single_johnson_graph_search.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "338ddade-1e33-4d7a-8cce-5aca9235e812",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Some parts of the following code are yet to be parametrized to the general J(n,k) graph\n",
    "# The used example is J(4,2)\n",
    "import math\n",
    "import scipy.special\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from qiskit import QuantumRegister, ClassicalRegister, QuantumCircuit, Aer, transpile\n",
    "from qiskit.circuit.library import SwapGate\n",
    "from qiskit.tools.visualization import plot_histogram"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "b46f39dd-a6c4-48de-83d6-e733cf6095b8",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Johnson graph J(n,k) main parameters\n",
    "n = 4\n",
    "k = 2\n",
    "\n",
    "nstates = int(scipy.special.binom(n, k))  # Number of vertices in a J(n,k) graph\n",
    "degree = k*(n-k)  # J(n,k) degree\n",
    "cnum = math.ceil(math.log2(int(scipy.special.binom(n, 2))))  # Required number of qubits for the coin register\n",
    "\n",
    "state_ = QuantumRegister(n, 'state')  # State register\n",
    "anci_ = QuantumRegister(n, 'anci')  # Ancillas\n",
    "coin_ = QuantumRegister(cnum, 'coin')  # Coin register\n",
    "clas_ = ClassicalRegister(n, 'measure')  # Classical lines\n",
    "qc = QuantumCircuit(state_, anci_ , coin_, clas_)  # Quantum circuit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "b72452b0-19e7-430a-8c09-c5a8910bb71d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Grover diffuser\n",
    "grover_op = QuantumCircuit(cnum, name='grover_op')\n",
    "for i in range(cnum):\n",
    "    grover_op.h(i)\n",
    "    grover_op.x(i)\n",
    "grover_op.h(cnum-1)\n",
    "grover_op.mcx([i for i in range(0, cnum-1)],[cnum-1])\n",
    "grover_op.h(cnum-1)\n",
    "for i in range(cnum):\n",
    "    grover_op.x(i)\n",
    "    grover_op.h(i)\n",
    "grover_gate = grover_op.to_gate()\n",
    "grover_control_gate = grover_op.to_gate().control(n)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "e920f7aa-77b7-4268-b35e-ea9bf1ad6ecb",
   "metadata": {},
   "outputs": [],
   "source": [
    "def init():\n",
    "    # Dicke state initialization on the state register (TODO)\n",
    "    qc.initialize([\n",
    "        0, 0, 0, 1/np.sqrt(nstates), 0,\n",
    "        1/np.sqrt(nstates), 1/np.sqrt(nstates), 0, 0,\n",
    "        1/np.sqrt(nstates), 1/np.sqrt(nstates), 0, 1/np.sqrt(nstates),\n",
    "        0, 0, 0\n",
    "    ], [state_[0], state_[1], state_[2], state_[3]])\n",
    "\n",
    "    # Uniform superposition initialization on the coin register\n",
    "    for i in range(cnum):\n",
    "        qc.h(coin_[i])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "eb7034a6-85ca-42a1-af5b-0fa4b95c20f4",
   "metadata": {},
   "outputs": [],
   "source": [
    "# The coin phase first applies a Grover operator regardless of the current state space, then reapplies it according to the oracle's output\n",
    "# The CNOT gates encode the following matrix:\n",
    "#  [ 1 1 0 0,\n",
    "#    1 0 1 1,\n",
    "#    1 1 1 0,\n",
    "#    0 1 0 1 ]\n",
    "# The controlled-Grover application checks whether a k-element subsets of the matrix's columns\n",
    "#  XORs to the syndrome s = [0, 0, 1, 1]\n",
    "\n",
    "def coin_phase():\n",
    "    qc.barrier()\n",
    "    \n",
    "    qc.append(grover_gate, [coin_[i] for i in range(cnum)])\n",
    "    \n",
    "    qc.cx(state_[0], anci_[0])\n",
    "    qc.cx(state_[0], anci_[1])\n",
    "    qc.cx(state_[0], anci_[2])\n",
    "    qc.cx(state_[1], anci_[0])\n",
    "    qc.cx(state_[1], anci_[2])\n",
    "    qc.cx(state_[1], anci_[3])\n",
    "    qc.cx(state_[2], anci_[1])\n",
    "    qc.cx(state_[2], anci_[2])\n",
    "    qc.cx(state_[3], anci_[1])\n",
    "    qc.cx(state_[3], anci_[3])\n",
    "    \n",
    "    qc.barrier()\n",
    "    \n",
    "    qc.x(anci_[0])\n",
    "    qc.x(anci_[1])\n",
    "    qc.append(grover_control_gate, [anci_[i] for i in range(n)] + [coin_[i] for i in range(cnum)])\n",
    "    qc.x(anci_[1])\n",
    "    qc.x(anci_[0])\n",
    "    \n",
    "    qc.barrier()\n",
    "    \n",
    "    qc.cx(state_[3], anci_[3])\n",
    "    qc.cx(state_[3], anci_[1])\n",
    "    qc.cx(state_[2], anci_[2])\n",
    "    qc.cx(state_[2], anci_[1])\n",
    "    qc.cx(state_[1], anci_[3])\n",
    "    qc.cx(state_[1], anci_[2])\n",
    "    qc.cx(state_[1], anci_[0])\n",
    "    qc.cx(state_[0], anci_[2])\n",
    "    qc.cx(state_[0], anci_[1])\n",
    "    qc.cx(state_[0], anci_[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "52267f21-814d-487c-96be-3d08afe2ec2a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# SWAP sequence (TODO)\n",
    "swapping = SwapGate().control(num_ctrl_qubits=cnum)\n",
    "def shift_phase():    \n",
    "    qc.append(swapping, [coin_[0], coin_[1], coin_[2], state_[0], state_[1]])\n",
    "    qc.x(coin_[0])\n",
    "    qc.append(swapping, [coin_[0], coin_[1], coin_[2], state_[2], state_[3]])\n",
    "    qc.x(coin_[0])\n",
    "    qc.x(coin_[1])\n",
    "    qc.append(swapping, [coin_[0], coin_[1], coin_[2], state_[0], state_[2]])\n",
    "    qc.x(coin_[0])\n",
    "    qc.append(swapping, [coin_[0], coin_[1], coin_[2], state_[1], state_[3]])\n",
    "    qc.x(coin_[0])\n",
    "    qc.x(coin_[1])\n",
    "    qc.x(coin_[2])\n",
    "    qc.append(swapping, [coin_[0], coin_[1], coin_[2], state_[0], state_[3]])\n",
    "    qc.x(coin_[0])\n",
    "    qc.append(swapping, [coin_[0], coin_[1], coin_[2], state_[1], state_[2]])\n",
    "    qc.x(coin_[0])\n",
    "    qc.x(coin_[2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "d7b38078-91bc-4e24-8dd8-e12b60d381d4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<qiskit.circuit.instructionset.InstructionSet at 0x7fc546375c00>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "init()\n",
    "nsteps = 2\n",
    "for _ in range(nsteps):\n",
    "    coin_phase()\n",
    "    shift_phase()\n",
    "    \n",
    "qc.barrier()\n",
    "qc.measure([state_[i] for i in range(n)], [clas_[i] for i in range(n)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "186d4cee-e219-462c-9ee3-51fbdc4debfd",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<frozen importlib._bootstrap>:219: RuntimeWarning: scipy._lib.messagestream.MessageStream size changed, may indicate binary incompatibility. Expected 56 from C header, got 64 from PyObject\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Transpile for simulator\n",
    "simulator = Aer.get_backend('aer_simulator')\n",
    "circ = transpile(qc, simulator)\n",
    "\n",
    "# Run and get counts\n",
    "result = simulator.run(circ).result()\n",
    "counts = result.get_counts(circ)\n",
    "plot_histogram(counts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "c600c027-de31-440e-be9a-e280aba841fd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1656.49x3094.28 with 1 Axes>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "qc.draw()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "70f0dd21-1e4b-42a5-8026-6954a191850a",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Qiskit v0.35.0 (ipykernel)",
   "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": "3.8.13"
  },
  "widgets": {
   "application/vnd.jupyter.widget-state+json": {
    "state": {},
    "version_major": 2,
    "version_minor": 0
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}