deutsch-algorithm.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "8d9c4590-e778-4433-950e-b4a92c71539c",
   "metadata": {},
   "outputs": [],
   "source": [
    "from qiskit import QuantumCircuit\n",
    "from qiskit.providers.fake_provider import GenericBackendV2\n",
    "from qiskit.visualization import plot_histogram"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "e892ee7e-f11c-4f37-bf65-380f6d607a53",
   "metadata": {},
   "outputs": [],
   "source": [
    "backend = GenericBackendV2(num_qubits=2)\n",
    "qc = QuantumCircuit(2, 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "7e13180f-6ece-431e-b6c4-c1c9006c6b89",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<qiskit.circuit.instructionset.InstructionSet at 0x7a0e8d350550>"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "qc.h(0)\n",
    "\n",
    "# bits are set to 0\n",
    "qc.x(1)\n",
    "qc.h(1)\n",
    "\n",
    "qc.barrier()\n",
    "\n",
    "# Oracle\n",
    "qc.x(0)\n",
    "qc.cx(0, 1)\n",
    "qc.x(0)\n",
    "qc.barrier()\n",
    "\n",
    "qc.h(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "f0f17b32-0876-457a-a7ec-766035ee4a45",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 872.572x284.278 with 1 Axes>"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Results\n",
    "job = backend.run(qc)\n",
    "qc.measure(0, 0)\n",
    "counts = job.result().get_counts()\n",
    "qc.draw(output=\"mpl\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "764816ad-4843-4b94-9ce2-d685ac6ef765",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plot_histogram(counts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b995625f-d64e-42cf-a5f3-b6c9dc4e0c17",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 [Qiskit 1.2.0]",
   "language": "python",
   "name": "python3_qiskit_9vrlwn"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}