Notebook_12.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "accessory-kitchen",
   "metadata": {},
   "source": [
    "# Notebook 12\n",
    "# Sunint Bindra"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "matched-outdoors",
   "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"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Libraries imported successfully!\n"
     ]
    }
   ],
   "source": [
    "# Importing standard libraries\n",
    "import numpy as np\n",
    "from qiskit import QuantumCircuit, execute, transpile, Aer, IBMQ\n",
    "from qiskit.tools.jupyter import *\n",
    "from qiskit.visualization import *\n",
    "from ibm_quantum_widgets import *\n",
    "from qiskit.quantum_info import random_unitary \n",
    "print('Libraries imported successfully!')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "latter-month",
   "metadata": {},
   "source": [
    "<a id=\"part1\"></a>\n",
    "# Superdense Coding Implementation"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1769b5a3-b0ee-4309-86d2-ba72b0b4b8c4",
   "metadata": {},
   "source": [
    "# Phase 0 - Sharing\n",
    "We have 2 users (lets call them Alice and Bob). They prepare an entangled state of two qubits, and they will then share the two qubits. This phase happens before the protocol actually begins. Remember that **entanglement is the infrastructure for superdense coding** - it needs to be in place before the protocol can be used. In this step Alice and Bob are setting up this infrastructure."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "referenced-worker",
   "metadata": {},
   "source": [
    "<a id=\"part1a\"></a>\n",
    "## Step 1: Alice and Bob entangled two qubits"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "actual-julian",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAKoAAACoCAYAAABwvnWJAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/YYfK9AAAACXBIWXMAAAsTAAALEwEAmpwYAAAKd0lEQVR4nO3df2zU9R3H8Wev0BahYFnHz5ZKsUUoPwZ1jhFGaRAE4yIRTDGGRFtTBjgZuoUZVpcFxoYSM7dkUzcMLlsg2jB+JCxTZ1ssZTB+WFAgRQaUVgSBYq3QFnq3Py4UW67tFe/u+31zr0dyCb1rP9+P5tnP93707hPj8/l8iLicx+kJiARDoYoJClVMUKhigkIVExSqmKBQxQSFKiYoVDFBoYoJClVMUKhigkIVExSqmKBQxQSFKiYoVDFBoYoJClVMUKhigkIVExSqmKBQxQSFKiYoVDFBoYoJPZyegNtt2gu1dc4ce2gSPHKvM8d2G4Xahdo6OH7O6VmITv1igkIVExSqmKBQxQSFKiYoVDFBoYoJClVM0BP+0upsPVRWQ2Mz3NkbJqZBnwSnZ+Xn6hXV6/Wydu1aMjIySEhIYPz48ZSVlTFy5EgKCwudnl5AxaumsWfzqqCvd4PGq7CuDH6zDbZXwvtH/C8d//If8M+D4IZ9c1y9ohYUFLBp0yaKiorIzs6moqKCxx57jM8//5xnn33W6endFrxe+EspfBLgZeIWL/zrkP/fs8dFdFo3cW2oGzZsYP369ZSWlpKTkwNAbm4u+/fvZ9OmTUycONHhGd4ejpwJHOnXvfcxTB0JveMjM6dAXHvqX716NbNmzWqN9Lq7776bnj17Mm6c/1f85MmT5OTkkJmZydixY/nggw+cmK5Zu49DTBff0+KFfScjMZuOuTLUmpoaPvroIx599NGbbquuriYrK4v4eP+v98KFC8nLy6OqqorXXnuN+fPn09zc3OUxYmJigrqUlZV2e/57tvyaPxXe2ebyaVV5t8cpKysNep63enl3xz66ugvq83pZ8auXwnL8YLny1F9TUwPAoEGD2lx/5coVysrKmD17NgDnz5+nvLycrVu3AjB58mSGDBlCSUkJDzzwQGQn/TX3PbyC++b8os11xaumOTOZLjR9VYfX24LHE9vh98R4PDRd/iKCs7qZK1fU5ORkAKqqqtpc/+KLL3LmzBmys7MB/+o6cODA1tUVYPjw4Zw6darLY/h8vqAuOTnTQvcf1k05OdOCnuetXn6af3+nkV637a+rwnL8YLlyRU1PT2fcuHGsXr2a/v37M3ToUIqLi9m+fTtAa6jyzWXf5X9kX9/Y8dNQY1NgYN+ITusmrlxRPR4Pb7/9NllZWSxatIgnn3yS5ORklixZQmxsbOsDqWHDhnH27Fmamppaf/bEiROkpaU5NXVz4nvCounQt90T+9fvPo4YAI9Pjvy82ouxtA36ggULqKys5ODBg63XzZw5kzlz5rB48WIqKiqYN28eJ0+eJC4uLiTH/MO7zr0VZcQA+PGMyByr6ar/kf1be/xfj0uF742AUYPB44LlzAVTCN7evXtvOu2/+uqrbNy4kczMTAoLC9mwYUPIIo0m8T1hcsaNr/OnQtZQd0QKLr2PGkhDQwNVVVUsXry4zfXp6ens2LHDoVlJpJgJtU+fPrS0tDg9DXGISxZ2kc4pVDFBoYoJClVMUKhigkIVE8w8PeWUoUnReWy3Uahd0Mc+uoNO/WKCQhUTFKqYoFDFBIUqJihUMUGhigkKVUxQqGKCQhUTFKqYoFDFBIUqJihUMUGhigkKVUxQqGKCQpVWDY03/l19AZquOTeX9kx9mp+E3rl62HnMv7/Upcttb4uJgUH94LvD/Z/s5+RmEwo1SjVehS37YdcnwX1/z1h46Dvwg5HgCf6j90NGoUahz76A10vg4lfd/9nMQf6PpEzoGfp5dUahRplz9fD7d6Chqevv7cjwZPjRdIiP4HuY9WAqilxrgfXlnUf6u8f9l86cOA/bDoR2bl1RqFHk34fh07rQjFVeBcfPhmasYLg6VIub9rpV8zUoPRLaMd/9OLTjdcbVn5SiTXtD58ApuHI1tGMePQPnv4TkxNCOG4hrQ9WmvaFV9Vl4xj12NjKhuvbUH+ymvS+88AKZmZl4PB6Ki4udmKoJpy+GadwL4Rm3PVeuqNc37V22bNlNt7XftHfWrFk88cQT5Ofnd+sY3dkw9naw6M/1xPW6sfR19ci+o9t/8ve2X//tra3kTXr4lucV7LOjrg0Vut60F/wb9UoQwvSLGRMTmZOyK0P9+qa9Dz74YOv17Tft/Sai7XWOlVvgQsONr9uvjNddX0k7ur29vLkPsWVt+P9fujJUbdobekOT2oYaKqn9Qz9mIK58MBXspr0SvBEDwjNuepjGbc+VKypAZmYmJSUlba5bsGABo0ePplevXg7Nyq57h8O2D/0vo4ZK2rci9/HtrlxROxJo096ioiJSUlLYtWsXCxcuJCUlhePHjzs0Q/fqHQ+T0kM7Zu7o0I7XGTOhXt+0t/0T/StXrqSmpoampiYuXLhATU0NI0aMcGiW7vbQBLjzjtCMNTYFxqeGZqxg6M/8osz/zsEf3/9mdwGS+8DSmZAYwXtgZlZUCY30AVA47db/lvTbibDk/shGClpRo9b5L2HjbvikG3+qNyUDfjgB4iP81/2gUKOa1weHa/1v7jv6KQQKIS4WJt4FUzIhJULPmQaiUAWApqtQW+d/q8o1r/+uwZAk/7tQY11wB1Ghigku+F0R6ZpCFRMUqpigUMUEhSomKFQxQaGKCQpVTFCoYoJCFRMUqpigUMUEhSomKFQxQaGKCQpVTFCoYoJCFRMUqpigUAM4ffo006dPZ9SoUWRlZfH88887PaWop1AD6NGjB2vWrOHIkSMcOHCA8vJytmzZ4vS0opprP83PSYMHD2bw4MEAxMXFMWHCBKqrqx2eVXTTitqFixcvsnnzZmbMmOH0VKKaQu1Ec3Mz8+bNY+nSpdxzzz1OTyeq6QMoOtDS0kJeXh7Dhg3j5Zdfdno6UU+hdqCgoACv18sbb7wRdVv9uJFCDWDnzp1MmTKFMWPGEBsbC0B+fj7PPPMMPp9P4TpAoXbT1vcqaGlpYc7MKQo2gvRgqhsu1Tew+8PDWlUdYD7UQ4cOMXfuXJKTk0lISCAjI4MVK1aE5Vil//kQn89H7vcnhGV86ZjpU/++ffuYOnUqqampLF++nLS0NE6cOEFFRQXr1q3r9Gd/vub1CM1SOvPb5YVBfZ/pV6aee+45evfuze7du+nXr1/r9QUFBQ7OSsLB7Ip6+fJlEhMTefrpp3nllVfCeqxL9Q289PpGssdk8sisqWE9lgRmdkWtq6vD6/WSkpJySz9/K6f+PZVH2VN59JaOJ4EFe+o3+2AqKSkJj8dDbW2t01ORCDB76gfIzc3l8OHDHDt2jL59+4blGJvfKWdP5RF+VjifpH6JYTmGdM3sigqwdu1aGhoamDRpEuvXr6ekpIQ333yTp556KiTjX6pv4L8Hj3Lv2JGK1GFm76MCZGdns2vXLoqKili2bBmNjY2kpqYyf/78kIx/4VI9ib3v0POmLmD61B8JXq8Xj8f0iee2oFDFBC0VYoJCFRMUqpigUMUEhSomKFQxQaGKCQpVTFCoYoJCFRMUqpigUMUEhSomKFQxQaGKCQpVTFCoYoJCFRMUqpigUMUEhSomKFQxQaGKCQpVTFCoYoJCFRMUqpjwf+a9tWhOKokFAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 206.852x204.68 with 1 Axes>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Step 1: Two users (Alice aand Bob) entangle two qubits\n",
    "qc_sdc = QuantumCircuit(2,2)\n",
    "qc_sdc.h(0)\n",
    "qc_sdc.cx(0,1)\n",
    "qc_sdc.draw()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ecf15f2a-0ddb-476b-8f1d-9e6376df1645",
   "metadata": {},
   "source": [
    "## Step 2 - Alice and Bob decide on a decision scheme\n",
    "*Conventional decision scheme for Bell States is used "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ff70719d-2f87-4da0-87fb-9d2cfd6151d0",
   "metadata": {},
   "source": [
    "## Step 3 - Alice and Bob share the two entangled qubits"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "configured-mapping",
   "metadata": {},
   "source": [
    "<a id=\"part1c\"></a>\n",
    "## Step 4 - Alice applies gates to her qubit to send message"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "8c736101-4239-4400-a1d6-0907c275d37b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 327.252x204.68 with 1 Axes>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Alex applies gate to qubit \n",
    "qc_sdc.z(0)\n",
    "qc_sdc.x(0)\n",
    "qc_sdc.draw()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "coupled-burke",
   "metadata": {},
   "source": [
    "<a id=\"part1d\"></a>\n",
    "## Step 5 - Alice sends Bob her qubit"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "naughty-demand",
   "metadata": {
    "tags": []
   },
   "source": [
    "<a id=\"part1e\"></a>\n",
    "## Step 6 - Bob makes Bell measurements on the two qubits and deciphers Alice's message"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "deluxe-cookie",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 447.652x204.68 with 1 Axes>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Bell measurement\n",
    "qc_sdc.cx(0,1)\n",
    "qc_sdc.h(0)\n",
    "qc_sdc.draw()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "42f3c96b-c4a0-4e30-8655-f598099718ff",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 507.852x204.68 with 1 Axes>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Adding measurements to circuit \n",
    "qc_sdc.measure([0,1],[0,1])\n",
    "qc_sdc.draw()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "hazardous-single",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Simulating on QASM simulator and plotting histogram \n",
    "backend = Aer.get_backend('qasm_simulator')\n",
    "job = execute(qc_sdc, backend, shots=1024)\n",
    "result = job.result()\n",
    "\n",
    "counts = result.get_counts()\n",
    "plot_histogram(counts)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "whole-checklist",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Running superdense coding circuit on quantum computer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "driven-controversy",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "least busy backend:  ibmq_lima\n"
     ]
    }
   ],
   "source": [
    "from qiskit.providers.ibmq import least_busy\n",
    "shots = 256\n",
    "\n",
    "# Load local account information\n",
    "IBMQ.load_account()\n",
    "# Get least busy backend\n",
    "provider = IBMQ.get_provider(hub='ibm-q')\n",
    "backend = least_busy(provider.backends(filters=lambda x: x.configuration().n_qubits >= 2 \n",
    "                                       and not x.configuration().simulator \n",
    "                                       and x.status().operational==True))\n",
    "print(\"least busy backend: \", backend)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "768d64d0-f643-464a-8236-869557875676",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Run circuit\n",
    "job = execute(qc_sdc, backend=backend, shots=shots)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "electrical-sheep",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Job Status: job has successfully run\n"
     ]
    }
   ],
   "source": [
    "# Monitoring status of job\n",
    "from qiskit.tools.monitor import job_monitor\n",
    "job_monitor(job)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "protective-adams",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Plotting histogram\n",
    "result = job.result()\n",
    "plot_histogram(result.get_counts())\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "backed-photographer",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy = 83.59%\n"
     ]
    }
   ],
   "source": [
    "# Find accuracy of measuremeents \n",
    "correct_results = result.get_counts()['11']\n",
    "accuracy = (correct_results/shots)*100\n",
    "print(\"Accuracy = %.2f%%\" % accuracy)\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Qiskit v0.34.2 (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": "3.8.12"
  },
  "widgets": {
   "application/vnd.jupyter.widget-state+json": {
    "state": {},
    "version_major": 2,
    "version_minor": 0
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}