Elitzur–Vaidman quantum bomb tester.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### How it works\n",
    "[Scott Aaronson lecture notes](https://www.scottaaronson.com/qclec/4.pdf)\n",
    "\n",
    "[Wikipedia](https://en.wikipedia.org/wiki/Elitzur%E2%80%93Vaidman_bomb_tester)\n",
    "\n",
    "Implemented by Dwarkesh Patel. Created by Avshalom Elitzur and Lev Vaidman."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from qiskit import(\n",
    "    QuantumCircuit,\n",
    "    QuantumRegister,\n",
    "    execute,\n",
    "    Aer)\n",
    "from qiskit.quantum_info.operators import Operator"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "e = np.pi / 100\n",
    "rotations = int(np.pi / (2*e))\n",
    "shots = 10000\n",
    "\n",
    "\n",
    "def elitzur_vaidman(bomb):\n",
    "    measurements = rotations + 1 if bomb else 1\n",
    "    circuit = QuantumCircuit(1, measurements)\n",
    "\n",
    "    rotate = Operator([\n",
    "        [np.cos(e), -np.sin(e)],\n",
    "        [np.sin(e), np.cos(e)]])\n",
    "\n",
    "    for i in range(rotations):\n",
    "        circuit.unitary(rotate, [0], label='Re')\n",
    "        if bomb:\n",
    "            circuit.measure(0, i)\n",
    "\n",
    "    circuit.measure(0, measurements - 1)\n",
    "\n",
    "    simulator = Aer.get_backend('qasm_simulator')\n",
    "    job = execute(circuit, simulator, shots=shots)\n",
    "    result = job.result()\n",
    "    counts = result.get_counts(circuit)\n",
    "    predict_bomb = predict_no_bomb = blown_up = 0\n",
    "    if bomb:\n",
    "        predict_bomb = counts['0' * measurements]\n",
    "        zeros_one = '0' * (predict_no_bomb - 1) + '1'\n",
    "        predict_no_bomb = counts[zeros_one] if zeros_one in counts else 0\n",
    "        blown_up = shots - predict_bomb - predict_no_bomb\n",
    "    else:\n",
    "        predict_bomb = counts['0'] if '0' in counts else 0\n",
    "        predict_no_bomb = counts['1']\n",
    "        blown_up = 0\n",
    "\n",
    "    y_pos = np.arange(3)\n",
    "    plt.bar(y_pos, [predict_bomb, predict_no_bomb, blown_up])\n",
    "    plt.xticks(y_pos, ['Predicts bomb', 'Predicts no bomb', 'Blown up'])\n",
    "    plt.ylabel('Trials')\n",
    "    plt.title('Elitzur-Vaidman results with' +\n",
    "              (' ' if bomb else ' no ') + 'bomb')\n",
    "\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "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": [
    "elitzur_vaidman(bomb=True)\n",
    "elitzur_vaidman(bomb=False)"
   ]
  }
 ],
 "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": "3.8.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}