qiskit-grover-sudoku.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "source": [
    "# Grover's Algorithm for Binary Sudoku\n",
    "\n",
    "The oracle checks if the solution is a correct Sudoku instance.\n",
    "\n",
    "![sudoku](binary_sudoku.png)"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "outputs": [],
   "source": [
    "from qiskit import Aer, transpile\n",
    "from qiskit.circuit import AncillaRegister, ClassicalRegister, QuantumCircuit, QuantumRegister\n",
    "from qiskit.visualization import plot_histogram"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "outputs": [],
   "source": [
    "def xor():\n",
    "    qr = QuantumRegister(3)\n",
    "    qc = QuantumCircuit(qr)\n",
    "\n",
    "    qc.cx(qr[0], qr[2])\n",
    "    qc.cx(qr[1], qr[2])\n",
    "\n",
    "    u = qc.to_gate()\n",
    "    u.name = \"XOR\"\n",
    "    return u"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "outputs": [],
   "source": [
    "def check_rows_columns():\n",
    "    qr = QuantumRegister(4, 'in')\n",
    "    ar = AncillaRegister(4, 'tmp')\n",
    "    qc = QuantumCircuit(qr, ar)\n",
    "\n",
    "    qc.append(xor(), [qr[0], qr[1], ar[0]])\n",
    "    qc.append(xor(), [qr[2], qr[3], ar[1]])\n",
    "    qc.append(xor(), [qr[0], qr[2], ar[2]])\n",
    "    qc.append(xor(), [qr[1], qr[3], ar[3]])\n",
    "\n",
    "    u = qc.to_gate()\n",
    "    u.name = \"XORs\"\n",
    "    return u"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "outputs": [],
   "source": [
    "def sudoku_oracle():\n",
    "    qr = QuantumRegister(4)\n",
    "    ar = AncillaRegister(4)\n",
    "    out = QuantumRegister(1)\n",
    "\n",
    "    qc = QuantumCircuit(qr, ar, out)\n",
    "\n",
    "    # XOR\n",
    "    qc.append(check_rows_columns(), list(qr) + list(ar))\n",
    "    # AND all the results\n",
    "    qc.mcx(ar, out)\n",
    "    # Uncompute using XOR\n",
    "    qc.append(check_rows_columns().inverse(), list(qr) + list(ar))\n",
    "\n",
    "    u = qc.to_gate()\n",
    "    u.name = \"$U_\\\\chi$\"\n",
    "    return u"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "outputs": [],
   "source": [
    "from qiskit.circuit.library import ZGate\n",
    "\n",
    "def reflect_zero(nqubits: int):\n",
    "    qr = QuantumRegister(nqubits)\n",
    "    qc = QuantumCircuit(qr)\n",
    "    # Apply transformation |00..0> -> |11..1> (X-gates)\n",
    "    qc.x(qr)\n",
    "    # Do multi-controlled-Z gate\n",
    "    qc.append(ZGate().control(nqubits - 1), qr)\n",
    "    # Apply transformation |11..1> -> |00..0>\n",
    "    qc.x(qr)\n",
    "    # We will return the diffuser as a gate\n",
    "    u = qc.to_gate()\n",
    "    u.name = \"$U_0$\"\n",
    "    return u"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "outputs": [],
   "source": [
    "from qiskit.circuit import Gate\n",
    "\n",
    "def reflect_initial(init_gate: Gate, nqubits: int):\n",
    "    qr = QuantumRegister(nqubits)\n",
    "    qc = QuantumCircuit(qr)\n",
    "\n",
    "    qc.append(init_gate.inverse(), [qr])\n",
    "    qc.append(reflect_zero(nqubits), qr)\n",
    "    qc.append(init_gate, [qr])\n",
    "\n",
    "    u = qc.to_gate()\n",
    "    u.name = \"$U_\\\\psi$\"\n",
    "    return u"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "outputs": [],
   "source": [
    "from qiskit.circuit.library import HGate\n",
    "\n",
    "def create_grover_circuit():\n",
    "    qr = QuantumRegister(4, 'in')\n",
    "    ar = AncillaRegister(4, 'anc')\n",
    "    pkb = QuantumRegister(1, 'pkb')\n",
    "    output = ClassicalRegister(4, 'out')\n",
    "\n",
    "    qc = QuantumCircuit(qr, ar, pkb, output)\n",
    "\n",
    "    # prepare initial state\n",
    "    qc.h(qr)\n",
    "    # phase-kickback trick (S_\\chi)\n",
    "    qc.x(pkb)\n",
    "    qc.h(pkb)\n",
    "\n",
    "    qc.barrier()\n",
    "\n",
    "    for i in range(2):\n",
    "        # S_\\chi\n",
    "        qc.append(sudoku_oracle(), list(qr) + list(ar) + list(pkb))\n",
    "        # A^-1\n",
    "        qc.append(reflect_initial(HGate(), 4), qr)\n",
    "        qc.barrier()\n",
    "\n",
    "    qc.measure(qr, output)\n",
    "\n",
    "    return qc"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 1240.87x869.556 with 1 Axes>",
      "image/png": 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\n"
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "circuit = create_grover_circuit()\n",
    "# circuit.decompose([\"$U_\\\\chi$\", \"$U_\\\\psi$\"]).decompose([\"XORs\", \"XORs_dg\", \"$U_0$\"]).draw(\"mpl\")\n",
    "circuit.draw(\"mpl\")"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "outputs": [],
   "source": [
    "backend = Aer.get_backend('aer_simulator')"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'1100': 4, '1110': 2, '1011': 3, '1000': 2, '0110': 500, '1101': 1, '0100': 11, '0000': 7, '0010': 5, '1001': 471, '0101': 2, '1111': 1, '0001': 6, '0011': 3, '0111': 2, '1010': 4}\n"
     ]
    },
    {
     "data": {
      "text/plain": "<Figure size 700x500 with 1 Axes>",
      "image/png": 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\n"
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "results = backend.run(transpile(circuit, backend)).result()\n",
    "counts = results.get_counts()\n",
    "print(counts)\n",
    "plot_histogram(counts)"
   ],
   "metadata": {
    "collapsed": false
   }
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}