Grover_3qubits_CZoracle.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "ab0c0f12-443a-4e68-98d9-d6cf8d0518c6",
   "metadata": {},
   "source": [
    "## Grover's algorithm with the CZ-gate model on a 3-qubits space"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4b355a31",
   "metadata": {},
   "source": [
    "Grover search for states |101> and |110>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e95c4d23-49e9-4b79-957f-71d4fd8c608d",
   "metadata": {},
   "source": [
    "Import required packages and initialize the least busy backend"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "4ef69942-dff1-453f-a0a0-a927f5fdd112",
   "metadata": {},
   "outputs": [],
   "source": [
    "from math import pi\n",
    "from qiskit import IBMQ, Aer, assemble, transpile\n",
    "from qiskit import QuantumCircuit\n",
    "from qiskit.providers.ibmq import least_busy\n",
    "from qiskit.visualization import plot_histogram\n",
    "from qiskit.tools.monitor import job_monitor\n",
    "\n",
    "provider = IBMQ.load_account()\n",
    "provider = IBMQ.get_provider(\"ibm-q\")\n",
    "device = least_busy(provider.backends(filters=lambda x: x.configuration().n_qubits >= 3 and \n",
    "                                   not x.configuration().simulator and x.status().operational==True))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "db383a0b-b6b1-4241-84b9-41bc6f17bb13",
   "metadata": {},
   "source": [
    "Initialise a uniform superposition"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "287212cb-55c2-4809-84fb-e41816313649",
   "metadata": {},
   "outputs": [],
   "source": [
    "def initialize_s(qc, qubits):\n",
    "    \"\"\"Apply a H-gate to 'qubits' in qc\"\"\"\n",
    "    for q in qubits:\n",
    "        qc.h(q)\n",
    "    return qc\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "270d971e-3642-4f7b-b939-966e01e6cd3f",
   "metadata": {},
   "source": [
    "N-qubit diffuser"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "37777f63-59f7-40dd-9df3-287e511ff0b1",
   "metadata": {},
   "outputs": [],
   "source": [
    "def diffuser(nqubits):\n",
    "    qc = QuantumCircuit(nqubits)\n",
    "    # |s> -> |00..0>\n",
    "    for qubit in range(nqubits):\n",
    "        qc.h(qubit)\n",
    "    # |00..0> -> |11..1>\n",
    "    for qubit in range(nqubits):\n",
    "        qc.x(qubit)\n",
    "        \n",
    "    # multi-controlled Z gate\n",
    "    qc.h(nqubits-1)\n",
    "    qc.mct(list(range(nqubits-1)), nqubits-1) \n",
    "    qc.h(nqubits-1)\n",
    "\n",
    "    # |11..1> -> |00..0>\n",
    "    for qubit in range(nqubits):\n",
    "        qc.x(qubit)\n",
    "    # |00..0> -> |s>\n",
    "    for qubit in range(nqubits):\n",
    "        qc.h(qubit)\n",
    "    # return the diffuser as a gate\n",
    "    U_s = qc.to_gate()\n",
    "    U_s.name = \"U$_s$\"\n",
    "    return U_s\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "63cd4ad1-6b13-4141-b41f-ee6b7b51e884",
   "metadata": {},
   "source": [
    "Creation of our Grover circuit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "6838ebcf-805c-4ad1-93ea-5fb33502eb31",
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 538.279x264.88 with 1 Axes>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "n = 3\n",
    "grover_circuit = QuantumCircuit(n)\n",
    "grover_circuit = initialize_s(grover_circuit, [0,1,2])\n",
    "qc = QuantumCircuit(3)\n",
    "qc.cz(0, 2)\n",
    "qc.cz(1, 2)\n",
    "oracle_ex3 = qc.to_gate()\n",
    "oracle_ex3.name = \"U$_\\omega$\"\n",
    "grover_circuit.append(oracle_ex3, [0,1,2])\n",
    "grover_circuit.append(diffuser(n), [0,1,2])\n",
    "grover_circuit.measure_all()\n",
    "grover_circuit.draw(output=\"mpl\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "71ef5d72-bdce-416a-a5b0-adcad5666cf8",
   "metadata": {},
   "source": [
    "Simulation of the circuit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "1938e516-c5ef-4492-876a-dc92cad96791",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "aer_sim = Aer.get_backend('aer_simulator')\n",
    "transpiled_grover_circuit = transpile(grover_circuit, aer_sim)\n",
    "qobj = assemble(transpiled_grover_circuit)\n",
    "results = aer_sim.run(qobj).result()\n",
    "counts = results.get_counts()\n",
    "plot_histogram(counts)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "59b63af9-d25a-45f4-956c-1fa5b8b506d5",
   "metadata": {},
   "source": [
    "Visualization of the circuit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "d7944538-56e3-49f4-a482-324e0a937b0c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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uHVxdXZGeno79+/cDgOqEhsbQ9tPAh4eF+z4kqVSG9He0y/m43M+Bu4W6zTO09zQkZi1ASPdI9OzSH+WV95H0r8Xo4uwDjw69cO/BbeScz0TSop9Uvz+JxAzVNdWofFQOKwsbSKUy1CS2XGZtsxfcuoSi4ny8H5MNoPaSgj9rTO76XLp0SeOYhIQEjZcwbN68uakiNcqyd5MA1P7t/PlxS5HJZE8ccwsLCwMApKamapy/oTICareCCgoK4Obmhh49eqjtTpVKpcjOzm6aF6LnjK6QTE1NkZaWhtmzZyMmJgYODg7461//itjYWMTFxcHf31/oiHpJWa2EUlmFKsUjAMCjqkoAgLmZJUxMTBAWNBkPq8rx4d5Y/H73V1hb2MHfXYq3Z/wLEokZTlw6gN5eETA1NcX7aTMxsl8MPDr0gkL5CBZmzXcMT1NuABqzd3zOCz5dB2Btylh06xCISWFxzZZXF4/vGiLttWvXDl27dkV5ebnGY3GayqjOiRMn4ObmhuDgYB7fq4fRFRIAeHl54dixY2rTpk6dCm9vb7Wrq6uqqqBUKlFdXY2qqipUVlbC0tLS4Pf3Posjp/6BTXumq34e/rfa3+M/lv8Cl3ZdAADDnp+FYc/Peur8d8tuwd7WAZWPypF7+SDGS9/EqSuHEdAtFKamzbdnWZvcmrI/UlRi8v8voblbghHZZwYcW7s2W2ZtjR8/XugIeqt9+/YAgOvXr0OpVNY7TtsyAoCrV2t3+3bo0KHpAxsIoyykp8nNzUXfvn3Vps2aNQspKSkAgG+//RYA8Msvv6BLly4tHQ8AELUiW6fpLSkiZBoiQqY98/x9eryI+F2TcKngB0wOW4n3016FrVVrLIxKarqQT9HY3ACwNX02bv7xM5TVCvT3eUkUZQQA3t7euHjxotAx9NKFCxdgb2+v8b5zlpaWcHJy0uqi17fffhvr169HeXl5U8c1GCwk1F7Mlp+f/8SZNDt27MCOHTuECWVkOjv3xPZFeaqfR/SbLVwYHS2bJN7bB9GzqampQVlZmcZxZWVlePHFF9G5c2ecO3euwbEsIs1YSKi93UdDm+VERPUpLS3VWEakHaM77ZvIWMhkMqEjEOmEhURkoPg1B6RvWEhEBiomJkboCEQ6YSERGShebEn6hoVERESiwEIiIiJRYCERGSheFEv6htchCci1rXGum1rGnj17ePsgLQUGBj7TfD8X3AQAuLu1V3vcEus2RCwkAY3pLXQCMmSrV69mIWlpy5YtzzRf3Z3JNyyNVntMz4a77IiISBRYSEREJAosJCIDtW3bNqEjEOmEhURkoHx8fISOQKQTFhKRgZJKpUJHINIJC4mIiESBhURkoEJCQoSOQKQTFhKRgTp58qTQEYh0wkIiIiJRYCEREZEosJCIDFR6errQEYh0wkIiIiJRYCERGaioqCihIxDphHf7FtA/c4GiO8Ks27Ut7zZOpO8WLFiAvLy8Fl9vYGDgM98hvSEsJAEV3QGu3RI6BRHpq7y8PMjlcqFjNBnusiMyULGxsUJHINIJC4nIQM2bN0/oCEQ6YSERGahBgwYJHYFIJywkIgNVXFwsdAQinbCQiIhIFFhIRAaqZ8+eQkcg0gkLichAZWRkCB2BDICtrS3MzFrmCiFeh0RkoFatWoW33npL6BgkEm3btsXYsWPRp08f+Pn5wdbWFg8fPsTly5eRm5uLzMxMXL9+XW0eW1tbHDhwAL///jsmTpwIhULRrBmNdgupuroamzZtgqenJ6ysrBAQEAC5XI7u3bsjOjpa6HhEjZaWliZ0BBIBJycnJCcno6ioCMnJyZg1axb69u0LPz8/9O7dG5MnT0ZCQgKuXbuGrKws+Pr6AvhfGQ0cOBDPP/88nJ2dmz2r0W4hzZgxA3v37sXKlSsRHByMnJwcTJw4EcXFxVi0aJHQ8Z4q/R0Z3HzD0eelFVpNb0nJ/16KHy7+C8V3b8DK0g7P9xiOmcPfRSubdoJl0kQfMxPpYuzYsdi+fTscHBwAAIcOHcKBAwdw5swZ3LlzB7a2tvDz84NMJsPYsWMxcuRIREREID4+HmFhYRg4cCBu3LiB0NBQFBUVNXteo9xC2r17N1JSUpCVlYXFixcjNDQUcXFx6NevHxQKBYKDg/Hw4UNMmzYNrq6uaNOmDQYPHoyLFy8KHV20TE0lWDZxJzLWlmD7wh9x+14hNn0xXehYDdLHzETamjt3LtLT0+Hg4ICvvvoKXl5eiIyMxNatW/HNN9/gp59+wvHjx5GcnIzJkyejY8eOSExMhIWFBdasWaNWRteuXWuRzEZZSOvXr0dkZCSkUqnadA8PD5ibm8PPzw8KhQIeHh44ceIESkpKEB4ejgkTJgiUWPxefTEeHq69YCYxRxu75zD6hXn48edsoWM1SB8z68KQ7nFGuhk1ahQ+/vhjAMCbb76JiIgIXLlypcF5bt++jTfffBPnzp1TTcvMzGyxMgKMsJAKCwtx7tw5jBs37onnCgoK4OPjA0tLS9ja2mLFihVwdXWFRCLBa6+9hp9++gmVlZUCpNY/Z658Dff2/kLH0Ik+Zm7I+fPnhY5AAnBwcEBSUhIAYNmyZdi0aZNW89UdM/L19UVxcTGqq6sRExOD4ODg5oyrxuiOIRUWFgIAXFxc1KZXVFRALpdj2LBhT50vJycHXbp0gZWVlcZ1mJiYaJVlbNwxdPSWaTW2zol963Bqv/o/sKrKMrj5huu0HLk8G68PDdVpnjqb5hxDQDdZvc9/ezYD+08k4/05TfsJXS7PRshE/coMNC53fRYuXKhxTEJCgsZxCQkJTRWpUZZu2A6g9m/nz4/FToy5V6xYAWdnZ2RnZ2Pjxo1azfPnExjqdtPNnTsXixYtwpYtWzBw4EC18XK5XKfXWVNTo9U4o9tCcnR0BADk5+erTd+4cSNu3ryJoKCgJ+a5c+cOYmNjsW7duhbJ2JA+o+MQk3RX7b8OXgOEjqUi/zENCemz8Na0LHh2fPJ3KUb6mJnoaWxsbDBt2jQAtR9atCmCp5XRtWvXsGrVKty7dw8DBgyAv3/L7Dkwui0kd3d3+Pv7Iz4+Hu3atYOrqyvS09Oxf/9+AHhi87SiogKjRo3ChAkTMGnSJK3Woe2ngQ8PC/d9SFKpDOnvaJfzcbmfA3cLn5x+8OTfkfTlG3hr+pfw7fpCIxM+SSqVoSZRvzIDjctdn0uXLmkck5CQoPEShs2bNzdVpEZZ9m7tLqaamhq1x2IndG6ZTKZ2rDAyMhJt2rTB8ePHtfrivvrKCAAePHiAf/zjH5g3bx5eeeUVnD17VjWfVCpFdnZ2U78c49tCMjU1RVpaGnx8fBATE4Pp06fD0dERsbGxMDMzU/skoFAoMH78eHh6eopi60jM9n73AZL+tRjrZx1qtjf2pqaPmXWxdu1aoSNQC+vdu/ZroA8fPqxxbENlVOfIkSNqy21uRreFBABeXl44duyY2rSpU6fC29sb1tbWqmkzZ85EdXW16gAh1W/bvvmQmJph8Sfqx0q+XFcmUCLN9DGzLsaPHy90BGphPj4+AIAff/yxwXHalBEA1VZW3XKbm1EW0tPk5uaib9++qp9//fVXpKSkwMrKCm3atFFNv3DhAtzc3ARICEStyNZpeks6/J74d688Th8z68Lb25vXzhmZPXv24OzZs2q7155m3bp1Wl1ndOvWLcTHx+Pu3bvNkPZJLCQAZWVlyM/Px9y5c1XTOnfurBf7sImI6uzatUurcStXrkSHDh2wfPnyBq8zqqioQFxcXFPF04iFBMDOzg5KpVLoGERELaK0tFSUu3SN7qQGImMhk8mEjkCkExYSkYFKTEwUOgKRTlhIRAYqJiZG6AhEOmEhERmo5rhwkag5sZCIiEgUWEhERCQKLCQiA8WLYknfsJCIDNSePXuEjkCkE14YKyDXtvq5bnunpsvRUusVKrOQ6169erUoL36kphMYGKjzPD8X3AQAuLu1V3vc3OvVBgtJQGNa5ga6Ta77YKET6E4fMxNpsmXLFp3nqfuajA1Lo9UeiwF32RERkSiwkIgM1LZt24SOQKQTFhKRgWqp77AhaiosJCIDJZVKhY5ApBMWEhERiQILiYiIRIGnfRPpoR49emgcs3r1aq3GEYkFt5CIDNSaNWuEjkCkExYSERGJAguJiIhEgYVERESiwEIiIiJRYCEREZEosJCIiEgUWEgCGDJkCAICAuDv74+oqCjcv39f6EhEei07Oxs+Pj7w8PDAzJkzoVQqhY6k0WuvvYaOHTvCzEx/Lge9ceMGwsLC4O3tDV9fXyxfvrxJl89CEkB6ejp+/PFHnD17Fm5ubti8ebPQkYj0VnV1NWbOnIm0tDRcvXoV9+/fx86dO4WOpdGECRNw6tQpoWPoxMzMDO+++y4uXryI06dPIycnB/v27Wuy5bOQBNC6dWsAtX9IDx48gImJicCJiPTXyZMn0aFDB/Ts2RMA8OqrryIjI0PgVJoNGDAAzs7OQsfQSfv27dG7d+03i1pYWMDf3x8FBQVNtnwWkkBGjRoFFxcXXL58GW+88YbQcYj0VmFhITp16qT62c3NDTdu3BAwkXEoKSlBZmYmhgwZ0mTLNKmpqalpsqWRTqqrqxEXFwdHR0eWEhmVKoUCqRlfoay8AgBw81YJAKC9k4Pa4zrDQp+HZ5eOT11Weno6MjMzVbvpLly4gMmTJ+PMmTNNnvvEj5fwn9PnVT83lLu9UzuMGybTuAfEzMwMCoWiybPWKa+oRErGITyqUmjMDADjhknRwdmxwWU+fPgQkZGRGDFiRJO+d3ELSUCmpqaYNm0aduzYIXQUohZlbmaGfsE+uHmrRPWmCOCJxzdvlaBNK1t4dHatd1mdOnVS221048YNdOz49PJqrF4+HqiurtaY+1bJHQzqEyCK3fE21lYI8vXS6nfdqf1zGstIqVRi8uTJ6NWrV5N/kGYhtbD79+/j5s2bqp8zMjL4zZ5klHp6dEZv/+4NjrG1tsKYyEENvrH37t0bRUVFuHDhAgDg008/xZgxY5o0ax1zMzNMGDkYEtOG3zqHDgyBy3PtmiXDs+gT0AM9urk1OKZdG3sMH9xP47Kio6Nhb2+P999/v6niqbCQWti9e/cwatQo+Pn5wd/fH3l5edi6davQsYgEMXJwP7RrbV/v82MiB8He1qbBZUgkEiQnJyMqKgrdunWDnZ0dpk6d2tRRVTo4OWDIwN71Pt+1U3sMDPHTuJzZs2ejY8eOUCqV6NixI2JjY5syphoTExOMjRwEG2vLep+fMDwUlhbmDS7n+++/x2effYbc3Fz06tULgYGB+OCDD5ouJ48hiUdNTY0oNvGJWtL1wv9i+64sPP5GFOznhXHDZEJE0qi6uhpJ//cvXC/8r9p0SwtzzJ8R1WDJCunc5V+wM/PwE9ND+wUiYlAfARKp4xaSiGR+9R2yjnwvdAyiFtWlowukfQPVprVtbY+RYf2FCaQFU1NTjB8ug8VjWxQjw/uLtowAwLd7VwT5eqlN6+DsgLAXggVKpE40hbRmzRqYmJjg7NmzePHFF2Fra4v27dvjvffeAwAcOHAAQUFBsLGxQa9evZCTk6M2f05ODiIiItC6dWtYW1tj4MCB+O6779TG5ObmYvz48XBzc4O1tTU8PDzw2muv4d69e2rjrl69iqioKLi4uMDS0hKurq4YNWoUSkpK0FxK7t7HybOXAHALiYxP+IBg1ZleJgDGDZfBytJC2FAatGvTCiPD/nfMpadnFwQ/9mYvRqPC+6NNKzsAgJlEggnDQ2EmkQicqpZoCqnOK6+8gvDwcOzbtw9DhgzBkiVLsGzZMrz55ptYsmQJ0tLSUFNTg1GjRqGsrAwA8NVXX0Emk8HU1BQ7duxAeno67O3tERYWhhMnTqiWff36dfj5+eGjjz7CwYMHsXz5chw8eBDDhg1TyzBs2DD8+uuv+PDDD3H48GEkJCTA2dkZFRUVzfa6j/3nDExNTCF7PqDZ1kEkVmYSCSaMCIVEYoqBffzh3qm90JG00tuvO7w9OsPOxhpjIgfqxS53K0sLjBsugwmACGkInEV08oVojiGtWbMGa9euxSeffILZs2cDqD3X3dnZGeXl5cjPz0eXLl0AAEePHkVYWBgyMjIwZswYeHl5wcnJCd9++63qH4RCoYCvry+6du2KAwcOPHWdCoUC//nPfzBo0CCcOXMGgYGBuH37Np577jlkZmZi9OjRz/Ralr2b9EzzEREZog1Lo7UaJ7otpD9vrVhaWsLd3R3e3t6qMgKAHj16AAAKCgpw9epVXLlyBZMmTYJSqYRCoVBdZBYeHo5vvvlGNV9paSmWL18ODw8PWFlZwdzcHIMGDQIAXL58GQDg4OAAd3d3LF26FElJScjPz2/ul0xERABEd5vZtm3bqv1sYWEBKyurJ6YBQGVlJX7//XcAQGxsbL2nTZaXl8PGxgbTp0/HoUOHsGbNGgQFBcHe3h43btzAmDFjVLvjTExMcOTIEaxZswZxcXG4ffs2OnXqhNjYWCxZskSrTXJtPw0AtceO3k/+An17+WBUuHgP4hIRNTfRFZKuHB1rrypes2YNhg8f/tQxVlZWqKysRGZmJlatWqV2dfHTvvqha9euSElJAQCcP38eSUlJWLZsGRwcHDBz5kyNmZ5ll13OqXPIOXVO5/mIiMRO2w/pel9IXl5ecHd3x9mzZ7F69ep6xz169AhKpRKWluoXhv39739vcPk+Pj7YunUrkpOT8dNPPzVJZiIiepLeF5KJiQkSExMxYsQIjB49GlOmTIGTkxOKi4tx+vRpVFVV4b333kOrVq3Qv39/vPfee3ByckKHDh2Qnp6O48ePqy3v7NmzeP311zF+/Hh4enoCAD7//HNUVFQgIiJCq0zafhpIPyBH3vmrWDL7FbSyt9XthRMRGRi9LyQAGDp0KHJycrBu3TrExMSgtLQUTk5OCAoKwqxZs1Tjdu/ejXnz5mHBggWQSCQYMWIEPv/8c9X3ewCAi4sLOnfujC1btqCoqAjm5ubw9vbGnj17njg9vDFK7t7H6XP56NvLh2VERAQRnfZtbK78UoiMg99g7pTRLCQiIrCQBFVdXQ1TDXcNJiIyFiwkIiISBX48JyIiUWAhERGRKLCQiIhIFFhIREQkCiwkIiISBRYSERGJAguJiIhEgYVERESiwEIiIiJRYCEREZEosJCIiEgUWEhERCQKLCQiIhIFFhIREYkCC4mIiESBhURERKLAQiIiIlFgIRERkSiwkIiISBRYSEREJAosJCIiEgUWEhERiQILiYiIRIGFREREosBCIiIiUWAhERGRKLCQiIhIFP4fBGMd+VZH0mIAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 538.279x264.88 with 1 Axes>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grover_circuit.draw(output=\"mpl\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "94af4d7f-05b9-46c6-9dd5-1f9535b6ac21",
   "metadata": {},
   "source": [
    "Processing of the circuit on quantum hardware"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "ba2a8088-fa44-4c4c-a6b1-5ff0144608aa",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Job Status: job has successfully run\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Run on the least busy backend\n",
    "transpiled_grover_circuit = transpile(grover_circuit, device, optimization_level=3)\n",
    "job = device.run(transpiled_grover_circuit)\n",
    "job_monitor(job, interval=2)\n",
    "\n",
    "results = job.result()\n",
    "answer = results.get_counts(grover_circuit)\n",
    "plot_histogram(answer)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5e31f7a7-7fd0-4ee7-a555-f1f5c105c372",
   "metadata": {},
   "source": [
    "Implementation of an error in the Grover circuit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "4d6d08cd-852c-424c-b55e-5b2dc62162bc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "n = 3\n",
    "grover_circuit = QuantumCircuit(n)\n",
    "grover_circuit = initialize_s(grover_circuit, [0,1,2])\n",
    "qc = QuantumCircuit(3)\n",
    "qc.cz(0, 2)\n",
    "qc.cz(1, 2)\n",
    "oracle_ex3 = qc.to_gate()\n",
    "oracle_ex3.name = \"U$_\\omega$\"\n",
    "grover_circuit.append(oracle_ex3, [0,1,2])\n",
    "\n",
    "# error after the oracle\n",
    "qc.rx(pi/4, 0)\n",
    "grover_circuit.append(diffuser(n), [0,1,2])\n",
    "grover_circuit.measure_all()\n",
    "grover_circuit.draw()\n",
    "\n",
    "aer_sim = Aer.get_backend('aer_simulator')\n",
    "transpiled_grover_circuit = transpile(grover_circuit, aer_sim)\n",
    "qobj = assemble(transpiled_grover_circuit)\n",
    "results = aer_sim.run(qobj).result()\n",
    "counts = results.get_counts()\n",
    "plot_histogram(counts)"
   ]
  }
 ],
 "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
}