Quantum_Communication/Teleportation.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "from math import pi, sqrt\n",
    "from qiskit import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 276.92x264.88 with 1 Axes>"
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Preparing qubit to be measured\n",
    "# Here, we prepare q0 to be (sqrt(3)/2)|0> + (1/2)|1> using the Ry gate\n",
    "prep_circuit = QuantumCircuit(3, 3)\n",
    "prep_circuit.ry(pi/3, 0)\n",
    "prep_circuit.barrier()\n",
    "prep_circuit.draw(output=\"mpl\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 337.12x264.88 with 1 Axes>"
      ]
     },
     "execution_count": 106,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Preparing the Bell state\n",
    "bell_circuit = QuantumCircuit(3, 3)\n",
    "bell_circuit.h(1)  # Superposition by Hadamard gate\n",
    "bell_circuit.cx(1, 2)  # Entanglement by CNOT gate\n",
    "bell_circuit.barrier()\n",
    "bell_circuit.draw(output=\"mpl\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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IiYnB2rVrkZiYWHGaZdeuXSwcdZCQAaSdrrxdD+D7s0DJfeDZx2WPRQ2Eqk6vLFmyBOHh4RWFo5yPjw/s7OwQEBAAwHDe1dfXFxqNBvHx8SKi1ujiDcM3AMmPe934NxuqvdTUVNERrN7KlSvRt29fnD9/Hn379q22cDyqTZs26NDhQWv28/ODnZ2dpWLWidLHR/6tqgvHw47kADnX5clDDY9qSkdubi5OnDiBcePGVXosJycHOp0ODg4OAIDw8HDs3btXsXcPvHzTMse9UwL8ZmJhKtUsMzNTdASrFhoaiujoaJSUlGD06NG4cMG8Fc4Pr+HYunUrTp8+jW7duuH111+3cOLaUfr4+OGs6X1sAHyvjCUyZIVUc3olN9ew6rJVq1ZG24uKipCamorhw4dXbOvXr5+s2Wr7Tpt9/rgQvZ8yXgVv6gqV6h6ftd34z96d/HDz8sla5VGL2bNnm9wnNjbW5H6xsbFSRaqXuW9tBGAYfw9/LtKrr74KAFi6dCmOHz9u1nMeLhzlazj69++Pr7/+GjNnzsTy5ctx586D+/9b6mtsCONj2PT/oHO/SdBoq//RUFpWig/+bw/G9x4tY7La2b/CMGUrejyribmnMVUz0+Hm5gYAyM7ONtq+fPly5OXlISgoSESsOim9X2K5Y98rttixiWri7e2N8PBwFBUVYc2aNWY9p6rCodfrcfDgQXzzzTdwcXHB008/beHkDUdx0W+AqR/Uej1Kin6TJxA1OKqZ6fD29kZAQACWLFkCV1dXtGnTBvHx8RXni0WWjtoudDt6Adh2yHjbozMW5cpnOKp7/GG2GuDGr2d5W/RqnDxpegYoNjbW5KXXq1atkipSvby6bBMAw/h7+HM5PfybaFhYGADgk08+wc2bps8hVlc4yn3wwQcICQnB4MGDsXXr1ortlvoaG8L4+OUq8M7+mvfRaG2x8vXJ2Lt+sjyh6uDASsN/uYhYeVTz40Wj0SAuLg46nQ7R0dGYOnUq3NzcEBMTA61WW7GI1Bp4WeiN2jyb831Y6mvhwoWiI1it8uL//fffm9zXVOF4+DhKmsVU+vjwdgfatzCs26iKDQCPZoC/p5ypqCFRzUwHAPj6+iI5Odlo25QpU+Dv749GjRoJSlV7LZyANs2BSxIvKO3eVtrjqdH48eNFR7Banp6Gn2SmbuRlTuEAgDNnzgAwXNWiFEofHzY2wLSBwHtfGb6/2MD4Sjm3psALgwANfzmhOlL90MnIyKj0m9C8efPg5eWFb7/9FtOnT4eXl5di7mgIGL4x9PeV9phaDdC7o7THVCM/Pz/REazWhAkT0Lx5c3z++ec17ufh4QF7e3uTN/4qLCxEixYt4OHhYYm4dWIN46OpIzAnHHiuP+D30IzG5H7A30YAzZuIy0bWT9Wlo7CwENnZ2ZVuCvaPf/wDubm5KC4uxvXr15Gbm4uOHZX1E7lXB6C1s3THG6IDnBylOx5RbRUXF6OgoAAlJTUvlN6xYwdCQkLMuvHXjRs3jK5cIfNoNUCP9kBU2INtwR0AO96JlOpJVadXHuXk5ITSUut8wxFbLTCpLxD7heFt6uujTXNgqE6aXERyMGfdBxEpj6pLh7Vr28LwlvQffFN98TB11UoLJ+D5gXwvBakMHDhQdARSMI4PUjuWDisX2B6w1wIffgf8r5a32PB2B57tDzg3tkw2NdqwYYPoCKRgHB+kdqpe09FQ6LyA10Ya1nlozLgBX1NH4KkgYMZQFg6pRUdHi45ACsbxQWrHmY4GwskReKYfMCrQ8P4J568BuTeAO8WGq11cmxhOx3RpDQS05ekUS0lJSREdgRSM44PUjqWjgWnWyHAlChERkdLw9AoRERHJgqWDSEJZWVmiI5CCcXyQ2rF0EElo165doiNYFb1eX6uPuW9txNy3Nlb6vDYfInF8kNqxdBBJaMGCBaIjkIJxfJDasXQQERGRLFg6iIiISBYsHUQSWr9+vegIpGAcH6R2LB1EEtLpeJMUqh7HB6kdSweRhEJDQ0VHIAXj+CC1Y+kgIiIiWbB0EEmoV69eoiOQgnF8kNqxdBBJKD09XXQEUjCOD1I7lg4iIiKSBUsHERERyYKlg0hC8fHxoiOQgnF8kNqxdBAREZEsWDqIJBQRESE6AikYxwepHUsHERERycJWdAAiIqKqHFgp5vlD/lq/17WxsanfAepAr9fL/pp1wZkOIgnFxMSIjkAKxvFBasfSQSShGTNmiI5ACsbxQWrH0kEkoQEDBoiOQApmTePj7j3g/LUHf75TLC4LNRxc00Ekofz8fNERSMGUPj5+uwN8+wtw+Dxw9ZbxY6/HA25OQGB7oF8noHkTIRHJyrF0EBGpXGkZsD8T2H/C8Hl1rhUa9juQCYT5A8MDADutfDnJ+rF0EEnI399fdARSMCWOj9t3gc0pQM5185+jB/DVz8DPl4DpYZz1IPNxTQeRhBISEkRHIAVT2vj4XzHw7oHaFY6H/fobsO6A4bQMycfZ2Vl0hDpj6SCS0Pz580VHIAVT0vjQ64H/+95QHGqy+hnDR3WuFwLbvzUcj2rHy8sLf/nLX/D+++8jPT0dx48fx3fffYfNmzcjKioKLVq0qPI5GRkZWLx4sYDE9ae60lFWVoaVK1eiU6dOcHR0RPfu3ZGamorOnTsjKipKdDyycnFxcaIjkIIpaXwcuwj8dFGaY2X/Cnz3izTHUoPOnTsjKSkJ58+fx5o1azBlyhQEBweja9eu6N27N6ZNm4aNGzciNzcX27Ztg6enJwBD4UhOToaPjw+GDRuGRo0aCf5Kak91azoiIyORmJiIefPmISgoCGlpaZg4cSLy8/MxZ84c0fGIiCxOrzcsGpXSgUygd0dAI//NOAEAe9P/jXc/eqnS9pJ7RQCAj/7xGxo5OMkdq5I5c+Zg8eLFcHR0RElJCeLj45GcnIyffvoJhYWFcHFxQY8ePfDEE09g+PDhePbZZzF69GjMnz8fM2fOhI+PDzIyMjB06FAUFRWJ/nJqTVWlY8eOHdi2bRtSUlIQGhoKAAgLC8Phw4eRmJiInj17Ck5IRGR5F64Dl25Ke8zrhcDJy4B/G2mPa67wXlMR3muq0bbUY7uwbOef8JexGxRRONauXYuXXjIUoy1btuDvf/87rly5Umm/gwcP4p133oG3tzfWrFmDkSNH4p133gGAisJRUFAga3apqOr0ypIlSxAeHl5ROMr5+PjAzs4OAQEBuHnzJkaOHAlfX190794dw4YNw5kzZwQlJmuTmpoqOgIpmFLGR3aeZY57uvLPT2H2//gBlu38E/46fmulMiLC3Llz8dJLL+Hu3bsYO3Yspk2bVmXheNjZs2cRHR1tdH+X9evXW23hAFRUOnJzc3HixAmMGzeu0mM5OTnQ6XRwcHCAjY0NZs2ahezsbBw7dgwjR47E1KniByxZh8zMTNERSMGUMj4u3rDMcet6FYzU9ny/GbHxz+O1idsxKHCS6Djo2rUrFi1aBACYMGECkpKSzHpe+RoOd3d35OTkAABWrFgBDw8Pi2W1NNWcXsnNzQUAtGrVymh7UVERUlNTMXz4cACAi4sLhgwZUvF4v379sHz5cotmE/GOhFR7s2fPNrlPbGysyf1iY2OlilQvc9/aCMAw/h7+XMmUnNmaxsfTi36Ah3cvo201XaFS3eOzthv/+cefTsNmmG890z2wf0XtL4n56NA72PzZ3zBvShz6+o+q0+tKPabefvtt2NvbY8OGDfj444/Nes7Di0bLT6ns2LED4eHhWLhwIV544QWLZq4tc9/lVjUzHW5ubgCA7Oxso+3Lly9HXl4egoKCqnze6tWrMWbMGIvnIyKSj4V+QAn+wbcrZQX+tWcuFj63u86FQ2q+vr4YNmwY7ty5g9dff92s51RVOAoKCioK6+TJk9GsWTNLxrYY1cx0eHt7IyAgAEuWLIGrqyvatGmD+Ph47NmzBwCqLB0LFy7EmTNn8NVXX1k0m7kNkcQ6efKkyX1iY2NNXnq9atUqqSLVy6vLNgEwjL+HP1cyJWe2pvGxMRnIumy87dFZi3LlMxzVPf6w7jofSf8+Dqw0f98P9i9CXOoKLI7cg+4dB9brdev7NTw86zBhwgQAhgsZzFmLUV3hAAxjLDk5GWFhYRg1ahS2b3/wl6KUfwemqGamQ6PRIC4uDjqdDtHR0Zg6dSrc3NwQExMDrVaLgIAAo/3/+c9/4tNPP8XevXvRuHFjQanJ2ixcuFB0BFIwpYwPr+aWOW5bV8sc15Qtn7+O+K/fxtJpX9S7cEgtODgYALB//36T+9ZUOMqVH6f8uNZGNTMdgGGaKzk52WjblClT4O/vb3STlYULF2LPnj3Yv38/XFxc5I5JVmz8+PGiI5CCKWV8dPQwvHGb1LzdpT+mKWcuHcXOr5ZCq7HFq5uHVXp8TMhLiHxyqfzBfqfT6QAAx44dq3E/cwoHABw9etTouNZGVaWjKhkZGejTp0/FnzMzM/Hmm2+iY8eOGDhwYMX28r9oopr4+fkhKytLdAxSKKWMD18PoIWT4d4aUnFyAALaSnc8c/m06VGnBadyWbduHdzd3XH58uUa99u6davJwgEAWVlZWLx4MU6fPm2JuBan6tJRWFiI7OxsvPjiixXbdDqd1ZwbIyKqC40GGNgFSMiQ7pgDOgO2fJv7SlavXm3Wfs8//zxWrlyJ559/vsa1H+fPn8cbb7whVTzZqbp0ODk5obS0VHQMIiLZhXQCDp8Hzl2r/7FauwCD/Ot/HDW7cOFClfeRamhUXTqIpPbwKTmiRylpfGg0wDP9gDX7gNt3q9/P1FUrjeyAP4VwloPMo5qrV4jksGHDBtERSMGUNj7cmgIxQwDnOr5ZaRMH4MXBhpkOInOwdBBJKDo6WnQEUjAljo9WzsDfRgBB/692z+vqBcwdAbRtYZFY1EDx9AqRhFJSUkRHIAVT6vho4gBMCTGs8/jmNHA0Bygtq7yfxgbo5gWE+AKdPITfgJSsEEsHEREBALxbGj4m9gEuFwB5BcC9UsBOC3g4A54ugD1/alA9cPgQEZERWy3QroXhg0hKXNNBJCEl3PiJlIvjg9SOpYNIQrt27RIdgRSM44PUjqdXiCS0YMECxby/BikPx0ftDPmr6AR1U9u7Wpe/Y/Jbc6OMPm+IONNBREREsmDpICIiIlmwdBBJaP369aIjkIJxfJDasXQQSUin04mOQArG8UFqx9JBJKHQ0FDREUjBOD5I7Vg6iIiISBYsHURERCQL3qeDyExdunQxuc+CBQvM2o8aHo4PItM400EkoTfffFN0BFIwjg9SO5YOIiIikgVLBxEREcmCpYOIiIhkwdJBREREsmDpICIiIlmwdBAREZEsWDpUZNiwYejRowe6deuGiIgI3Lp1S3QkslIpKSnQ6XTw8fHBtGnTUFpaKjqSSTNnzoSXlxdsbXl7Imo4Ll68iMGDB8PPzw86nQ6vvfaa6Eg1YulQkbi4OBw9ehTHjx+Hl5cXVq1aJToSWaGysjJMmzYNcXFxOHPmDG7duoX//ve/omOZNG7cOGRkZIiOQSQpW1tbLFu2DFlZWThy5AgOHTqE3bt3i45VLZYOFXF2dgZg+KFx9+5d2NjYCE5E1ig9PR2enp7w9/cHAERGRiIhIUFwKtP69++PVq1aiY5BJKnWrVsjODgYAGBvb4/AwEDk5OQITlU9lg6Veeqpp9CyZUucOnUKL7/8sug4ZIVyc3PRtm3bij+3a9cOFy9eFJiIiADgxo0b+OijjzB06FDRUarFk5sqk5SUhJKSEkRGRiI+Ph7PPfec6Egkk++O/Izvj2ZV2r7m3wmVPndp5oQpY4dBU8VsmF6vt1zIR9wpuot/x32O+6VlRturygwAIwf3Rcd2nrLlI6qL3F/zkfD515W2VzWuNTY2+NMfn4Bz0yY1HrOkpAQRERGYOXOmot/fhzMdKmRvb4+nn34aSUlJoqOQjLr7dcRvtwuRd/U68q5er9j+6Od5V6+jh79PlYUDANq2bWs0s5GTkwMvLy+LZG7cyBHe7TzNymyr1aBD29YWyUEkpTYebnBq7GjWuPZq7W6ycJSWlmLSpEno0aOH4mewWTpU4vbt28jLywNgWNPx8ccfQ6fTCU5Fcmrk6IBhj/cyuV0lN6sAAASWSURBVF/7Nh4I6OJd7ePBwcHIzc3Fzz//DADYsmULxo4dK1nOR4X1DYRTk0Ym9xs5uF+1RYlISWxsbDBiUF+T6+oc7O0w9PFgk8eLiopC06ZN8fbbb0sV0WJYOlTi9u3bGD16NAICAhAQEID79+/jjTfeEB2LZNarexd4uDWvcZ9Rg/vV+M1Qq9XiX//6FyIiItCxY0c4OTlhypQpUket4OhgjydMlKUe/j5o38ajxn2mT58OLy8vlJaWwsvLCzExMVLGJKqVVu6u6N3Dr8Z9BocEwalxzYX7m2++wdatW5GRkYHAwED06NEDa9eulTKqpGz0cp6gJUXS6/W8kkVFTp/LxZZde6p8rGdXX4wfMVDeQGYoKyvDO/9JMpp+Lmdnq8XLz0+ASzMnAcmI6u5/d+5ixaaduFtcUumxFs2bYXbkONhqtQKSWQ5nOh6xe/dujBw5Ei1btoSDgwPat2+PSZMm4fjx46KjWczOT77Cvq/TRccgmXTq4AU/n3aVttvb2SJ8gOnTLyJoNBqMGty3yscGPNadhYOsUpPGjhgc0rPKx54M69PgCgfA0lHh/v37eOaZZzBmzBgcP34cY8eOxcyZMxEYGIiEhARcunRJdESLuHzlGo5l/QKNhkNBTZ4M6wONxnh2a2CfHmhmYsGaSN7tPNHVt4PRtmZOjRHau7ugRET117enDm7NnY22+bRvA3+f9oISWRYvmf3dSy+9hA8//BAzZsxAbGys0a2Sc3NzK26s1dB8mXYYjg72CAnuKjoKycjd1QX9enbFoQzDDJ5LMyc83itAcCrThof1RtYvF1D6+yW04aGPwd7eTnAqorqz1Wrx5KA+eD/hCwDli0z7NNhT3lzTAeDgwYMYMGAAwsPDsWfPHtn/sl9dtknW1yMiIpLSW3OjzNqPc+oAVq9eDQB46623Gmy7JCIiEo0zHQCaNm0KNzc3nDt3TnQU2Vy+cg1rtyViSEgQhvQPEh2HBCktK8ONgltwd3URHaVWrly7afLSXyJro4ZxrfrSUVBQgObNm2PgwIFITk4WkoGnV4iIyJrx9IqZyjvX1atXBSchIiJq2FQ/0wEAHTt2xLlz57Bv3z4MGTLE6LFTp06hc+fOgpJZxgdJ+/DLhcuY+8JENHJ0EB2HiIhUgpfMAli6dCkmTJiA4cOH4w9/+AM6duyIq1evIi0tDf7+/g3qjdEuX7mGzOzzGBISxMJBRESyYukAMH78eDg7O2PFihXYv38/PvnkE7Rs2RKPPfYYZs2aJTqepG4U3IarS1Pel4OIiGTH0ysqVFZWxjuQEhGR7Fg6iIiISBb8dZeIiIhkwdJBREREsmDpICIiIlmwdBAREZEsWDqIiIhIFiwdREREJAuWDiIiIpIFSwcRERHJgqWDiIiIZMHSQURERLJg6SAiIiJZsHQQERGRLFg6iIiISBYsHURERCQLlg4iIiKSBUsHERERyYKlg4iIiGTB0kFERESyYOkgIiIiWbB0EBERkSxYOoiIiEgWLB1EREQkC5YOIiIikgVLBxEREcmCpYOIiIhkwdJBREREsmDpICIiIln8fztoYhk+hkKfAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 698.32x264.88 with 1 Axes>"
      ]
     },
     "execution_count": 107,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create circuit that uses Bell state to teleport\n",
    "teleport_circuit = QuantumCircuit(3, 3)\n",
    "\n",
    "# Step 0: Apply CNOT and Hadamard\n",
    "teleport_circuit.cx(0, 1)\n",
    "teleport_circuit.h(0)\n",
    "teleport_circuit.barrier()\n",
    "\n",
    "# Step 1: Measure first two qubits\n",
    "# N.B.: We overwrite the reads because now we do not care much what measurement we got\n",
    "# We could keep it to send, but our qubits are close enough just to use CNOT and CZ gates\n",
    "teleport_circuit.measure([0, 1], [0, 1])\n",
    "teleport_circuit.barrier()\n",
    "\n",
    "# Step 2: Apply CNOT and CZ gates to recover original qubit\n",
    "teleport_circuit.cx(1, 2)\n",
    "teleport_circuit.cz(0, 2)\n",
    "\n",
    "# In addition, we measure the qubit to check if it matches our expectations\n",
    "teleport_circuit.measure(2, 2)\n",
    "\n",
    "teleport_circuit.draw(output=\"mpl\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 999.32x264.88 with 1 Axes>"
      ]
     },
     "execution_count": 108,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Finally, we merge all the steps together\n",
    "circuit = prep_circuit + bell_circuit + teleport_circuit\n",
    "circuit.draw(output=\"mpl\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# We simulate to verify that the qubit was teleported\n",
    "simulator = Aer.get_backend(\"qasm_simulator\")\n",
    "job = execute(circuit, simulator, shots=2**20)\n",
    "result = job.result()\n",
    "counts = result.get_counts()\n",
    "visualization.plot_histogram(counts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.8660567876508071|0> + 0.49994563760869526|1>\n"
     ]
    }
   ],
   "source": [
    "# Extracting alpha and beta from counts\n",
    "alpha_sq = 0\n",
    "beta_sq = 0\n",
    "\n",
    "for key, value in counts.items():\n",
    "    if key[0] == \"0\":\n",
    "        alpha_sq += value\n",
    "    else:\n",
    "        beta_sq += value\n",
    "\n",
    "alpha = sqrt(alpha_sq/(2**20))\n",
    "beta = sqrt(beta_sq/(2**20))\n",
    "\n",
    "print(\"{}|0> + {}|1>\".format(alpha, beta))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'qiskit-terra': '0.11.0',\n",
       " 'qiskit-aer': '0.3.4',\n",
       " 'qiskit-ignis': '0.2.0',\n",
       " 'qiskit-ibmq-provider': '0.4.4',\n",
       " 'qiskit-aqua': '0.6.1',\n",
       " 'qiskit': '0.14.0'}"
      ]
     },
     "execution_count": 115,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# The results match our expectations! Roughly (sqrt(3)/2)|0> + (1/2)|1>\n",
    "# For purposes of reproducibility, the Qiskit version is\n",
    "qiskit.__qiskit_version__"
   ]
  }
 ],
 "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": "3.7.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}