[[2,2]] surface code (1).ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "5cf5fb14-6fbf-499f-83b7-d9fdc6c45392",
   "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.providers.aer.noise import NoiseModel\n",
    "from qiskit.providers.aer.noise.errors import pauli_error, depolarizing_error\n",
    "from qiskit import Aer, QuantumCircuit, execute, ClassicalRegister, QuantumRegister\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",
    "import qiskit as q\n",
    "from qiskit.providers.aer import QasmSimulator\n",
    "from qiskit import QuantumCircuit, Aer, transpile, assemble\n",
    "from qiskit.visualization import plot_histogram\n",
    "aer_sim = Aer.get_backend('aer_simulator')\n",
    "qasm_sim = q.Aer.get_backend(\"qasm_simulator\")\n",
    "statevec_sim = q.Aer.get_backend(\"statevector_simulator\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "c622cead-11d1-4908-a8bb-57b3475509ca",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 568.052x325.08 with 1 Axes>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#initiating quantum register \n",
    "d = QuantumRegister(2, 'd')\n",
    "a = QuantumRegister(2, 'a')\n",
    "c = ClassicalRegister(2, 'c')\n",
    "\n",
    "#initiating quantum circuit\n",
    "circuit = QuantumCircuit (d, a, c)\n",
    "\n",
    "#error simulation\n",
    "#circuit.z(d[1])\n",
    "#circuit.x(d[4])\n",
    "\n",
    "circuit.h(a[0])\n",
    "circuit.h(a[1])\n",
    "circuit.barrier()\n",
    "\n",
    "\n",
    "circuit.cx(a[0], d[0])\n",
    "circuit.cx(a[0], d[1])\n",
    "\n",
    "\n",
    "circuit.cz(a[1], d[0])\n",
    "circuit.cz(a[1], d[1])\n",
    "\n",
    "circuit.barrier()\n",
    "\n",
    "circuit.h(a[0])\n",
    "circuit.h(a[1])\n",
    "\n",
    "#measurement\n",
    "#circuit.measure(a[0],c[0])\n",
    "#circuit.measure(a[1],c[1])\n",
    "\n",
    "#drawing the circuit \n",
    "\n",
    "circuit.draw()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "4356b237-46df-47c8-ba85-167ab7a9d7ce",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAiUAAAE6CAYAAADJBSI4AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/YYfK9AAAACXBIWXMAAAsTAAALEwEAmpwYAAAeXklEQVR4nO3de5RdZZnn8e+TFInmwiUXQqqKGGPS2iQEMKUCHSD2MmaANQjaCCw0wyAwgCbQDKKsRqZxUFtt6dC2SBN6CcF2QHEaR+QSRdOxIYROwqTBSwINCSYklQQiUUIqt2f+OCdMdVmVOid1qmrD+X7WOqvOft93v+fZ/MMv+/LuyEwkSZL624D+LkCSJAkMJZIkqSAMJZIkqRAMJZIkqRAMJZIkqRAMJZIkqRAa+ruA/jRq1KgcP358f5chSSqQ5cuXb8nM0e22D29oaLgdmIL/mO+JvcDTu3fvvmjatGmbOhtQ16Fk/PjxLFu2rL/LkCQVSESsbb/d0NBw+xFHHPHHo0eP3jpgwAAX9zpAe/fujc2bNx+1cePG24EzOhtj4pMkaf+mjB49epuBpGcGDBiQo0ePfoXSGafOx/RhPZIkvRENMJDURvm/Y5fZw1AiSZIKwVAiSZIKoa5vdJUk6UBcPI9pvTn//CtZ3pvz90RTU9PR3/jGN9aceeaZv9vXdt55571tyZIlw1944YXB8+bNWzN37tyXDmRuz5RIkqQemTp16vabb7557VFHHbW9J/MYSiRJegN79tlnD/rgBz/4jsMOO+yYQw899NjZs2eP27NnD9dcc83YxsbGo0eMGHHMWWedNf6ll14aCHD//fcPHzNmzNT2czQ1NR193333DQe46qqrGk877bQJZ5111vihQ4ceN3HixMmLFy8eAnDmmWe+fcOGDYPOPffcSUOGDDnuuuuuGwNw7bXXbv7Qhz70u8GDB+/tybEYSiRJeoPavXs3p59++qQjjzxy59q1a5968cUXV55//vkvf/3rXx959913j/zJT36y6vnnn3/q1VdfHfiJT3xiXKXzPvLII4eee+65W1955ZUnZ82a9ds5c+aMA7jvvvueHzt27M677777me3btz954403ttbyeAwlkiS9QS1atGjopk2bDrr11lt/c/DBB+8dMmRIzpo16/f33HPPyMsvv7z1qKOO2nnIIYfs/epXv7ru/vvvP2zXrl0VzTtt2rTfn3POOa80NDRw4YUXvrRq1aohvXwogKFEkqQ3rDVr1gxqamraedBBB/2H9tbW1oPGjx+/c9/2pEmTdu7ZsyfWrVt30B9M0onRo0e/nl6GDRu2t62tLSoNND1hKJEk6Q1q/PjxO1988cVBHQPDmDFjdq1Zs2bQvu1nn3120MCBA7O5uXnX8OHD9+zYseP1///v3r2bl19+uRBP4xpKJEl6g5oxY8aro0eP3vXJT36yedu2bQO2b98eCxcuHHr22We//M1vfnPMr3/960GvvPLKgGuuuabp9NNP33rQQQcxZcqUtp07d8bdd999SFtbW3zmM58Zu2vXrorzwKhRo3Y9++yzg9u37dixI7Zv3x6ZGbt27Yrt27fHnj17qj4eQ4kkSW9QDQ0N3H///c8+99xzg8eNGze1qalp6ne+850RV1xxxZazzz77pRkzZrxr/PjxRw8ePDhvv/32FwBGjhy558tf/vILc+bMedvYsWOnDh06dO+YMWN2dvdb+3z605/e+LWvfW3s8OHDj73++uvHAJx88sl/NHTo0Hc/+eSTQ6+++uq3DR069N0PPvjg8GqPJzLrdzn/lpaW9C3BkqT2ImJ5Zrbs2165cuWaY445Zkt/1vRmsnLlylHHHHPM+M76PFMiSZIKwVAiSZIKwVAiSZIKwVAiSZIKwVAiSdL+7d27d2/0dxFvBuX/jl2+H8dQIknS/j29efPmQwwmPbN3797YvHnzIcDTXY0pxApukiQV1e7duy/auHHj7Rs3bpyC/5jvib3A07t3776oqwGGEkmS9mPatGmbgDP6u456YOKT3oQuvPBCDj/8cKZMmdJpf2Yyd+5cJk6cyNSpU1mxYsXrfXfeeSeTJk1i0qRJ3Hnnna+3L1++nKOPPpqJEycyd+5c6nnhRUm9w1AivQldcMEFPPTQQ132P/jggzzzzDM888wz3HbbbVx22WUAvPzyy9xwww0sXbqUJ554ghtuuIGtW7cCcNlllzF//vzX99vf/JJ0IAwl0pvQySefzIgRI7rs/8EPfsDs2bOJCI4//nh++9vfsmHDBh5++GFmzpzJiBEjOOyww5g5cyYPPfQQGzZsYNu2bRx//PFEBLNnz+a+++7ruwOSVBcMJVIdWr9+PUceeeTr283Nzaxfv36/7c3NzX/QLkm1ZCiRJEmFYCiR6lBTUxO/+c1vXt9et24dTU1N+21ft27dH7RLUi0ZSqQ6dMYZZ7BgwQIyk8cff5xDDjmEsWPHMmvWLBYuXMjWrVvZunUrCxcuZNasWYwdO5aDDz6Yxx9/nMxkwYIFfOhDH+rvw5D0JuM6JdKb0HnnnceiRYvYsmULzc3N3HDDDezatQuASy+9lNNOO40HHniAiRMnMmTIEL71rW8BMGLECD73uc/xnve8B4Drr7/+9Rtmb7nlFi644AJee+01Tj31VE499dT+OThJb1pRz2sNtLS05LJly/q7DElSgUTE8sxs6e866pGXbyRJUiEYSiRJUiEYSiRJUiEYSiRJUiEYSiRJUiEYSiRJUiEYSiRJUiEYSiRJUiH0aSiJiJMj4v9ExPqIyIi4oIJ9jo6If46I18r7XR8R0WHMRyLilxHRVv57Vq8dhCRJ6hV9faZkGPA0cAXwWneDI+Jg4MdAK/Ce8n6fBq5qN+YE4B7gH4Fjy3+/FxHvq3HtkiSpF/Xpu28y8wHgAYCIuKOCXc4HhgD/JTNfA56OiHcBV0XETVlaI/9K4GeZ+YXyPl+IiPeX28+r7RFIkqTeUvR7Sk4Afl4OJPs8DDQC49uNWdhhv4eBE3u9OkmSVDNFf0vwEcC6Dm2t7fqeL/9t7WTMEZ1NGBGXAJcANDY2smjRIgAmTJjA8OHDWblyJQAjR45k8uTJLF68GICGhgamT5/OihUr2LZtGwAtLS20trbyVz98R0+OUZJUA58/ZwOrVq0CoKmpiebmZpYuXQrAsGHDaGlpYcmSJbS1tQEwffp0Vq9ezaZNmwCYMmXK633qH/32luCI+D3wqcy8Yz9jFgLrMvPCdm3jgLXAiZm5JCJ2Ahdl5oJ2Y2YD8zNz8P5qqNVbgi+e1+MpJEk9NP/K2szjW4L7T9Ev32wExnRoG9Oub39jNiJJkt4wih5KlgAnRcRb2rXNBF4E1rQbM7PDfjOBx3q9OkmSVDN9vU7JsIg4NiKOLf/2uPL2uHL/lyLikXa7fAfYDtwREVMi4sPAZ4F9T94A3Az8aUR8NiLeFRHXAu8H5vXRYUmSpBro6zMlLcCT5c9bgRvK3z9f7h8LvH7XaGa+QumsRyOwDPgG8DXgpnZjHgPOBS4A/g2YDZyTmUt791AkSVIt9fU6JYuA2E//BZ20PQWc3M289wL39rA8SZLUj4p+T4kkSaoThhJJklQIhhJJklQIhhJJklQIhhJJklQIhhJJklQIhhJJklQIhhJJklQIhhJJklQIhhJJklQIhhJJklQIhhJJklQIhhJJklQIhhJJklQIhhJJklQIhhJJklQIhhJJklQIhhJJklQIhhJJklQIhhJJklQIhhJJklQIhhJJklQIhhJJklQIhhJJklQIhhJJklQIhhJJklQIhhJJklQIhhJJklQIhhJJklQIhhJJklQIhhJJklQIhhJJklQIhhJJklQIhhJJklQIhhJJklQIhhJJklQIhhJJklQIhhJJklQIhhJJklQIhhJJklQIhhJJklQIhhJJklQIhhJJklQIhhJJklQIVYWSiBgQEQPabR8RERdFxJ/UvjRJklRPqj1T8iNgDkBEDAOWAV8FFkXE7BrXJkmS6ki1oaQF+Gn5+4eBbcDhwMXA1ZVMEBGXR8TzEbEjIpZHxEn7GXtHRGQnn1fbjZnRxZh3VXlskiSpH1UbSoYBvy1//yDwT5m5i1JQeUd3O0fEOcDNwBeB44DHgAcjYlwXu1wBjO3weQ74bidjJ3cY90xFRyRJkgqh2lDyAvAnETEUmAX8uNw+Athewf5XAXdk5vzM/FVmzgE2AJd1NjgzX8nMjfs+lILPBGB+J8M3tR+bmXuqPDZJktSPqg0lNwF3AeuA9cDicvvJwFP72zEiBgHTgIUduhYCJ1b4+xcDv8jMxzrpWxYRGyLikYh4f4XzSZKkgmioZnBm/n1ELAeOBH6cmXvLXf8OfK6b3UcBA4HWDu2twAe6++2IOAT4KHBth659Z1r+FRgEfBx4JCJOycyfdzLPJcAlAI2NjSxatAiACRMmMHz4cFauXAnAyJEjmTx5MosXl3JXQ0MD06dPZ8WKFWzbtg2AlpYWWltbqeDKlSSpl23YsIFVq1YB0NTURHNzM0uXLgVg2LBhtLS0sGTJEtra2gCYPn06q1evZtOmTQBMmTLl9T71j8jMvvmhiEZKZ1dOyczF7dqvB87PzHd2s/8nga8BjZn5cjdjHwB2Z+YZ+xvX0tKSy5Ytq/QQunTxvB5PIUnqoflX1maeiFiemS21mU3VqHrxtPLTM7+IiO0RMaHc9pmI+Gg3u24B9gBjOrSPATZW8NMXA9/vLpCULQUmVTBOkiQVRLWLp10JXAfcBkS7rheBT+1v38zcCSwHZnbomknpKZz9/e57gWPo/AbXzhxL6bKOJEl6g6jqnhLgUuDizPxRRNzYrn0FpUdyu3MTcFdEPAE8Wp6vEbgVICIWAGRmx4XYLgGeycxFHScsB6U1wC8o3VPyMeBM4CMVHpMkSSqAakPJ24CnO2nfBby1u50z856IGEnpbMvY8lynZeba8pA/WK8kIoYD5wKf72LaQZRWlW0GXqMUTk7PzAe6q0eSJBVHtaHkOeDdwNoO7acBv6xkgsy8Bbili74ZnbT9jtKibV3N9xXgK5X8tiRJKq5qQ8lfA38XEUMo3VNyQkR8HLgGuLDWxUmSpPpR7Tol34qIBkrLxA+htJDai8DczLynF+qTJEl1otozJWTmfGB+RIwCBmTmptqXJUmS6k3VoWSfzNxSy0IkSVJ96zaURMS/UVqFdWtEPAV0uQRsZk6tZXGSJKl+VHKm5PtAW7vvfbMuvSRJqivdhpLMvKHd97/s1WokSVLdqnaZ+Z9GxKGdtB8cET+tWVWSJKnuVPtCvhmUVlDt6C3AST2uRpIk1a2Knr6JiHe325waEe3f1DsQmAWsr2VhkiSpvlT6SPAySje4JrCwk/7XgDm1KkqSJNWfSkPJ2yktK/8c8F5gc7u+ncCmzNxT49okSVIdqSiUtHuLb7X3oEiSJFWkksXTPgz8MDN3lb93KTP/d80qkyRJdaWSMyX3AkcAm8rfu5KUbnqVJEmqWiWLpw3o7LskSVItGTIkSVIhVHpPSUW8p0SSJB2oSu8pqYT3lEiSpANW1T0lkiRJvcXAIUmSCsF1SiRJUiG4TokkSSoE1ymRJEmFYMiQJEmFUHUoiYh3R8SCiFhW/twVEe/ujeIkSVL9qCqURMT5wL8CY4EHyp8xwBMR8bHalydJkupFJTe6tvcF4HOZ+cX2jRFxLXAj8O1aFSZJkupLtZdvRgPf7aT9e8DhPS9HkiTVq2pDyc+AGZ20zwD+uafFSJKk+lXtC/keBL4UES3A4+W244EPA39Z8+okSVLdONAX8l1S/rT3deCWHlckSZLqki/kkyRJhWDgkCRJhVDtI8FExGHAqcA4YFD7vsz8fI3qkiRJdaaqUBIRxwM/AtooPR68ntJCam3AGsBQIkmSDki1l2++Cvwj0ATsAP6U0hmTZcCXa1uaJEmqJ9WGkqnA32VmAnuAwZnZCnwGHwmWJEk9UG0o2dnueyvwtvL33wONNalIkiTVpWpvdF0BvAdYDSwCboyIMcDHgH+rbWmSJKmeVHum5C+AF8vfrwM2U1o07TD+cDE1SZKkilV1piQzl7X7vpnSo8GSJEk9VvU6JQAR8Q7gj8ubv8zM52pXkiRJqkfVrlMyEvgH4Axg7/9vjvuBCzPzpRrXJ0mS6kS195TcDkwETgLeUv6cDLwdmF/b0iRJUj2pNpTMAi7OzEczc3f58yjw38p93YqIyyPi+YjYERHLI+Kk/YydERHZyeddHcZ9JCJ+GRFt5b9nVXlckiSpn1UbSjYDr3bSvh3o9tJNRJwD3Ax8ETgOeAx4MCLGdbPrZErL2e/7PNNuzhOAeyitNHts+e/3IuJ93dUjSZKKo9pQ8nlgXkQ07Wsof/8alb335irgjsycn5m/ysw5wAbgsm7225SZG9t99rTruxL4WWZ+oTznFyitoXJlxUclSZL6Xbc3ukbEU0C2a3o7sCYi1pe3970H53BK95x0Nc8gYBrw1x26FgIndlPGsogYDPwSuDEzf9au7wRKa6W09zDwqW7mlCRJBVLJ0zf31ui3RgEDKS1P314r8IEu9tl3FuVfgUHAx4FHIuKUzPx5ecwRXcx5RGcTRsQllBd6a2xsZNGiRQBMmDCB4cOHs3LlSgBGjhzJ5MmTWbx4MQANDQ1Mnz6dFStWsG3bNgBaWlpobW0F3tHtwUuSeteGDRtYtWoVAE1NTTQ3N7N06VIAhg0bRktLC0uWLKGtrQ2A6dOns3r1ajZt2gTAlClTXu9T/4jSu/X64IciGoH1wCmZubhd+/XA+Zn5zgrneQDYnZlnlLd3Ahdl5oJ2Y2YD8zNz8P7mamlpyWXLlu1vSEUuntfjKSRJPTT/ytrMExHLM7OlNrOpGge6eNqfAkdRuqzzi8xcVMFuWyi9WXhMh/YxwMYqfn4pcG677Y01mFOSJPWzqm50jYimiHgC+DHwGeCzlC6nLC2fCelSZu4ElgMzO3TNpPQUTqWOpXRZZ58lNZhTkiT1s2rPlPwtpbMdEzPzeYCImAB8u9z3Z93sfxNwVznYPApcCjQCt5bnWgCQmbPL21cCa4BfULqn5GPAmcBH2s15M7A4Ij4L3AecBbwfmF7lsUmSpH5UbSiZCczYF0gAMvO5iJgLPNLdzpl5T3mp+usorTfyNHBaZq4tD+m4Xskg4KtAM/AapXByemY+0G7OxyLiXOBGSo8l/ztwTmYurfLYJElSPzqQe0o6uzO24rtlM/MW4JYu+mZ02P4K8JUK5ryX2j0lJEmS+kG1i6c9Anw9Io7c11BejXUeFZwpkSRJ6kq1oWQuMBR4LiLWRsRaSpdLhpb7JEmSDki1l29eAt4LzAD2vRTvV5n5k1oWJUmS6k/FoSQiBgKvAMdk5o8pPRYsSZJUExVfvim/BG8tpSdiJEmSaqrae0r+J/BXETGqN4qRJEn1q9p7Sq6m9Jbg9RGxDni1fWdmTq1VYZIkqb5UG0rupbQmSfRCLZIkqY5VFEoiYgillVXPBA6itCbJnMzc0nulSZKkelLpPSU3ABcAPwL+F/AB4Ju9VJMkSapDlV6++TDwicy8GyAi/hF4NCIGlp/KkSRJ6pFKz5QcCfx830ZmPgHspvSGX0mSpB6rNJQMBHZ2aNvNgb3QT5Ik6Q9UGioC+HZEtLVrewswPyK272vIzDNqWZwkSaoflYaSOztp+3YtC5EkSfWtolCSmf+1twuRJEn1rdpl5iVJknqFoUSSJBWCoUSSJBWCoUSSJBWCoUSSJBWCoUSSJBWCoUSSJBWCoUSSJBWCoUSSJBWCoUSSJBWCoUSSJBWCoUSSJBWCoUSSJBWCoUSSJBWCoUSSJBWCoUSSJBWCoUSSJBWCoUSSJBWCoUSSJBWCoUSSJBWCoUSSJBWCoUSSJBWCoUSSJBWCoUSSJBWCoUSSJBWCoUSSJBWCoUSSJBWCoUSSJBWCoUSSJBWCoUSSJBVCn4eSiLg8Ip6PiB0RsTwiTtrP2A9HxMKI2BwRv4uIpRFxRocxF0REdvJ5S+8fjSRJqpU+DSURcQ5wM/BF4DjgMeDBiBjXxS6nAD8FTi+PfwD4p06CzHZgbPtPZu6o/RFIkqTe0tDHv3cVcEdmzi9vz4mI/wRcBlzbcXBmXtGh6YaIOB04E/j5fxyaG3uhXkmS1Ef67ExJRAwCpgELO3QtBE6sYqrhwNYObW+NiLURsS4i7o+I43pQqiRJ6gd9eaZkFDAQaO3Q3gp8oJIJIuKTQDNwV7vmVcCFwEpKgeUK4NGIOCYzn+lkjkuASwAaGxtZtGgRABMmTGD48OGsXLkSgJEjRzJ58mQWL14MQENDA9OnT2fFihVs27YNgJaWFlpbW4F3VFK+JKkXbdiwgVWrVgHQ1NREc3MzS5cuBWDYsGG0tLSwZMkS2traAJg+fTqrV69m06ZNAEyZMuX1PvWPyMy++aGIRmA9cEpmLm7Xfj1wfma+s5v9P0IpjJyTmT/cz7iBwP8FfpaZc/c3Z0tLSy5btqzyg+jCxfN6PIUkqYfmX1mbeSJieWa21GY2VaMvb3TdAuwBxnRoHwPs936QiPgzSoFk9v4CCUBm7gGWAZMOvFRJktTX+iyUZOZOYDkws0PXTEpP4XQqIj5KKZBckJn3dvc7ERHAVGDDgVcrSZL6Wl8/fXMTcFdEPAE8ClwKNAK3AkTEAoDMnF3ePpdSILkaWBwRR5Tn2ZmZL5fH/A/gceAZ4GBgLqVQclkfHZMkSaqBPg0lmXlPRIwErqO0nsjTwGmZubY8pON6JZdSqnFe+bPPPwMzyt8PBW4DjgBeAZ4ETs7MJ2p+AJIkqdf09ZkSMvMW4JYu+mbsb7uLff4c+PNa1CZJkvqP776RJEmFYCiRJEmFYCiRJEmFYCiRJEmFYCiRJEmFYCiRJEmFYCiRJEmFYCiRJEmFYCiRJEmFYCiRJEmFYCiRJEmFYCiRJEmFYCiRJEmFYCiRJEmFYCiRJEmFYCiRJEmFYCiRJEmFYCiRJEmFYCiRJEmFYCiRJEmFYCiRJEmFYCiRJEmFYCiRJEmFYCiRJEmFYCiRJEmFYCiRJEmFYCiRJEmFYCiRJEmFYCiRJEmFYCiRJEmFYCiRJEmFYCiRJEmFYCiRJEmFYCiRJEmFYCiRJEmFYCiRJEmFYCiRJEmFYCiRJEmFYCiRJEmFYCiRJEmFYCiRJEmFYCiRJEmFYCiRJEmFYCiRJEmFYCiRJEmF0OehJCIuj4jnI2JHRCyPiJO6GX9KedyOiHguIi7t6ZySJKl4+jSURMQ5wM3AF4HjgMeAByNiXBfj3w48UB53HPAl4OsR8ZEDnVOSJBVTX58puQq4IzPnZ+avMnMOsAG4rIvxlwIvZuac8vj5wJ3A1T2YU5IkFVCfhZKIGARMAxZ26FoInNjFbid0Mv5hoCUiDjrAOSVJUgH15ZmSUcBAoLVDeytwRBf7HNHF+IbyfAcypyRJKqCG/i6gr0XEJcAl5c3fR8Sq/qxHKpBRwJb+LkI6ULf/ec2melvNZlJV+jKUbAH2AGM6tI8BNnaxz8Yuxu8uzxfVzpmZtwG3VVy1VCciYllmtvR3HZLqV59dvsnMncByYGaHrpmUnpjpzJIuxi/LzF0HOKckSSqgvr58cxNwV0Q8ATxK6emaRuBWgIhYAJCZs8vjbwU+FRHzgL8H/gS4ADiv0jklSdIbQ5+Gksy8JyJGAtcBY4GngdMyc215yLgO45+PiNOAv6H0iO+LwNzM/H4Vc0qqjJc1JfWryMz+rkGSJMl330iSpGIwlEiSpEIwlEiSpEIwlEiSpEKouxVdJZVERDMwkdIihHuBVZnZ1UKGktTrfPpGqkMRcRlwIXAM8CrwLLAOeBy4LzNXRcSAzNzbj2VKqjNevpHqTHldny8CP6C0ts8JwJ2UXtkwG/jbiDgqM/dGRPRfpZLqjWdKpDoTEXOAj2Xm+zrpmw58CWgC3puZvqBPUp/xTIlUf3YCwyNiCkBEDI6IQQCZ+S/A+cAO4IP9V6KkemQokerPvZRubL0yIoZnZltm7oyIAQCZ+QLwW6C5H2uUVIcMJVIdKd8j8jKld0XNBF6MiH+IiGnl/nER8THgaOC7/VeppHrkPSVSHYqIQym9APNE4CxKb+AG2EjpEeG7MvMv+6U4SXXLUCLViYg4HPg48N+BLcBrlC7T/AulR4EPorRuyUOZubqfypRUxwwlUp2IiDuAycAPKV3CGUHpMs0fAZuA6zJzab8VKKnuGUqkOlC+l+R3wGmZubhd2zjgfcBFwATgo5m5ot8KlVTXvNFVqg9HAc9TehwYgCxZm5nfBf4zpUs5Z/dPeZJkKJHqxXOULtH8TURM2vf47z6Z2UZpVddT+6M4SQJDiVQXMvM14C+AtwILgNkRcWREDAOIiCHAKcDT/VelpHrnPSVSHSmv4vo54AxKL+JbAmwGPgBsAC7KzKf6r0JJ9cxQItWh8uPBpwNnUlpS/mnge5n56/6sS1J9M5RIdS4iBmTm3v6uQ5IMJZIkqRC80VWSJBWCoUSSJBWCoUSSJBWCoUSSJBWCoUSSJBWCoUSSJBWCoUSSJBXC/wOQgHN+o1mI5gAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "count1 = q.execute(circuit,backend=statevec_sim).result().get_counts()\n",
    "plot_histogram([count1], legend = ['count1'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "93bd91f3-5cfd-4ce4-97f4-4fface69ce67",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (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": {
     "0bf50b260d4d478794112d684e023326": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "1576ca1e51ba49b49aa9c15b6460ce3e": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "95px"
      }
     },
     "16f0994c82ab4200bba39b39f1372d25": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_7eebb1466b984a2996b724c7cd9bd588",
        "IPY_MODEL_8a725d412abb45db8ea91c11e23765dc",
        "IPY_MODEL_e538242d3cfa42129e7f0efc5ac33d68",
        "IPY_MODEL_9731437d561b469abdc2f61936635c22",
        "IPY_MODEL_affb04e97f2041149ce98eb1818f5bc5"
       ],
       "layout": "IPY_MODEL_2633ba667e5f4eeabde931be9fc82e09"
      }
     },
     "19189e26e9674f61a848fed50481195e": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HTMLModel",
      "state": {
       "layout": "IPY_MODEL_bb4a8f18ccc047f49deca2c2352e8bc7",
       "style": "IPY_MODEL_26c9c680663f45c68823ddf3e6860c47",
       "value": "<p style='font-family: IBM Plex Sans, Arial, Helvetica, sans-serif; font-size: 20px; font-weight: medium;'>Circuit Properties</p>"
      }
     },
     "2499e5c3155b4101b3184145b5d3edc7": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "GridBoxModel",
      "state": {
       "children": [
        "IPY_MODEL_ca24f2dc34894d45b9ef291e5abab367"
       ],
       "layout": "IPY_MODEL_a735ba409765421b9fdb09a4c538818a"
      }
     },
     "2633ba667e5f4eeabde931be9fc82e09": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "margin": "0px 0px 0px 37px",
       "width": "600px"
      }
     },
     "26c9c680663f45c68823ddf3e6860c47": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "28acbb0dace24fea91fd879196694038": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "44e9789c19714b578533f9378cc81128": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonStyleModel",
      "state": {}
     },
     "5fe423958aa94635b4cd83c2187c879c": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "6f1e234c9baf480fba4fbfb2ef3a0483": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "7060fc5fa5dc4386afb0807d4060ce80": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "70px"
      }
     },
     "7bf6c6227ed84bd4a02db48a565cdd29": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "190px"
      }
     },
     "7eebb1466b984a2996b724c7cd9bd588": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HTMLModel",
      "state": {
       "layout": "IPY_MODEL_7bf6c6227ed84bd4a02db48a565cdd29",
       "style": "IPY_MODEL_28acbb0dace24fea91fd879196694038",
       "value": "<h5>Job ID</h5>"
      }
     },
     "8a725d412abb45db8ea91c11e23765dc": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HTMLModel",
      "state": {
       "layout": "IPY_MODEL_e8e6968abb7f466e82eae958d7a8053d",
       "style": "IPY_MODEL_cf2db1d76e524fde94def20ac98cfd2e",
       "value": "<h5>Backend</h5>"
      }
     },
     "9731437d561b469abdc2f61936635c22": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HTMLModel",
      "state": {
       "layout": "IPY_MODEL_7060fc5fa5dc4386afb0807d4060ce80",
       "style": "IPY_MODEL_0bf50b260d4d478794112d684e023326",
       "value": "<h5>Queue</h5>"
      }
     },
     "a735ba409765421b9fdb09a4c538818a": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "grid_template_areas": "\n                                       \". . . . right \"\n                                        ",
       "grid_template_columns": "20% 20% 20% 20% 20%",
       "width": "100%"
      }
     },
     "affb04e97f2041149ce98eb1818f5bc5": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HTMLModel",
      "state": {
       "layout": "IPY_MODEL_5fe423958aa94635b4cd83c2187c879c",
       "style": "IPY_MODEL_6f1e234c9baf480fba4fbfb2ef3a0483",
       "value": "<h5>Message</h5>"
      }
     },
     "bb4a8f18ccc047f49deca2c2352e8bc7": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "margin": "0px 0px 10px 0px"
      }
     },
     "c7fb55f4324e4ba8a50f0ff54aa7f9c9": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "ca24f2dc34894d45b9ef291e5abab367": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ButtonModel",
      "state": {
       "button_style": "primary",
       "description": "Clear",
       "layout": "IPY_MODEL_e9c827408ab04b4e9f3e5eb2ac9b2ebf",
       "style": "IPY_MODEL_44e9789c19714b578533f9378cc81128"
      }
     },
     "cf2db1d76e524fde94def20ac98cfd2e": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "e538242d3cfa42129e7f0efc5ac33d68": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HTMLModel",
      "state": {
       "layout": "IPY_MODEL_1576ca1e51ba49b49aa9c15b6460ce3e",
       "style": "IPY_MODEL_c7fb55f4324e4ba8a50f0ff54aa7f9c9",
       "value": "<h5>Status</h5>"
      }
     },
     "e8e6968abb7f466e82eae958d7a8053d": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "width": "145px"
      }
     },
     "e9c827408ab04b4e9f3e5eb2ac9b2ebf": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "grid_area": "right",
       "padding": "0px 0px 0px 0px",
       "width": "70px"
      }
     }
    },
    "version_major": 2,
    "version_minor": 0
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}