MasterMind.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from qiskit import *\n",
    "from qiskit.visualization import plot_histogram"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "colors = {\n",
    "    \"red\":(0,0),\n",
    "    \"green\":(0,1),\n",
    "    \"orange\":(1,0),\n",
    "    \"yellow\":(1,1)\n",
    "    }\n",
    "\n",
    "code_len = 4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1694.03x1047.48 with 1 Axes>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "n_qubits = 16 # in the video we watched 11 but we are going to need 5 auxiliar qubits (the last)\n",
    "              #                                       (we can do it with only 2 auxiliar qubits)\n",
    "code = [\"red\", \"orange\", \"red\", \"orange\"]\n",
    "game_operator = QuantumCircuit(n_qubits, n_qubits - 5)\n",
    "\n",
    "for i, color in enumerate(code):\n",
    "    for j,k in enumerate(colors[color]):\n",
    "        if k == 0:\n",
    "            game_operator.x(2*i+j)\n",
    "            \n",
    "    game_operator.ccx(2*i, 2*i + 1, 11 + i)\n",
    "    \n",
    "    for j,k in enumerate(colors[color]):\n",
    "        if k == 0:\n",
    "            game_operator.x(2*i+j)\n",
    "    \n",
    "\n",
    "for i in range(11,15):\n",
    "    game_operator.ccx(i, 10, 15)\n",
    "    game_operator.ccx(15,9, 8)\n",
    "    game_operator.ccx(i, 10, 15)\n",
    "    game_operator.ccx(i, 10, 9)\n",
    "    game_operator.cx(i, 10)\n",
    "    \n",
    "# I repeat this part to clean the ancillas (if you don't use the gate more than one time\n",
    "# in the circuit,it is not necessary)\n",
    "\"\"\"\n",
    "for i, color in enumerate(code):\n",
    "    for j,k in enumerate(colors[color]):\n",
    "        if k == 0:\n",
    "            game_operator.x(2*i+j)\n",
    "            \n",
    "    game_operator.ccx(2*i, 2*i + 1, 11 + i)\n",
    "    \n",
    "    for j,k in enumerate(colors[color]):\n",
    "        if k == 0:\n",
    "            game_operator.x(2*i+j)\n",
    "\"\"\"          \n",
    "\n",
    "game_operator.draw(output = 'mpl')\n",
    "\n",
    "            \n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "quest = [\"orange\", \"orange\", \"red\", \"orange\"]\n",
    "quest_operator = QuantumCircuit(n_qubits, n_qubits - 5)\n",
    "\n",
    "\n",
    "for i, color in enumerate(quest):\n",
    "    for j,k in enumerate(colors[color]):\n",
    "        if k == 1:\n",
    "            quest_operator.x(2*i+j)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1694.03x1047.48 with 1 Axes>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "circ = quest_operator + game_operator\n",
    "circ.draw(output = 'mpl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "circ.measure(range(11), range(11))\n",
    "backend = Aer.get_backend('qasm_simulator')\n",
    "job = execute(circ, backend, shots=1)\n",
    "result = job.result()\n",
    "counts = result.get_counts(circ)\n",
    "plot_histogram(counts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "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": "3.6.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}