distance_black_box.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from qiskit import QuantumRegister, ClassicalRegister, QuantumCircuit\n",
    "from qiskit import IBMQ, Aer, execute\n",
    "from qiskit.tools.visualization import plot_histogram"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "## distance_black_box\n",
    "\n",
    "distances = {\n",
    "    \"32\": 3,\n",
    "    \"31\": 2,\n",
    "    \"30\": 4,\n",
    "    \"21\": 7,\n",
    "    \"20\": 6,\n",
    "    \"10\": 5,\n",
    "}\n",
    "\n",
    "def dist_single():\n",
    "    qr = QuantumRegister(2)\n",
    "    qr_target = QuantumRegister(5)\n",
    "    qc = QuantumCircuit(qr, qr_target, name='dist_single')\n",
    "    \n",
    "    for edge in distances:\n",
    "        if edge[0] == '3':\n",
    "            node = format(int(edge[1]), '02b')[::-1]\n",
    "            d_bin = format(distances[edge], '02b')[::-1]\n",
    "            \n",
    "            for idx in range(len(node)):\n",
    "                if node[idx] == '0':\n",
    "                    qc.x(qr[idx])\n",
    "            \n",
    "            for idx in range(len(d_bin)):\n",
    "                if d_bin[idx] == '1':\n",
    "                    qc.ccx(qr[0], qr[1], qr_target[idx])\n",
    "            \n",
    "            for idx in range(len(node)):\n",
    "                if node[idx] == '0':\n",
    "                    qc.x(qr[idx])\n",
    "    \n",
    "    return qc\n",
    "\n",
    "def dist():\n",
    "    qr1 = QuantumRegister(2)\n",
    "    qr2 = QuantumRegister(2)\n",
    "    qr_target = QuantumRegister(5)\n",
    "    qr_anc = QuantumRegister(2)\n",
    "    qc = QuantumCircuit(qr1, qr2, qr_target, qr_anc, name='dist')\n",
    "    \n",
    "    for edge in distances:\n",
    "        if edge[0] != '3':\n",
    "            # convert to binaries\n",
    "            node1 = format(int(edge[0]), '02b')[::-1]\n",
    "            node2 = format(int(edge[1]), '02b')[::-1]\n",
    "            d_bin = format(distances[edge], '02b')[::-1]\n",
    "\n",
    "            for idx in range(len(node1)): # assume node1 and node2 have the same length\n",
    "                if node1[idx] == '0':\n",
    "                    qc.x(qr1[idx])\n",
    "                    \n",
    "            for idx in range(len(node2)):\n",
    "                if node2[idx] == '0':\n",
    "                    qc.x(qr2[idx])\n",
    "\n",
    "            for idx in range(len(d_bin)):\n",
    "                if d_bin[idx] == '1':\n",
    "                    qc.mct(qr1[:]+qr2[:], qr_target[idx], qr_anc)\n",
    "                    \n",
    "            for idx in range(len(node2)): # invert back\n",
    "                if node2[idx] == '0':\n",
    "                    qc.x(qr2[idx])\n",
    "\n",
    "            for idx in range(len(node1)):\n",
    "                if node1[idx] == '0':\n",
    "                    qc.x(qr1[idx])\n",
    "                    \n",
    "    return qc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "qr1 = QuantumRegister(2) # node reg.\n",
    "qr2 = QuantumRegister(2) # node reg.\n",
    "qr_target = QuantumRegister(5) # distance reg.\n",
    "qr_anc = QuantumRegister(2)\n",
    "c = ClassicalRegister(5)\n",
    "qc = QuantumCircuit(qr1, qr2, qr_target, qr_anc, c)\n",
    "\n",
    "qc.x(qr1[0])\n",
    "# qc.x(qr2[0])\n",
    "qc.append(dist(), qr1[:] + qr2[:] + qr_target[:] + qr_anc[:])\n",
    "qc.measure(qr_target, c)\n",
    "\n",
    "# qc.draw(output='mpl')\n",
    "\n",
    "backend = Aer.get_backend('qasm_simulator')\n",
    "job = execute(qc, backend, shots=1024)\n",
    "counts = job.result().get_counts()\n",
    "\n",
    "plot_histogram(counts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'01'"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "format(1, '02b')"
   ]
  }
 ],
 "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": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}