hardware_benchmarking.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "#imports\n",
    "from qiskit import*\n",
    "from qiskit.tools.visualization import plot_bloch_multivector\n",
    "from qiskit.tools.visualization import plot_histogram\n",
    "import numpy as np\n",
    "from numpy import linalg as LA\n",
    "import random\n",
    "from qiskit.extensions.simulator import snapshot\n",
    "from matplotlib import pyplot as plt\n",
    "from sortedcontainers import SortedDict\n",
    "from qiskit.extensions.simulator import snapshot\n",
    "from qiskit.providers.aer import noise\n",
    "%matplotlib inline\n",
    "from qiskit import IBMQ"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Choose a real device to simulate\n",
    "IBMQ.load_account()\n",
    "provider = IBMQ.get_provider(group='open')\n",
    "device = provider.get_backend('ibmq_16_melbourne')\n",
    "properties = device.properties()\n",
    "coupling_map = device.configuration().coupling_map\n",
    "\n",
    "# Generate an Aer noise model for device\n",
    "noise_model = noise.device.basic_device_noise_model(properties)\n",
    "basis_gates = noise_model.basis_gates\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def probabilty_dist(state):\n",
    "    probability_list = []\n",
    "    for i in range(len(state)): \n",
    "        probability_list.append(np.absolute(state[i])**2)\n",
    "    return probability_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def fidelity(initial_prob_list,final_prob_list):\n",
    "    fidelity = 0\n",
    "    for i in range(len(initial_prob_list)):\n",
    "        fidelity += np.sqrt(initial_prob_list[i]*final_prob_list[i])\n",
    "    return fidelity**2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "def normalize(vector):\n",
    "    return vector / LA.norm(vector)\n",
    "\n",
    "def random_initialize(circuit,no_q):\n",
    "    initial_prob_list = []\n",
    "    state_list = []\n",
    "    for i in range(no_q):\n",
    "        state = np.array([complex(random.random(),random.random()),complex(random.random(),random.random())])\n",
    "        state = normalize(state)\n",
    "        state_list.append(state)\n",
    "        circuit.initialize(state.tolist(),i)\n",
    "    initial_state = state_list[0]\n",
    "    for i in range(1,no_q):\n",
    "        initial_state =  np.kron(state_list[i],initial_state)\n",
    "    initial_prob_list = probabilty_dist(initial_state)\n",
    "    return initial_prob_list\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "def scramble(circuit,no_g):\n",
    "    l = []\n",
    "    #scramble\n",
    "    for i in range(no_g):\n",
    "        n = list(range(no_q))\n",
    "        a = random.choice(n)\n",
    "        n.remove(a)\n",
    "        b = random.choice(n)\n",
    "        l.append([a,b])\n",
    "        circuit.cx(a,b)\n",
    "    circuit.barrier()\n",
    "    #invert\n",
    "    for i in range(1,no_g + 1):\n",
    "        circuit.cx(l[-i][0],l[-i][1])\n",
    "    for i in range(no_q):\n",
    "        circuit.measure(i,i)\n",
    "    circuit.barrier()\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "def benchmark(no_q,no_g,circuit):\n",
    "    initial_prob_list = random_initialize(circuit,no_q)\n",
    "    scramble(circuit,no_g)\n",
    "    return initial_prob_list\n",
    "    \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "def final_problist(b):\n",
    "    keys = []\n",
    "    b = dict((int(key), value) for (key, value) in b.items())\n",
    "    for i in range(len(initial_prob_list)):\n",
    "        keys.append(int(bin(i)[2:]))\n",
    "    for k in keys:\n",
    "        if (k not in b.keys()):\n",
    "            b.update({k:0})\n",
    "    b = SortedDict(b)\n",
    "    final_prob_list = np.array(b.values())/shots\n",
    "    return final_prob_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "no_q = 5 #no of qubits\n",
    "no_g = 50 #no of gates\n",
    "shots = 100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.7787763046885422\n"
     ]
    }
   ],
   "source": [
    "avg_fidelity = 0\n",
    "tries = 50\n",
    "for i in range(tries):\n",
    "    circuit = QuantumCircuit(no_q,no_q)\n",
    "    initial_prob_list = benchmark(no_q,no_g,circuit)\n",
    "    simulator = Aer.get_backend('qasm_simulator')\n",
    "    result = execute(circuit,simulator,shots = shots,coupling_map=coupling_map,\n",
    "                     noise_model=noise_model,\n",
    "                     basis_gates=basis_gates).result()\n",
    "    final_prob_list = final_problist(result.get_counts())\n",
    "    avg_fidelity += fidelity(initial_prob_list,final_prob_list)\n",
    "avg_fidelity = avg_fidelity/tries\n",
    "print(avg_fidelity)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x143cc6dea90>]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "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": [
    "no_g_list = np.arange(1,no_g)\n",
    "fidelity_list = np.zeros(len(no_g_list))\n",
    "for j in no_g_list:\n",
    "    avg_fidelity = 0\n",
    "    tries = 100\n",
    "    for i in range(tries):\n",
    "        circuit = QuantumCircuit(no_q,no_q)\n",
    "        initial_prob_list = benchmark(no_q,j,circuit)\n",
    "        simulator = Aer.get_backend('qasm_simulator')\n",
    "        result = execute(circuit,simulator,shots = shots,coupling_map=coupling_map,\n",
    "                         noise_model=noise_model,\n",
    "                         basis_gates=basis_gates).result()\n",
    "        final_prob_list = final_problist(result.get_counts())\n",
    "        avg_fidelity += fidelity(initial_prob_list,final_prob_list)\n",
    "    avg_fidelity = avg_fidelity/tries\n",
    "    fidelity_list[j-1] = avg_fidelity\n",
    "plt.plot(no_g_list,fidelity_list)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "job = execute(circuit, backend = device)\n",
    "from qiskit.tools.monitor import job_monitor\n",
    "job_monitor(job)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "ename": "QiskitError",
     "evalue": "'Index out of range.'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mIndexError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[1;32mC:\\an\\lib\\site-packages\\qiskit\\circuit\\quantumcircuit.py\u001b[0m in \u001b[0;36m_bit_argument_conversion\u001b[1;34m(bit_representation, in_array)\u001b[0m\n\u001b[0;32m    283\u001b[0m                 \u001b[1;31m# circuit.h(0) -> circuit.h([qr[0]])\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 284\u001b[1;33m                 \u001b[0mret\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m[\u001b[0m\u001b[0min_array\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mbit_representation\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    285\u001b[0m             \u001b[1;32melif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mbit_representation\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mslice\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mIndexError\u001b[0m: list index out of range",
      "\nDuring handling of the above exception, another exception occurred:\n",
      "\u001b[1;31mQiskitError\u001b[0m                               Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-16-2c96a1314f4f>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      6\u001b[0m     \u001b[1;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mtries\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      7\u001b[0m         \u001b[0mcircuit\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mQuantumCircuit\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mj\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mj\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 8\u001b[1;33m         \u001b[0minitial_prob_list\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mbenchmark\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mj\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mno_g\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mcircuit\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      9\u001b[0m         \u001b[0msimulator\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mAer\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_backend\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'qasm_simulator'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     10\u001b[0m         result = execute(circuit,simulator,shots = shots,coupling_map=coupling_map,\n",
      "\u001b[1;32m<ipython-input-9-fd7eaa8e0163>\u001b[0m in \u001b[0;36mbenchmark\u001b[1;34m(no_q, no_g, circuit)\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mbenchmark\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mno_q\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mno_g\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mcircuit\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      2\u001b[0m     \u001b[0minitial_prob_list\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mrandom_initialize\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mcircuit\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mno_q\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 3\u001b[1;33m     \u001b[0mscramble\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mcircuit\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mno_g\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      4\u001b[0m     \u001b[1;32mreturn\u001b[0m \u001b[0minitial_prob_list\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      5\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m<ipython-input-8-1c942462f0ff>\u001b[0m in \u001b[0;36mscramble\u001b[1;34m(circuit, no_g)\u001b[0m\n\u001b[0;32m      8\u001b[0m         \u001b[0mb\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mrandom\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mchoice\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mn\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      9\u001b[0m         \u001b[0ml\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0ma\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mb\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 10\u001b[1;33m         \u001b[0mcircuit\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcx\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0ma\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mb\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     11\u001b[0m     \u001b[0mcircuit\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mbarrier\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     12\u001b[0m     \u001b[1;31m#invert\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\an\\lib\\site-packages\\qiskit\\extensions\\standard\\cx.py\u001b[0m in \u001b[0;36mcx\u001b[1;34m(self, ctl, tgt)\u001b[0m\n\u001b[0;32m     46\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mcx\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mctl\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtgt\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     47\u001b[0m     \u001b[1;34m\"\"\"Apply CX from ctl to tgt.\"\"\"\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 48\u001b[1;33m     \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mCnotGate\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m[\u001b[0m\u001b[0mctl\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtgt\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m[\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     49\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     50\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\an\\lib\\site-packages\\qiskit\\circuit\\quantumcircuit.py\u001b[0m in \u001b[0;36mappend\u001b[1;34m(self, instruction, qargs, cargs)\u001b[0m\n\u001b[0;32m    352\u001b[0m             \u001b[0minstruction\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0minstruction\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mto_instruction\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    353\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 354\u001b[1;33m         \u001b[0mexpanded_qargs\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m[\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mqbit_argument_conversion\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mqarg\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mqarg\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mqargs\u001b[0m \u001b[1;32mor\u001b[0m \u001b[1;33m[\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    355\u001b[0m         \u001b[0mexpanded_cargs\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m[\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcbit_argument_conversion\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mcarg\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mcarg\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mcargs\u001b[0m \u001b[1;32mor\u001b[0m \u001b[1;33m[\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    356\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\an\\lib\\site-packages\\qiskit\\circuit\\quantumcircuit.py\u001b[0m in \u001b[0;36m<listcomp>\u001b[1;34m(.0)\u001b[0m\n\u001b[0;32m    352\u001b[0m             \u001b[0minstruction\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0minstruction\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mto_instruction\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    353\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 354\u001b[1;33m         \u001b[0mexpanded_qargs\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m[\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mqbit_argument_conversion\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mqarg\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mqarg\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mqargs\u001b[0m \u001b[1;32mor\u001b[0m \u001b[1;33m[\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    355\u001b[0m         \u001b[0mexpanded_cargs\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m[\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcbit_argument_conversion\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mcarg\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mcarg\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mcargs\u001b[0m \u001b[1;32mor\u001b[0m \u001b[1;33m[\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    356\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\an\\lib\\site-packages\\qiskit\\circuit\\quantumcircuit.py\u001b[0m in \u001b[0;36mqbit_argument_conversion\u001b[1;34m(self, qubit_representation)\u001b[0m\n\u001b[0;32m    321\u001b[0m             \u001b[0mList\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mtuple\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mWhere\u001b[0m \u001b[0meach\u001b[0m \u001b[0mtuple\u001b[0m \u001b[1;32mis\u001b[0m \u001b[0ma\u001b[0m \u001b[0mqubit\u001b[0m\u001b[1;33m.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    322\u001b[0m         \"\"\"\n\u001b[1;32m--> 323\u001b[1;33m         \u001b[1;32mreturn\u001b[0m \u001b[0mQuantumCircuit\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_bit_argument_conversion\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mqubit_representation\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mqubits\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    324\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    325\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0mcbit_argument_conversion\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mclbit_representation\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\an\\lib\\site-packages\\qiskit\\circuit\\quantumcircuit.py\u001b[0m in \u001b[0;36m_bit_argument_conversion\u001b[1;34m(bit_representation, in_array)\u001b[0m\n\u001b[0;32m    304\u001b[0m                                                                     type(bit_representation)))\n\u001b[0;32m    305\u001b[0m         \u001b[1;32mexcept\u001b[0m \u001b[0mIndexError\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 306\u001b[1;33m             \u001b[1;32mraise\u001b[0m \u001b[0mQiskitError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'Index out of range.'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    307\u001b[0m         \u001b[1;32mexcept\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    308\u001b[0m             raise QiskitError('Type error handling %s (%s)' % (bit_representation,\n",
      "\u001b[1;31mQiskitError\u001b[0m: 'Index out of range.'"
     ]
    }
   ],
   "source": [
    "no_q_list = np.arange(3,no_q + 2)\n",
    "fidelity_list = np.zeros(len(no_q_list))\n",
    "for j in no_q_list:\n",
    "    avg_fidelity = 0\n",
    "    tries = 50\n",
    "    for i in range(tries):\n",
    "        circuit = QuantumCircuit(int(j),int(j))\n",
    "        initial_prob_list = benchmark(int(j),no_g,circuit)\n",
    "        simulator = Aer.get_backend('qasm_simulator')\n",
    "        result = execute(circuit,simulator,shots = shots,coupling_map=coupling_map,\n",
    "                         noise_model=noise_model,\n",
    "                         basis_gates=basis_gates).result()\n",
    "        final_prob_list = final_problist(result.get_counts())\n",
    "        avg_fidelity += fidelity(initial_prob_list,final_prob_list)\n",
    "    avg_fidelity = avg_fidelity/tries\n",
    "    fidelity_list[j-3] = avg_fidelity\n",
    "plt.plot(no_q_list,fidelity_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[3 4 5]\n"
     ]
    }
   ],
   "source": []
  },
  {
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