QAdder.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Qiskit Libraries\n",
    "\n",
    "from qiskit import *\n",
    "from qiskit_aer import AerSimulator\n",
    "from qiskit.visualization import plot_histogram\n",
    "\n",
    "from qiskit import QuantumCircuit\n",
    "#from qiskit.transpiler.passes import Decompose"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Definition of classical and quantum bits\n",
    "\n",
    "quantum_bits = QuantumRegister(8)\n",
    "classical_bits = ClassicalRegister(2)\n",
    "\n",
    "circuit = QuantumCircuit(quantum_bits, classical_bits)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1225.45x785.944 with 1 Axes>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Qauntum Adder Circuit\n",
    "# 4.5.2 Making the Classical Adder a Qauntum Gate,\n",
    "# from \"Introduction to Classical and Quantum Computing\", Thomas G. Wang (2022), p170\n",
    "\n",
    "circuit.x(1)\n",
    "circuit.x(3)\n",
    "circuit.barrier()\n",
    "\n",
    "circuit.cx(1, 3)\n",
    "circuit.cx(2, 3)\n",
    "circuit.cx(3, 4)\n",
    "circuit.cx(0, 4)\n",
    "circuit.barrier()\n",
    "circuit.ccx(1, 2, 5)\n",
    "circuit.ccx(0, 3, 5)\n",
    "circuit.barrier()\n",
    "circuit.x(7)\n",
    "circuit.x(5)\n",
    "circuit.x(6)\n",
    "circuit.ccx(5, 6, 7)\n",
    "circuit.x(5)\n",
    "circuit.x(6)\n",
    "\n",
    "\n",
    "circuit.draw(output='mpl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Measurement Results: {'00': 1024}\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Add measurements\n",
    "\n",
    "circuit.measure(4, 0)  # Measure sum qubit\n",
    "circuit.measure(7, 1)  # Measure carry-out qubit\n",
    "\n",
    "# Simulate the circuit\n",
    "simulator = AerSimulator()\n",
    "result = simulator.run(circuit).result()\n",
    "counts = result.get_counts()\n",
    "\n",
    "# Output\n",
    "print(\"Measurement Results:\", counts)\n",
    "circuit.draw('mpl')\n",
    "plot_histogram(counts)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "qiskit",
   "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": "3.12.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}