Grover_6qubits.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "8fdff334-b170-489e-bfe2-1b3b715f1342",
   "metadata": {},
   "source": [
    "## Grover's algorithm on a 6-qubits space with the V-Oracle model\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "791c1f3c",
   "metadata": {},
   "source": [
    "Search for the state |111111>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d0964c08-8331-4ee7-ac0b-28d1ab3864f4",
   "metadata": {},
   "source": [
    "Import the required packages\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "bde5a824-3350-4c8f-b792-99c5eb5b267a",
   "metadata": {},
   "outputs": [],
   "source": [
    "from qiskit import QuantumRegister, ClassicalRegister, QuantumCircuit\n",
    "from qiskit import Aer, assemble\n",
    "from qiskit.visualization import plot_histogram"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d195028e-862a-4402-b154-c3d7f53eab3c",
   "metadata": {},
   "source": [
    "Definine the registers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "afa2b574-cadc-4899-8bb8-afd43a6043d2",
   "metadata": {},
   "outputs": [],
   "source": [
    "qreg_q = QuantumRegister(10, 'q')\n",
    "creg_c = ClassicalRegister(6, 'c')\n",
    "circuit = QuantumCircuit(qreg_q, creg_c)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5e3e8d6f-7305-4e8f-8205-5aecb6cfc012",
   "metadata": {},
   "source": [
    "Initialise the states"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "fd6f45f9-24a3-4e56-841e-7eb58b543700",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<qiskit.circuit.instructionset.InstructionSet at 0x7f1798eb2680>"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "circuit.h(qreg_q[0])\n",
    "circuit.h(qreg_q[1])\n",
    "circuit.h(qreg_q[2])\n",
    "circuit.h(qreg_q[3])\n",
    "circuit.h(qreg_q[4])\n",
    "circuit.h(qreg_q[5])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a2485535-55a7-4514-90b7-5611eaca1558",
   "metadata": {},
   "source": [
    "Quantum barrier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "53ceeb9c-44e6-4d80-8ddb-a4fe04a35544",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<qiskit.circuit.instructionset.InstructionSet at 0x7f1798d2af40>"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "circuit.barrier(qreg_q[0], qreg_q[1], qreg_q[2], qreg_q[3], qreg_q[4], qreg_q[5], qreg_q[6], qreg_q[7], qreg_q[8], qreg_q[9])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "11968abe-ed8e-4f19-ab8b-ca4a8c3b875d",
   "metadata": {},
   "source": [
    "Iteration 1"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b1f219de-df6d-4efd-bfca-91a160502156",
   "metadata": {},
   "source": [
    "V-oracle model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "fac1ac7c-e133-4a8b-9869-1ac66b686d6f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<qiskit.circuit.instructionset.InstructionSet at 0x7f1793997900>"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "circuit.ccx(qreg_q[0], qreg_q[1], qreg_q[6])\n",
    "circuit.ccx(qreg_q[2], qreg_q[3], qreg_q[7])\n",
    "circuit.ccx(qreg_q[6], qreg_q[7], qreg_q[8])\n",
    "circuit.ccx(qreg_q[4], qreg_q[8], qreg_q[9])\n",
    "circuit.cz(qreg_q[9], qreg_q[5])\n",
    "circuit.ccx(qreg_q[4], qreg_q[8], qreg_q[9])\n",
    "circuit.ccx(qreg_q[6], qreg_q[7], qreg_q[8])\n",
    "circuit.ccx(qreg_q[2], qreg_q[3], qreg_q[7])\n",
    "circuit.ccx(qreg_q[0], qreg_q[1], qreg_q[6])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "66caa8f4-9eb8-4a6e-807c-25d8d1dbbc24",
   "metadata": {},
   "source": [
    "Quantum barrier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "36f3e8e7-4834-4890-a7d5-104dbc92310a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<qiskit.circuit.instructionset.InstructionSet at 0x7f17939d9100>"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "circuit.barrier(qreg_q[0], qreg_q[1], qreg_q[2], qreg_q[3], qreg_q[4], qreg_q[5], qreg_q[6], qreg_q[7], qreg_q[8], qreg_q[9])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "21f873c5-93a9-4896-a9f1-463e04096f67",
   "metadata": {},
   "source": [
    "Diffuser"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "1b6c13a9-411d-416e-b9fa-0c04127347e0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<qiskit.circuit.instructionset.InstructionSet at 0x7f1793a3f140>"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "circuit.h(qreg_q[0])\n",
    "circuit.h(qreg_q[1])\n",
    "circuit.h(qreg_q[2])\n",
    "circuit.h(qreg_q[3])\n",
    "circuit.h(qreg_q[4])\n",
    "circuit.h(qreg_q[5])\n",
    "circuit.x(qreg_q[0])\n",
    "circuit.x(qreg_q[1])\n",
    "circuit.x(qreg_q[2])\n",
    "circuit.x(qreg_q[3])\n",
    "circuit.x(qreg_q[4])\n",
    "circuit.x(qreg_q[5])\n",
    "circuit.ccx(qreg_q[0], qreg_q[1], qreg_q[6])\n",
    "circuit.ccx(qreg_q[2], qreg_q[3], qreg_q[7])\n",
    "circuit.ccx(qreg_q[6], qreg_q[7], qreg_q[8])\n",
    "circuit.ccx(qreg_q[4], qreg_q[8], qreg_q[9])\n",
    "circuit.cz(qreg_q[9], qreg_q[5])\n",
    "circuit.ccx(qreg_q[4], qreg_q[8], qreg_q[9])\n",
    "circuit.ccx(qreg_q[6], qreg_q[7], qreg_q[8])\n",
    "circuit.ccx(qreg_q[2], qreg_q[3], qreg_q[7])\n",
    "circuit.ccx(qreg_q[0], qreg_q[1], qreg_q[6])\n",
    "circuit.x(qreg_q[0])\n",
    "circuit.x(qreg_q[1])\n",
    "circuit.x(qreg_q[2])\n",
    "circuit.x(qreg_q[3])\n",
    "circuit.x(qreg_q[4])\n",
    "circuit.x(qreg_q[5])\n",
    "circuit.h(qreg_q[0])\n",
    "circuit.h(qreg_q[1])\n",
    "circuit.h(qreg_q[2])\n",
    "circuit.h(qreg_q[3])\n",
    "circuit.h(qreg_q[4])\n",
    "circuit.h(qreg_q[5])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4d87771b-0434-48c3-a7c4-2bec038c050a",
   "metadata": {},
   "source": [
    "Quantum barrier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "a32287f4-3728-4e5e-93bb-d9a62fb1661b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<qiskit.circuit.instructionset.InstructionSet at 0x7f179398e600>"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "circuit.barrier(qreg_q[0], qreg_q[1], qreg_q[2], qreg_q[3], qreg_q[4], qreg_q[5], qreg_q[6], qreg_q[7], qreg_q[8], qreg_q[9])\n",
    "circuit.barrier(qreg_q[0], qreg_q[1], qreg_q[2], qreg_q[3], qreg_q[4], qreg_q[5], qreg_q[6], qreg_q[7], qreg_q[8], qreg_q[9])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bba389e3-fe5e-469a-9849-04f25cdf4f50",
   "metadata": {},
   "source": [
    "Iteration 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "f78abef6-a4fe-4e4a-a9f9-fc7bda8f00ec",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<qiskit.circuit.instructionset.InstructionSet at 0x7f17939d64c0>"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# oracle iteration 2\n",
    "circuit.ccx(qreg_q[0], qreg_q[1], qreg_q[6])\n",
    "circuit.ccx(qreg_q[2], qreg_q[3], qreg_q[7])\n",
    "circuit.ccx(qreg_q[6], qreg_q[7], qreg_q[8])\n",
    "circuit.ccx(qreg_q[4], qreg_q[8], qreg_q[9])\n",
    "circuit.cz(qreg_q[9], qreg_q[5])\n",
    "circuit.ccx(qreg_q[4], qreg_q[8], qreg_q[9])\n",
    "circuit.ccx(qreg_q[6], qreg_q[7], qreg_q[8])\n",
    "circuit.ccx(qreg_q[2], qreg_q[3], qreg_q[7])\n",
    "circuit.ccx(qreg_q[0], qreg_q[1], qreg_q[6])\n",
    "# barier\n",
    "circuit.barrier(qreg_q[0], qreg_q[1], qreg_q[2], qreg_q[3], qreg_q[4], qreg_q[5], qreg_q[6], qreg_q[7], qreg_q[8], qreg_q[9])\n",
    "# diffuser iteration 2\n",
    "circuit.h(qreg_q[0])\n",
    "circuit.h(qreg_q[1])\n",
    "circuit.h(qreg_q[2])\n",
    "circuit.h(qreg_q[3])\n",
    "circuit.h(qreg_q[4])\n",
    "circuit.h(qreg_q[5])\n",
    "circuit.x(qreg_q[0])\n",
    "circuit.x(qreg_q[1])\n",
    "circuit.x(qreg_q[2])\n",
    "circuit.x(qreg_q[3])\n",
    "circuit.x(qreg_q[4])\n",
    "circuit.x(qreg_q[5])\n",
    "circuit.ccx(qreg_q[0], qreg_q[1], qreg_q[6])\n",
    "circuit.ccx(qreg_q[2], qreg_q[3], qreg_q[7])\n",
    "circuit.ccx(qreg_q[6], qreg_q[7], qreg_q[8])\n",
    "circuit.ccx(qreg_q[4], qreg_q[8], qreg_q[9])\n",
    "circuit.cz(qreg_q[9], qreg_q[5])\n",
    "circuit.ccx(qreg_q[4], qreg_q[8], qreg_q[9])\n",
    "circuit.ccx(qreg_q[6], qreg_q[7], qreg_q[8])\n",
    "circuit.ccx(qreg_q[2], qreg_q[3], qreg_q[7])\n",
    "circuit.ccx(qreg_q[0], qreg_q[1], qreg_q[6])\n",
    "circuit.x(qreg_q[0])\n",
    "circuit.x(qreg_q[1])\n",
    "circuit.x(qreg_q[2])\n",
    "circuit.x(qreg_q[3])\n",
    "circuit.x(qreg_q[4])\n",
    "circuit.x(qreg_q[5])\n",
    "circuit.h(qreg_q[0])\n",
    "circuit.h(qreg_q[1])\n",
    "circuit.h(qreg_q[2])\n",
    "circuit.h(qreg_q[3])\n",
    "circuit.h(qreg_q[4])\n",
    "circuit.h(qreg_q[5])\n",
    "#barier *2\n",
    "circuit.barrier(qreg_q[0], qreg_q[1], qreg_q[2], qreg_q[3], qreg_q[4], qreg_q[5], qreg_q[6], qreg_q[7], qreg_q[8], qreg_q[9])\n",
    "circuit.barrier(qreg_q[0], qreg_q[1], qreg_q[2], qreg_q[3], qreg_q[4], qreg_q[5], qreg_q[6], qreg_q[7], qreg_q[8], qreg_q[9])\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "db4fad66-2cf0-4619-bd53-f3a8575651c6",
   "metadata": {},
   "source": [
    "Iteration 3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "7afb4c73-7e03-409c-80df-f305113becbe",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<qiskit.circuit.instructionset.InstructionSet at 0x7f1793a3fd80>"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# oracle iteration 3\n",
    "circuit.ccx(qreg_q[0], qreg_q[1], qreg_q[6])\n",
    "circuit.ccx(qreg_q[2], qreg_q[3], qreg_q[7])\n",
    "circuit.ccx(qreg_q[6], qreg_q[7], qreg_q[8])\n",
    "circuit.ccx(qreg_q[4], qreg_q[8], qreg_q[9])\n",
    "circuit.cz(qreg_q[9], qreg_q[5])\n",
    "circuit.ccx(qreg_q[4], qreg_q[8], qreg_q[9])\n",
    "circuit.ccx(qreg_q[6], qreg_q[7], qreg_q[8])\n",
    "circuit.ccx(qreg_q[2], qreg_q[3], qreg_q[7])\n",
    "circuit.ccx(qreg_q[0], qreg_q[1], qreg_q[6])\n",
    "# barier\n",
    "circuit.barrier(qreg_q[0], qreg_q[1], qreg_q[2], qreg_q[3], qreg_q[4], qreg_q[5], qreg_q[6], qreg_q[7], qreg_q[8], qreg_q[9])\n",
    "# diffuser iteration 3\n",
    "circuit.h(qreg_q[0])\n",
    "circuit.h(qreg_q[1])\n",
    "circuit.h(qreg_q[2])\n",
    "circuit.h(qreg_q[3])\n",
    "circuit.h(qreg_q[4])\n",
    "circuit.h(qreg_q[5])\n",
    "circuit.x(qreg_q[0])\n",
    "circuit.x(qreg_q[1])\n",
    "circuit.x(qreg_q[2])\n",
    "circuit.x(qreg_q[3])\n",
    "circuit.x(qreg_q[4])\n",
    "circuit.x(qreg_q[5])\n",
    "circuit.ccx(qreg_q[0], qreg_q[1], qreg_q[6])\n",
    "circuit.ccx(qreg_q[2], qreg_q[3], qreg_q[7])\n",
    "circuit.ccx(qreg_q[6], qreg_q[7], qreg_q[8])\n",
    "circuit.ccx(qreg_q[4], qreg_q[8], qreg_q[9])\n",
    "circuit.cz(qreg_q[9], qreg_q[5])\n",
    "circuit.ccx(qreg_q[4], qreg_q[8], qreg_q[9])\n",
    "circuit.ccx(qreg_q[6], qreg_q[7], qreg_q[8])\n",
    "circuit.ccx(qreg_q[2], qreg_q[3], qreg_q[7])\n",
    "circuit.ccx(qreg_q[0], qreg_q[1], qreg_q[6])\n",
    "circuit.x(qreg_q[0])\n",
    "circuit.x(qreg_q[1])\n",
    "circuit.x(qreg_q[2])\n",
    "circuit.x(qreg_q[3])\n",
    "circuit.x(qreg_q[4])\n",
    "circuit.x(qreg_q[5])\n",
    "circuit.h(qreg_q[0])\n",
    "circuit.h(qreg_q[1])\n",
    "circuit.h(qreg_q[2])\n",
    "circuit.h(qreg_q[3])\n",
    "circuit.h(qreg_q[4])\n",
    "circuit.h(qreg_q[5])\n",
    "#barier *2\n",
    "circuit.barrier(qreg_q[0], qreg_q[1], qreg_q[2], qreg_q[3], qreg_q[4], qreg_q[5], qreg_q[6], qreg_q[7], qreg_q[8], qreg_q[9])\n",
    "circuit.barrier(qreg_q[0], qreg_q[1], qreg_q[2], qreg_q[3], qreg_q[4], qreg_q[5], qreg_q[6], qreg_q[7], qreg_q[8], qreg_q[9])\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "efd0c723-5e6f-4138-8020-1b0cb52ccf7a",
   "metadata": {},
   "source": [
    "Iteration 4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "930b224c-9b1e-49ac-baec-393c909ff5e7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<qiskit.circuit.instructionset.InstructionSet at 0x7f1793943280>"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# oracle iteration 4\n",
    "circuit.ccx(qreg_q[0], qreg_q[1], qreg_q[6])\n",
    "circuit.ccx(qreg_q[2], qreg_q[3], qreg_q[7])\n",
    "circuit.ccx(qreg_q[6], qreg_q[7], qreg_q[8])\n",
    "circuit.ccx(qreg_q[4], qreg_q[8], qreg_q[9])\n",
    "circuit.cz(qreg_q[9], qreg_q[5])\n",
    "circuit.ccx(qreg_q[4], qreg_q[8], qreg_q[9])\n",
    "circuit.ccx(qreg_q[6], qreg_q[7], qreg_q[8])\n",
    "circuit.ccx(qreg_q[2], qreg_q[3], qreg_q[7])\n",
    "circuit.ccx(qreg_q[0], qreg_q[1], qreg_q[6])\n",
    "# barier\n",
    "circuit.barrier(qreg_q[0], qreg_q[1], qreg_q[2], qreg_q[3], qreg_q[4], qreg_q[5], qreg_q[6], qreg_q[7], qreg_q[8], qreg_q[9])\n",
    "# diffuser iteration 4\n",
    "circuit.h(qreg_q[0])\n",
    "circuit.h(qreg_q[1])\n",
    "circuit.h(qreg_q[2])\n",
    "circuit.h(qreg_q[3])\n",
    "circuit.h(qreg_q[4])\n",
    "circuit.h(qreg_q[5])\n",
    "circuit.x(qreg_q[0])\n",
    "circuit.x(qreg_q[1])\n",
    "circuit.x(qreg_q[2])\n",
    "circuit.x(qreg_q[3])\n",
    "circuit.x(qreg_q[4])\n",
    "circuit.x(qreg_q[5])\n",
    "circuit.ccx(qreg_q[0], qreg_q[1], qreg_q[6])\n",
    "circuit.ccx(qreg_q[2], qreg_q[3], qreg_q[7])\n",
    "circuit.ccx(qreg_q[6], qreg_q[7], qreg_q[8])\n",
    "circuit.ccx(qreg_q[4], qreg_q[8], qreg_q[9])\n",
    "circuit.cz(qreg_q[9], qreg_q[5])\n",
    "circuit.ccx(qreg_q[4], qreg_q[8], qreg_q[9])\n",
    "circuit.ccx(qreg_q[6], qreg_q[7], qreg_q[8])\n",
    "circuit.ccx(qreg_q[2], qreg_q[3], qreg_q[7])\n",
    "circuit.ccx(qreg_q[0], qreg_q[1], qreg_q[6])\n",
    "circuit.x(qreg_q[0])\n",
    "circuit.x(qreg_q[1])\n",
    "circuit.x(qreg_q[2])\n",
    "circuit.x(qreg_q[3])\n",
    "circuit.x(qreg_q[4])\n",
    "circuit.x(qreg_q[5])\n",
    "circuit.h(qreg_q[0])\n",
    "circuit.h(qreg_q[1])\n",
    "circuit.h(qreg_q[2])\n",
    "circuit.h(qreg_q[3])\n",
    "circuit.h(qreg_q[4])\n",
    "circuit.h(qreg_q[5])\n",
    "#barier *2\n",
    "circuit.barrier(qreg_q[0], qreg_q[1], qreg_q[2], qreg_q[3], qreg_q[4], qreg_q[5], qreg_q[6], qreg_q[7], qreg_q[8], qreg_q[9])\n",
    "circuit.barrier(qreg_q[0], qreg_q[1], qreg_q[2], qreg_q[3], qreg_q[4], qreg_q[5], qreg_q[6], qreg_q[7], qreg_q[8], qreg_q[9])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ba65f6da-2d6c-40fa-bbfe-788069ab167b",
   "metadata": {},
   "source": [
    "Iteration 5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "ca861141-b5e3-4ec5-a8ec-077dd51ba07f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<qiskit.circuit.instructionset.InstructionSet at 0x7f17904cb040>"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# oracle iteration 1\n",
    "circuit.ccx(qreg_q[0], qreg_q[1], qreg_q[6])\n",
    "circuit.ccx(qreg_q[2], qreg_q[3], qreg_q[7])\n",
    "circuit.ccx(qreg_q[6], qreg_q[7], qreg_q[8])\n",
    "circuit.ccx(qreg_q[4], qreg_q[8], qreg_q[9])\n",
    "circuit.cz(qreg_q[9], qreg_q[5])\n",
    "circuit.ccx(qreg_q[4], qreg_q[8], qreg_q[9])\n",
    "circuit.ccx(qreg_q[6], qreg_q[7], qreg_q[8])\n",
    "circuit.ccx(qreg_q[2], qreg_q[3], qreg_q[7])\n",
    "circuit.ccx(qreg_q[0], qreg_q[1], qreg_q[6])\n",
    "# barier\n",
    "circuit.barrier(qreg_q[0], qreg_q[1], qreg_q[2], qreg_q[3], qreg_q[4], qreg_q[5], qreg_q[6], qreg_q[7], qreg_q[8], qreg_q[9])\n",
    "# diffuser iteration 1\n",
    "circuit.h(qreg_q[0])\n",
    "circuit.h(qreg_q[1])\n",
    "circuit.h(qreg_q[2])\n",
    "circuit.h(qreg_q[3])\n",
    "circuit.h(qreg_q[4])\n",
    "circuit.h(qreg_q[5])\n",
    "circuit.x(qreg_q[0])\n",
    "circuit.x(qreg_q[1])\n",
    "circuit.x(qreg_q[2])\n",
    "circuit.x(qreg_q[3])\n",
    "circuit.x(qreg_q[4])\n",
    "circuit.x(qreg_q[5])\n",
    "circuit.ccx(qreg_q[0], qreg_q[1], qreg_q[6])\n",
    "circuit.ccx(qreg_q[2], qreg_q[3], qreg_q[7])\n",
    "circuit.ccx(qreg_q[6], qreg_q[7], qreg_q[8])\n",
    "circuit.ccx(qreg_q[4], qreg_q[8], qreg_q[9])\n",
    "circuit.cz(qreg_q[9], qreg_q[5])\n",
    "circuit.ccx(qreg_q[4], qreg_q[8], qreg_q[9])\n",
    "circuit.ccx(qreg_q[6], qreg_q[7], qreg_q[8])\n",
    "circuit.ccx(qreg_q[2], qreg_q[3], qreg_q[7])\n",
    "circuit.ccx(qreg_q[0], qreg_q[1], qreg_q[6])\n",
    "circuit.x(qreg_q[0])\n",
    "circuit.x(qreg_q[1])\n",
    "circuit.x(qreg_q[2])\n",
    "circuit.x(qreg_q[3])\n",
    "circuit.x(qreg_q[4])\n",
    "circuit.x(qreg_q[5])\n",
    "circuit.h(qreg_q[0])\n",
    "circuit.h(qreg_q[1])\n",
    "circuit.h(qreg_q[2])\n",
    "circuit.h(qreg_q[3])\n",
    "circuit.h(qreg_q[4])\n",
    "circuit.h(qreg_q[5])\n",
    "#barier *2\n",
    "circuit.barrier(qreg_q[0], qreg_q[1], qreg_q[2], qreg_q[3], qreg_q[4], qreg_q[5], qreg_q[6], qreg_q[7], qreg_q[8], qreg_q[9])\n",
    "circuit.barrier(qreg_q[0], qreg_q[1], qreg_q[2], qreg_q[3], qreg_q[4], qreg_q[5], qreg_q[6], qreg_q[7], qreg_q[8], qreg_q[9])\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "023b8665",
   "metadata": {},
   "source": [
    "Iteration 6"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "6fb7e78c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<qiskit.circuit.instructionset.InstructionSet at 0x7f17939c6440>"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# oracle iteration 6\n",
    "circuit.ccx(qreg_q[0], qreg_q[1], qreg_q[6])\n",
    "circuit.ccx(qreg_q[2], qreg_q[3], qreg_q[7])\n",
    "circuit.ccx(qreg_q[6], qreg_q[7], qreg_q[8])\n",
    "circuit.ccx(qreg_q[4], qreg_q[8], qreg_q[9])\n",
    "circuit.cz(qreg_q[9], qreg_q[5])\n",
    "circuit.ccx(qreg_q[4], qreg_q[8], qreg_q[9])\n",
    "circuit.ccx(qreg_q[6], qreg_q[7], qreg_q[8])\n",
    "circuit.ccx(qreg_q[2], qreg_q[3], qreg_q[7])\n",
    "circuit.ccx(qreg_q[0], qreg_q[1], qreg_q[6])\n",
    "# barier\n",
    "circuit.barrier(qreg_q[0], qreg_q[1], qreg_q[2], qreg_q[3], qreg_q[4], qreg_q[5], qreg_q[6], qreg_q[7], qreg_q[8], qreg_q[9])\n",
    "# diffuser iteration 6\n",
    "circuit.h(qreg_q[0])\n",
    "circuit.h(qreg_q[1])\n",
    "circuit.h(qreg_q[2])\n",
    "circuit.h(qreg_q[3])\n",
    "circuit.h(qreg_q[4])\n",
    "circuit.h(qreg_q[5])\n",
    "circuit.x(qreg_q[0])\n",
    "circuit.x(qreg_q[1])\n",
    "circuit.x(qreg_q[2])\n",
    "circuit.x(qreg_q[3])\n",
    "circuit.x(qreg_q[4])\n",
    "circuit.x(qreg_q[5])\n",
    "circuit.ccx(qreg_q[0], qreg_q[1], qreg_q[6])\n",
    "circuit.ccx(qreg_q[2], qreg_q[3], qreg_q[7])\n",
    "circuit.ccx(qreg_q[6], qreg_q[7], qreg_q[8])\n",
    "circuit.ccx(qreg_q[4], qreg_q[8], qreg_q[9])\n",
    "circuit.cz(qreg_q[9], qreg_q[5])\n",
    "circuit.ccx(qreg_q[4], qreg_q[8], qreg_q[9])\n",
    "circuit.ccx(qreg_q[6], qreg_q[7], qreg_q[8])\n",
    "circuit.ccx(qreg_q[2], qreg_q[3], qreg_q[7])\n",
    "circuit.ccx(qreg_q[0], qreg_q[1], qreg_q[6])\n",
    "circuit.x(qreg_q[0])\n",
    "circuit.x(qreg_q[1])\n",
    "circuit.x(qreg_q[2])\n",
    "circuit.x(qreg_q[3])\n",
    "circuit.x(qreg_q[4])\n",
    "circuit.x(qreg_q[5])\n",
    "circuit.h(qreg_q[0])\n",
    "circuit.h(qreg_q[1])\n",
    "circuit.h(qreg_q[2])\n",
    "circuit.h(qreg_q[3])\n",
    "circuit.h(qreg_q[4])\n",
    "circuit.h(qreg_q[5])\n",
    "#barier *2\n",
    "circuit.barrier(qreg_q[0], qreg_q[1], qreg_q[2], qreg_q[3], qreg_q[4], qreg_q[5], qreg_q[6], qreg_q[7], qreg_q[8], qreg_q[9])\n",
    "circuit.barrier(qreg_q[0], qreg_q[1], qreg_q[2], qreg_q[3], qreg_q[4], qreg_q[5], qreg_q[6], qreg_q[7], qreg_q[8], qreg_q[9])\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4cfb1190-5a69-43e9-88f4-6816897d23ca",
   "metadata": {},
   "source": [
    "Measurements"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "efcbbfba-481b-4ef4-b1f0-0a4a0b2be1b8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<qiskit.circuit.instructionset.InstructionSet at 0x7f179399c440>"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "circuit.measure(qreg_q[0], creg_c[0])\n",
    "circuit.measure(qreg_q[1], creg_c[1])\n",
    "circuit.measure(qreg_q[2], creg_c[2])\n",
    "circuit.measure(qreg_q[3], creg_c[3])\n",
    "circuit.measure(qreg_q[4], creg_c[4])\n",
    "circuit.measure(qreg_q[5], creg_c[5])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "32899f84-ed21-4019-acea-838f2acf1805",
   "metadata": {},
   "source": [
    "Simulation of the circuit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "62cc278e-e645-4f0a-a645-666f7d8ded3a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "aer_sim = Aer.get_backend('aer_simulator')\n",
    "qobj = assemble(circuit)\n",
    "result = aer_sim.run(qobj).result()\n",
    "counts = result.get_counts()\n",
    "plot_histogram(counts)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0136f232-ee98-4f09-9311-2c23a894ce93",
   "metadata": {},
   "source": [
    "Visualization of the circuit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "e7474577-0a45-4702-9b3f-308b5ee08ac5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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jRo2SJOXm5qp169ZKTk5WcnKyvvvd75oNDgBN9Hmp9PO/SwdP1F1eXSO9/7n0/1ZLNT4z2QAgmjx9+8g7c7pqnntB/qNHVf3sAnlv/aa8WcNMRwNahLPV0ot/s876urT5JUnFR6T/flcqOWomm1ux3wNiz7YNsGeeeUYTJ05UTk5OneUDBgxQQkKChg2r3TH87ne/U0VFhSoqKvSb3/wmxkndp6CgwHQEoMXx+aXXPrUuf/Q3sE7hfmnz3pjGAnAetTH6vLfdKk+f3qq+d47k9co7/R7TkYAW46MvpL0NNLj8kqqqpTfWxTRSi8B+D4gtW14CWVJSoi1btujBBx8MeKy4uFiZmZlKTEw0kCw8n/7xKa1bubDOsqozFeo99HpDiRpn69at6tq1q+kYQIvy5UHpSEXwdTwe6R9F0vA+sckEoJaTaqNTxyEej0eerGHyr1sv753T5ElIMB0JaDH+URT8cb+kHYekgyelbu1iEqlFcOJ+z6k1BpBs3ACTpO7du9dZfvr0aRUUFGjSpEl1ls+ePVv333+/Ro8erZ/85CcaOHBgyNfweDxhZbl93ir1zMgNL/h5Y26dpzG3/bDOsrwnG7cNSSooyNf3b5zQ6OeFUl9j8VKLFi0Kax07efc565yZcP+72oETMzuVE97rrBvmaML0/wm6jt8vffbFQXlu7B50PZOc8F67hVPfazvmDlXzJHO10dQ4pDljkLjnnpU3O6vRz/Pv2iXf0lflvWOqfC8vlfe6a+RpZNMxPz9fntFjG/3azWHHz3Q4nJrbiez+Xnu8cfr+b6vDWvcrX71NO9f9McqJms7Ue+3U/Z4Ta0xz2P3/i/VxYmY7s+UlkKmpqZKkoqK6hyIWLFig0tJSjRw5ss6y3bt3a/fu3Ro5cqRuueUWVVeHtwMHALuoqTob3nrV3BISgPv4z1Wp+tnn5J18m+L+eYY814xTzYLn5fcx8SEQbX5fjXw14X1/Cne8gtDY7wGxZ8szwPr166esrCw9/fTT6tSpk9LS0pSXl6eVK1dK0sUJ8CVpzJgxF3//8Y9/rF/84hcqKirSkCFDgr6G39/QLDt1/fRd63RfE3JycpX3ZHg5G2P79u1BH1+0aJFmzZoVdJ0XXnghkpGa7b3zZ+GG+9/VDpyY2amc8F4frZCe+GPD839dMHFsL/0/G/87nPBeu4VT32s75g5VFyVztdHUOKQ5Y5Dr136i1ccaN1u271e/lic+Xt577pYkxd1/n6rvmyvf8jcUN/X2sLeTm5ur92L82bLjZzocTs3tRE54r1/Kl7btCz4OaRUvbV/7tpJsfJWeqffaqfs9J9aY5nDC/xcv58TMsZKbm9vo59jyDDCv16tly5YpMzNTs2fP1owZM5Samqo5c+YoPj5eWVn1n17q8Xg4NTACHn/8cdMRgBanU7KU1Sv4Ol6PdO2g2OQBUBe1MXp8GzbKt/IdxT36iDzx1rFZT5s2invkB/L99mX5d+0ynBBwv5zBoQ/CjRsgWze/nIT9HmCGLc8Ak6RBgwZp1apVdZbdc889ysjIUOvWrSVJx48f15o1azR+/Hj5/X49/fTT6tChgwYNMvcNccoP8xu13I6mTZtmOgLQIt1xtXS4Qtp3TPKodiDqOf8/3x4n9ehgLB7QojmlNjpxHOIdMVzeFa8HLh+aKe9bbxhIBLQ8g7pLt4yQVmwIHIP4zz/+jeHG4rmOU/d7TqwxwKVseQZYQ9auXVvn8seqqio9+uijSk1NVVpamtauXasVK1YoPt62fT1HyMjIMB0BaJHaJErfv1G6/SqpW/va5aP7ST+YKF11pblsQEtHbQTgdl8dIj1wg5TVu3ZZz07SXWOleydICXHmsgFAJDimU1RRUaGioiLdf//9F5d16dJF69atM5gKACIrMV66Lt36+bdXrGXfHmc2EwAAaBn6d7V+LoxBfvB1s3kAIJIc0wBLTk5WTU2N6RgAAAAAAABwGEddAonYaMrdFAAAcDNqIwAAgLPRAEOAxYsXm44AAICtUBsBAACcjQYYAsyePdt0BAAAbIXaCAAA4Gw0wBAgPz/fdAQAAGyF2ggAAOBsNMAAAAAAAADgajTAAAAAAAAA4Go0wBCgsLDQdAQAAGyF2ggAAOBsNMAQ4LXXXjMdAQAAW6E2AgAAOFu86QB2l9ax5b32/PnzNW3aNDMvDgCADZmqjabGAs153eyUlMgFcdBrA2i5nLrfc2KNAZqDBlgIk68ynQAAALRUThyHPJ8+xHQEAIgpp+73nFhjgObgEkgAAAAAAAC4Gg0wBHjxxRdNRwAAwFaojQAAAM5GAwwBMjMzTUcAAMBWqI0AAADORgMMAXJyckxHAADAVqiNAAAAzkYDDAAAAAAAAK5GAwwAAAAAAACuRgMMAUaPHm06AgAAtkJtBAAAcDYaYAiwZs0a0xEAALAVaiMAAICz0QADAAAAAACAq9EAAwAAAAAAgKvRAEOAvLw80xEAALAVaiMAAICz0QADAAAAAACAq9EAQ4ApU6aYjgAAgK1QGwEAAJyNBhgAAAAAAABcjQYYAAAAAAAAXI0GGALMmTPHdAQAAGyF2ggAAOBsNMAQYO7cuaYjNIqvpvZ3v89cDgBAcDXnTCdoOqfVRsSG31/7e02VuRwAAHdz8hjKTuJNB4D9jB8/XqtXrzYdI6jKI9K+z6TjJVL54drlq/5bSukqdeotpWVJSe3MZQSAls7nkw7vkA4USicPSGdO1j72/s+ldt2lbulS14GS1+YjEifURsRGzTnpwHbp0BfW5/qCVf8ltekotesh9RgideojeTzmcgIAnKemSjr4uXSoSDp5sHb5qv+WWrc/X2MypM5XSh5OZ2o0mw83YUJZWZnpCA06Uy5tf8/6QlUfX7V0Yr/1s+sTqUemNChXSkiKaUwAaPEOfSkV/c3ab9fnbIVU9qX1k9BGGphjNQ3s2jCwc21EbPh90t4N0s4Ppeqz9a9z6pj1c2Cb1KaTlHGD1LFXbHMCAJzH77dO8NjxvlR1pv51Tp+wfg5ut5phg6+3GmEIHw0wOMahImnrO404/dMvlW6RjuySsm6ROqRFNR4AQNaBiMJ3pdKt4T+n6pS07W1rPz/0Zim+VfTyAU1xrlL6bIV0fF/4zzl1VFr3B6nPVdKAHPs2dwEAZlWdkTb/STq6O/znnD4hbVgupWVL6V+TvJwNFhbeJgQYMmSI6QgBDmyXPnuradc+n6uU1i+Tju2NfC4AQC1fjdUkaEzz61KHd0gb8uw5z4UdayNi49wpae0fGtf8utSetVLhX+rOFwYAgGQ1v9Yva1zz61L7Nklb/sRc2OGiAYYAy5cvNx2hjvIyaetKSUEGjtc/bP00xFctbXrTuuQGABAdX74vHd4ZfJ1Q++sT+6XC9yKbKxLsVhsRG36/dVT+1NGG1wn1mZak/Vukvesjmw0A4Gx+v7TtHan8YMPrhFNjDhVJuz6ObDa3snUDzOfzaeHChRo4cKCSkpKUnZ2tgoICpaena9asWabjudZjjz1mOsJFvhrrsphIdLSrz1qX5QAAIu/4fql4bWS2dWCbVNbAXI+m2Kk2Inb2bZKOFUdmW1++b80PBgCAZM3lVfZlZLa162Op/FBktuVmtp4DbObMmXrjjTf0ox/9SKNGjdKHH36ou+66S2VlZXrooYdMx3OtZcuW6cc//rHpGJKksi8i+3/kwzukE6VS+x6R22ZL4PdZd7sq2ShVHLbuOJLaT+o1wrrrJuBENeek0m1SyWfW3QnjW0ndB0s9h3MH2abY+UFkt7fjH9Z+xi7zJtmpNiI2fDXWhPcR2161dYOezImR22ZLUXnEGoMc+sJ6H9t0sua96T5Y8saZTgc0zfESae9Gq8nu91vfT3oOP393P5vUPkSP3y/tiODYye+Tdn4kZd8auW26kW0bYEuXLtWSJUuUn5+vnJwcSdKECRO0fv16vf766xo1apQkye/36z//8z/1y1/+UpWVlRozZozee8+G106gSfZujPw2SzbSAGuMC3P6HN4hyaOLl6Lu32z9ZNwopWWZTAg03rlKad1r1peqC6rPSLs/te7yNnwyd25rjMqj0tE9kd1mRZl1OSQ3MIEph76w5v+KpIOF0qAcKaF1ZLfrZgeLAue3OVFq7R/2b5ZGTJbiuHEGHGbnh+cb7JeMrQ/vsqYRSMu27u5HE8zdju6WTh+P7DbLvrTuvp2UEtntuoltL4F85plnNHHixIvNrwsGDBighIQEDRs2TJL0/PPPa8OGDdq4caOOHTumBQsWmIiLKKg+ax0ZibTDO5mItjF2/ON880uqdx62wr82fWJgwJTNf6rb/LpUTbW08Y3If/F1syO7orPdUPOJAdEUjc+fr0Y6GqFLKluCyiMNTO58fjxyvETa/reYxwKa5WDRJWeXXjq2Pv/7vk3WwTi4W1k0xjh+6cjuKGzXRWzZACspKdGWLVs0derUgMeKi4uVmZmpxMRE1dTUaNGiRfrlL3+pbt26KS4uTiNHjjSQ2F0KCgpMR5AUvWuYq05LZ8ujs223qT5nnTEXlIeJfeEs5YdC3BXWb10euX9LzCI53skgk7facbtNYZfaiNgpPxCl7droc213ezeGnge2dJt0tjImcYCI2LNG1plfQRSv4a5+bhetWhCt2uUWtrwEsqTEOu2ne/fudZafPn1aBQUFmjRpkiSrGebxePTTn/70YhPsySef1G233RbyNTwt+JzSBx98MOjjO3bsUP/+/YOus2jRokhGqtdNV31XD9/x6zrLQt0Bo6HH31tY9+9Xj8jVZzvNfpl59znrMI+dP4tjBn9dT/3zyuAr+aW9W88o6xb7Xs/hhPe6Pv/6svNyO+G9vvv6H+q7Nz0RdB2f36c/LvlI/3b1tTFK1Xh2eq9/MucDZfb9Sp1lTdlfX76v3rz2S42aOrCZ6UILVRcl+9RGxM6fnz6tVglJF/8eqTHIkpde05M5dzQzXfPZaR/SkKXz9qpLh57BV/JLt+R+V39duyQ2oZrACe/15Zw4BpHs/16ntOmk1x9v4BT0S5wpl/r3zNKu0s0xSNVy2Onz8dpjB9QxpdvFv0eqxrz52l/0/93IZJMNseUZYKmpqZKkoqKiOssXLFig0tLSi2d57d+/X/v27dPp06dVUlKixYsXa/r06dq9e3esI7vKihUrTEeQJHm90evPxsclRG3bbpKY0Cas9VrFJ9mikADhSIxvLX+I66C9Hq+SEtvGKJHzxUVpf22nfbVdaiNiJ1qf62ht142SWoU3Dgl3vAKYltSIz2pj1oXzUGPM8PhDfQswwOfzacSIESotLdXChQuVlpamvLw8rVy5UsXFxfr444919dVXa8OGDRo5cqSOHDmiTp06SZJuueUWTZ48Wd/97nfN/iNsbPv27UEfz8jIUGFhYdB1Bg8eHMlI9Tq43ZqnJxwXOuKXd8AbMuY7UrvuodeLpgtZQ3X7TSovkz4J44BqUnvp2u9FP09TOeG9rs+/vWL9+ZO7zeZoDCe81/u3SNveCbGSR+o2SBr2zZhEahI7vdfrl4U/CX5j9tfJXaSx05ueK1yh6qJkn9qI2Cn4mTVtQiiNHYP0GGqPO0HaaR/SkE9fkU4eUL1zkF5qxFSpc5+YRGoSJ7zXl3PiGESy/3vtq7b2LTVVIVb0SNfdJ3EsLrLs9Pn44CXp9InQ6zW2xnQZ2HLuBJmbmytJys/PD/s5tjwDzOv1atmyZcrMzNTs2bM1Y8YMpaamas6cOYqPj1dWlnXLuYEDByohwT5HhxFZyV2js12PR2rbOTrbdpuULucbhSFO7uo1PBZpgMjoNiiMO4b5rbswITwpUdpfR2u7QDiSu0Rnu3yuw9dzuEI2v5LaSZ16xyIN0HzeeOmKYSFW8khdB9L8crtofdelxgRnywaYJA0aNEirVq1SZWWliouL9cQTT2jz5s3KyMhQ69bWXEPJycm69dZb9cwzz6iqqkoff/yxVq9efbETiKZ5/PHHTUeQJLXpGJ3bhCd3lWx0VY3tDZpw/jbMDTTB2qbSKICzxLWSBuUGX6frIKljr5jEcYX2V0Rpuz2is92msEttROy0hM+13XUfLHVIC77O4K+dH6cADtH3aikxWfWPrT3W95T+9p2CFBHSgRpjhG0bYPVZu3atRo0aVWfZ4sWLVVhYqI4dO2r69On6zW9+o759+5oJ6BLTpk0zHUGSNZjpkRn57V4xNPLbdLMOadLIaVZD8nJdBkij7pDiQ51NA9hMWpY05OvS5dPLeOKkXiOloTfzhaoxUq+M/AELb7zUzUZXFNqlNiJ2rojCGKRtZ/NTMDiJN04afrvUY4gCmgVJ7aTh35JSg9+bArCdxLbS6G9LHeu5v0NKV2n0XVLbTrHPhdjqniF5ItyN4YzY0BwzQ1pFRYWKiop0//3311mempqqP/0pzImiEJZw5jmJlZ7Dpb3rI3cb4PjE84MoNErHntK4GdLxEmndH6xl13xPat3ebC6gOa7ItM4uOLJb2vSGtWz8fdE589TtvPHW/nrXR5HbZo9M6ZIb8Blnp9qI2GjTUUrtJx3eGblt9h5Fc72x4ltJmZOkAeOl939uLRsxRerUh/cSzpXUzjqIXHlE+uj8Te/tMEcxYicxWeqWLh2I4NCi14jIN9XcxjENsOTkZNXU1JiOgRhr00G6cqy088PIbC/9a1YTDI3n8dS9JIzmF9zAGyd1ueTsAZpfTdd3jHXzklPHmr+tVm2lAVz+ARtI/6p0bG8YE1aHoX0aZ6E3R2Jy7e+d+xqLAUTUpfMS0/xqeQbmSod3SdVnmr+t5C7WVQwIzjENMLRcfa+WjuyRTuxreJ1w7orRbbB1qikAIPLiEqyzNNa9KvmCHK8Kub/2WHfIoxkJO2jdwTp4FuzOseGMQeKTrM81R+YBABcktpWG3Ch9tqLhdcKpMXHnz5T1xkUum1tRhhHAbjcR8MZZczw0ZzLaLgPODzw5VR4AoqZ9Dyn7W9YlkU3h8UrDbpY6XxnZXJFgt9qI2LliqDToq01/fkKSNHJK/XNpAgBatq6DpCE3qcEbjoUS10oaPllKidKdi92GBhgCLF682HSEAAlJ0sip1twZjeHxSgOuk4bd0vQvZACA8HXuK425W0rp1rjntekkXXWnvSa+v5QdayNip/dIacTtdS/DC0fH3tKYe7i0CQDQsCuGSaOmNX6KmfZXWHPH1XdDBdSPBhgCzJ4923SEesUlSIMmSKPvtiYMDHYZgTfeusvb2OnWJZRePukAEDPJXaw7XA2+QUpODb5um47WHBhX39O8M32jza61EbHT+UrrhjD9rpESU4Kv2/4K626yI6cyZyYAILSOvazvrgPGWzdJCCalm3XW2FV3csfQxuKcGATIz883HSGo9j2kYd+Uzp2STpRK5Qet3+Wxjsy262atw2T3AGCON07qmW0djKg8LJ08KFUclnxV1kGKtp2tAVxKV2dcnm732ojYiE+U+o2zDq6VH5ROHrBu/OCvsS5DSelqne3F5Y4AgMaKa2XdVKjPVVL5IWvsVHlU8ldbjyWnnq8xnZwxdrIjGmBwrFZtrLu3XXoHNwCAvXg81hlhycxNARfxeq2Dbe17mE4CAHAbj9dqdHH5fORxYRgAAAAAAABcjQYYAhQWFpqOAACArVAbAQAAnI0GGAK89tprpiMAAGAr1EYAAABnowGGAPPnzzcdAQAAW6E2AgAAOBsNMAAAAAAAALgaDTAAAAAAAAC4Gg0wBHjxxRdNRwAAwFaojQAAAM5GAwwBMjMzTUcAAMBWqI0AAADORgMMAXJyckxHAADAVqiNAAAAzkYDDAAAAAAAAK5GAwwBRo8ebToCAAC2Qm0EAABwNhpgCLBmzRrTEQAAsBVqIwAAgLPRAAMAAAAAAICr0QADAAAAAACAq9EAQ4C8vDzTEQAAsBVqIwAAgLPRAAMAAAAAAICr0QBDgClTppiOAACArVAbAQAAnI0GGAAAAAAAAFyNBhgAAAAAAABcjQYYAsyZM8d0BAAAbIXaCAAA4Gw0wBBg7ty5piMAAGAr1EYAAABnowGGAOPHjzcdwbV8NdLRYmnPmtpl29+TSjZKJw9Kfr+xaAAc4Nxp6dCX0o5/1C77Il86UCidOWksVotAbYQbnDom7d8qfb6qdtnOj6TDO6Xqs+ZyAUC0nCmXDm6XviioXfbl+9KhIulcpblcMCPedADYT1lZmekIrlN1RipeK+37TDp3qu5jJRtrf2/bWeo1QroiS/LSngZwXkWZtHuNdOhzq5F+qT1ra3/vfKXU5yqpU5/Y5msJqI1wKr9fKvtCKl4vHS8JfHznB9afcQlS9yFS39FS6w4xjQgAEXesxDrp4PBOSZedZLD7E+tPj1fqOlDqM0Zq1y3mEWEADTAgyg7vkLb9NbwjDJVHrDPC9m2WMidKyV2inw+AfflqrEHaro8lvy/0+kd2WT89hkrpE6T4xOhnBGBfZyulwr9aY5FQaqqkfZukA9ukAeOlnsMljyfqEQEgoqrPSV8WSCWbQq/r90kHP5cOFkl9x0j9xkleOiSuxjkmCDBkyBDTEVyjeJ208Y3Gn15bflBas9S6XBJAy+Srlj77o7Tzw/CaX5cq3SKt+b315ReRQW2E05w6Jq15Obzm16VqqqTP/2Y1zpiaAYCTVJ2W1v8hvOZXHX7rgOPG16Wac1GJBpugAYYAy5cvNx3BFfZvlYpWhV6vITVV0qY3pPJDkcsEwBn8fmnr2+dP22+iysPShuXWvgTNR22Ek5w7Ja1fZs1901T7N1tzDAKAE/hqrAbWyYNN38bRYmnzn2j+uxkNMAR47LHHTEdwvNMnpM/fC77O9Q9bP8HUVFlfgi+f8weAux3YZp2SH0w4+5CKQ9KODyKXqyWjNsJJPv9b6BtjhLMPKV7H2egAnGHXx9KJ0uDrhLPfO7zTuhwc7mTrBpjP59PChQs1cOBAJSUlKTs7WwUFBUpPT9esWbNMx3OtZcuWmY7geEWrInfWRUWZNQA1ze+rezZK5RFzWYBIqamSDmyv/fvZCnNZLqg+J33+98htr3ittR9B81Ab4RRHdoduoDdG4V8bfxl2NJw6Xvv7oS84OAh3OHmg9vdjeznzqKlOHa+d2D4Sviiw7rwN97H1FG8zZ87UG2+8oR/96EcaNWqUPvzwQ911110qKyvTQw89ZDoeUK/TJ6SyLyO7zZKN1p3dPIZa1kd2S4V/qXspxUe/tu40lzlJSmxrJhfQHCUbrdtgV5+tXfb+L6QrMqX066U4QxXywLa6mSJh70Yp44bIbhOAPe1dH9ntnT4uHd4ldekf2e2Gq+qMtO2dumOrz/4otWojpX9N6pZuJhfQHKeOSVv+XLcBtu4PUptO0tBJUrvu5rI50b6NkW3U11RZ86n2GR25bcIebHsG2NKlS7VkyRKtWLFCDz/8sCZMmKB58+Zp3Lhxqq6u1qhRo1RcXKzk5OSLP23btpXH49G6dTY4XQYtVum2yG/zzEnrqJAJR4ut6+nP1HNmzNE90rpXrcEp4CR711t3XA1oNPml/VukzSvMHYXdvzXy2zywjbMlgJbgXGXz5g5sSOmWyG8zHDXV0oa8+g8snjslbX5LOlQU+1xAc5wpl9b+vv65qk4dsxphnLkdPr8/OmOn/Yb2e4gu2zbAnnnmGU2cOFE5OTl1lg8YMEAJCQkaNmyYevfurYqKios/v//979W7d2+NHDnSUGp3KCgoMB3B0U7sj9J2Q1zTHg1+v3U5p98vqYFmwKljTbjTCmBQ9Tnpi/eDr3N4p9XgjTVftXUX2EirqeKy5eaiNsIJLj2bJJJORGm7oRwoDP1v+nyVPS7RBMK1+xOrgVvv2NpvNX6//EesUznX6RPW3R8jrfJI5M/Ih3m2bICVlJRoy5Ytmjp1asBjxcXFyszMVGJiYsBjr7zyir797W/L4/HEIqZrbd0ahRZ6C1JxODrbNXE3yPJD549AhTgTZt/GWKQBIuPgdskXao4+j7Tvs5jEqaPyaPS+yJVzNLlZqI1wgmj9//xsuZn5cPZtkhRiWH+23MwBC6ApaqrDOLPILx3eYY95SZ2gIorfkaL1vQ7m2HIOsJKSEklS9+51L34+ffq0CgoKNGnSpIDnlJeX66233tKnn34a1mu05CbZgw8+GPTxRYsWhbUO6vfmEyfUNqndxb+HutNIQ4+/t7Du3//81jvKvvXrzUzXONcNu12P/VNeyPXOlEter1d+m87c+e5zVi6n/f/+X192Xm4nvNczJz6lO7/6qDzBJtXzSx/lb1T2rSNiF0zS0Cuv1aL7656eFql9yP33PqA/fvA/zUjnXqFqnkRthDP8y6RndceE/6izLFL7kD49++nA0V3NSNd4rz9+RCltOoVcb8bd9+utjxbHIFHTOKE2Xs6JYxDJ/u91l/Y9tfSH4c1rMiJzrAqLIzizu0vdeNV0/fsdv6mzLFL7vZuun6RPt7/d9HCwHVueAZaamipJKiqqe1H/ggULVFpaWu8ljq+//roGDhyooUOHxiQj0JCaSN3+8TLVUdpuMKfPhXfo6VzVads2v4DLnTlXGbz5JesuxKcNHHqt8VVHb9sG9iEAYiuaYwUT+5Bw98NnzlVGOQkQGY35rJ7mcx2WaI6dTHz/QnR5/Db81urz+TRixAiVlpZq4cKFSktLU15enlauXKni4mJ9/PHHuvrqq+s858Ybb9T111+vRx55xFBq59i+fXvQxzMyMlRYWBh0ncGDB0cykqt8+nJ4c3BcOPJw+ZGGhvQaJaVPaHqupqipklYvlmrOBVnJI3UfLA29OWaxGu3CexzqaJDd/Nsr1p8/udtsjsZwwntdcVj6+Deh1xuYa919NZbOnZJWvxjeuo3dh4yYKnXu07RcbheqLkrURjjD/i3WHRPD0Zh9iDdemvD92N+NumiVVBzi3lYer3TdfdZdIe3KCbXxck4cg0jOeK/Xviod36egU4y0bi995V8km57IZisn9ktrloa3bmPHTtf8i9S6Q5NiIQZyc3MlSfn5+WE/x5ZngHm9Xi1btkyZmZmaPXu2ZsyYodTUVM2ZM0fx8fHKysqqs/6BAweUn5+vu+66y1Bid3n88cdNR3C0lG7R2W67KG03mLgEqVcY95QIZx3ALpJTpc59g6zgkeITpSsyY5WoVqs2UmJKdLbdrmt0tttSUBvhBNEaK6R0jX3zS5J6Dpe8ccHXuWKovZtfwOX6jFbI+XX7jKH5Fa7kLtF5r+KTpKT2kd8uzLJlA0ySBg0apFWrVqmyslLFxcV64okntHnzZmVkZKh169Z11n311Vf1la98Rb169TKU1l2mTZtmOoKjdRkQ+W164kJ8YY+ifl+RuqVfCHLZgx4p8+tS+x6xTgU0z9CbL2lWX/a5jm8ljbhdSmgd8LSYiMY+pEOauX+PW1Ab4QRtU60zRyKtS//IbzMcbTpKWbfW0wQ7v9/u1EcaFOOz44Hm6tJfGphTzwPnP9e9R0lpWfU8jnrFJUid+kZ+u13604R0I9s2wOqzdu1ajRo1KmD5K6+8orvvdtj5uTaWkZFhOoKjde4b+cFnt3RzRze9XmnoN6Tht0up/WqX9xopjZsh9RhiJhfQHAmtpavushq4Ha6oXd7/WmncTKn9FQ0/N9p6Zkdhm7Gdy9+VqI1wAo/HOmsqotuMk64YFtltNkZqP2u/3PeS2U869ZaybrHGJnEJ5rIBTdVntDTmnrr/3+qWLo2602rq0nhpnEjv96K1TZjnmAZYRUWFioqK6p0Af82aNfre975nIBUQyOOR+l8Xue1546Qrx0Zue03h8UipV0rDv1W7LP2rUtvQN2YCbCsuXuqRaTXCLrhyrJTY1lwmybpEs3sEG8sp3aSuAyO3PQD2lpYtJUXwUuo+o8xfYti6vTTgkrHVyKlS10HWQTrAqdp1k4bcVPv3Yd+QOvY0l8fJUvtZZ7tHSpcBXOHiVo4pG8nJyaqpqdEDDzxgOgoQUrf0yH3h7H8djSagpUmfILWKQCPO45WGTAw9hw4A94hvJWVMjMy22na2pkIAADvzeM6Pd+Kbv62EJGnwDc3fDuwpAh8RuM2Fuymg6TweacjXpTPlDd8RMpy7j1wxzJoHAEDLktBaGj5ZWv+aVH22/nVC7kM85+c66xLxeC0StRFO0rmPNOirUtHfG14n1D4kMVnK/lZkvlACQLS16ShlfVPa9EfJ76t/nVD7vbgEa79n+moARI9jzgBD7CxevNh0BFeIb2Wdon/pvFmN0XeMlHEjcwAALVW7btKoO5o2p2B8opR96yU3sECzURvhNL1HShk3Na2BldxVuupOqU2HiMcCgKhJ7W8dQGzKjX+SUqSR0yJ7KSXshwYYAsyePdt0BNeIT7SOIgz5eviXMyV3seYkGjCe5hfQ0qV0lcZOl3qNCv8yxq6DrAmjo3E3yZaM2ggnShtm7UPCvUNaXCup3zXSmLul1h2imQwAoqNzX+tGXd2HKPAO9vXweK0bEI39LvN+tQSc1IwA+fn5piO4iscjXZEpdR8slX0pHSqSTh6UTh8//7jXmmOjXXdrQu4OaTS+ANSKa2XNCXblWKl0i3R0j7UPqTp9/vEEa6L7Dj2ltKF8aY0WaiOcqk1HaeQUqeKwtH+zdKJUKj8k+aqtxxOTrX1I6pXWF8b4VmbzAkBztWojDZ0kDbhW2rdZOl5ijZ1qzlmPJyRZ+71OvaUrhkZm3lU4Aw0wIEa8cdblSBcuSfL5JH+NtdzDuZgAQmjV2rptep/Rkt9v7T/8fuvyJprmAEJJTpUGTbB+9/utBpjHy00yALhXUjup/zXW736/5KuxTgrzxDF2aqlogAGGeL3iImQATeLxSB4qOIAm8niss0cBoKXweKQ4xk4tHl+/EaCwsNB0BAAAbIXaCAAA4Gw0wBDgtddeMx0BAABboTYCAAA4Gw0wBJg/f77pCAAA2Aq1EQAAwNlogAEAAAAAAMDVaIABAAAAAADA1WiAIcCLL75oOgIAALZCbQQAAHA2GmAIkJmZaToCAAC2Qm0EAABwNhpgCJCTk2M6AgAAtkJtBAAAcDYaYAAAAAAAAHA1GmAIMHr0aNMRAACwFWojAACAs9EAQ4A1a9aYjgAAgK1QGwEAAJyNBhgAAAAAAABcjQYYAAAAAAAAXI0GGALk5eWZjgAAgK1QGwEAAJyNBhgAAAAAAABcjQYYAkyZMsV0BAAAbIXaCAAA4Gw0wAAAAAAAAOBqNMAAAAAAAADgajTAEGDOnDmmIwAAYCvURgAAAGejAYYAc+fONR0BAABboTYCAAA4Gw0wBBg/frzpCLAhv186U1779+qz5rIAkeL3S6eP1/69ptpYFNgctREwq+Zc7e9nTlr7b8Dpqk7X/n6u0lwOoKWINx0A9lNWVmY6AmzC75OO7Jb2bZZO7JPOnap9LP+nUpuOUue+Us/hUtvOhkICjVRTJR38XCrdJp08UPdLVf5/S21Tpa4DpbQsKbGtuZywF2ojEHunj0sln0mHd0iVR2uX/+OXUkKS1K6HdMUwqUt/yRtnLCbQKCcPSCWbpGPF0ukTtctXL5YSk6WOvawxSIeeksdjLifgRjTAANTr+H6p8J26A87LnTpm/ezdIHVLl9K/JrVqE7uMQGP4/Vbj6/O/1T3iWmcdn1RxyPrZ9ZHU+yqp31ekOKolAMRM9VnpiwJp32cNr1N1Rjqyy/pJaidl3GgdlAPs6vQJqfBd6ejuhtc5WyEdKLR+2nWXhkyUklNjFhFwPYb0CDBkyBDTEWCQ3y/t+lja+UHjnnfwc+losZR1q9SxZ3SyAU3lq5a2viMd3B7+c/w+ac+n1pkHwydLrdtHLx/sj9oIxEb5IWnjG9LZ8tDrXnDmpLQhT+o1Uho0gbNmYD+HvpC2rrTOQg/XyQPSJ7+1DjD3zI5eNqAlYQ4wBFi+fLnpCDBoxz8a3/y6oOq0NQA9VhLZTEBz+Gqkz1Y0rvl1qcoj0tpX616mgJaH2ghEX3mZtO4PjWt+XWrveqnwr8wPBns5WGSNQxrT/LrA75O2v2tdbQGg+WiAIcBjjz1mOgIMOVQk7f4k+DrXP2z9NMRXLX32x7rzhQEm7fpIOrwz+DqhPtdny6XNb0k+X2SzwTmojUB01ZyTPnsz+E12Qu2rJWn/5uCXTgKxdOqYdeaXgjRlw/lcf/536cT+iEYDWiRbN8B8Pp8WLlyogQMHKikpSdnZ2SooKFB6erpmzZplOp5rLVu2zHQEGFB1Wip8L3Lb+vxvkdkW0BwnD0q7QjR1w97WAal4bWS2BeehNgLR9eU/Inem7Rf51mWRgEl+v7TtHevgcPM3Zk3lwN2qgeaxdQNs5syZeuKJJ3Tvvffq7bff1rRp03TXXXdp586dGjVqlOl4gKuUfCZVRfCsrYOfW5eOmXSiVNr8p9q/v/8La36zqjPmMrnV0T3Sxtdr//7B/0p71jbtdP9I2v2Jgh51baw9nzL4BIBIO1splWyM3PZqqqQ96yK3vaaoOiPt/Mgae1yw+U/W2ASRdbZC+vJ9qeBntcu2/UWqOGwukyQd2ysd3xe57Z06Kh36PHLbA1oi2zbAli5dqiVLlmjFihV6+OGHNWHCBM2bN0/jxo1TdXX1xQbY+vXrNXbsWLVr106DBg1ijg6gCfw+ad/GyG+3ZFPktxmu/VulNa9YjbgLzpZbc5ytecUabCMy9qyR1i+TDu+qXXb6uHUEft0fgl/OEk1nK6xJZyOp6gyDTwCItP2brbFIJJVuMXcQ5myF9OnL1pyql85ndvBzac1SqXSbmVxuVHnUmih+9yd17/C8f7P0ye/qjk1irSQK83ZFslEMtES2bYA988wzmjhxonJycuosHzBggBISEjRs2DBJ0j/90z9p8uTJOn78uF566SVNnz5dhw8bbvc7XEFBgekIiLHKo9KZJk44G0yw2zxHU+UR65RzSfWe/XNxPgY027G91q3qJdX7Xp88YM1bYcLRYkX07K8LjuyO/DZhf9RGIHqisV+tPmvubKstKxu4nNNv/Wx92xp7oXn8/vPzzp5u4PEac/PS+v3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au3evpk6dKr/fr5ycHHXp0kW7d/O/Dm8oKIjivNcY8mpu2BMMSGUO3eHOxJ3zTp+wzpA1KGgtjH7w01glil8nD0gnShrZIGjNtmts8VennD7uzOWuNecav1EE4hP9IuAcp26cY+ruvXs/kuRrfJvdazmZ0lTBoPU+Nvpe+6zZYCbE09jaSxJNB6hPSYk1Wu7WrVud9srKShUUFGjSpEkX22bPnq0//vGPeuSRR1RQUKBAIKCsrKyQr3FhoOLzhTj6AE3w4IMPNvr4zp07dfXVVze6zaJFi6IZKaRQmSV35oZzOrfvqaVz6p4eC3U3moYef3th3e8f+dH/pz++9XgT0kXuztxH9L2b/k+j2wQCNfrTb9bo4V9/JUapIve/XrJGxm7ux2bevEi3XvdD+f0JDW5TE6jWf8x9VfOX3h3DZNKXsm7R4/e9XqctWp/rG778La0t/Iv9cHAV+kXArCem/0XXZt5Upy0ax+vdhYc02tet/g0d0iqlrVb8/Lj8vsbnoVQckfp0y1TxYfdOBXP7OCQ9LUMv/HuIaVZBayH6Nq06qDzGlyW88ugX6tS2+8XvozUGWf7y3zTnK5Pq3xjunAGWlpYmSSoqqvuBXbBggQ4cOKCRI0debPv617+uX//610pJSdGkSZO0aNEitWrVKqZ5AbtWrlxpOoItXs0Ne1okJju276SEFo7tuyGtW7ZXMNj4NXd+f4LatOwYo0TxK7VlewVDnML2yafUlPaxCXSJJCc/1w7uG+5Evwg4J9GhsYKJY3Xr5LYhi18Xt23Z3tkwcS41gvevdUo754I0wKkxsImxtZf4gqFGpgYEAgGNGDFCBw4c0MKFC5Wenq68vDytWrVKxcXFWrt2ra699lodPXpU/fr10x//+EfddNNN2rZtmyZNmqQ333xTQ4YMafQ1cnNzJUn5+fnO/4PQbG3f3vhZm8zMTBUWNr6q56BBg6IZKaRQmSV35oZzzpZL7/46vG0vnJ26/GxUQ67+stR3rL1cdu3bKO34R4iNfFJaX2n4bTGJZMu/vWz9+R+xnTgVkc//WXeB33r5pPShUuaNMYl00ZGd0qYV4W0b6ed6+O3W5wfxgX4RMGvz61Lp5+FtG8nxOjlVuv4HtmPZUlMl5f9KCoZxF+Qvz5BS2jqfyS63j0POlEn//E3o7Xx+KXe2FOu60T9/Y2UMJdIxSNrV0vBv28/lJXZqOq6cAeb3+7Vs2TJlZWVp5syZmjZtmtLS0jRr1iwlJiYqOztbkrRr1y517NhRN998sxISEpSdna2xY8fq3XffNfwvAID40aK1lNTSmX2ndnZmv43pOkjyNXxFniUoXTU0JnHi2lWhVySw3uvGz1k5wsnPXmqac/sGgObGqWOqiTFIQpLUbZBCrkvVobe7i19ekNJG6thbId/rboNiX/ySnPv8mfhce4krC2CSNGDAAK1evVoVFRUqLi7WvHnztGXLFmVmZqply5YXtzlx4oRWrVqlYDCorVu3as2aNSFnfwFu8fjjsV37KFq8mhv2+HxSW4eWyGjb1Zn9NqZFS6nvtY1v0+4q6wwamqZVByl9WOPbdO4vXbIERswkt5FaOLBiQovW1qwCNC/0i4BznOojnBrbhNLnWikhUfUXZnzWuOvq62KdKj5d/WXr/WzovU5ItP4/THBsbG3oc+0Vri2A1Wf9+vUaNWrUxe/btWunV155Rf/7f/9vtW3bVjfddJMeeeQRXX/99QZTAuGbMmWK6Qi2eDU37Os+OPr77NjbXKGg7zjrq75lODqdv/TR76ke0r0GflXqMUL1Dj67ZUpDbjo/OI0xn8+Zz3X3LDP/HphFvwg4p1NvKcmBExZO9AHhaN1RGnWnNUPpckkp1hik/VWxzxWP2nWXRtxe/5UMyanSyClS606xzyVZY6BoS2oppfWJ/n7jiSvvAlmf8vJyFRUV6YEHHqjT/vWvf11f//rXDaUCmiacNUPcyKu5YV+XDGtmy7mK6O2zx4jo7StSF86u9hwhHSyUilZb7WPvZep4tPn90qCvSn3GWO/152us9i99T2rV3mg0pQ+X9m6QFK3VUH1Sj+wo7QueQr8IOMefaB1bd4daUzICnfpYs5RNadtNuu570tHdtetRDv2m1DlDauTGybChY2/p+vul0s+kLedv0Dzs29ZanWHej8ARrTpYJ12P7o7ePtOzrZ8XNMwz57dTU1NVU1OjH/7wh6ajAECz40+UBn4levtL6yd1dsElhi1aSb1qJxZT/HJQShurCHaB6eKXZGXoMzp6++t7rcRNuwAg+nqPid6aWL4EacCE6OyrSTn8dZdb6DqI4pdT/AnW+3tB56vNFr8uGDAhev/nKW3NXc7pJdQHAQBh6TpQKt0pHfy04W3CuUNNUktp0Ne4TAzu0O9L0pE9UvnhhrcJ53Pdpqt1WS0AIPoSW0hZ35A+XiYFAw1vF87xOiPH3GVvwKVad7Q+jzveaXibsO7+6JMGT7R+TtA4F9Q9gebrwq1bvcarudF0g2+0Zm/ZldRSGnlH/eteACb4E631QZryy1DrNGnEbZy5b87oFwHndeh5ft3IJvwG22estfwB4BY9R0p9xzZhBz7r56Jjr6hFimsUwACDFi9ebDqCLV7NjabzJ0rZt5yfYh3hDK52V0mjvyO16eJINMC25NbSNXfVvTwiXN0yree2aB39XPAO+kUgNroOPH8iLcLLIRNaSIO/LvX/MjPQ4T5Xf/n8DK7kyJ6X0tb6eehmY/zSXFEAAwyaOXOm6Qi2eDU3osOfIPW/Xhpzt9S5v0IWwlp1lAbdYBUJTC44CzQmqaW1APGwW6V26aG3b59uLaI75Cbrrl1o3ugXgdjp0FMae581a6ZFiLtD+hOthcHH3SddNTQW6QB7rhpifa7DWci+RStrNuPY+5j5FSnWAAMMys/PNx3BFq/mRnS17WYVC86cko7ulcoOSpWnJAWlxBRrplf7q6xiAmdb4RWd+1tf5aXS8X3SqUO1dz9t0Vpq29X65YsbJuBS9ItAbCW2sGbN9B0nHdsjnTwolR+Raqqsuw+37ii16Wbd7ZGTFPCKlDZS5o3WumBHdltj64rjUqBGSkiSUtOs8Xen3tzt0S7eNgBAk6S0ldKHSuLMKuJIameKXADgdv4E606KaS64szQQLYnJ1mWNXNoYfVwCCQAAAAAAgLhGAQwwqLCw0HQEW7yaGwAAJ9AvAgDgfhTAAINeffVV0xFs8WpuAACcQL8IAID7UQADDJo7d67pCLZ4NTcAAE6gXwQAwP0ogAEAAAAAACCuUQADAAAAAABAXKMABhj03HPPmY5gi1dzAwDgBPpFAADcjwIYYFBWVpbpCLZ4NTcAAE6gXwQAwP0ogAEG5eTkmI5gi1dzAwDgBPpFAADcjwIYAAAAAAAA4hoFMMCg0aNHm45gi1dzAwDgBPpFAADcjwIYYNC6detMR7DFq7kBAHAC/SIAAO5HAQwAAAAAAABxjQIYAAAAAAAA4hoFMMCgvLw80xFs8WpuAACcQL8IAID7UQADAAAAAABAXKMABhg0efJk0xFs8WpuAACcQL8IAID7UQADAAAAAABAXKMABgAAAAAAgLhGAQwwaNasWaYj2OLV3AAAOIF+EQAA96MABhg0e/Zs0xFs8WpuAACcQL8IAID7UQADDBo/frzpCLZ4NTdwqaoz0rG90t71tW2Hi6Qzp6Rg0FyueHTutHRkl7R3XW1b6U7pbLm5TEA00S8CiEQgIJWVSvu31LaVbJZOHZQC1eZyxaNAjfW+lmyubdu/RSo7bP0/oHlJNB0AaM5KS0tNR7DFq7kBSTpWLO372CrA6LJC1ycrrT/bdJV6DJe6D5b8CbFOGB+CQenITmnfJunYnisf37zC+rN9D+u97jpA8nFaDh5FvwggHGfLpZJN0v5PrJNDl9r+lvVnYrJ01RCpxwipVftYJ4wflSekfRulL7ZJ1WfqPlb4d+vPFq2kq7KlnsOl5NRYJ4QJFMAAAM3CudPSjn9Ih3aE3rbskDU42rdBGvwNqW1X5/PFkzOnpML/kY7uCb3tiRLra99V0uCJUuuOjscDACCmgkHpi61S0Wqp5lzj21aflYo3WIWyq78s9RrFCaJIBAPW+7fzn9bsr8acOy3tWWudGB0wwSo8+nyxyQkz+FECDBo8eLDpCLZ4NTear4pj0od/DK/4danyI9K6l6VD253JFY9OHpDWvhhe8avO876QPnxROrrXkViAo+gXATQkGLBOChX+PXTx61KBGumzAmnz61INl0WGpaZa2vxn630LVfyq87xz1v/Pp3+3/r8QvyiAAQYtX77cdARbvJobzdOZMunjV6WzZfaeHwxIW/56/pJJNKr8iLQx78pLDcIVqLYujTzxRXRzAU6jXwTQkB3/kL7YEnq7hhzZJW39C+uThhIMSlv/ai2/YNeBrdL2f0QvE9yHAhhg0GOPPWY6gi1ezY3mJxi0zuiFWmz9hoetr4Z3JH36pnSuIqrx4kqgRtq2yrp0ozGh3utAtbTtr5GdJQdMo18EUJ/Dn9VdfL0+Iccgkko/ty6JRMP2b5ZKP2t8m3De6/2brf83xCdXF8ACgYAWLlyojIwMpaSkaNiwYSooKNDAgQM1Y8YM0/GAJlu2bJnpCLZ4NTean4OFkV+K15CqSqmoIDr7aqryS2ZYHXXJnRSLN1h3VIqGypPSrg+isy8gFugXAVyupqp2Yfto+HyNO+6eHAhIOw/X/d60sxXWZY/RUviWVM2JuLjk6gLY9OnTNW/ePN1///3629/+pilTpmjq1KnatWuXRo0aZToeAMDFgkGrKBNNh7abHXyePie9/IE0d0Vt27w/S79+Rzpi8xLPaAgErDstRVPJZmaBAQC86+D2K+/02BQ1VdbdI036aJc17vjlJYW9n/9Z+tDwMhH7P7Hen2ipOs36r/HKtQWwpUuXasmSJVq5cqUefvhhTZgwQXPmzKkG+9sAAQAASURBVNG4ceNUXV19sQC2adMmfelLX1KbNm0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      "text/plain": [
       "<Figure size 1591.6x5020.68 with 1 Axes>"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "circuit.draw(output=\"mpl\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "25ff4b79",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "interpreter": {
   "hash": "eca16aa7a5f8b35a277530dea12079435ebf8cbf4ee51249fed3c4b16880e759"
  },
  "kernelspec": {
   "display_name": "Python 3.9.7 ('base')",
   "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": "3.9.7"
  },
  "widgets": {
   "application/vnd.jupyter.widget-state+json": {
    "state": {},
    "version_major": 2,
    "version_minor": 0
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}