGJS0hQREYlJSVNERCQmJU0REZGYlDRFRERiUtIUERGJSUlTREQkJiVNERGRmJQ0RUREYlLSFBERiUlJU0REJCYlTRERkZiUNEVERGJS0hQREYlJSVNERCQmJU0REZGYlDRFRERiUtIUERGJSUlTREQkJiVNERGRmJQ0RUREYlLSFBERiUlJU0REJCYlTRERkZiUNEVERGJS0hQREYlJSVNERCQmJU0REZGYlDRFRERiUtIUERGJSUlTREQkJiVNERGRmDJKmmZ2tpmdkPD6x2a21MyeM7OS7IcnIiJSODI90xxT88TMDgdGA78BmgG3ZS8sERGRwtM0w/LdgHnR868Cf3H3cWb2PPBcViMTEREpMJmeaW4G2kTPvwxMiZ6vS5guIiKyS8r0TPNl4DYz+ydwBDAimt4LWJLNwERERApNpmeaVwJbCcnycndfHk0/GVXPiojILi6jM013XwoMTzH9e1mLSEREpEBlfJ2mmbU0sxFmdr2Z7RNN+4KZtc9+eCIiIoUjozNNM+tJ6PyzF7AP8DjwMXBF9PrSbAcoIiJSKDI90xwPPA/sD3yaMP2vwLBsBSUiIlKIMu09exQw0N2rzSxx+mKgNGtRiYiIFKCdGXu2WYppXQnXaoqIiOyyMk2azwOjEl67mbUFbgKeyVpUIiIiBSjT6tlRwItmNg9oCTwK9ARWAmdnOTYREZGCktGZZjSYwWHALcAE4A3gOuBwd18VZxlm9m0ze8/MNpvZTDMbUkfZY8zsVTNbY2afmtm7ZnZtinJnmtk7ZrYl+vvVTNZLREQkjkzPNHH3T4H7okdGzOwc4NfAt4F/Rn8nm1lfd1+c4i0bCXdReRvYBBwNTDCzTe5+R7TMQYQz3huBScAZwONmdrS7v5ZpjCIiIunUmzTN7Azgb+5eFT1Py90n1bO4UcD97n539Pq7ZnYS4TrPG1IsbyYwM2HSe1EMQ4A7omnfA150959Fr39mZsOi6efVE4+IiEhscc40nwA6AR9Gz9NxoEm6mWbWHBgA3Jo063nCpSz1MrPyqOyYhMmDgN8mFX2OME6uiIhI1tSbNN19j1TPd8K+hKS6Mmn6SuC4ut5oZkuBjoR4b3L3OxNmd0qzzE5plnUZcBlASUkJs2bNAqC0tJRWrVqxYMECAPbee2969OjB7NmzAWjSpAllZWXMmzePTz75BIA+ffqwdu1aoF1d4TfY1q1bmTNnDgAtWrSgX79+zJ07ly1btgDQv39/VqxYwZo1awDo3r077s6iRYsA6NixIx07duSdd94BYM8996RPnz68/fbbVFVVAVBWVsbixYv56KOPAOjRowdbt25l6dKlAOy///60b9+eyspKAFq3bk3v3r2pqKiguroagPLychYuXMi6deHqo549e7Jp0yaWLw/j+peUlNC2bVvmzQu3ZG3Tpg0HHXQQs2fPxt0xM8rLy5k/fz4bNmwAoHfv3qxfv54VK1YADfueVq4Mm8kBBxxA8+bNWbhwIQDt2rWja9euVFRUANCsWTMOOeQQKisr+fTTMIZH3759WbVqFatWhab7bt26YWa8//77AHTo0IGSkhJ9T/qe9D3V8T3FPD/aaWvWrMnK91QXc/fYAZnZUOBVd9+WNL0JcLS7T6vjvaXAMmCou7+cMP1G4Dx3P7iO9x5IGLpvIKET0tXu/lA0byvwjZrX0bSLgAnu3rKu9SkvL/epU6fWVSSW6x7IbdIcd9FHOV2+iEhjKJZ9Zfv27We6+xGp5mXaEehFoIRQVZton2he2upZYDVQzY5ngPux45nidtz9vejp22a2P6F6tiZJfrAzyxQREclUptWtRmi7TNYB+KSuN7r7VkKnnuOTZh0PvJpBDHsALRJeT8/CMkVEROoV60zTzP4aPXXgYTPbkjC7CdCfeEnqduAhM3sdeAW4nDBm7Z3R/3kQwN0vjF5/F3gPmBe9fyhwLZ/3nIVwCcs0M7sBeBL4KmHw+MFx1k1ERCSuuNWza6K/BnzE9nc42Uq45vLu5Dclc/dHzawD8ENCNe8c4BR3XxQV6Zr0liaENszuwDbgP8APiJJstMxXzexc4GbCcH7/Ac7RNZoiIpJtsZKmu18CYGbvA7e6e51VsfUs6w62P1NMnHds0uvxhNuR1bfMJ6j7chgREZEGy6gjkLvflKtARERECl2cEYHeAo5x94/M7G1SdwQCwN0PzWZwIiIihSTOmeZEoKbjj6pARURktxVnRKCbUj0XERHZ3TRkWDwREZHdSpw2zTrbMROpTVNERHZlce9yIiIistvLqE1TRERkd6Y2TRERkZh0naaIiEhMuk5TREQkJl2nKSIiElOmN6EGwMy+APSJXla6+3+yF5KIiEhhyihpRrf1uhc4Ffjs88n2NPB1d1+T9s0iIiJFLtPes/cAPYEhQMvoMRQ4kBj30xQRESlmmVbPngh82d2nJ0x7xcy+BUzJXlgiIiKFJ9MzzVVAqhtQbwJUNSsiIru0TJPmT4DxZta5ZkL0/LZonoiIyC5rZwZsPxB438yWRa87A5uB/QhtniIiIrskDdguIiISkwZsFxERiUkDtouIiMSUUdI0s+ZmdpOZ/dvMNptZdeIjV0GKiIgUgkzPNH8KXEToLfsZ8D/A7wmXm3w7u6GJiIgUlkyT5tnA5e4+AagGnnL3q4AbgeOzHZyIiEghyTRp7g+8Ez3fCOwTPf9/wAnZCkpERKQQZZo0FwOl0fMFhGH1AAYBn2YrKBERkUKUadJ8Evhy9PzXwE1m9h5wPxrYQEREdnEZDdju7jckPH/CzJYCRwH/dvensx2ciIhIIdmpm1DXcPcZwIwsxSIiIlLQMh7cwMwON7MHzeyN6PGQmR2ei+BEREQKSaaDG4wE/gWUAM9Gj/2B183s/OyHJyIiUjgyrZ79GfAjdx+bONHMbgBuBh7OVmAiIiKFJtPq2Y7AYymmP064NZiIiMguK9Ok+SJwbIrpxwIvNTQYERGRQhbnJtRnJLycDPzczI7g816zA4EzgDFZj05ERKSA7OxNqC+LHol+C9zR4IhEREQKVJybUOuemyIiIugm1CIiIrHtzOAGXzGzaWa22sxWmdlLZnZKLoITEREpJJkObnApYdD2/wDXAz8A3gOeNLOvZz88ERGRwpHp4AbXA6Pc/XcJ0+41s5mEBHpf1iITEREpMJlWz3Yl3HA62WSgW8PDERERKVw7cxPq41NMPwFY1PBwREREClem1bO3Ar+N7mryKuDAYOAC4LtZjk1ERKSgZHoT6glm9iHwfcIoQACVwNnu/lS2gxMRESkksZOmmTUlVMNOc/cncxeSiIhIYYrdpunu24BJQJvchSMiIlK4Mu0IVAH0zEUgIiIihS7TpDkGuM3MTjezLmbWPvGRg/hEREQKRqa9Z5+J/k4i9JytYdHrJtkISkREpBBlmjSH5SQKERGRIhAraZpZK+CXwOlAM2AKcJW7r85hbCIiIgUlbpvmTcDFhOrZ/yOMCvSHHMUkIiJSkOJWz54BfMPd/wxgZn8CXjGzJu5enbPoRERECkjcM80uwMs1L9z9dWAbUJqLoERERApR3KTZBNiaNG0bmXckEhERKVpxk54BD5vZloRpLYG7zWxTzQR3PzWbwYmIiBSSuEnzgRTTHs5mICIiIoUuVtJ090tyHYiIiEihy3QYPRERkd2WkqaIiEhMSpoiIiIxKWmKiIjEpKQpIiISk5KmiIhITEqaIiIiMSlpioiIxNToSdPMvm1m75nZZjObaWZD6ihbYmaPmNm7ZlZtZvenKHOxmXmKR8ucroiIiOx2GjVpmtk5wK+BsZwoczwAABtHSURBVEA58Cow2cy6pnlLC2A18AvgtToWvQkoSXy4++ZsxS0iIgKNf6Y5Crjf3e9290p3/y6wArgiVWF3f9/dr3L3+4G1dSzX3f2DxEf2QxcRkd1doyVNM2sODACeT5r1PHBUAxe/p5ktMrOlZva0mZU3cHkiIiI7aMz7Ye5LuC/nyqTpK4HjGrDcecDXgQqgDXA18IqZlbn7/OTCZnYZcBlASUkJs2bNAqC0tJRWrVqxYMECAPbee2969OjB7NmzAWjSpAllZWXMmzePTz75BIA+ffqwdu1aoF0Dwq/f1q1bmTNnDgAtWrSgX79+zJ07ly1bwp3a+vfvz4oVK1izZg0A3bt3x91ZtGgRAB07dqRjx4688847AOy555706dOHt99+m6qqKgDKyspYvHgxH330EQA9evRg69atLF26FID999+f9u3bU1lZCUDr1q3p3bs3FRUVVFdXA1BeXs7ChQtZt24dAD179mTTpk0sX74cCJ9327ZtmTdvHgBt2rThoIMOYvbs2bg7ZkZ5eTnz589nw4YNAPTu3Zv169ezYsUKoGHf08qVYdM74IADaN68OQsXLgSgXbt2dO3alYqKCgCaNWvGIYccQmVlJZ9++ikAffv2ZdWqVaxatQqAbt26YWa8//77AHTo0IGSkhJ9T/qe9D3V8T01/PyobmvWrMnK91QXc/ccrkLCPzIrBZYBQ9395YTpNwLnufvB9bz/aWC1u19cT7kmwJvAi+5+VV1ly8vLferUqTHXIL3rHsht0hx30Uc5Xb6ISGMoln1l+/btZ7r7EanmNWab5mqgGuiUNH0/djz73GnuXg28ARyUrWWKiIhAIyZNd98KzASOT5p1PKEXbVaYmQGHEjoYiYiIZE1jtmkC3A48ZGavA68AlwOlwJ0AZvYggLtfWPMGMzssetoW+Cx6vdXd34nm3wjMAOZHZa4iJM2UPXJFRER2VqMmTXd/1Mw6AD8kXE85BzjF3RdFRVJdrzk76fVwYBHQPXq9D3AXodp3XVR+qLu/nt3oRURkd9fYZ5q4+x3AHWnmHZtimtWzvGuAa7ISnIiISB009qyIiEhMSpoiIiIxKWmKiIjEpKQpIiISk5KmiIhITEqaIiIiMSlpioiIxKSkKSIiEpOSpoiISExKmiIiIjEpaYqIiMSkpCkiIhKTkqaIiEhMSpoiIiIxKWmKiIjEpKQpIiISk5KmiIhITEqaIiIiMSlpioiIxKSkKSIiEpOSpoiISExKmiIiIjEpaYqIiMSkpCkiIhKTkqaIiEhMSpoiIiIxKWmKiIjEpKQpIiISk5KmiIhITEqaIiIiMSlpioiIxKSkKSIiEpOSpoiISExKmiIiIjEpaYqIiMSkpCkiIhKTkqaIiEhMSpoiIiIxKWmKiIjEpKQpIiISk5KmiIhITEqaIiIiMSlpioiIxKSkKSIZmzJlCkceeSQDBgxg/PjxO8zfsmULX//61xkwYADHHXccixcvBmDmzJkMHTqUoUOHMmTIEJ5++unt3lddXc0xxxzDueee2yjrIZIpJc3dXLZ3fkuXLuXUU0/lS1/6EoMGDeLOO+9s1PWR3Kuurua6667jscceY/r06UycOJF33313uzIPP/ww++yzDzNnzuSKK65gzJgxAPTp04epU6cybdo0Hn/8cUaNGsW2bdtq33fnnXfSq1evxlwdkYwoae7GcrHza9q0KT/96U957bXXeP7557n33nt3WKbk5kytvmVmy8yZMznwwAPp3r07zZs354wzzmDy5MnblXn22WdrzxZPO+00pk2bhrvTqlUrmjZtWruOZlb7nmXLlvHCCy9wwQUX5Cx2kYZS0tyN5WLn16lTJ8rKygBo06YNvXr1YsWKFY24VoUvFwcrcZaZLStWrKBz5861r0tLS3f4jhPLNG3alLZt27J27VoA3njjDQYNGsTgwYO57bbbarej0aNHM2bMGPbYQ7slKVzaOndjudr51Vi8eDFvvfUWAwYMyPGaFJdcHKzEWWa2uPsO0xLPGOsrc8QRRzB9+nSmTJnC+PHj2bx5M8899xwdO3bksMMOy0nMItmipLkby8XOr8bGjRu56KKLGDt2LG3bts1y5MUtFwcrcZaZLaWlpSxbtqz29fLly+nUqVPaMtu2bWP9+vW0a9duuzK9e/emVatWVFZW8tprrzF58mTKysq49NJLefnll/nWt76Vk/hFGkJJczeWi50fQFVVFRdddBEjRoxg+PDhOV6L4pOLg5U4y8yWww8/nIULF7Jo0SK2bt3KpEmTOOmkk7Yrc/LJJ/PnP/8ZgKeeeoohQ4ZgZixatKi248+SJUtYsGABXbt25cc//jFz586loqKCe+65hyFDhjBhwoScxL+z7ckvvvgiw4YN4+ijj2bYsGFMmzat9j0jRoxgyJAhDBo0iFGjRlFdXZ2T2CX/lDR3Y7nY+bk7V111Fb169eI73/lOo69TMcjFwUqcZWZL06ZNGTduHCNGjGDgwIGcfvrp9OnTh7Fjx9ZWCZ9//vmsXbuWAQMG8Ic//IEbb7wRgBkzZjBkyBCGDh3KBRdcwC9/+Us6dOiQkzhTaUh7cocOHXjkkUd45ZVX+P3vf88VV1xR+5777ruPl19+mVdffZXVq1fzl7/8JSfx5yLh33zzzfTv358uXbrkJOZdTdP6i8iuKnHnV11dzciRI2t3fuXl5Zx88smcf/75XH755QwYMIB27dpxzz33AGHnN378eJo1a8Yee+xRu/ObMWMGjz76KH379mXo0KEA/OhHP+L444/P56oWlMSDlZKSEiZNmsRdd921XZmag5Ujjzxyh4OVzp0707Rp0+0OVvbee+96l5lNxx9//A7f6ejRo2uft2zZkvvvv3+H951zzjmcc845dS578ODBDB48OCtxJkts+wVq234PPvjg2jLPPvss119/PRDak6+//nrcnUMPPbS2TJ8+fdi8eTNbtmyhRYsWtU0Q27Zto6qqKidn+TUJf9KkSZSWlvLlL3+Zk046abvYExP+xIkTGTNmDPfdd19twi8pKeGdd97hrLPOYu7cuQCceOKJXHrppXzxi1/Mesy7IiXN3Vy2d34DBw6sbXuT1HJxsAKkXKZsL1Xb78yZM9OWSWxPTjwj/utf/8qhhx5KixYtaqedeeaZzJo1i+OOO47TTjst67HnKuErWWZGSVMkD3JxppZqmbK9hrYnA1RWVnLTTTcxceLE7cpMnDiRzZs3c9lllzFt2jSGDRuWpaiDXCZ8iU9JU4rWlClTGD16NNXV1VxwwQV873vf227+li1buOKKK6ioqKBdu3bcd999dO3albVr13LxxRcze/ZszjvvPMaNG1f7nuHDh7Ny5UpatmwJhB1hx44dG3W9isF1D7Srv1ADjLvoo5wsN5P25M6dO+/Qnrxs2TIuvPBC7rjjDg488MAdlt+yZUtOPvlkJk+enPWkmcuEL/Epae7minXn15D2nRYtWjB69GgqKytre/wmmjBhAuXl5TmJW/KrIe3J69at49xzz+VHP/oRAwcOrC2/ceNGNm7cSKdOndi2bRsvvPACgwYNynrsuU74Eo+SphSlhrTvtG7dmoEDB7Jw4cJ8hF6rWA9YillD2pPvvvtu3nvvPW699VZuvfVWINREuDsjR45ky5YtVFdXM3ToUC655JKsx56LhC+ZU9KUopSt9p1UrrzySpo0acLw4cO59tprc3a9o+THzrYnX3vttVx77bUpl/n3v/89qzGmkouE37FjR2688UaeeOIJNm3aRL9+/bjgggv4wQ9+kPP1KVZKmlKUstG+k8qECRMoLS1lw4YNXHTRRTz66KO6TZUUjFwk/Jtuuombbropq3HuyjS4gRSlbA0QkGq5EAabHzFiBLNmzcpy5CJSzHSmKUWpIe076Wzbto1169bRoUMHqqqqeO655zj22GNzvCaSD7lsT1Zb8q5NSVOKUkPadwDKysrYsGEDVVVVPPPMM0ycOJEuXbowYsQIqqqqqK6u5phjjuHCCy/M41qK7EgdyPJLSVOK1s627wBUVFSknP7iiy9mLT4R2fWoTVNERCQmnWlKUVPblIg0Jp1pioiIxKSkKSIiElOjJ00z+7aZvWdmm81sppkNqaf8MVG5zWa20Mwub+gyRUREdkajJk0zOwf4NTAWKAdeBSabWdc05Q8Eno3KlQM/B35rZmfu7DJFRER2VmOfaY4C7nf3u9290t2/C6wArkhT/nJgubt/Nyp/N/AAkDgeVKbLFBER2SmNljTNrDkwAHg+adbzwFFp3jYoRfnngCPMrNlOLlNERGSnNOaZ5r5AE2Bl0vSVQKcdi0M0PVX5ptHydmaZIiIiO8VS3QkiJ//IrBRYBgx195cTpt8InOfuB6d4z7+Bh9z9pwnTjgH+AZQQkn6my7wMuCx62RuY1/C1y9i+wOo8/N9sUOz5U8zxF3PsUNzxK/bMdXP3jqlmNObgBquBanY8A9yPHc8Ua3yQpvw2YA1gmS7T3e8C7ko1r7GY2RvufkQ+Y9hZij1/ijn+Yo4dijt+xZ5djVY96+5bgZnA8Umzjif0eE1lOnBcivJvuHvVTi5TRERkpzT2MHq3Aw+Z2evAK4TesaXAnQBm9iCAu9fcWuJO4EozGw9MAI4GLgbOi7tMERGRbGnUpOnuj5pZB+CHhDbJOcAp7r4oKtI1qfx7ZnYK8CvCJSTLgavcfWIGyyxEea0ebiDFnj/FHH8xxw7FHb9iz6JG6wgkIiJS7DT2rIiISExKmiIiIjEpaeaBmVm+YxARkcwpaeaBqyE5L3SwIiINpY5AjcTMWgCHAl8F1gFzgQXAYnffZGamZNo49Fk3PjPbw90/y3ccu6PEz17bfsMpaTYSM/sNcAbhDiztgO6ES2ieBH7j7v/JX3TxmFkTwolyUe38zGwvYChwLvARMB/4N/C2u6/IZ2xxmVlT4LNi++ylMJhZG3ffkO84dgVKmo3AzPoCM4ARwEx3X2NmHYFvAN8iDAN4NXB3IR4FmtkAd5+ZNK0JYSdecPEmM7MHCElzPuGApQvwMTALuMfdp+YxvDqZ2WB3/2fStKJJoGbWBfg68EXgP4SxnucQDlg+KtQzn8S4iunzTmRmfQi3TiwnqtUC3gRedvclUZmC/PwLmZJmIzCz0cBJ7j40et3U3bclzB9LOAv9L3dfnqcwUzKzgwg7uncIt1x7yN1nJ8w3wiAZ5cCb0dCGBSM6YHmNMLTiv9y92sz2Bs4Gvkm4tdxPgJspsIMAMzuY8Ll/AjwD/NbdX0mYb0Az4ETgdXdPN4ZzXkQ3kZ8I7An8C+hPGBd6LTAN+FWh1rBEB7V93H1awjQj3FWpupC2k1TM7AvAs4QxuF8BDiYcnLcgJNB73D35looFwcz2J/xen3X3tXWUa+buVY0XWaCOQI2jEigxs54A7r7NzJqaWcto/t3AJuCsfAVYh/MIZwgvAAOBp81shpldZ2Zdop3HfoQz6f3yGGc6JwBvufuMKGE2d/d10U3LjwS+A1wKfKEAd4RnABXAWKAz8JKZfWBmt5pZTbz7AE8BzfMYZzrXE+5CNMzdL3T3wwn3uX0EGA7MMLPT8hlgHcYA/4g+79+bWV8Ptrm7m9keZtbVzM6Kal0KzbWEJoivuPsN7v5V4HTgt4Tk+aSZfSOfAdbhh8CDwAIze9zMTon6hNQys67A1cnTG4OSZuOYRrgzy9NmdraZtYh+fJshDBdIOILdnM8g0+hNOGK9hXBmNppQvXY+MN3M/kYYF7jS3ZfmLcr0KoCuZvZlCDcOiA5Y9ozmPw4sYvvxjAtFZ8JZwgTgNOC/gPuArwDzzewt4M+Ez35J3qJMrx8wzd0/iG4a39TdF7v7L9y9GzAFuDxKQIXWs/mLhPGr/wAMBuaY2QIzG21m7aOq2ouAW9y9Op+BptENmOXuG8ysiZk1cfeV7v7HqMbrTuCbZtYqz3GmcgRhf/N9QnPKk8B7ZvZbMzs8KvNN4HJ339Lo0bm7Ho3wIAwi/yifV3P+lLAT7AX8GlgFtM53nEkxNwW+BtyQNL09MAi4EngM+Az4Rr7jTbMOLQlnySsIg/nvmaLMm8B38h1rUkxNgFOAbydNb04Yo/m/CTUUnwGX5DveNOswJvps2yRMa1bzHRCS0X+AgfmONSnubsBzhJtD7EE4eDkR+D2hXfAzwsHMWuCafMebZh2ujmI9OGnbaR497wu8R6gFyHu8CTGWEg5kL4teNyVULV8fbUvVwNuEJour8xGj2jQbUTSw/FcIVYY9CGdx7YCXgAnu/uc8hlevVG0IZnYG8ASwl7tvyk9kdYvOKn9G6Ij1KaEq+SlgI3AJYefdu1Djh9SXbJjZicBkCvSzN7MBwN8I98Ud4+5/TZrfm1AT0L6Q4jeztoRLw95395cSpu9J2KkPAL5N2G7auPuneQm0DlF78iRC9f1P3f2+pPn9CR3h9imwz7414WTiQ3d/LWleK0K7+LWEpou8fPZKmjlmZgcAPaOXnxDOND8lJM29CG2Zq72OBu98SXdtXdSbsNrd3cxuBY5w92MbPcAYomqp6uiyk8HAEOBLhCqgPQhVhPe4+7N5DHMHUXWlpfr8E8qMAQa5+4mNFlhMNb0yo3b8cYT28NXAPwmJvi9wJiExnZ2/SOtW0/nHEzruRdP/BHQu1O0ewmUmwM+BkYQz/OcJ23t/wm/hTf/8NowFKVXvXjO7n9AHYUheYlLSzB0zu4LQ3b6MkBwXAkuAfwBPeGG2Q9VKSPhGqJKa5+4fJMw3QlvbMnf/V36izIyZNQc6Eg5cWgLr3P2T/Ea1c8zsWGCVu8/Ndyx1iTq8HRc9vkRo61wD3EvojV3It/EDtu85S+gNPA34uSfcprBQRLHuER0stgQOIVxy9V/A4YRq2YeBSYm/50JgZnsQrgVPmZiis/2ngD+4+5ONGlxNDEqauRFVxS4AbiN0JuhI2GkMIxxlLyPcG/SdQrxWKinhf0JYl6XAdOApd5+Xx/DqZWZ7Jlbd1PdjLCTJsReb6LM+jbDN70lot5zm7uujnbgTqtZW5zHMlJJib0X4nb7k7h8mlGkBHOfuz+QnysxZwnXVZra3u6/Ld0w7w8yaEWq2pucthiLYhxQlM/sucL67fynFvMGEapPOwJGFtvOoJ+EfTNiRfC9K+E28wHoPmlk7QlvZM4Qj6ldrkmVi8rRw8fdSL6CRUuqJPfGC+z7ACnf/OG/BphBVCd5L2FY+I2wrRjjwmgL8yd3nR2ULami9FLEvJST4Twn9Dh5293fzF2HdooRyILDIU/QqLcSD8xr1xV5IdMlJ7mwF2kQN7phZi6hqEA8jvIwkXGJyQv5CTOtrwL/d/WZ3X+Pu77r779z9TMIIRnsSLp/Zt9ASZuR8YH9Ch41phOu9fmJmvd295mi7C+F6wY75DDSFumKvSZg1sbfPX5hpXUXo4HaKu+9P2JZuI1ymNBy43cLAARRSwowkxz4SGE8YJ/pEYFxN7AXqO8Bs4E4zG25mnRKvIY22+7ZmdnKUpApJnbFD6KBlZl+p2Y/mi840cyQ6W3uJ0FPzmpqzGdt+8ORXgb+4+7j8RbojM/sWocv62e4+J6qOco9G+7FwYfH/A25290fyGGpKZnY3oe3px4QLuc8j9JztQRiZ5j6gA/C/7r5XvuJMpZhjBzCzl4En3f32pOlNgKMJZ3L/cfeT8hFfXYo5dgAzm044EG9KGERiMeEax0mEYQvXmdnlwMXuPjB/ke6omGLXmWYORA3xawkjWxwPLDeze6Mu+FgYSeR8QgP9Y/mLNK0nCNVT37Mw0PMWD4MC7AHg7osJY7cekM8gU4kS/DvAEnf/0N3fcvcbCL1lT4zmjSFcgnJL3gJNoZhjh9pe1XOAM2vOyOzzC+urPQxJdzlwgJmV5TPWZMUcO9QO+1dFGL96COFa03sJ1/NOA6aa2fXA9wjDShaMoovdC+CC1l31QbhG6lDCj+05wnWBGwnthQsJ167lPc6kmC16nE4YKWcDYQMeQDjI6kqoQtwAdM93vGnWoQXQKXrehNCTMHH+sYSDggPyHeuuFHsU30BCx59bgP1TzO8S/QY65zvWXSz2EuAa4MQU88oJAzOsibadgoq/2GJX9WyWmdl+wAWEIaBWEzoRfAy8TDhKagZ8gZBE53uBfgFmtg8hQR5FuND76GjWB4Tk+aC7j8lPdOklXB/YA/jEEwYxT5j3Y0I1T4/8RbqjYo4dajtZ7UEYMGIsoartCcJIWEsIB5DDCQOhfzFfcaZSzLHXiC7HcHffHNV2AZ/f9N7MfkZory3PV4zpFFPsSppZZuHC236EkVDWEjprHEIYLu9D4IeeNNJFoSj2hJ8Q/yjCZ72NMHze44Rr0j6JfpDfBJa7+9N5CzZJMceeSnTQdTGhI9BhhJqJLcDrhOsbC/I3AEUfe8oeshZG05kF/NHdC65qH4ondiXNLIp2ahsIR0TTEqZ1JVT9fIPQoeNsd5+Vt0DTKOaED2njLydcJrMU+KUX7u2Q7qdIY4faoec2JO70orO3loSRr/oTzp4Lbvsp5tghdfwpyrQEzgH+zwvo9n3FGLuSZhaZWT/CXSe+6e4zUsxvQRjo+QUPHTwKxi6Q8NPF34UwCs03CR0Mziu0+Is59hpmNoFwJvY64Vq79SnKtPMCvPF0MccOsePfxwvsml4o0tjz3ai6Kz0I1y/+nTBqzkEkdeKIynyXMOZj3uNNiqsf4e4BKe84Qeig8gaheirv8e5E/M0LNf5ijj2K7zxCJ42PCR3cJhAG1O7J53c02Qv4C3BIvuPdVWKvI/6vEppRauKvGXquf77j3RVi15lmlpnZQMK96j4lbAR/B9Z6aJNqRbi56mZ3Pz+PYe4gaoh/mjB02IWE69GS76rxXcItwA7LQ4h1Kub4izl22O7a0nGEhHMRYcc3j3Av1r8TBg34tbsX1M2yizl2KO74izV2Jc0csDAK0I+AUwnDh00n3C/zOELnjkvd/e38RZhasSb8GsUcf7HGHl3feB3Q1t1/kDC9H6FaeQShbXAf4AF3/0ZeAk2hmGOH4o6/qGNX0sydqEfkVwjXPG4mXDz9uBf2+JVFmfBrFHP8xRq7hfFy93f3dy0McVblCTsWMzsH+D/gcHd/M19xplLMsUNxx1+ssStpNhIrsMGp61OMCT9RMcdfzLHXiHqfmofbU32TUMXWKt9xxVHMsUNxx18MsStpSr2KLeEnK+b4izn2GmY2inAj51/mO5ZMFXPsUNzxF2rsSpoiklMW7qhRXYzJv5hjh+KOv1BjV9IUERGJSXc5ERERiUlJU0REJCYlTRERkZiUNEVERGJS0hQREYlJSVNERCSm/w/cZ6ui5TmU6AAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get the basis gates for the noise model\n",
    "basis_gates = noise_model.basis_gates\n",
    "\n",
    "# Select the QasmSimulator from the Aer provider\n",
    "simulator = Aer.get_backend('qasm_simulator')\n",
    "\n",
    "# Execute noisy simulation and get counts\n",
    "result_noise = execute(circ, simulator, \n",
    "                       noise_model=noise_model,\n",
    "                       coupling_map=coupling_map,\n",
    "                       basis_gates=basis_gates).result()\n",
    "counts_noise = result_noise.get_counts(circ)\n",
    "plot_histogram(counts_noise, title=\"Counts for 3-qubit GHZ state with depolarizing noise model\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Cloud Simulator\n",
    "\n",
    "It is also possible to run noisy simulations on the `ibmq_qasm_simulator`, which is hosted online, and is part of the `IBMQ` provider."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-19T16:57:46.160483Z",
     "start_time": "2019-08-19T16:57:38.913520Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Select the ibmq_qasm_simulator from the IBMQ provider\n",
    "simulator = provider.get_backend('ibmq_qasm_simulator')\n",
    "\n",
    "# Execute noisy simulation and get counts\n",
    "result_noise = execute(circ, simulator, \n",
    "                       noise_model=noise_model,\n",
    "                       coupling_map=coupling_map,\n",
    "                       basis_gates=basis_gates).result()\n",
    "counts_noise = result_noise.get_counts(circ)\n",
    "plot_histogram(counts_noise, title=\"3-qubit GHZ state with depolarizing noise model on IBMQ qasm simulator\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Comparison to the real device\n",
    "\n",
    "Now we will execute the circuit on the real device to see the effect of the actual noise processes on the output counts. Note that this execution may take some time to return the results."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-19T17:12:16.614580Z",
     "start_time": "2019-08-19T16:57:46.194353Z"
    },
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# Submit job to real device and wait for results\n",
    "job_device = execute(circ, device)\n",
    "job_monitor(job_device)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-19T17:12:16.619630Z",
     "start_time": "2019-08-19T16:57:41.471Z"
    }
   },
   "outputs": [],
   "source": [
    "# Get results from completed execution\n",
    "result_device = job_device.result()\n",
    "counts_device = result_device.get_counts(0)\n",
    "plot_histogram(counts_device, title='Counts for 3-qubit GHZ state on IBMQ device: {}'.format(device.name()))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You might notice that the counts returned in the above histogram don't look exactly like our simulation. This is because the real errors that happen on a device can be very complicated, and characterizing them to create accurate models is an active area of quantum computing research. The *basic device noise model* we used for our simulation is a simplified error model that only takes into account *local* errors occurring on the qubits participating in each individual gate, and treats the errors as a relaxation process combined with an error operation which acts to randomize the state of the qubit with some probability *p* (the depolarizing probability). While this model is an approximation, due to its simplicity it is a useful starting point for studying the effects of noise on quantum computations."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For those who'd like to know what these noise model look like, here is one printed as a dictionary."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'errors': [{'type': 'qerror', 'operations': ['u2'], 'instructions': [[{'name': 'id', 'qubits': [0]}], [{'name': 'z', 'qubits': [0]}], [{'name': 'reset', 'qubits': [0]}]], 'probabilities': [0.9969396316915222, 0.0015878972318940962, 0.001472471076583659], 'gate_qubits': [[0]]}, {'type': 'qerror', 'operations': ['u2'], 'instructions': [[{'name': 'kraus', 'qubits': [0], 'params': [array([[0.99990007, 0.        ],\n",
      "       [0.        , 0.99894197]]), array([[-0.01413701,  0.        ],\n",
      "       [ 0.        ,  0.01415057]]), array([[0.        , 0.04375727],\n",
      "       [0.        , 0.        ]])]}]], 'probabilities': [1], 'gate_qubits': [[1]]}, {'type': 'qerror', 'operations': ['u2'], 'instructions': [[{'name': 'kraus', 'qubits': [0], 'params': [array([[0.99994709, 0.        ],\n",
      "       [0.        , 0.99925542]]), array([[-0.01028703,  0.        ],\n",
      "       [ 0.        ,  0.01029415]]), array([[0.        , 0.03718377],\n",
      "       [0.        , 0.        ]])]}]], 'probabilities': [1], 'gate_qubits': [[2]]}, {'type': 'qerror', 'operations': ['u2'], 'instructions': [[{'name': 'kraus', 'qubits': [0], 'params': [array([[0.99986217, 0.        ],\n",
      "       [0.        , 0.99913969]]), array([[-0.0166022,  0.       ],\n",
      "       [ 0.       ,  0.0166142]]), array([[0.        , 0.03799813],\n",
      "       [0.        , 0.        ]])]}]], 'probabilities': [1], 'gate_qubits': [[3]]}, {'type': 'qerror', 'operations': ['u2'], 'instructions': [[{'name': 'id', 'qubits': [0]}], [{'name': 'z', 'qubits': [0]}], [{'name': 'reset', 'qubits': [0]}]], 'probabilities': [0.9979199991897366, 0.000530684168841692, 0.0015493166414216608], 'gate_qubits': [[4]]}, {'type': 'qerror', 'operations': ['u2'], 'instructions': [[{'name': 'kraus', 'qubits': [0], 'params': [array([[1.        , 0.        ],\n",
      "       [0.        , 0.99785794]]), array([[0.        , 0.06541808],\n",
      "       [0.        , 0.        ]])]}]], 'probabilities': [1], 'gate_qubits': [[5]]}, {'type': 'qerror', 'operations': ['u2'], 'instructions': [[{'name': 'id', 'qubits': [0]}], [{'name': 'z', 'qubits': [0]}], [{'name': 'reset', 'qubits': [0]}]], 'probabilities': [0.9982046687483329, 0.000339407670128993, 0.001455923581538121], 'gate_qubits': [[6]]}, {'type': 'qerror', 'operations': ['u2'], 'instructions': [[{'name': 'kraus', 'qubits': [0], 'params': [array([[1.        , 0.        ],\n",
      "       [0.        , 0.99884553]]), array([[0.        , 0.04803762],\n",
      "       [0.        , 0.        ]])]}]], 'probabilities': [1], 'gate_qubits': [[7]]}, {'type': 'qerror', 'operations': ['u2'], 'instructions': [[{'name': 'id', 'qubits': [0]}], [{'name': 'z', 'qubits': [0]}], [{'name': 'reset', 'qubits': [0]}]], 'probabilities': [0.9982498630343064, 0.00013334675861594622, 0.001616790207077612], 'gate_qubits': [[8]]}, {'type': 'qerror', 'operations': ['u2'], 'instructions': [[{'name': 'kraus', 'qubits': [0], 'params': [array([[1.        , 0.        ],\n",
      "       [0.        , 0.99872734]]), array([[0.        , 0.05043514],\n",
      "       [0.        , 0.        ]])]}]], 'probabilities': [1], 'gate_qubits': [[9]]}, {'type': 'qerror', 'operations': ['u2'], 'instructions': [[{'name': 'kraus', 'qubits': [0], 'params': [array([[0.99986623, 0.        ],\n",
      "       [0.        , 0.99908843]]), array([[-0.01635625,  0.        ],\n",
      "       [ 0.        ,  0.01636898]]), array([[0.        , 0.03942552],\n",
      "       [0.        , 0.        ]])]}]], 'probabilities': [1], 'gate_qubits': [[10]]}, {'type': 'qerror', 'operations': ['u2'], 'instructions': [[{'name': 'kraus', 'qubits': [0], 'params': [array([[0.99990561, 0.        ],\n",
      "       [0.        , 0.99911444]]), array([[-0.01373927,  0.        ],\n",
      "       [ 0.        ,  0.01375015]]), array([[0.        , 0.03976508],\n",
      "       [0.        , 0.        ]])]}]], 'probabilities': [1], 'gate_qubits': [[11]]}, {'type': 'qerror', 'operations': ['u2'], 'instructions': [[{'name': 'kraus', 'qubits': [0], 'params': [array([[0.99997475, 0.        ],\n",
      "       [0.        , 0.99925175]]), array([[-0.00710566,  0.        ],\n",
      "       [ 0.        ,  0.00711081]]), array([[0.        , 0.03801801],\n",
      "       [0.        , 0.        ]])]}]], 'probabilities': [1], 'gate_qubits': [[12]]}, {'type': 'qerror', 'operations': ['u2'], 'instructions': [[{'name': 'kraus', 'qubits': [0], 'params': [array([[0.99992623, 0.        ],\n",
      "       [0.        , 0.99812104]]), array([[-0.01214615,  0.        ],\n",
      "       [ 0.        ,  0.01216811]]), array([[0.       , 0.0600527],\n",
      "       [0.       , 0.       ]])]}]], 'probabilities': [1], 'gate_qubits': [[13]]}, {'type': 'qerror', 'operations': ['u3'], 'instructions': [[{'name': 'id', 'qubits': [0]}], [{'name': 'z', 'qubits': [0]}], [{'name': 'reset', 'qubits': [0]}]], 'probabilities': [0.993891150654847, 0.003166075363056994, 0.0029427739820959697], 'gate_qubits': [[0]]}, {'type': 'qerror', 'operations': ['u3'], 'instructions': [[{'name': 'kraus', 'qubits': [0], 'params': [array([[0.99980055, 0.        ],\n",
      "       [0.        , 0.9978847 ]]), array([[-0.01997156,  0.        ],\n",
      "       [ 0.        ,  0.02000991]]), array([[0.       , 0.0618525],\n",
      "       [0.       , 0.       ]])]}]], 'probabilities': [1], 'gate_qubits': [[1]]}, {'type': 'qerror', 'operations': ['u3'], 'instructions': [[{'name': 'kraus', 'qubits': [0], 'params': [array([[0.99989433, 0.        ],\n",
      "       [0.        , 0.99851126]]), array([[-0.01453721,  0.        ],\n",
      "       [ 0.        ,  0.01455735]]), array([[0.        , 0.05256761],\n",
      "       [0.        , 0.        ]])]}]], 'probabilities': [1], 'gate_qubits': [[2]]}, {'type': 'qerror', 'operations': ['u3'], 'instructions': [[{'name': 'kraus', 'qubits': [0], 'params': [array([[0.9997248 , 0.        ],\n",
      "       [0.        , 0.99827975]]), array([[-0.02345883,  0.        ],\n",
      "       [ 0.        ,  0.02349279]]), array([[0.        , 0.05371807],\n",
      "       [0.        , 0.        ]])]}]], 'probabilities': [1], 'gate_qubits': [[3]]}, {'type': 'qerror', 'operations': ['u3'], 'instructions': [[{'name': 'id', 'qubits': [0]}], [{'name': 'z', 'qubits': [0]}], [{'name': 'reset', 'qubits': [0]}]], 'probabilities': [0.995844606408531, 0.0010591606906810173, 0.0030962329007879763], 'gate_qubits': [[4]]}, {'type': 'qerror', 'operations': ['u3'], 'instructions': [[{'name': 'kraus', 'qubits': [0], 'params': [array([[1.        , 0.        ],\n",
      "       [0.        , 0.99572047]]), array([[0.       , 0.0924161],\n",
      "       [0.       , 0.       ]])]}]], 'probabilities': [1], 'gate_qubits': [[5]]}, {'type': 'qerror', 'operations': ['u3'], 'instructions': [[{'name': 'id', 'qubits': [0]}], [{'name': 'z', 'qubits': [0]}], [{'name': 'reset', 'qubits': [0]}]], 'probabilities': [0.9964126759085354, 0.0006775966418634875, 0.0029097274496010517], 'gate_qubits': [[6]]}, {'type': 'qerror', 'operations': ['u3'], 'instructions': [[{'name': 'kraus', 'qubits': [0], 'params': [array([[1.        , 0.        ],\n",
      "       [0.        , 0.99769239]]), array([[0.        , 0.06789625],\n",
      "       [0.        , 0.        ]])]}]], 'probabilities': [1], 'gate_qubits': [[7]]}, {'type': 'qerror', 'operations': ['u3'], 'instructions': [[{'name': 'id', 'qubits': [0]}], [{'name': 'z', 'qubits': [0]}], [{'name': 'reset', 'qubits': [0]}]], 'probabilities': [0.9965028068293694, 0.00026622676704887835, 0.00323096640358167], 'gate_qubits': [[8]]}, {'type': 'qerror', 'operations': ['u3'], 'instructions': [[{'name': 'kraus', 'qubits': [0], 'params': [array([[1.       , 0.       ],\n",
      "       [0.       , 0.9974563]]), array([[0.        , 0.07128069],\n",
      "       [0.        , 0.        ]])]}]], 'probabilities': [1], 'gate_qubits': [[9]]}, {'type': 'qerror', 'operations': ['u3'], 'instructions': [[{'name': 'kraus', 'qubits': [0], 'params': [array([[0.99973293, 0.        ],\n",
      "       [0.        , 0.9981773 ]]), array([[-0.02311011,  0.        ],\n",
      "       [ 0.        ,  0.02314613]]), array([[0.        , 0.05573443],\n",
      "       [0.        , 0.        ]])]}]], 'probabilities': [1], 'gate_qubits': [[10]]}, {'type': 'qerror', 'operations': ['u3'], 'instructions': [[{'name': 'kraus', 'qubits': [0], 'params': [array([[0.99981155, 0.        ],\n",
      "       [0.        , 0.99822939]]), array([[-0.01941303,  0.        ],\n",
      "       [ 0.        ,  0.0194438 ]]), array([[0.        , 0.05621408],\n",
      "       [0.        , 0.        ]])]}]], 'probabilities': [1], 'gate_qubits': [[11]]}, {'type': 'qerror', 'operations': ['u3'], 'instructions': [[{'name': 'kraus', 'qubits': [0], 'params': [array([[0.99994958, 0.        ],\n",
      "       [0.        , 0.998504  ]]), array([[-0.0100414 ,  0.        ],\n",
      "       [ 0.        ,  0.01005594]]), array([[0.        , 0.05374615],\n",
      "       [0.        , 0.        ]])]}]], 'probabilities': [1], 'gate_qubits': [[12]]}, {'type': 'qerror', 'operations': ['u3'], 'instructions': [[{'name': 'kraus', 'qubits': [0], 'params': [array([[0.99985302, 0.        ],\n",
      "       [0.        , 0.99624509]]), array([[-0.01714487,  0.        ],\n",
      "       [ 0.        ,  0.01720697]]), array([[0.        , 0.08485074],\n",
      "       [0.        , 0.        ]])]}]], 'probabilities': [1], 'gate_qubits': [[13]]}, {'type': 'qerror', 'operations': ['cx'], 'instructions': [[{'name': 'kraus', 'qubits': [0], 'params': [array([[0.99933055, 0.        ],\n",
      "       [0.        , 0.99284135]]), array([[-0.03658498,  0.        ],\n",
      "       [ 0.        ,  0.0368241 ]]), array([[0.        , 0.11362238],\n",
      "       [0.        , 0.        ]])]}, {'name': 'id', 'qubits': [1]}], [{'name': 'kraus', 'qubits': [0], 'params': [array([[0.99933055, 0.        ],\n",
      "       [0.        , 0.99284135]]), array([[-0.03658498,  0.        ],\n",
      "       [ 0.        ,  0.0368241 ]]), array([[0.        , 0.11362238],\n",
      "       [0.        , 0.        ]])]}, {'name': 'z', 'qubits': [1]}], [{'name': 'kraus', 'qubits': [0], 'params': [array([[0.99933055, 0.        ],\n",
      "       [0.        , 0.99284135]]), array([[-0.03658498,  0.        ],\n",
      "       [ 0.        ,  0.0368241 ]]), array([[0.        , 0.11362238],\n",
      "       [0.        , 0.        ]])]}, {'name': 'reset', 'qubits': [1]}]], 'probabilities': [0.9794820138009688, 0.01057701634367594, 0.009940969855355308], 'gate_qubits': [[1, 0]]}, {'type': 'qerror', 'operations': ['cx'], 'instructions': [[{'name': 'kraus', 'qubits': [0, 1], 'params': [array([[0.99917103, 0.        , 0.        , 0.        ],\n",
      "       [0.        , 0.99393593, 0.        , 0.        ],\n",
      "       [0.        , 0.        , 0.99539283, 0.        ],\n",
      "       [0.        , 0.        , 0.        , 0.99017752]]), array([[-0.02396617, -0.        ,  0.        ,  0.        ],\n",
      "       [-0.        , -0.0238406 ,  0.        ,  0.        ],\n",
      "       [ 0.        ,  0.        ,  0.02405714,  0.        ],\n",
      "       [ 0.        ,  0.        ,  0.        ,  0.02393109]]), array([[0.        , 0.        , 0.08678423, 0.        ],\n",
      "       [0.        , 0.        , 0.        , 0.08632953],\n",
      "       [0.        , 0.        , 0.        , 0.        ],\n",
      "       [0.        , 0.        , 0.        , 0.        ]]), array([[-0.03289754,  0.        , -0.        ,  0.        ],\n",
      "       [ 0.        ,  0.03307082,  0.        ,  0.        ],\n",
      "       [-0.        ,  0.        , -0.03277315,  0.        ],\n",
      "       [ 0.        ,  0.        ,  0.        ,  0.03294576]]), array([[ 0.00078908, -0.        , -0.        ,  0.        ],\n",
      "       [-0.        , -0.00079324,  0.        ,  0.        ],\n",
      "       [-0.        ,  0.        , -0.00079208,  0.        ],\n",
      "       [ 0.        ,  0.        ,  0.        ,  0.00079625]]), array([[-0.        ,  0.        , -0.00285736,  0.        ],\n",
      "       [ 0.        ,  0.        ,  0.        ,  0.00287241],\n",
      "       [-0.        ,  0.        , -0.        ,  0.        ],\n",
      "       [ 0.        ,  0.        ,  0.        ,  0.        ]]), array([[0.        , 0.10209156, 0.        , 0.        ],\n",
      "       [0.        , 0.        , 0.        , 0.        ],\n",
      "       [0.        , 0.        , 0.        , 0.10170552],\n",
      "       [0.        , 0.        , 0.        , 0.        ]]), array([[-0.        , -0.00244877,  0.        ,  0.        ],\n",
      "       [-0.        , -0.        ,  0.        ,  0.        ],\n",
      "       [ 0.        ,  0.        ,  0.        ,  0.00245807],\n",
      "       [ 0.        ,  0.        ,  0.        ,  0.        ]]), array([[0.        , 0.        , 0.        , 0.00886729],\n",
      "       [0.        , 0.        , 0.        , 0.        ],\n",
      "       [0.        , 0.        , 0.        , 0.        ],\n",
      "       [0.        , 0.        , 0.        , 0.        ]])]}]], 'probabilities': [1], 'gate_qubits': [[1, 2]]}, {'type': 'qerror', 'operations': ['cx'], 'instructions': [[{'name': 'kraus', 'qubits': [0, 1], 'params': [array([[0.9986388 , 0.        , 0.        , 0.        ],\n",
      "       [0.        , 0.99366257, 0.        , 0.        ],\n",
      "       [0.        , 0.        , 0.9934299 , 0.        ],\n",
      "       [0.        , 0.        , 0.        , 0.98847963]]), array([[-0.04432392, -0.        ,  0.        ,  0.        ],\n",
      "       [-0.        , -0.04410305,  0.        ,  0.        ],\n",
      "       [ 0.        ,  0.        ,  0.04455633,  0.        ],\n",
      "       [ 0.        ,  0.        ,  0.        ,  0.0443343 ]]), array([[0.        , 0.        , 0.10176358, 0.        ],\n",
      "       [0.        , 0.        , 0.        , 0.10125649],\n",
      "       [0.        , 0.        , 0.        , 0.        ],\n",
      "       [0.        , 0.        , 0.        , 0.        ]]), array([[-0.02746722,  0.        , -0.        ,  0.        ],\n",
      "       [ 0.        ,  0.02760477,  0.        ,  0.        ],\n",
      "       [-0.        ,  0.        , -0.02732395,  0.        ],\n",
      "       [ 0.        ,  0.        ,  0.        ,  0.02746079]]), array([[ 0.00121911, -0.        , -0.        ,  0.        ],\n",
      "       [-0.        , -0.00122522,  0.        ,  0.        ],\n",
      "       [-0.        ,  0.        , -0.00122551,  0.        ],\n",
      "       [ 0.        ,  0.        ,  0.        ,  0.00123164]]), array([[-0.        ,  0.        , -0.00279897,  0.        ],\n",
      "       [ 0.        ,  0.        ,  0.        ,  0.00281299],\n",
      "       [-0.        ,  0.        , -0.        ,  0.        ],\n",
      "       [ 0.        ,  0.        ,  0.        ,  0.        ]]), array([[0.        , 0.09953176, 0.        , 0.        ],\n",
      "       [0.        , 0.        , 0.        , 0.        ],\n",
      "       [0.        , 0.        , 0.        , 0.09901261],\n",
      "       [0.        , 0.        , 0.        , 0.        ]]), array([[-0.        , -0.00441765,  0.        ,  0.        ],\n",
      "       [-0.        , -0.        ,  0.        ,  0.        ],\n",
      "       [ 0.        ,  0.        ,  0.        ,  0.00444081],\n",
      "       [ 0.        ,  0.        ,  0.        ,  0.        ]]), array([[0.        , 0.        , 0.        , 0.01014251],\n",
      "       [0.        , 0.        , 0.        , 0.        ],\n",
      "       [0.        , 0.        , 0.        , 0.        ],\n",
      "       [0.        , 0.        , 0.        , 0.        ]])]}]], 'probabilities': [1], 'gate_qubits': [[2, 3]]}, {'type': 'qerror', 'operations': ['cx'], 'instructions': [[{'name': 'id', 'qubits': [0]}, {'name': 'kraus', 'qubits': [1], 'params': [array([[0.9990003 , 0.        ],\n",
      "       [0.        , 0.99370267]]), array([[-0.0447035 ,  0.        ],\n",
      "       [ 0.        ,  0.04494183]]), array([[0.       , 0.1026413],\n",
      "       [0.       , 0.       ]])]}], [{'name': 'z', 'qubits': [0]}, {'name': 'kraus', 'qubits': [1], 'params': [array([[0.9990003 , 0.        ],\n",
      "       [0.        , 0.99370267]]), array([[-0.0447035 ,  0.        ],\n",
      "       [ 0.        ,  0.04494183]]), array([[0.       , 0.1026413],\n",
      "       [0.       , 0.       ]])]}], [{'name': 'reset', 'qubits': [0]}, {'name': 'kraus', 'qubits': [1], 'params': [array([[0.9990003 , 0.        ],\n",
      "       [0.        , 0.99370267]]), array([[-0.0447035 ,  0.        ],\n",
      "       [ 0.        ,  0.04494183]]), array([[0.       , 0.1026413],\n",
      "       [0.       , 0.       ]])]}]], 'probabilities': [0.9848600556149415, 0.0038389879171262945, 0.011300956467932166], 'gate_qubits': [[4, 3]]}, {'type': 'qerror', 'operations': ['cx'], 'instructions': [[{'name': 'id', 'qubits': [0]}, {'name': 'kraus', 'qubits': [1], 'params': [array([[0.99904602, 0.        ],\n",
      "       [0.        , 0.99343761]]), array([[-0.04366978,  0.        ],\n",
      "       [ 0.        ,  0.04391631]]), array([[0.        , 0.10560812],\n",
      "       [0.        , 0.        ]])]}], [{'name': 'z', 'qubits': [0]}, {'name': 'kraus', 'qubits': [1], 'params': [array([[0.99904602, 0.        ],\n",
      "       [0.        , 0.99343761]]), array([[-0.04366978,  0.        ],\n",
      "       [ 0.        ,  0.04391631]]), array([[0.        , 0.10560812],\n",
      "       [0.        , 0.        ]])]}], [{'name': 'reset', 'qubits': [0]}, {'name': 'kraus', 'qubits': [1], 'params': [array([[0.99904602, 0.        ],\n",
      "       [0.        , 0.99343761]]), array([[-0.04366978,  0.        ],\n",
      "       [ 0.        ,  0.04391631]]), array([[0.        , 0.10560812],\n",
      "       [0.        , 0.        ]])]}]], 'probabilities': [0.9851059372102934, 0.0037770829251414346, 0.011116979864565169], 'gate_qubits': [[4, 10]]}, {'type': 'qerror', 'operations': ['cx'], 'instructions': [[{'name': 'kraus', 'qubits': [0], 'params': [array([[1.        , 0.        ],\n",
      "       [0.        , 0.98299147]]), array([[0.        , 0.18365121],\n",
      "       [0.        , 0.        ]])]}, {'name': 'id', 'qubits': [1]}], [{'name': 'kraus', 'qubits': [0], 'params': [array([[1.        , 0.        ],\n",
      "       [0.        , 0.98299147]]), array([[0.        , 0.18365121],\n",
      "       [0.        , 0.        ]])]}, {'name': 'z', 'qubits': [1]}], [{'name': 'kraus', 'qubits': [0], 'params': [array([[1.        , 0.        ],\n",
      "       [0.        , 0.98299147]]), array([[0.        , 0.18365121],\n",
      "       [0.        , 0.        ]])]}, {'name': 'reset', 'qubits': [1]}]], 'probabilities': [0.9834884178044242, 0.004184051903277553, 0.012327530292298272], 'gate_qubits': [[5, 4]]}, {'type': 'qerror', 'operations': ['cx'], 'instructions': [[{'name': 'kraus', 'qubits': [0], 'params': [array([[1.        , 0.        ],\n",
      "       [0.        , 0.98299147]]), array([[0.        , 0.18365121],\n",
      "       [0.        , 0.        ]])]}, {'name': 'id', 'qubits': [1]}], [{'name': 'kraus', 'qubits': [0], 'params': [array([[1.        , 0.        ],\n",
      "       [0.        , 0.98299147]]), array([[0.        , 0.18365121],\n",
      "       [0.        , 0.        ]])]}, {'name': 'z', 'qubits': [1]}], [{'name': 'kraus', 'qubits': [0], 'params': [array([[1.        , 0.        ],\n",
      "       [0.        , 0.98299147]]), array([[0.        , 0.18365121],\n",
      "       [0.        , 0.        ]])]}, {'name': 'reset', 'qubits': [1]}]], 'probabilities': [0.9857304675990267, 0.002681323216245956, 0.01158820918472736], 'gate_qubits': [[5, 6]]}, {'type': 'qerror', 'operations': ['cx'], 'instructions': [[{'name': 'kraus', 'qubits': [0, 1], 'params': [array([[1.        , 0.        , 0.        , 0.        ],\n",
      "       [0.        , 0.98099102, 0.        , 0.        ],\n",
      "       [0.        , 0.        , 0.98866713, 0.        ],\n",
      "       [0.        , 0.        , 0.        , 0.96987358]]), array([[0.        , 0.        , 0.1501243 , 0.        ],\n",
      "       [0.        , 0.        , 0.        , 0.14727059],\n",
      "       [0.        , 0.        , 0.        , 0.        ],\n",
      "       [0.        , 0.        , 0.        , 0.        ]]), array([[0.        , 0.19405312, 0.        , 0.        ],\n",
      "       [0.        , 0.        , 0.        , 0.        ],\n",
      "       [0.        , 0.        , 0.        , 0.19185394],\n",
      "       [0.        , 0.        , 0.        , 0.        ]]), array([[0.        , 0.        , 0.        , 0.02913209],\n",
      "       [0.        , 0.        , 0.        , 0.        ],\n",
      "       [0.        , 0.        , 0.        , 0.        ],\n",
      "       [0.        , 0.        , 0.        , 0.        ]])]}]], 'probabilities': [1], 'gate_qubits': [[5, 9]]}, {'type': 'qerror', 'operations': ['cx'], 'instructions': [[{'name': 'id', 'qubits': [0]}, {'name': 'id', 'qubits': [1]}], [{'name': 'z', 'qubits': [0]}, {'name': 'id', 'qubits': [1]}], [{'name': 'reset', 'qubits': [0]}, {'name': 'id', 'qubits': [1]}], [{'name': 'id', 'qubits': [0]}, {'name': 'z', 'qubits': [1]}], [{'name': 'z', 'qubits': [0]}, {'name': 'z', 'qubits': [1]}], [{'name': 'reset', 'qubits': [0]}, {'name': 'z', 'qubits': [1]}], [{'name': 'id', 'qubits': [0]}, {'name': 'reset', 'qubits': [1]}], [{'name': 'z', 'qubits': [0]}, {'name': 'reset', 'qubits': [1]}], [{'name': 'reset', 'qubits': [0]}, {'name': 'reset', 'qubits': [1]}]], 'probabilities': [0.9687435497077612, 0.0029480346990249165, 0.012753843344418692, 0.0011581767939954882, 3.5245090172049454e-06, 1.5247797417815618e-05, 0.014148300446601583, 4.30554408970193e-05, 0.00018626726086605702], 'gate_qubits': [[6, 8]]}, {'type': 'qerror', 'operations': ['cx'], 'instructions': [[{'name': 'kraus', 'qubits': [0], 'params': [array([[1.        , 0.        ],\n",
      "       [0.        , 0.99263437]]), array([[0.        , 0.12114873],\n",
      "       [0.        , 0.        ]])]}, {'name': 'id', 'qubits': [1]}], [{'name': 'kraus', 'qubits': [0], 'params': [array([[1.        , 0.        ],\n",
      "       [0.        , 0.99263437]]), array([[0.        , 0.12114873],\n",
      "       [0.        , 0.        ]])]}, {'name': 'z', 'qubits': [1]}], [{'name': 'kraus', 'qubits': [0], 'params': [array([[1.        , 0.        ],\n",
      "       [0.        , 0.99263437]]), array([[0.        , 0.12114873],\n",
      "       [0.        , 0.        ]])]}, {'name': 'reset', 'qubits': [1]}]], 'probabilities': [0.9888522209484151, 0.0008453848645706519, 0.010302394187014285], 'gate_qubits': [[7, 8]]}, {'type': 'qerror', 'operations': ['cx'], 'instructions': [[{'name': 'kraus', 'qubits': [0], 'params': [array([[1.        , 0.        ],\n",
      "       [0.        , 0.98866713]]), array([[0.       , 0.1501243],\n",
      "       [0.       , 0.       ]])]}, {'name': 'id', 'qubits': [1]}], [{'name': 'kraus', 'qubits': [0], 'params': [array([[1.        , 0.        ],\n",
      "       [0.        , 0.98866713]]), array([[0.       , 0.1501243],\n",
      "       [0.       , 0.       ]])]}, {'name': 'z', 'qubits': [1]}], [{'name': 'kraus', 'qubits': [0], 'params': [array([[1.        , 0.        ],\n",
      "       [0.        , 0.98866713]]), array([[0.       , 0.1501243],\n",
      "       [0.       , 0.       ]])]}, {'name': 'reset', 'qubits': [1]}]], 'probabilities': [0.9844454277512048, 0.0011769491004305088, 0.01437762314836466], 'gate_qubits': [[9, 8]]}, {'type': 'qerror', 'operations': ['cx'], 'instructions': [[{'name': 'kraus', 'qubits': [0, 1], 'params': [array([[0.99894297, 0.        , 0.        , 0.        ],\n",
      "       [0.        , 0.98881763, 0.        , 0.        ],\n",
      "       [0.        , 0.        , 0.99271998, 0.        ],\n",
      "       [0.        , 0.        , 0.        , 0.98265771]]), array([[-0.04596665, -0.        ,  0.        ,  0.        ],\n",
      "       [-0.        , -0.04550073,  0.        ,  0.        ],\n",
      "       [ 0.        ,  0.        ,  0.0462548 ,  0.        ],\n",
      "       [ 0.        ,  0.        ,  0.        ,  0.04578596]]), array([[0.        , 0.        , 0.1112094 , 0.        ],\n",
      "       [0.        , 0.        , 0.        , 0.11008218],\n",
      "       [0.        , 0.        , 0.        , 0.        ],\n",
      "       [0.        , 0.        , 0.        , 0.        ]]), array([[0.        , 0.14186881, 0.        , 0.        ],\n",
      "       [0.        , 0.        , 0.        , 0.        ],\n",
      "       [0.        , 0.        , 0.        , 0.14098503],\n",
      "       [0.        , 0.        , 0.        , 0.        ]]), array([[-0.        , -0.00652813,  0.        ,  0.        ],\n",
      "       [-0.        , -0.        ,  0.        ,  0.        ],\n",
      "       [ 0.        ,  0.        ,  0.        ,  0.00656906],\n",
      "       [ 0.        ,  0.        ,  0.        ,  0.        ]]), array([[0.        , 0.        , 0.        , 0.01579384],\n",
      "       [0.        , 0.        , 0.        , 0.        ],\n",
      "       [0.        , 0.        , 0.        , 0.        ],\n",
      "       [0.        , 0.        , 0.        , 0.        ]])]}]], 'probabilities': [1], 'gate_qubits': [[9, 10]]}, {'type': 'qerror', 'operations': ['cx'], 'instructions': [[{'name': 'kraus', 'qubits': [0, 1], 'params': [array([[0.99854149, 0.        , 0.        , 0.        ],\n",
      "       [0.        , 0.99353282, 0.        , 0.        ],\n",
      "       [0.        , 0.        , 0.99396233, 0.        ],\n",
      "       [0.        , 0.        , 0.        , 0.98897663]]), array([[-0.0415862 , -0.        ,  0.        ,  0.        ],\n",
      "       [-0.        , -0.04137761,  0.        ,  0.        ],\n",
      "       [ 0.        ,  0.        ,  0.04177779,  0.        ],\n",
      "       [ 0.        ,  0.        ,  0.        ,  0.04156823]]), array([[0.        , 0.        , 0.09543601, 0.        ],\n",
      "       [0.        , 0.        , 0.        , 0.0949573 ],\n",
      "       [0.        , 0.        , 0.        , 0.        ],\n",
      "       [0.        , 0.        , 0.        , 0.        ]]), array([[-0.0344009 ,  0.        , -0.        ,  0.        ],\n",
      "       [ 0.        ,  0.03457432,  0.        ,  0.        ],\n",
      "       [-0.        ,  0.        , -0.03424314,  0.        ],\n",
      "       [ 0.        ,  0.        ,  0.        ,  0.03441577]]), array([[ 0.00143269, -0.        , -0.        ,  0.        ],\n",
      "       [-0.        , -0.00143991,  0.        ,  0.        ],\n",
      "       [-0.        ,  0.        , -0.00143929,  0.        ],\n",
      "       [ 0.        ,  0.        ,  0.        ,  0.00144655]]), array([[-0.        ,  0.        , -0.00328788,  0.        ],\n",
      "       [ 0.        ,  0.        ,  0.        ,  0.00330445],\n",
      "       [-0.        ,  0.        , -0.        ,  0.        ],\n",
      "       [ 0.        ,  0.        ,  0.        ,  0.        ]]), array([[0.        , 0.09982828, 0.        , 0.        ],\n",
      "       [0.        , 0.        , 0.        , 0.        ],\n",
      "       [0.        , 0.        , 0.        , 0.09937048],\n",
      "       [0.        , 0.        , 0.        , 0.        ]]), array([[-0.        , -0.00415754,  0.        ,  0.        ],\n",
      "       [-0.        , -0.        ,  0.        ,  0.        ],\n",
      "       [ 0.        ,  0.        ,  0.        ,  0.0041767 ],\n",
      "       [ 0.        ,  0.        ,  0.        ,  0.        ]]), array([[0.        , 0.        , 0.        , 0.00954113],\n",
      "       [0.        , 0.        , 0.        , 0.        ],\n",
      "       [0.        , 0.        , 0.        , 0.        ],\n",
      "       [0.        , 0.        , 0.        , 0.        ]])]}]], 'probabilities': [1], 'gate_qubits': [[11, 3]]}, {'type': 'qerror', 'operations': ['cx'], 'instructions': [[{'name': 'kraus', 'qubits': [0, 1], 'params': [array([[0.99837341, 0.        , 0.        , 0.        ],\n",
      "       [0.        , 0.99267848, 0.        , 0.        ],\n",
      "       [0.        , 0.        , 0.99276877, 0.        ],\n",
      "       [0.        , 0.        , 0.        , 0.98710581]]), array([[-0.04364038, -0.        ,  0.        ,  0.        ],\n",
      "       [-0.        , -0.04339144,  0.        ,  0.        ],\n",
      "       [ 0.        ,  0.        ,  0.04388675,  0.        ],\n",
      "       [ 0.        ,  0.        ,  0.        ,  0.04363641]]), array([[0.        , 0.        , 0.10553702, 0.        ],\n",
      "       [0.        , 0.        , 0.        , 0.10493501],\n",
      "       [0.        , 0.        , 0.        , 0.        ],\n",
      "       [0.        , 0.        , 0.        , 0.        ]]), array([[-0.03665367,  0.        , -0.        ,  0.        ],\n",
      "       [ 0.        ,  0.03686395,  0.        ,  0.        ],\n",
      "       [-0.        ,  0.        , -0.03644791,  0.        ],\n",
      "       [ 0.        ,  0.        ,  0.        ,  0.03665701]]), array([[ 0.00160219, -0.        , -0.        ,  0.        ],\n",
      "       [-0.        , -0.00161138,  0.        ,  0.        ],\n",
      "       [-0.        ,  0.        , -0.00161123,  0.        ],\n",
      "       [ 0.        ,  0.        ,  0.        ,  0.00162047]]), array([[-0.        ,  0.        , -0.00387462,  0.        ],\n",
      "       [ 0.        ,  0.        ,  0.        ,  0.00389685],\n",
      "       [-0.        ,  0.        , -0.        ,  0.        ],\n",
      "       [ 0.        ,  0.        ,  0.        ,  0.        ]]), array([[0.        , 0.10641165, 0.        , 0.        ],\n",
      "       [0.        , 0.        , 0.        , 0.        ],\n",
      "       [0.        , 0.        , 0.        , 0.10581428],\n",
      "       [0.        , 0.        , 0.        , 0.        ]]), array([[-0.        , -0.00465141,  0.        ,  0.        ],\n",
      "       [-0.        , -0.        ,  0.        ,  0.        ],\n",
      "       [ 0.        ,  0.        ,  0.        ,  0.00467767],\n",
      "       [ 0.        ,  0.        ,  0.        ,  0.        ]]), array([[0.        , 0.        , 0.        , 0.01124867],\n",
      "       [0.        , 0.        , 0.        , 0.        ],\n",
      "       [0.        , 0.        , 0.        , 0.        ],\n",
      "       [0.        , 0.        , 0.        , 0.        ]])]}]], 'probabilities': [1], 'gate_qubits': [[11, 10]]}, {'type': 'qerror', 'operations': ['cx'], 'instructions': [[{'name': 'x', 'qubits': [0]}], [{'name': 'y', 'qubits': [0]}], [{'name': 'z', 'qubits': [0]}], [{'name': 'x', 'qubits': [1]}], [{'name': 'x', 'qubits': [0]}, {'name': 'x', 'qubits': [1]}], [{'name': 'y', 'qubits': [0]}, {'name': 'x', 'qubits': [1]}], [{'name': 'z', 'qubits': [0]}, {'name': 'x', 'qubits': [1]}], [{'name': 'y', 'qubits': [1]}], [{'name': 'x', 'qubits': [0]}, {'name': 'y', 'qubits': [1]}], [{'name': 'y', 'qubits': [0]}, {'name': 'y', 'qubits': [1]}], [{'name': 'z', 'qubits': [0]}, {'name': 'y', 'qubits': [1]}], [{'name': 'z', 'qubits': [1]}], [{'name': 'x', 'qubits': [0]}, {'name': 'z', 'qubits': [1]}], [{'name': 'y', 'qubits': [0]}, {'name': 'z', 'qubits': [1]}], [{'name': 'z', 'qubits': [0]}, {'name': 'z', 'qubits': [1]}], [{'name': 'id', 'qubits': [0]}]], 'probabilities': [0.008364173324451293, 0.008364173324451293, 0.008364173324451293, 0.008364173324451293, 0.008364173324451293, 0.008364173324451293, 0.008364173324451293, 0.008364173324451293, 0.008364173324451293, 0.008364173324451293, 0.008364173324451293, 0.008364173324451293, 0.008364173324451293, 0.008364173324451293, 0.008364173324451293, 0.8745374001332307], 'gate_qubits': [[11, 12]]}, {'type': 'qerror', 'operations': ['cx'], 'instructions': [[{'name': 'kraus', 'qubits': [0, 1], 'params': [array([[0.99940188, 0.        , 0.        , 0.        ],\n",
      "       [0.        , 0.99382608, 0.        , 0.        ],\n",
      "       [0.        , 0.        , 0.99406306, 0.        ],\n",
      "       [0.        , 0.        , 0.        , 0.98851704]]), array([[-0.02845188, -0.        ,  0.        ,  0.        ],\n",
      "       [-0.        , -0.02829314,  0.        ,  0.        ],\n",
      "       [ 0.        ,  0.        ,  0.02860469,  0.        ],\n",
      "       [ 0.        ,  0.        ,  0.        ,  0.0284451 ]]), array([[0.        , 0.        , 0.10312151, 0.        ],\n",
      "       [0.        , 0.        , 0.        , 0.10254618],\n",
      "       [0.        , 0.        , 0.        , 0.        ],\n",
      "       [0.        , 0.        , 0.        , 0.        ]]), array([[-0.01964822,  0.        , -0.        ,  0.        ],\n",
      "       [ 0.        ,  0.01975845,  0.        ,  0.        ],\n",
      "       [-0.        ,  0.        , -0.01954326,  0.        ],\n",
      "       [ 0.        ,  0.        ,  0.        ,  0.0196529 ]]), array([[ 0.00055936, -0.        , -0.        ,  0.        ],\n",
      "       [-0.        , -0.0005625 ,  0.        ,  0.        ],\n",
      "       [-0.        ,  0.        , -0.00056237,  0.        ],\n",
      "       [ 0.        ,  0.        ,  0.        ,  0.00056552]]), array([[-0.        ,  0.        , -0.00202737,  0.        ],\n",
      "       [ 0.        ,  0.        ,  0.        ,  0.00203874],\n",
      "       [-0.        ,  0.        , -0.        ,  0.        ],\n",
      "       [ 0.        ,  0.        ,  0.        ,  0.        ]]), array([[0.        , 0.10540164, 0.        , 0.        ],\n",
      "       [0.        , 0.        , 0.        , 0.        ],\n",
      "       [0.        , 0.        , 0.        , 0.10483858],\n",
      "       [0.        , 0.        , 0.        , 0.        ]]), array([[-0.        , -0.00300067,  0.        ,  0.        ],\n",
      "       [-0.        , -0.        ,  0.        ,  0.        ],\n",
      "       [ 0.        ,  0.        ,  0.        ,  0.00301679],\n",
      "       [ 0.        ,  0.        ,  0.        ,  0.        ]]), array([[0.        , 0.        , 0.        , 0.01087568],\n",
      "       [0.        , 0.        , 0.        , 0.        ],\n",
      "       [0.        , 0.        , 0.        , 0.        ],\n",
      "       [0.        , 0.        , 0.        , 0.        ]])]}]], 'probabilities': [1], 'gate_qubits': [[12, 2]]}, {'type': 'qerror', 'operations': ['cx'], 'instructions': [[{'name': 'kraus', 'qubits': [0, 1], 'params': [array([[0.99627018, 0.        , 0.        , 0.        ],\n",
      "       [0.        , 0.95569927, 0.        , 0.        ],\n",
      "       [0.        , 0.        , 0.97448684, 0.        ],\n",
      "       [0.        , 0.        , 0.        , 0.93480301]]), array([[-0.06592117, -0.        ,  0.        ,  0.        ],\n",
      "       [-0.        , -0.06323668,  0.        ,  0.        ],\n",
      "       [ 0.        ,  0.        ,  0.06739475,  0.        ],\n",
      "       [ 0.        ,  0.        ,  0.        ,  0.06465025]]), array([[0.        , 0.        , 0.20672011, 0.        ],\n",
      "       [0.        , 0.        , 0.        , 0.19830189],\n",
      "       [0.        , 0.        , 0.        , 0.        ],\n",
      "       [0.        , 0.        , 0.        , 0.        ]]), array([[-0.05555739,  0.        , -0.        ,  0.        ],\n",
      "       [ 0.        ,  0.05791588,  0.        ,  0.        ],\n",
      "       [-0.        ,  0.        , -0.05434263,  0.        ],\n",
      "       [ 0.        ,  0.        ,  0.        ,  0.05664956]]), array([[ 0.00367612, -0.        , -0.        ,  0.        ],\n",
      "       [-0.        , -0.00383218,  0.        ,  0.        ],\n",
      "       [-0.        ,  0.        , -0.00375829,  0.        ],\n",
      "       [ 0.        ,  0.        ,  0.        ,  0.00391784]]), array([[-0.        ,  0.        , -0.01152783,  0.        ],\n",
      "       [ 0.        ,  0.        ,  0.        ,  0.0120172 ],\n",
      "       [-0.        ,  0.        , -0.        ,  0.        ],\n",
      "       [ 0.        ,  0.        ,  0.        ,  0.        ]]), array([[0.        , 0.28093691, 0.        , 0.        ],\n",
      "       [0.        , 0.        , 0.        , 0.        ],\n",
      "       [0.        , 0.        , 0.        , 0.27479426],\n",
      "       [0.        , 0.        , 0.        , 0.        ]]), array([[-0.        , -0.01858902,  0.        ,  0.        ],\n",
      "       [-0.        , -0.        ,  0.        ,  0.        ],\n",
      "       [ 0.        ,  0.        ,  0.        ,  0.01900456],\n",
      "       [ 0.        ,  0.        ,  0.        ,  0.        ]]), array([[0.        , 0.        , 0.        , 0.05829273],\n",
      "       [0.        , 0.        , 0.        , 0.        ],\n",
      "       [0.        , 0.        , 0.        , 0.        ],\n",
      "       [0.        , 0.        , 0.        , 0.        ]])]}]], 'probabilities': [1], 'gate_qubits': [[13, 1]]}, {'type': 'qerror', 'operations': ['cx'], 'instructions': [[{'name': 'kraus', 'qubits': [0, 1], 'params': [array([[0.99857658, 0.        , 0.        , 0.        ],\n",
      "       [0.        , 0.97169404, 0.        , 0.        ],\n",
      "       [0.        , 0.        , 0.98775753, 0.        ],\n",
      "       [0.        , 0.        , 0.        , 0.96116625]]), array([[-0.0272382 , -0.        ,  0.        ,  0.        ],\n",
      "       [-0.        , -0.02650492,  0.        ,  0.        ],\n",
      "       [ 0.        ,  0.        ,  0.02753654,  0.        ],\n",
      "       [ 0.        ,  0.        ,  0.        ,  0.02679523]]), array([[0.        , 0.        , 0.14653977, 0.        ],\n",
      "       [0.        , 0.        , 0.        , 0.1425948 ],\n",
      "       [0.        , 0.        , 0.        , 0.        ],\n",
      "       [0.        , 0.        , 0.        , 0.        ]]), array([[-0.04584037,  0.        , -0.        ,  0.        ],\n",
      "       [ 0.        ,  0.04710857,  0.        ,  0.        ],\n",
      "       [-0.        ,  0.        , -0.04534371,  0.        ],\n",
      "       [ 0.        ,  0.        ,  0.        ,  0.04659817]]), array([[ 0.00125039, -0.        , -0.        ,  0.        ],\n",
      "       [-0.        , -0.00128498,  0.        ,  0.        ],\n",
      "       [-0.        ,  0.        , -0.00126408,  0.        ],\n",
      "       [ 0.        ,  0.        ,  0.        ,  0.00129906]]), array([[-0.        ,  0.        , -0.00672701,  0.        ],\n",
      "       [ 0.        ,  0.        ,  0.        ,  0.00691312],\n",
      "       [-0.        ,  0.        , -0.        ,  0.        ],\n",
      "       [ 0.        ,  0.        ,  0.        ,  0.        ]]), array([[0.        , 0.22988689, 0.        , 0.        ],\n",
      "       [0.        , 0.        , 0.        , 0.        ],\n",
      "       [0.        , 0.        , 0.        , 0.22739619],\n",
      "       [0.        , 0.        , 0.        , 0.        ]]), array([[-0.        , -0.00627063,  0.        ,  0.        ],\n",
      "       [-0.        , -0.        ,  0.        ,  0.        ],\n",
      "       [ 0.        ,  0.        ,  0.        ,  0.00633931],\n",
      "       [ 0.        ,  0.        ,  0.        ,  0.        ]]), array([[0.        , 0.        , 0.        , 0.03373559],\n",
      "       [0.        , 0.        , 0.        , 0.        ],\n",
      "       [0.        , 0.        , 0.        , 0.        ],\n",
      "       [0.        , 0.        , 0.        , 0.        ]])]}]], 'probabilities': [1], 'gate_qubits': [[13, 12]]}, {'type': 'roerror', 'operations': ['measure'], 'probabilities': [[0.9763999999999999, 0.023600000000000065], [0.023600000000000065, 0.9763999999999999]], 'gate_qubits': [[0]]}, {'type': 'roerror', 'operations': ['measure'], 'probabilities': [[0.9139, 0.08609999999999995], [0.08609999999999995, 0.9139]], 'gate_qubits': [[1]]}, {'type': 'roerror', 'operations': ['measure'], 'probabilities': [[0.9596, 0.04039999999999999], [0.04039999999999999, 0.9596]], 'gate_qubits': [[2]]}, {'type': 'roerror', 'operations': ['measure'], 'probabilities': [[0.7713, 0.22870000000000001], [0.22870000000000001, 0.7713]], 'gate_qubits': [[3]]}, {'type': 'roerror', 'operations': ['measure'], 'probabilities': [[0.9734, 0.026599999999999957], [0.026599999999999957, 0.9734]], 'gate_qubits': [[4]]}, {'type': 'roerror', 'operations': ['measure'], 'probabilities': [[0.9521999999999999, 0.047800000000000065], [0.047800000000000065, 0.9521999999999999]], 'gate_qubits': [[5]]}, {'type': 'roerror', 'operations': ['measure'], 'probabilities': [[0.9131, 0.08689999999999998], [0.08689999999999998, 0.9131]], 'gate_qubits': [[6]]}, {'type': 'roerror', 'operations': ['measure'], 'probabilities': [[0.9225, 0.07750000000000001], [0.07750000000000001, 0.9225]], 'gate_qubits': [[7]]}, {'type': 'roerror', 'operations': ['measure'], 'probabilities': [[0.9525, 0.04749999999999999], [0.04749999999999999, 0.9525]], 'gate_qubits': [[8]]}, {'type': 'roerror', 'operations': ['measure'], 'probabilities': [[0.9005, 0.09950000000000003], [0.09950000000000003, 0.9005]], 'gate_qubits': [[9]]}, {'type': 'roerror', 'operations': ['measure'], 'probabilities': [[0.9477, 0.05230000000000001], [0.05230000000000001, 0.9477]], 'gate_qubits': [[10]]}, {'type': 'roerror', 'operations': ['measure'], 'probabilities': [[0.8865000000000001, 0.11349999999999993], [0.11349999999999993, 0.8865000000000001]], 'gate_qubits': [[11]]}, {'type': 'roerror', 'operations': ['measure'], 'probabilities': [[0.9609, 0.039100000000000024], [0.039100000000000024, 0.9609]], 'gate_qubits': [[12]]}, {'type': 'roerror', 'operations': ['measure'], 'probabilities': [[0.9542999999999999, 0.045700000000000074], [0.045700000000000074, 0.9542999999999999]], 'gate_qubits': [[13]]}], 'x90_gates': []}\n"
     ]
    }
   ],
   "source": [
    "print(noise_model.as_dict())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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