quantum_key_distribution.ipynb

{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Quantum cryptography is a method of encryption that uses the naturally occurring properties of quantum mechanics to secure and transmit data in a way that cannot be hacked. Cryptography is the process of encrypting and protecting data so that only the person who has the right secret key can decrypt it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from qiskit import QuantumCircuit, Aer, transpile\n",
    "from qiskit.visualization import plot_histogram, plot_bloch_multivector\n",
    "from numpy.random import randint\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"word-wrap: normal;white-space: pre;background: #fff0;line-height: 1.1;font-family: &quot;Courier New&quot;,Courier,monospace\">     ┌───┐ ░ ┌───┐┌─┐\n",
       "  q: ┤ H ├─░─┤ H ├┤M├\n",
       "     └───┘ ░ └───┘└╥┘\n",
       "c: 1/══════════════╩═\n",
       "                   0 </pre>"
      ],
      "text/plain": [
       "     ┌───┐ ░ ┌───┐┌─┐\n",
       "  q: ┤ H ├─░─┤ H ├┤M├\n",
       "     └───┘ ░ └───┘└╥┘\n",
       "c: 1/══════════════╩═\n",
       "                   0 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 700x500 with 1 Axes>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "qc = QuantumCircuit(1,1)\n",
    "# Alice prepares qubit in state |+>\n",
    "qc.h(0)\n",
    "qc.barrier()\n",
    "# Alice now sends the qubit to Bob\n",
    "# who measures it in the X-basis\n",
    "qc.h(0)\n",
    "qc.measure(0,0)\n",
    "\n",
    "# Draw and simulate circuit\n",
    "display(qc.draw())\n",
    "aer_sim = Aer.get_backend('aer_simulator')\n",
    "job = aer_sim.run(qc)\n",
    "plot_histogram(job.result().get_counts())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"word-wrap: normal;white-space: pre;background: #fff0;line-height: 1.1;font-family: &quot;Courier New&quot;,Courier,monospace\">     ┌───┐┌─┐ ░ ┌───┐┌─┐\n",
       "  q: ┤ H ├┤M├─░─┤ H ├┤M├\n",
       "     └───┘└╥┘ ░ └───┘└╥┘\n",
       "c: 1/══════╩══════════╩═\n",
       "           0          0 </pre>"
      ],
      "text/plain": [
       "     ┌───┐┌─┐ ░ ┌───┐┌─┐\n",
       "  q: ┤ H ├┤M├─░─┤ H ├┤M├\n",
       "     └───┘└╥┘ ░ └───┘└╥┘\n",
       "c: 1/══════╩══════════╩═\n",
       "           0          0 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 700x500 with 1 Axes>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "qc = QuantumCircuit(1,1)\n",
    "# Alice prepares qubit in state |+>\n",
    "qc.h(0)\n",
    "# Alice now sends the qubit to Bob\n",
    "# but Eve intercepts and tries to read it\n",
    "qc.measure(0, 0)\n",
    "qc.barrier()\n",
    "# Eve then passes this on to Bob\n",
    "# who measures it in the X-basis\n",
    "qc.h(0)\n",
    "qc.measure(0,0)\n",
    "\n",
    "# Draw and simulate circuit\n",
    "display(qc.draw())\n",
    "aer_sim = Aer.get_backend('aer_simulator')\n",
    "job = aer_sim.run(qc)\n",
    "plot_histogram(job.result().get_counts())"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can see here that Bob now has a 50% chance of measuring 1, and if he does, he and Alice will know there is something wrong with their channel.\n",
    "\n",
    "The quantum key distribution protocol involves repeating this process enough times that an eavesdropper has a negligible chance of getting away with this interception."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "qenv2",
   "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": "3.8.16"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}