qiskit_lesson_3.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "from qiskit import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "qr = QuantumRegister(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "cr = ClassicalRegister(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "circuit = QuantumCircuit(qr, cr)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"word-wrap: normal;white-space: pre;background: #fff0;line-height: 1.1;font-family: &quot;Courier New&quot;,Courier,monospace\">      \n",
       "q0_0: \n",
       "      \n",
       "q0_1: \n",
       "      \n",
       "c0: 2/\n",
       "      </pre>"
      ],
      "text/plain": [
       "      \n",
       "q0_0: \n",
       "      \n",
       "q0_1: \n",
       "      \n",
       "c0: 2/\n",
       "      "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "circuit.draw()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<qiskit.circuit.instructionset.InstructionSet at 0x1e67548ea00>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "circuit.h(qr[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"word-wrap: normal;white-space: pre;background: #fff0;line-height: 1.1;font-family: &quot;Courier New&quot;,Courier,monospace\">      ┌───┐\n",
       "q0_0: ┤ H ├\n",
       "      └───┘\n",
       "q0_1: ─────\n",
       "           \n",
       "c0: 2/═════\n",
       "           </pre>"
      ],
      "text/plain": [
       "      ┌───┐\n",
       "q0_0: ┤ H ├\n",
       "      └───┘\n",
       "q0_1: ─────\n",
       "           \n",
       "c0: 2/═════\n",
       "           "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "circuit.draw()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 213.813x204.68 with 1 Axes>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "circuit.draw(output='mpl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<qiskit.circuit.instructionset.InstructionSet at 0x1e604016fd0>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "circuit.cx(qr[0],qr[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 274.013x204.68 with 1 Axes>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "circuit.draw(output='mpl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<qiskit.circuit.instructionset.InstructionSet at 0x1e603ff7640>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "circuit.measure(qr, cr)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 394.413x204.68 with 1 Axes>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "circuit.draw(output='mpl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    " simulator = Aer.get_backend('qasm_simulator')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<qiskit.providers.aer.aerjob.AerJob at 0x1e603fce730>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "execute(circuit, backend = simulator)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "result = execute(circuit, backend = simulator).result()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "from qiskit.tools.visualization import plot_histogram"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plot_histogram(result.get_counts(circuit))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plot_histogram(result.get_counts())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\User\\anaconda3\\lib\\site-packages\\qiskit\\providers\\ibmq\\ibmqfactory.py:192: UserWarning: Timestamps in IBMQ backend properties, jobs, and job results are all now in local time instead of UTC.\n",
      "  warnings.warn('Timestamps in IBMQ backend properties, jobs, and job results '\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<AccountProvider for IBMQ(hub='ibm-q', group='open', project='main')>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "IBMQ.load_account()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "provider = IBMQ.get_provider('ibm-q')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "qcomp = provider.get_backend('ibmq_16_melbourne')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "job = execute(circuit, backend=qcomp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "from qiskit.tools.monitor import job_monitor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "Job Status: job has successfully run\n"
     ]
    }
   ],
   "source": [
    "job_monitor(job)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "result = job.result()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Svh/4+JlWNLM/AsVAJ4LDs1+PWtwX+O9mtpkZ+Zn7mmzrNuA2gOzsbNauXQvAoEGD6NatG1u2bAGgV69eFBQUsH79egAyMzMZN24clZWVvPPOOwCUlJSwf/9+4LKzfPTzR8N/j8LCQo4dO0ZVVRUAubm59OnTh4qKCgC6d+9OcXExGzZs4OTJkwCMHz+ebdu2cejQIQBGjhxJXV0du3btAmDAgAH07NmTyspKAHr06MHIkSNZt24d7o6ZMWHCBLZs2cLhw4cBKC4u5q233qKmpgZo3X7as2cPAIMHD6ZTp05s3boVgKysLIYMGcKGDRsA6NSpE2PHjqWiooIjR44AMGbMGPbu3UttbfAEvKFDh5KRkcH27dsB6Nu3LwMHDqSsrAyAzp07M2bMGMrLyzl69CgAY8eOpbq6mjfeeAOA4cOHU19fz44dOwDo378/OTk5lJeXA9C1a1dKSkooKyvj2LFjAIwbN46dO3dy4MAB7Sftp7jsJ7iE9mLfvn1x2U9nYu4eU1GRZ2vOAYZHml4FfuDulWdZL5vgmZvj3f0PUe3fAj7n7sPOsG4u0I3gnOaDwCJ3vz+ybCew1N3/Par/BGAt0M/d32hpuyUlJd7wj7Y1Zs1v9SZSxpI5ya5ARBJJv79OZ2ab3b2kuWUxXT1rZjcCLwL9CC6+KQX6AJvM7AtnWf0gUE8wMoyWxemjz1O4+x533+7uy4B/Ab5lZg2j5Dda2OZJ4NBZahIREQkt1sOz/wF8093vi240s68B3wV+3tKK7n7czDYDE4HlUYsmEtsFOx0I6s4gCMYyYGqTPhOBCnc/EcN2RUREzijW+zQvBn7dTPtygtHd2TwM3Gxmt5pZvpktALKBxQBmdr+ZPdfQ2cy+aGafNrNhZjbIzD4D3A+scPeGA8+LgRwzmx/Z5q3AzcD3Y/xsIiIiZxTrSPP3wDWcehsIkbZ1TTs35e6/MrNewDcIDvFuBSZHPeS6H6deVXOS4FaUwYABu4FFwA+itlltZpMjbbcDrwN36x5NERGJt1gnbF8N3G9mJcALkbargGnAt8P8QHd/FHi0hWU3N3m/DFgWYpvrCK6uFRERaTPnOmF7420bUR6hhTAUERFpDzRhu4iISEgKRBERkZBinhHIzHoSTGV3CXDK00bc/d/iVJeIiEjKiSk0zewq4GngGMHtJ7UEV7weA2oAhaaIiLRbsR6efRD4BdAfeB/4O4IRZwXwQHxLExERSS2xhublwEIPJqytBzq5+37gXkLeciIiInK+ijU0j0e93g9cGnl9hGBmHxERkXYr1guBKoHRwE6Cp4h818z6AF8A/hTf0kRERFJLrCPNfyWYpg6CqfDeJJjUoAenT3YgIiLSrsQ00nT3iqjXbwJ/H/eKREREUlTM92kCmNllQH7k7XZ33xW/kkRERFJTrPdp9gJ+DEwBPvhbs/0WuMXd9dBnERFpt2I9p/n/gDzgauDCyJ/xwEBgSXxLExERSS2xHp6dBHzM3cui2jaa2f8C/jt+ZYmIiKSeWEeabwLvNtP+HqBDsyIi0q7FGpr/Bsw3s/4NDZHXD6F5Z0VEpJ076+FZM3sF8KimgUCNmdVG3jfMQ5tFcM5TRESkXQpzTnNFm1chIiJyHjhraLr7dxJRiIiISKo718kN/g4YTnDYdpu7r41nUSIiIqko1skN+gMrgVH8bQ7abDOrAG5w99dbXFlEROQ8F+vVs/9J8BzNPHfPdfdcYHCk7T/jXZyIiEgqifXw7ETgGnevbmhw911mdjfwXFwrExERSTGxjjRb8sHZu4iIiJzfYg3N54D/NLPchgYzuwRYgEaaIiLSzsUamncDXYBdZrbbzGqAv0ba7o5zbSIiIikl1nOah4ArgWuBYYARPE9Tk7WLiEi7Fzo0zSwD+B9gpLs/CzzbZlWJiIikoNCHZ929HtgNdGy7ckRERFJXrOc0/x2YZ2a926IYERGRVBbrOc17CJ5yUmtme2nybE13vzxehYmIiKSaWENzBcF8s9YGtYiIiKS0UKFpZl2AB4GpwAUE92Te5e4H27A2ERGRlBL2nOZ3gJuBp4FlwMeB/9tGNYmIiKSksIdnpwEz3f0JADP7BbDRzDIiV9WKiIi0e2FHmrnAHxreuPsm4CSQ3RZFiYiIpKKwoZkBHG/SdpJzfIi1iIjI+Shs6BnwczM7FtV2IbDEzN5raHD3KfEsTkREJJWEDc2fNtP283gWIiIikupChaa7f6mtCxEREUl18XoItYiISLun0BQREQlJoSkiIhKSQlNERCQkhaaIiEhICk0REZGQFJoiIiIhKTRFRERCUmiKiIiEpNAUEREJSaEpIiISkkJTREQkJIWmiIhISApNERGRkBSaIiIiISk0RUREQlJoioiIhJTw0DSzO8ys2szeN7PNZnb1GfpeaGaPm9mfzOyEma1tps81ZubN/BnWph9ERETSTkJD08w+CywA7gOuAP4IrDazS1pYJQN4H1gIPH2WzRcA/aL+VMWjZhERkQaZCf55c4HH3X1J5P1dZnYdcDvwtaad3f1dYDaAmV0OXHSGbR9w94NxrldERKRRwkaaZtYRGAWsabJoDfCROPyICjPbZ2bPmdm1cdieiIjIKRI50uxNcLh1f5P2/cDHW7HdfQQj1ReBjsAXgefM7Bp3X9+0s5ndBtwGkJ2dzdq1awEYNGgQ3bp1Y8uWLQD06tWLgoIC1q8PNpGZmcm4ceOorKzknXfeAaCkpIT9+/cDl7Wi/NTS8N+jsLCQY8eOUVUVHOXOzc2lT58+VFRUANC9e3eKi4vZsGEDJ0+eBGD8+PFs27aNQ4cOATBy5Ejq6urYtWsXAAMGDKBnz55UVlYC0KNHD0aOHMm6detwd8yMCRMmsGXLFg4fPgxAcXExb731FjU1NUDr9tOePXsAGDx4MJ06dWLr1q0AZGVlMWTIEDZs2ABAp06dGDt2LBUVFRw5cgSAMWPGsHfvXmprawEYOnQoGRkZbN++HYC+ffsycOBAysrKAOjcuTNjxoyhvLyco0ePAjB27Fiqq6t54403ABg+fDj19fXs2LEDgP79+5OTk0N5eTkAXbt2paSkhLKyMo4dOwbAuHHj2LlzJwcOHNB+0n6Ky36Cls6OnX/27dsXl/10JububfgRon6QWTZQC4x39z9EtX8L+Jy7n/HCHTNbCBS6+zUhflYpcNLdp5ypX0lJiTf8o22NWfNbvYmUsWROsisQkUTS76/Tmdlmdy9pblkiLwQ6CNQDfZu0Z3H66LO1yoHBcd6miIikuYSFprsfBzYDE5ssmkhwFW08FREcthUREYmbRF89+zCw1Mw2ARsJrozNBhYDmNn9wJXu/rGGFcxsOMG5yt5AVzMrAnD3lyPL5wA1wLZIvy8AU4HpiflIIiKSLhIamu7+KzPrBXyD4F7KrcBkd98d6dKP06+qKQUujXr/UuRvi/zdEfg+0B84ShCe17t7afw/gYiIpLNEjzRx90eBR1tYdnMzbQPOsr3vAd+LR20iIiJnorlnRUREQlJoioiIhKTQFBERCUmhKSIiEpJCU0REJCSFpoiISEgKTRERkZAUmiIiIiEpNEVEREJSaIqIiISk0BQREQlJoSkiIhKSQlNERCQkhaaIiEhICk0REZGQFJoiIiIhKTRFRERCUmiKiIiEpNAUEREJSaEpIiISkkJTREQkJIWmiIhISApNERGRkBSaIiIiISk0RUREQlJoioiIhKTQFBERCUmhKRLxzDPPMHToUPLy8pg3b95py92du+++m7y8PC6//HIqKysblw0YMIARI0ZQVFRESUlJY/u3v/1t+vfvT1FREUVFRZSWlibks4hI28hMdgEiqaC+vp4777yTZ599lpycHEaPHs2UKVMYPnx4Y5/Vq1dTVVVFVVUV5eXl3H777ZSXlzcu//3vf0/v3r1P2/aXv/xl7rnnnoR8DhFpWxppigCbNm0iLy+PQYMG0bFjR2bMmMGqVatO6bNq1SpuuukmzIyrrrqKt99+m3379iWpYhFJBoWmCFBbW0tubm7j+5ycHGpra0P3MTM+8YlPMGrUKH70ox+dst7ChQu5/PLLueWWWzh8+HAbfgoRaWsKTRGC85VNmVnoPhs3bqSyspLVq1ezaNEi1q9fD8Dtt9/OX//6V15++WX69evHV77ylTaoXkQSRaEpQjBq3LNnT+P7vXv3kp2dHbpPw99ZWVnccMMNbNq0CYA+ffqQkZFBhw4dmDVrVmO7iJyfFJoiwOjRo6mqqqK6uprjx4/zxBNPMGXKlFP6TJkyhZ/97Ge4Oy+88AIf/vCH6devH++++y51dXUAvPvuu6xZs4bCwkKAU855rly5srFdRM5PunpWBMjMzGThwoVMmjSJ+vp6brnlFgoKCli8eDEAs2fPZvLkyZSWlpKXl0eXLl147LHHANi/fz833HADACdPnuTzn/881113HQBf/epXefnllzEzBgwYwA9/+MPkfEARiQtr7jxNuigpKfGKiopWb2fW/DgUkyKWzEl2BSKSSPr9dToz2+zuJc0t0+FZERGRkHR4Vtqt9vINWqN/kdShkaaIiEhICk0REZGQFJoiIiIhKTRFJKWd69Nn9uzZw7XXXkt+fj4FBQUsWLCgcR09fUbOlS4EEpGU1Zqnz2RmZvLQQw9RXFxMXV0do0aNYuLEiY3r6ukzci400hSRlNWap8/069eP4uJiALp160Z+fv5pk/CLxEqhKSIpq7VPn2lQU1PDSy+9xJgxYxrb9PQZORcKTRFJWa19+gzAkSNHmD59OvPnz6d79+6Anj4j506hKSIpq7VPnzlx4gTTp0/nxhtvZNq0aY199PQZOVcKTRFJWa15+oy7M3PmTPLz85k7d+4p6+jpM3KudPWsiKSs1jx9ZuPGjSxdupQRI0ZQVFQEwH333cfkyZP19Bk5ZwpNEUlpkydPZvLkyae0zZ49u/G1mbFo0aLT1hs3blyz5zsBli5dGt8iJW3o8KyIiEhIGmmKSMK0lyfPgJ4+k6400hQREQlJoSkiIhKSQlNERCQkhaaIiEhICk0REZGQFJoiIiIhKTRFRERCSnhomtkdZlZtZu+b2WYzu/os/UeY2TozO2pmtWb2f6zJYw7MbEJkW++b2S4zm93S9kRERM5VQkPTzD4LLADuA64A/gisNrNLWujfHXgW2A+MBu4G/hmYG9VnIFAa2dYVwP3AI2Y2ve0+iYiIpKNEjzTnAo+7+xJ3f9Xd7wL2Abe30P9GoAvwT+6+1d2fBB4A5kaNNmcDr7v7XZFtLgF+CtzTth9FRETSjbU0oXHcf5BZR+A94HPuvjyqfRFQ6O4TmlnnZ0Avd78+qm00sAkY5O7VZrYeeMXd74zq82ngl0AXdz/RZJu3AbdF3g4FdsTrM7ax3sDBZBchp9F+ST3aJ6npfNovl7r7xc0tSOTcs72BDIJDrdH2Ax9vYZ2+wN5m+jcsq478/d/N9MmM/Mx90Qvc/UfAj2IpPBWYWYW7lyS7DjmV9kvq0T5JTe1lvyTj6tmmQ1trpu1s/Zu2h+kjIiLSKokMzYNAPcHIMFoWp48+G7zRQn+i1mmpz0ng0DlVKiIi0oyEhaa7Hwc2AxObLJpIcOVrc8qAq83swib9Xwdqovo0Pbw7Eahoej7zPHfeHVJOE9ovqUf7JDW1i/2SsAuBoPGWk6XAHcBGgitfZwIF7r7bzO4HrnT3j0X6f5jgQp21wHeBIcDjwHfc/aFIn4HAVmAJ8EPgo8CjBBccPZmwDyciIu1eQh9C7e6/MrNewDeAfgRhN9ndd0e69AMui+r/P2Y2EVgEVACHgYeAh6P6VJvZZOAHBLeuvA7crcAUEZF4S+hIU0RE5HymuWdFRERCUmiKiIiEpNAUkXajYXrNpg91EIkXndNMYWY2HBgOfBh4Fyh39+rkViVy/mgIT9cvOokThWaKMrN/IZiwfjBQSzBRwwfASwTz6m4k+F2gHZggZnYpcMjdjyS7FjmVmXUA/gG4mOAhD7XAOnc/kNTCpN1RaKagyG05NcA/u/tiM8sFrgTGAqOAC4GvufvapBWZZsysB/Bngi8rTwJ/APY180CAjwJ/cfeWZrmSODOzbsCPgWsJvljuJZhC8yiwDvi5u//ZzExfMhPDzNLeCooAAAT5SURBVC4ABgK73f1YsuuJJ53TTE2fBv7s7osB3H2Puz/p7vcAcwi+Rf/GzAYls8g0cyNwAdAV+AnBfcOLzWySmV1sZh0iX24eA3oksc50dDfBE4smu3sfgn01H9gGTAK+Z2YXKzAT6k6Co2KLzexTZtbXzDKiO5hZdzP7+0jAnjc00kxBkUebfY/gOaLrG/6xuXt9ZPmFBLMk/czdH01aoWkk8gi7TIIJND4E3AR8CSgG/gL8iuCw4Ex3vyhZdaYjM/sDsNLdH27SnkEwQ9iPgb+6+3XJqC8dmVkZ8D7B/zMfAV4DVgJPETzK8X/MbDZws7tflbxKY6eRZmp6GtgNfMXMRrh7fUNgArj7+wQT0vdKVoHpJPJNuIzg8Ky5e527L4o85mgI8GtgBvBl4PvJqzT9mFkmwcxi083s4khbhpllRP6/WU8wXWeOmY1MZq3pIrIfTgBL3P1q4FKCLy6fBNYDz5vZvQRHzcqTVug50kgzxTScd4mcG3sEGAGsJvhH9yegJ8E3t38DrnD3mmTVmk4iwdnV3Q9HRjAdgA+iRv/DCA4HXuruTZ8BK23IzK4CfgGsAB5uej45ctj8VWCou9cmocS0Ymb9CL5Ebnf33zVZdgVwa2R5DyD3fNsnCs0UZWbdgU4EF/58Ebg+8v4NglHmQndfkLwK00fUF5nLgLroKzLNrIO7f2Bm3wRmufslyas0/USumu1AcKj8PoLDgSsIDpfvAS4HPgXku/voZNWZbsysM8HV/e9H3zPbcF7ZzP6D4Bz0Fcmq8VwpNFOImWURBORc4C2CcwKvExyufR64CLgE2KirMxOjyT45QPCFZR+wHHjK3d+N9LseOOLu65JVa7ozs4uAm4HPA0VAHXAM2ATc7+7n3aHA81lLVyubWRegEnjM3R9IfGWto9BMIWb2OFAA/BdBaPYERgLDCMLz6+7+YtIKTEMt7JMrCPbJXuBBd1+TtALTWORoTF30L+bIyPNCgqucC4F3FZaJ09w+aabPhcBngWWR5yyfVxSaKSJyCKOO4JDF+qi2S4AxBOcBBgGfdveXklZoGjnDPskl2CezCC5ymKF9knhm9kOCUeQmgvsB32mmT4/IeWjdo5kAIffJRe7+dsKLixNdPZs6hgPVQOM3Lw/sdvdfE1x59jbwmSTVl45a2ievuftygn1Sh/ZJwpnZ5wi+tDwErAIeNLNpZpYXOZ+GmXUFHotcga7AbGMt7JMbzOyyqH3SGfipmRUmsdRW0UgzRUT+Mf2W4F6/mwjuK/ugSZ+7CO4DLEpCiWlH+yR1mdkSoJ7gfuZpwD8RPMB+B1AKPEcw4cECd++YrDrTSbrsE400U4S7HwX+FegM/Ay4ycxyzexD0HjyfALBPWmSANonqSlyb2Y18La773L377v7CGA0wbR5/0Rw7+wjwNLkVZo+0mmfaKSZYiKHLb4JTCF4skkZ8CbwcYKrNm9191eSV2H60T5JPZG5gPtE5pTtCJxockHQZ4FlQLG7v5ysOtNJuuwThWaKitzqcD0wleDWk63Acnf/c1ILS2PaJ6ktcuWsuXu9mc0iOAzYJdl1pbP2uE8UmueBhhvok12H/I32SWozs7lAhrs/mOxaJNBe9olCU0Tanci0h/X6YpM62ss+UWiKiIiEpKtnRUREQlJoioiIhKTQFBERCUmhKSIiEpJCU0REJCSFpoiISEj/H8Xzj5zX9o0RAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plot_histogram(result.get_counts(circuit))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plot_histogram(result.get_counts())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}