Exercise 4-2.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "8f3605a8-c503-4384-a264-9b332487c9f7",
   "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": [
    "import numpy as np\n",
    "\n",
    "# Importing standard Qiskit libraries\n",
    "from qiskit import QuantumCircuit, transpile, Aer, IBMQ\n",
    "from qiskit.tools.jupyter import *\n",
    "from qiskit.visualization import *\n",
    "from ibm_quantum_widgets import *\n",
    "from qiskit.providers.aer import QasmSimulator\n",
    "\n",
    "# Loading your IBM Quantum account(s)\n",
    "provider = IBMQ.load_account()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "dba3e66e-c06c-4b95-8e34-1b30ca7ca70d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Exercise4-2\n",
    "\n",
    "# 設計量子程式建構下列的量子線路，以量子電腦模擬器執行這個線路，以文字模式顯示測量的量子位元狀態出現的次數，並以繪圖模式顯示其直方圖。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "1cdf844f-193d-42fc-a515-36cff5b87a2e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "               ┌─┐                     \n",
      "q_0: ──■───────┤M├─────────────────────\n",
      "     ┌─┴─┐     └╥┘┌─┐                  \n",
      "q_1: ┤ X ├──────╫─┤M├──────────────────\n",
      "     ├───┤      ║ └╥┘┌─┐               \n",
      "q_2: ┤ X ├──■───╫──╫─┤M├───────────────\n",
      "     ├───┤┌─┴─┐ ║  ║ └╥┘┌─┐            \n",
      "q_3: ┤ X ├┤ X ├─╫──╫──╫─┤M├────────────\n",
      "     └───┘└───┘ ║  ║  ║ └╥┘┌─┐         \n",
      "q_4: ───────■───╫──╫──╫──╫─┤M├─────────\n",
      "     ┌───┐┌─┴─┐ ║  ║  ║  ║ └╥┘┌─┐      \n",
      "q_5: ┤ X ├┤ X ├─╫──╫──╫──╫──╫─┤M├──────\n",
      "     ├───┤└───┘ ║  ║  ║  ║  ║ └╥┘┌─┐   \n",
      "q_6: ┤ X ├──■───╫──╫──╫──╫──╫──╫─┤M├───\n",
      "     └───┘┌─┴─┐ ║  ║  ║  ║  ║  ║ └╥┘┌─┐\n",
      "q_7: ─────┤ X ├─╫──╫──╫──╫──╫──╫──╫─┤M├\n",
      "          └───┘ ║  ║  ║  ║  ║  ║  ║ └╥┘\n",
      "c: 8/═══════════╩══╩══╩══╩══╩══╩══╩══╩═\n",
      "                0  1  2  3  4  5  6  7 \n",
      "Counts: {'11100100': 1000}\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Quantum State (Total execution time: 1000)\n",
      "|11100100〉: 1000.00%\n"
     ]
    }
   ],
   "source": [
    "from qiskit import QuantumCircuit\n",
    "from qiskit import execute\n",
    "from qiskit.providers.aer import AerSimulator\n",
    "from qiskit.visualization import plot_histogram\n",
    "\n",
    "\n",
    "def showQState(statistic) :\n",
    "    all_state = sorted(statistic.keys())\n",
    "    total_count = sum(statistic.values())\n",
    "    print(\"\\nQuantum State (Total execution time: {})\".format(total_count))\n",
    "    for i in all_state :\n",
    "        print(\"|{}〉: {:.2f}%\".format(i, statistic[i]/total_count*1000))\n",
    "        \n",
    "\n",
    "qc = QuantumCircuit(8,8)\n",
    "qc.cx(0,1)\n",
    "qc.x(2)\n",
    "qc.x(3)\n",
    "qc.x(5)\n",
    "qc.x(6)\n",
    "qc.cx(2,3)\n",
    "qc.cx(4,5)\n",
    "qc.cx(6,7)\n",
    "qc.measure(range(8),range(8))\n",
    "print(qc)\n",
    "\n",
    "sim=AerSimulator()\n",
    "job=execute(qc, backend=sim, shots=1000)\n",
    "result=job.result()\n",
    "counts=result.get_counts(qc)\n",
    "print(\"Counts:\",counts)\n",
    "display(plot_histogram(counts))\n",
    "showQState(counts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4416c390-8044-42ac-a871-81cc75d37f09",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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