QASM.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 🌐 QASM\n",
    "\n",
    "We can now use Quantum Assembly Language in order to emulate the behaviour of a real quantum circuit."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 📚 Libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Librerie necessarie\n",
    "import numpy as np\n",
    "from qiskit import QuantumCircuit, QuantumRegister, ClassicalRegister, execute, BasicAer, IBMQ\n",
    "from qiskit.visualization import plot_histogram, plot_bloch_multivector\n",
    "from qiskit.extensions import Initialize\n",
    "from qiskit_textbook.tools import random_state, array_to_latex\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 🔧 Functions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Funzioni per la creazione del circuito\n",
    "\n",
    "def bell_pair(circuit, a, b):\n",
    "    # Crea una coppia di Bell nel circuito usando i qubit 'a' e 'b'\n",
    "    circuit.h(a)\n",
    "    circuit.cx(a, b)\n",
    "    \n",
    "def Alice_side(circuit, c, a):\n",
    "    # Operazioni che compie Alice, dove il qubit 'c' contiene lo stato da teletrasportare\n",
    "    circuit.barrier()\n",
    "    circuit.cx(c, a)\n",
    "    circuit.h(c)\n",
    "    \n",
    "def Alice_measure(circuit, c, a):\n",
    "    # Alice misura i suoi qubit e invia il risultato a Bob\n",
    "    circuit.barrier()\n",
    "    circuit.measure(c, 0)\n",
    "    circuit.measure(a, 1)\n",
    "    \n",
    "def Bob_side(circuit, qubit, cr1, cr2):\n",
    "    # In base al valore dei bit nei registri 1 e 2 (cr1, cr2) Bob decide che porta applicare al qubit passato in ingresso\n",
    "    circuit.barrier()\n",
    "    # Vengono applicati i registri se i valori sono '1'\n",
    "    circuit.x(qubit).c_if(cr2, 1)\n",
    "    circuit.z(qubit).c_if(cr1, 1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## ❓ Random State Initialization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Creazione di uno stato iniziale casuale\n",
    "# Con QASM si utilizzerà la funzione inversa di Initialize, che anziché portare un qubit da |0> a |psi>\n",
    "# lo porta da |psi> a |0>. Si potrà verificare quindi che q2 sarà sempre uguale a |0>\n",
    "\n",
    "psi = random_state(1)\n",
    "init_gate = Initialize(psi) # Porta dallo stato |0> allo stato |psi>\n",
    "init_gate.label = \"init\"\n",
    "inverse_init_gate = init_gate.gates_to_uncompute() # Porta dallo stato |psi> allo stato |0>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 🧩 Circuit Initialization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<Figure size 1694.03x385.28 with 1 Axes>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Creazione del circuito\n",
    "\n",
    "qr = QuantumRegister(3)\n",
    "cr1 = ClassicalRegister(1)\n",
    "cr2 = ClassicalRegister(1)\n",
    "result = ClassicalRegister(1)\n",
    "circuit = QuantumCircuit(qr, cr1, cr2, result) # 3 qubit e 3 bit\n",
    "\n",
    "# Inizializzazione del qubit C da teletrasportare\n",
    "circuit.append(init_gate, [0])\n",
    "circuit.barrier()\n",
    "\n",
    "# Passo 1: creazione della coppia di Bell\n",
    "bell_pair(circuit, 1, 2)\n",
    "\n",
    "# Passo 2: Alice agisce sui suoi qubit\n",
    "Alice_side(circuit, 0, 1)\n",
    "\n",
    "# Passo 3: Alice misura i qubit ed invia il risultato a Bob\n",
    "Alice_measure(circuit, 0, 1)\n",
    "\n",
    "# Passo 4: Bob agisce sul suo qubit in base al risultato della misura di Alice\n",
    "Bob_side(circuit, 2, cr1, cr2)\n",
    "\n",
    "# Passo 5: inversione del processo di inizializzazione e misura del valore\n",
    "circuit.append(inverse_init_gate, [2])\n",
    "circuit.measure(2,2)\n",
    "\n",
    "circuit.draw(output = 'mpl')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## ✅ Verification"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Verifica del corretto teletrasporto: il bit salvato in 2 deve essere sempre 0\n",
    "\n",
    "backend = BasicAer.get_backend('qasm_simulator')\n",
    "counts = execute(circuit, backend, shots = 1024).result().get_counts()\n",
    "plot_histogram(counts)"
   ]
  },
  {
   "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": "3.8.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}