tereportation.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from qiskit import QuantumCircuit\n",
    "from qiskit import QuantumRegister\n",
    "from qiskit import ClassicalRegister\n",
    "from qiskit import visualization\n",
    "from qiskit import BasicAer\n",
    "from qiskit.aqua import run_algorithm\n",
    "from qiskit.visualization import plot_histogram"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "backend = BasicAer.get_backend('qasm_simulator')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "from qiskit import execute"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<qiskit.extensions.standard.u3.U3Gate at 0x1259dcd30>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q = QuantumRegister(3)\n",
    "c0 = ClassicalRegister(1,'c0')\n",
    "c1 = ClassicalRegister(1,'c1')\n",
    "c2 = ClassicalRegister(1,'c2')\n",
    "\n",
    "qc = QuantumCircuit(q, c0,c1,c2)\n",
    "qc.u3(0.3, 0.2, 0.1, q[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 301x379.26 with 1 Axes>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "qc.draw(output='mpl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1083.6x379.26 with 1 Axes>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "qc.h(q[1])\n",
    "qc.cx(q[1],q[2])\n",
    "qc.barrier(q)\n",
    "qc.cx(q[0], q[1])\n",
    "qc.h(q[0])\n",
    "qc.barrier(q)\n",
    "\n",
    "qc.measure(q[0], c0[0])\n",
    "qc.measure(q[1], c1[0])\n",
    "qc.z(q[2]).c_if(c0, 1)\n",
    "qc.x(q[2]).c_if(c1, 1)\n",
    "\n",
    "qc.measure(q[2], c2[0])\n",
    "qc.draw(output='mpl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "res = execute(qc, backend, shots=1024)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'1 1 0': 5, '1 0 0': 7, '0 0 1': 264, '0 0 0': 251, '1 0 1': 5, '0 1 0': 224, '0 1 1': 262, '1 1 1': 6}\n"
     ]
    }
   ],
   "source": [
    "print(res.result().get_counts(qc))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plot_histogram(res.result().get_counts(qc))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 421.4x138.46 with 1 Axes>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q1 = QuantumRegister(1)\n",
    "c5 = ClassicalRegister(1)\n",
    "qc2 = QuantumCircuit(q1,c5)\n",
    "qc2.u3(0.3, 0.2, 0.1, q1)\n",
    "qc2.measure(q1, c5)\n",
    "qc2.draw(output='mpl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.024"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "0.006+0.006+0.008+0.004"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "j = execute(qc2, backend, shots=1024)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plot_histogram(j.result().get_counts(qc2))"
   ]
  },
  {
   "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": "3.6.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}