Q-teleportation 1.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h1>Quantum Teleportation</h1>\n",
    "<h2>Example 1</h2>\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from qiskit import *\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "circuit=QuantumCircuit(3,3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 178.192x264.88 with 1 Axes>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "circuit.draw(output='mpl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 298.592x264.88 with 1 Axes>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "circuit.x(0)\n",
    "circuit.barrier()\n",
    "circuit.draw(output='mpl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 418.992x264.88 with 1 Axes>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "circuit.h(1)\n",
    "circuit.cx(1,2)\n",
    "circuit.draw(output='mpl')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now q1 and q2 are entangled"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 539.392x264.88 with 1 Axes>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "circuit.cx(0,1)\n",
    "circuit.h(0)\n",
    "circuit.draw(output='mpl')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<b>int this measure means measure qubits(0,1)and put it in a classical register (0,1)</b>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 719.992x264.88 with 1 Axes>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "circuit.barrier()\n",
    "circuit.measure([0,1], [0,1])\n",
    "circuit.draw(output='mpl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900.592x264.88 with 1 Axes>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "circuit.barrier()\n",
    "circuit.cx(1,2)\n",
    "circuit.cz(0,2)\n",
    "circuit.draw(output='mpl')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<b>this is a quantum teleportation ckt.<br>\n",
    "before barrier 1 we have changed the q-state of our target bit to  1<br>\n",
    "inside the barrier 2 we are now entangling the two bits q1,q2<br>\n",
    "barrier 3 measures 1,0 and copies it to 2<br>\n",
    "and hence teleported</b>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "circuit.measure(2,2)\n",
    "simulator=Aer.get_backend('qasm_simulator')\n",
    "result=execute(circuit,backend=simulator,shots=1024).result()\n",
    "count=result.get_counts()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from qiskit.tools.visualization import plot_histogram\n",
    "plot_histogram(count)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'111': 286, '110': 230, '100': 256, '101': 252}"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "count\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<b>In this graph </br>\n",
    "100 represents c2,c1,c0 in order</br>\n",
    "as our results were one always for c2 <br>\n",
    "hence the graph has all the co-ordiantes with result 1 in it</b>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.7.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}