teleportation.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "34d268ae-3c48-4da2-9dec-1e677adf217f",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<frozen importlib._bootstrap>:219: RuntimeWarning: scipy._lib.messagestream.MessageStream size changed, may indicate binary incompatibility. Expected 56 from C header, got 64 from PyObject\n"
     ]
    }
   ],
   "source": [
    "# Do the necessary imports\n",
    "import numpy as np\n",
    "from qiskit import QuantumCircuit, QuantumRegister, ClassicalRegister\n",
    "from qiskit import IBMQ, Aer, transpile, assemble, execute\n",
    "from qiskit.visualization import plot_histogram, plot_bloch_multivector, array_to_latex\n",
    "from qiskit.extensions import Initialize\n",
    "from qiskit.quantum_info import random_statevector"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "4521cd0e-a89c-435f-a000-3e0bfe45239d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 1 Qubit Gate - Generate a random state\n",
    "def random_state_gate():\n",
    "    psi = random_statevector(2)\n",
    "    gate = Initialize(psi)\n",
    "    gate.label = \"init\"\n",
    "    return gate\n",
    "\n",
    "# N Qubit Gate - Reverse a gate\n",
    "def reverse_gate(gate):\n",
    "    inverse_gate = gate.gates_to_uncompute()\n",
    "    inverse_gate.label = \"disentangler\"\n",
    "    return inverse_gate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "c2e0e4cb-35ad-4607-84e3-726a2cdc7bcf",
   "metadata": {},
   "outputs": [],
   "source": [
    "def create_bell_pair(qc, a, b):\n",
    "    qc.h(a)    # Put qubit a into state |+>\n",
    "    qc.cx(a,b) # CNOT with a as control and b as target\n",
    "    \n",
    "def alice_gates(qc, psi, a):\n",
    "    qc.cx(psi, a)\n",
    "    qc.h(psi)\n",
    "    \n",
    "def bob_gates(qc, a, b, c):\n",
    "    qc.cx(b, c)\n",
    "    qc.cz(a, c)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "55f47dc3-31bc-4e06-9322-94b4e75f73ca",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1110x264.88 with 1 Axes>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Main gates to work with\n",
    "init_gate = random_state_gate()    # random state\n",
    "dis_gate = reverse_gate(init_gate) # gates to reverse random state\n",
    "\n",
    "# Protocol uses 3 qubits and 2 classical bits in 2 different registers\n",
    "qr = QuantumRegister(3, name=\"q\")  # Protocol uses 3 qubits\n",
    "c = ClassicalRegister(1, name=\"c\") # and 1 classical bits\n",
    "qc = QuantumCircuit(qr, c)\n",
    "\n",
    "# First, let's initialize Alice's q0\n",
    "qc.append(init_gate, [0])\n",
    "qc.barrier()\n",
    "\n",
    "# Now begins the teleportation protocol\n",
    "create_bell_pair(qc, 1, 2)\n",
    "qc.barrier()\n",
    "\n",
    "# Send q1 to Alice and q2 to Bob\n",
    "alice_gates(qc, 0, 1)\n",
    "qc.barrier()\n",
    "\n",
    "# Bob decodes qubits\n",
    "bob_gates(qc, 0, 1, 2)\n",
    "qc.barrier()\n",
    "\n",
    "# Finally, lets reverse the qubit we got to see if its correct\n",
    "qc.append(dis_gate, [2])\n",
    "qc.measure(2, c)\n",
    "\n",
    "# Display the circuit\n",
    "qc.draw()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "841f8fab-f0f1-48de-b593-2bd6823ca8af",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Simulate and plot results\n",
    "aer_simulator = Aer.get_backend('aer_simulator')\n",
    "transpiled_qc = transpile(qc, aer_simulator)\n",
    "qobj = assemble(transpiled_qc)\n",
    "results = aer_simulator.run(qobj).result().get_counts()\n",
    "\n",
    "# Actual quantum computer to get results\n",
    "#provider = IBMQ.load_account()\n",
    "#backend = provider.get_backend('ibmq_manila')\n",
    "#results = execute(qc,backend,shots=1024).result().get_counts()\n",
    "\n",
    "plot_histogram(results)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Qiskit v0.35.0 (ipykernel)",
   "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": "3.8.13"
  },
  "widgets": {
   "application/vnd.jupyter.widget-state+json": {
    "state": {},
    "version_major": 2,
    "version_minor": 0
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}