Bernstein_Vazirani_Algorithm.ipynb

{
  "cells": [
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "trusted": true
      },
      "outputs": [],
      "source": "%matplotlib inline\n# Importing standard Qiskit libraries and configuring account\nfrom qiskit import QuantumCircuit, execute, Aer, IBMQ\nfrom qiskit.compiler import transpile, assemble\nfrom qiskit.tools.jupyter import *\nfrom qiskit.visualization import *\n# Loading your IBM Q account(s)\nprovider = IBMQ.load_account()"
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "trusted": true
      },
      "outputs": [],
      "source": "from qiskit import *\nfrom qiskit.tools.visualization import *"
    },
    {
      "cell_type": "code",
      "execution_count": 47,
      "metadata": {
        "trusted": true
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": "Enter the secret number: 111\n"
        },
        {
          "data": {
            "image/png": 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cqSlTptzwXE5OjuLj41WtWjVJ0qBBg/TUU0/pv/7rv/ySxV8/AM8s8v03X252huo3bquQsOqG6SdztqtR64r9Bc0P9PduNr6ul5yc7HW+5ORksyKZonhs2fV7XS8qRj/9/YFy53FLOnVRqhfVWhdOHg5IrsrC7uPainVfoH8Wnnv1rZL3Lf3YSkFBQXrzzTclSVOnTtXmzZt9el3pE1I+/vhj/fSnP1VGRob69u2rn/zkJ/r73/9umN/qz9OJ3D7+JUxBlKcgSp5T70u7fPmy0tPTNXjw4JJpvXv3Dmg2K+RmZ+hcbpbe+nmkYfq1/Dx1f+h5i1IBtyYoJMwv86LyYd1nnoEDByomJkaHDh3SrFmzfHrN9eWw+JjDF154Qe+8846SkpJuKIjwHwqipMhIz8pg//79evDBB0umz5w5U8ePHw/oCSq+NvuKmrzY93lzD23RXY++rPZ9njRMX/x8R0VVcAuivz4fJ9q718t+Tnm2oowfP77ceWbPnm1WJFMUjy27fq/zr0kvLJOuFZY/X1iIlJuzT2GsFSvE7uPainVfoH8WfvXa2yXvW/pxIF2/JW/06NGSpPnz56uw0MsPn8ouh5LnHIFZs2bprrvuUmxsrA4c+H6PgF3XO5UBq0JJ0dHRSkhI0IwZMxQREaFmzZopNTVVq1atkqQqdQbzuW+ylH/prFolDFTtBs2N0789p6joHhamq/ymTZtmdYRKp1qo1KO1tDnLeIJKaS5JPaNFOfQTJ4xr1n3m6tmzpyRp9erVXuctrxxKnr15aWlpeuSRR9SjRw9DQYT/cJKKPMdKpKSkKD4+XhMnTtSYMWMUGRmppKQkBQcHl5ygUhXkZmcopFpNNWzZyTD9+IFNCm/QQjXrNrIoWdXANb78Y2CCVLempwhezyWpXk1pYIebPAlTOGFcs+4zT82aNdWmTRvl5+dr9+7d5c7rrRwW27p1qyRVqd/HVuPv5e+0bdtW69evN0wbPXq04uLiVKNGDYtSBV5udoaiWvdQULBxaBzP2lzh3cuouPbt22vPnj1Wx6h06taQJg+UUr6Qdh/7fkuiS1KH5tKwHlLtqvNjHnBOGNes+8wTFBSk+fPnq6CgoNzdy2FhYVqzZo1P1zncvHmzFixYoMzMTH/FxnUoiOXYsmWLevXqZZj24osv6i9/+YtOnjypHTt2aPLkyUpPT1ebNm0sSmmuvj+5+XFA946ZF+AkgLnq1ZR+1k86kye98r5n2ktDpfq1rEwFu2DdZ568vDxNnDjR63xXr17VpEmTNHHiRA0bNqzc6xyuW7dO69atMzMmvGAXcxny8vK0f//+Gy6QPX36dB09elT5+fk6ffq0jh49WmnKIVAVRIR//5hyCFjrgw8+0A9/+EMugm1DbEEsQ3h4uE9nXgFm6tevn9URANMxrgHnYQsiYCPz5rE7C5UP4xpwHgoiYCO+HLcDOA3jGnAeCiJgI2lpaVZHAEzHuAach4IIAAAAAwoiAAAADCiIgI3Y/WLCwK1gXAPOQ0EEbGTp0qVWRwBMx7gGnIfrIFYRc0ZZnQC+mDp1qiPuWwtUhJXjmnVfYLjdbu8zXedXr70tSXr1ufGGx7AHtiACAADAgIIIAAAAAwoiYCNz5861OgJgOsY14DwURMBG4uPjrY4AmI5xDTgPBRGwkcTERKsjAKZjXAPOQ0EEAACAAQURAAAABhREwEZ69OhhdQTAdIxrwHkoiICNZGRkWB0BMB3jGnAeCiIAAAAMKIgAAAAwoCACNpKammp1BMB0jGvAeSiIAAAAMKAgAjYybNgwqyMApmNcA85DQQQAAIBBiNUBEBiTF1vzvnNGWfO+ACBZs+5jveccLpcr4O/pdrsD/p63gi2IgI0kJSVZHQEwHeMacB4KImAjkyZNsjoCYDrGNeA8FETARvr27Wt1BMB0jGvAeSiIgI2cPHnS6giA6RjXgPNQEAEAAGBAQQRsJC4uzuoIgOkY14DzcJkbwEaWLVtmdQTAdIxrVBa1atVShw4dVKdOHV27dk1ZWVk6evRomfPfddddql27ttatWxfAlOZgCyJgIy+99JLVEQDTMa7hZPXr19eUKVO0fft2XbhwQZ999pk++ugjrV+/XkeOHFFubq7+9Kc/qUuXLobX3XXXXVqzZo1Wrlypzp07WxP+NlAQSykqKtKsWbMUGxur6tWrq1OnTkpPT1e7du00fvx4q+OhCkhJSbE6AmzodJ60bpe0MlNK2yNduGx1oophXMOpfvazn+nw4cOaPXu2EhISVFhYqG3btmnt2rXasGGDzpw5o0aNGmncuHHKzMzU0qVLFRkZWVIO69atq5UrV2rHjh1WfyoVRkEsZezYsZo+fbomTJig1atXa8SIERo5cqSys7PVrVs3q+MF1IJJTbVz/QLDNLfbrXnj6igrY4VFqYCq5VqhtGiTNP196YNt0r/3SO9lSi+vkN77Uioqsjph5cO6D5JUo0YNvffee3r77bdVp04dffzxxxo6dKhq166tLl26aMCAAerbt68aNGig+Ph4JScnKy8vT8OHD9e+ffu0bt061a1bV++++65GjRqlwsJCqz+lCuMYxO8sWbJECxcuVFpamhITEyVJ/fv3V2ZmppYvX66uXbtanDBw8s4c06Vzx9WwVWfD9PMnsnX1ykVFRXe3JhhQhbjd0t8+lXYcufG5IreUttfz/6P8OJqGdR8kKTQ0VO+9954GDBigM2fOaOLEiVq6dGmZ8+/evVu/+MUv9Ic//EGpqanq3t0zTtauXevYciixBbHEjBkzNGjQoJJyWCwmJkahoaFKSEjQ2bNnNWTIELVt21adOnXSgAEDlJWVZVFi/8nNzpArKFgNmncwTD+Vs10160apdoMWFiWr/NLT062OAJs4fOrm5bC0T/Z5dj/bnVPGNes+SNLUqVM1YMAA5ebm6u677y63HJbWuHFjxcbGlnwcExOj6tWr+yum31EQJR09elQ7d+7U8OHDb3guJydH8fHxqlatmlwulyZPnqz9+/dr+/btGjJkiMaMGWNBYv/Kzc5Q/cZtFRJmHNgnc7arUWv+gvanXbt2WR0BNvH5Qcnlw3wZ2X6PctucMq5Z96Fz58567rnnVFRUpEcffVR79+716XWljzlcunSpMjMz1bp1a/32t7/1c2L/YRezVHKKeuPGjQ3TL1++rPT0dA0ePFiSVK9ePd1///0lz/fu3VszZ840NYvL5cuvhIp7ZpHb53lzszN0LjdLb/080jD9Wn6euj/0fIXe11+fjxNNmTLF6zzJycle50tOTjYrkimKx5aTvtdOyDz0l/9Syw4PyBVU9t/xRYUF+v0bf9XgBeMCmMzI7uPainVfoMfVc6++VfK+pR/bnR1z//KXv1RISIhef/11bdq0yafXlC6HxcccxsfHa+vWrRo/frymTZum06dPl8xv9efodvv2M0FBlBQZ6VkZ7N+/Xw8++GDJ9JkzZ+r48eNlnqAyZ84cDR06NBARAyr30Bbd9ejLat/nScP0xc93VBR/RQMBkX/5vNwqkqucHT0ul0v5l88HMFXlxrqvamvYsKEee+wxFRYW6ne/+51Pr7lZOSwsLNRXX32lVatWlexpnDVrlp/Tm4+CKCk6OloJCQmaMWOGIiIi1KxZM6WmpmrVqlWSdNOCOG3aNGVlZenf//63qVl8bfYVNXmxb/Od+yZL+ZfOqlXCQNVu0Nw4/dtzioruUaH39dfn40S+7KpITk72ekml2bNnmxXJFMVjy0nfaydk3pYjLdxQ/jyuoGD9bc4vdMeiXwQm1E3YfVxbse4L9Lj61Wtvl7xv6cd2Z4fcpbfm3XPPPQoLC9O6devKvfh1sbLKYbG//e1vGjJkiO677z5DQXTC90biGERJUlBQkFJSUhQfH6+JEydqzJgxioyMVFJSkoKDg5WQkGCY/9e//rU++OAD/etf/1LNmjUtSu0fudkZCqlWUw1bdjJMP35gk8IbtFDNuo0sSlY1TJs2zeoIsImOzaWGtcs+DtElqU0jqVWDQKa6NU4Y16z7UHy1ks8//9zrvN7KoSR98cUXkm6+kckJ2IL4nbZt22r9+vWGaaNHj1ZcXJxq1KhRMm3atGlatWqV1q5dq3r16gU4pf/lZmcoqnUPBQUbh8bxrM3sYgmAESNGWB0BNhEcJP38Xmnux8YzlV2S3JKaR0hj7pEccKiZI8Y16z40a9ZMknTw4MFy5/OlHErSf/7zHxUUFKhhw4YKCQlRQUGBX3L7CwWxHFu2bFGvXr1KPt61a5defvlltWnTRv369SuZvm3btsCH85O+P7n5bp57x8wLcJKqqX379tqzZ4/VMWATDcKl537o2d38j82eaXHNpJ7RUofmnhLpBE4Y16z7MGHCBE2ePFlXrlwpd77IyEjVqFHDp4tgR0VF6cqVK44rhxIFsUx5eXnav3+/nn766ZJp8fHxjjl2AEDlEBbiKYTFBfFn/SyNA1RaV69e1dWrV73O9+GHH6pPnz7KzMz0ehHsM2fOmBUv4CiIZQgPD3fs1c8BAID/ZGRkWB3B7xyygwKoGkofugBUFoxrwHkoiICNzJvH8U6ofBjXgPNQEAEbmThxotURANMxrgHnoSACNpKWlmZ1BMB0jGvAeSiIAAAAMKAgAgAAwICCCNiI3S8mDNwKxjXgPFwHsYqYM8rqBPDF0qVLHXFbMqAirBzXrPtQnore/OJXr70tSXr1ufGGx5URWxABG5k6darVEQDTMa4B56EgAgAAwICCCAAAAAMKImAjc+fOtToCYDrGNeA8FETARuLj462OAJiOcQ04DwURsJHExESrIwCmY1wDzkNBBAAAgAEFEbCRHj16WB0BMB3jGnAeCiJgIxkZGVZHAEzHuAach4IIAAAAAwoiAAAADCiIgI2kpqZaHQEwHeMacB4KIgAAAAwoiICNDBs2zOoIgOkY14DzUBABAABgEGJ1AARG2NrVlrzv1QcG39brJy82KUgFzBkV+PcEAMBO2III2EhSUpLVEQDTMa4B56EgAjYyadIkqyMApmNcA85DQQRspG/fvlZH8NmVa9LhU99//G2+dVl8VeSWci98/3HuBc80u7tU6mt7+JTna+8kThrXADw4BhGwkZMnT1odoVznL0ufZUlfHpZOXDA+93+pUoNwqUsrqXeMFBFuScQbFBVJu7+WNh2QDp6Q8gu+f+63/5SqhUhtGkl3x0rtm0pBNvmz+XSeJ/O2HM/jYnPWSC5JDetI3e+QesVIdWpYldI3dh/XAG5EQQTgVWGRtG6X9NFOz+OynM7zzPfxLqlfe2lwghRm4Vom57S0ZLN0/HzZ8+QXeArk7q+lJvWkJ34gtYgIWMQbXC2QVm2X0vdKZW3cdMtT0Fd9Ja3ZKQ3qKN0bJwXbpNwCcD4KImAjcXFxVke4Qd4V6e00T9nylVvS+j3Snq+lCf2l+rX8la5s6Xul9zMrtgv5+Dkp+V/SI92ke9r5LVqZTudJb62/cetseQqLpA+3SzuPST9LlMKr+y/frbLjuAZQPv7eBGxk2bJlVkcwuJQvvbmuYuWwtG/OS2+slc59a24ub9L2Siu+vLXjC4vc0rIt0if7zM9VnrOXpD+urVg5LO0/p6S5H0vfXjU3lxnsNq4BeEdBBGzkpZdesjqCQcoX5e+elTzXjSzv2pFnLkmLNwXuZJBDJ6X3vyx/Hm+ZJWnFFk/pCoQit/T3T6Wz5RRpXzJ/fU5K/cLUaKaw27gG4B0FEbCRlJQUqyOU2J7jOUHCDAdypc0HzFlWeQoKpSWflX3sXkW4Jf1jc/nHXJrl0/1StknncWT+R9pxxJxlmcVO4xqAbyiIpRQVFWnWrFmKjY1V9erV1alTJ6Wnp6tdu3YaP3681fECxn35sq4N/7GKPtn4/bT8fBVMflYFr/xG7qIA/Ma8RQsmNdXO9QsM09xut+aNq6OsjBUWpXIet1tau9PcZa7b7Tmj2J+2H7n1XbQ3k3vB/2WrsEj6eLe5y1y7y9zlAah6KIiljB07VtOnT9eECRO0evVqjRgxQiNHjlR2dra6detmdbyAcdWooaBhj6lw8T/kdrvlLixU4a9/K4WGKvhXv5TLLtcBuU7emWO6dO64GrbqbJh+/kS2rl65qKjo7tYEc6Cc09LRs+Yu8+wlz0kr/vTpfvOXudHPWz53HzP/GM2c09KRWzxuFAAkzmIusWTJEi1cuFBpaWlKTEyUJPXv31+ZmZlavny5unbtanHCwAr60UMqSl0u94ZPVZSxRe5TpxQya6ZcYaFWRytTbnaGXEHBatC8g2H6qZztqlk3SrUbtLAome/S09OtjiBJ2v+Nn5abK8U398+yrxZIh/xwzGD2CelaoRQabP6yJT9+rb+RWjTwz7Iryi7jGoDv7LkpyAIzZszQoEGDSsphsZiYGIWGhiohIUGSNHToUCUkJKhLly7q2bOn1q1bZ0Vcv3PVqK6g4Y+pcNZsub/6SiEzpstVq6bVscqVm52h+o3bKiTMeJ2Pkznb1ai1M7Ye7tplj32DR874abl+3Kp17Kxn17jZitzS1yZvTS3Nb19rPy33VthlXAPwHVsQJR09elQ7d+7UlClTbnguJydH8fHxqlatmiRp4cKFqlevniRp69at6tevn86cOaPgYHM2L7hcLlOWc73Qj1bd2guvXFHw4yPkql//ll5+u5/PM4t8/42fm52hc7lZeuvnkYbp1/Lz1P2h531ejr++BzcbX9dLTk72Ol9ycrJZkco04uXNahLTyzDN2xm0N3t+8mLjx5k7D8o1MOY2091cTM9h+uH/GE+GuJXM0o257xv8iA5uee/Ww5VjzJzDqhPZyqdc5T13feZVazdqTN97bjOdd04a15XVc6++Jcmz7ir92O6cmNuJma/n9vEvaQqiPAVRkho3bmyYfvnyZaWnp2vw4MEl04rLoSSdP39eLpfL5y+2kxSt+7eK3l0q18ABKlzxvlyDB9r+hyD30Bbd9ejLat/nScP0xc93VJRDtiDahUv++V77cwz5d3z6Mbe/lm3zn1cA9kZBlBQZ6dnitH//fj344IMl02fOnKnjx4/fcIJKUlKSVq9erfPnz2vZsmUKCTHvy+ivshm2drXP8xZ9kaHCP76p4Fdelis2VgVPjpH7kw1yJfat8Pve7udz/VaRspz7Jkv5l86qVcJA1W7Q3Dj923OKiu7h83v663uwd+9er/MkJyd7PWN+9uzZZkUq09vrPbeeK62s70XxFi1fvlcd20f77et7INdzUe/SzMgsSWs+XK42jW49W3lmrZaOXrc7+Ga5Kpp5wL13a+k0///x6qRxXVn96rW3JXnWXaUf250Tczsx862iIEqKjo5WQkKCZsyYoYiICDVr1kypqalatcqzW/b6gvjmm29K8hx4PWXKFH3yyScKDw8PeG5/KNq1W4UzXlXw/z6roISOkuQ5FnHRErnu6WPbM5hzszMUUq2mGrbsZJh+/MAmhTdooZp1/fTb3WTTpk2zOoIkqXnEjQXRrOX6S/NbOwrCK5cfl63vln19QTRluRbeT/p6dhnXAHxnz9/2ARYUFKSUlBTFx8dr4sSJGjNmjCIjI5WUlKTg4OCSE1Sul5iYqKCgIH366acBTuwf7kOHVfjSywqe8DMF3d27ZHrQj4ZI58/L/ckGC9OVLzc7Q1Gteygo2Pg3z/GszY7avTxixAirI0iS37aWtWnon+VKUo0wqakfilyzCKmaH0/ed+LXuqLsMq4B+I4tiN9p27at1q9fb5g2evRoxcXFqUaNGpKkvLw8nT59Wq1aeQ4o37p1qw4ePKj27dsHPK8/uFrfodBlS2+cXr26Qpf+w4JEvuv7k5vvnrp3zLwAJ7k97du31549e6yOodjGUoNw6XSeecusVU1KaGne8m6md4yUmmH+Mv2pU0tp+ZfSZRPvodywttQmyrzl3S67jGsAvqMglmPLli3q1ev7MzkvXbqkxx9/XHl5eQoJCVH16tW1aNEitWzp5996QIAFuaT+7c0tW/e09d+1BIt1by39a4eUd8Wc5dWuLnW7w5xllSUsxPO1+cjEO9f0b+/5HgLAraIgliEvL0/79+/X008/XTItKipKn332mYWpgMDpHStlHjbnHsFN6kr3x9/+crypHiqN6Cn9+RNzlvf4Xf7dvVzsgQ6e+16bcZvAmCipl5+3egKo/CiIZQgPD1dhYaHVMVDF9OvXz+oIJYJc0qje0pw10sVytsh5O6u2eqg0+m4pxM9bD4sltJD6tJU2lnPbPV/OBO7bTurgp7u+XC80WHrybumP66Qr124+jy+Z69aQnuhlv62HdhrXAHzDSSqAjcybZ69jJhuES0n3S/Vu8SY6NcOkp+/zz8kj5Xm0u9Qn9tZff087aWiAb7/ePEL6+b2er9mtqFdTevp+KcKGF1Sw27gG4B0FEbCRiRMnWh3hBo3rSv/7YMWPxYtvJj03RGppwf2Ag1zSYz08W+VqVaBwhVeTnrpHeqy7NVvh7oiUfvlDKa5pxV7Xo7X0ywelqDr+yXW77DiuAZSPXcyAjaSlpVkd4aZqVfPsJi7edbstRyosunG+IJdnt2yftlJslLU383C5pK53SO2aSJ8flDYdkE6VcVZ2ZG3p7lipZ7Tnc7VSvZrSz/pJ+7/xfK13HfPcD/p6IUFS55ZSn3aeYmlndh3XAMpGQQTgs9YNPf9G9pK+Pid9c166WuA5vrBxXalpPc9ZuXZSq5p0b5znzN5z30pHzkgXL0tySXWqSy0aeI7ds9Od6VwuT7Ft18Tz9T12Vsq9IBUUer6+TepKTeoF7rhOAFWPzVblAJwgJNiz69iK3ce3yuWS6tfy/HOSsJDvizkABArHIAI2wsWEURkxrgHnoSACNrJ06Y13sgGcjnENOA+7mKuIqw8MtjrCLZkzyuoEgTV16lTuW4tKh3ENOA9bEAEAAGBAQQQAAIABBRGwkblz51odATAd4xpwHgoiYCPx8fFWRwBMx7gGnIeCCNhIYmKi1REA0zGuAeehIAIAAMCAgggAAAADroMIBMidd97pdZ6pU6f6NB9gF4xroHJiCyJgIy+//LLVEQDTMa4B56EgAgAAwICCCAAAAAMKIgAAAAwoiAAAADCgIAIAAMCAgggAAAADCiIAAAAMKIjw2YABA9S5c2d17NhRw4YN04ULF6yOBAC4TWlpaYqPj1dMTIzGjRunwsJCqyN59cwzz6h58+YKCXHO/T6OHDmi++67T+3bt1d8fLyef/55qyOVi4IIn6WkpGjbtm3asWOHmjdvrtmzZ1sdCQBwG4qKijRu3DilpKQoKytLFy5c0KJFi6yO5dXw4cO1ZcsWq2NUSEhIiF577TXt2bNHW7du1caNG/X+++9bHatMFET4rG7dupI8K5QrV67I5XJZnAgAcDsyMjLUtGlTxcXFSZLGjh2rZcuWWZzKuz59+qhx48ZWx6iQJk2aqHv37pKksLAwdenSRTk5ORanKpvL7Xa7rQ4B53jkkUe0YcMGdezYUf/85z8VHh5udSQAqFKKior012VrdCHvW0nS8ROnJUlNGjUwPC7Wu2u8enS6+b2wly1bpuXLl2vx4sWSpD179uiJJ57Q1q1bTc+9bXeW0j/fXvJxeblr1aiup4YPUkhwcLnLDAkJUUFBgelZi129VqA/L12l/KvXvGaWpPv7dFN87B1el3vmzBl17txZH330kW3vU84WRFTIihUr9PXXX6t58+ZKTU21Og4AVDlBQUHq1L6Njp84XVJSJN3w+PiJ07p46Vsl3Bld5rICuY0oPvYOXb6S71PuDu1aey2HgRAWGqL2MS19ylxQUKg7o1t6XebVq1c1bNgwPfPMM7YthxIFEbcgLCxMP/7xj7VixQqrowBAldQ5PlYtmjT0Ot/Avj1UrVpYmc+3aNFCR44cKfk4JydHzZs3NyXj9UJDQzS4311e54uKrF/mFk8r3N2toyLq1fY635B7eyk4uPxaVVhYqCeeeEKdO3fWs88+a1ZEv6AgwicXL17U8ePHJXl2b6xcuVLx8fEWpwKAqinI5dKQ+3qXO0/TqAbq1qFtufN0795dR48e1e7duyVJ77zzjh599FHTcl4v4c5otWoWVe48D93XW8FB9qknISHBerB/r3Lnadu6hdq18b71cPz48apdu7Z+//vfmxXPb+zzHYCtXbx4UT/60Y+UkJCghIQEFRQU6IUXXpAU2F0UAACPVs2i1Kl9mzKfH3LvDxTkpWgFBwdrwYIFGjZsmNq0aaPw8HCNHj3a7KglXC6Xhtz3gzKfbx/TSjF3NPO6nAkTJqh58+YqLCxU8+bNlZSUZGbMG8TH3qHolk1u+lyQy6Uf3lt+gZSkTz/9VH/+85+1ZcsWdenSRZ07d9brr79udlTTcJIKbtvO/Ye06cudGvnQfaodXtPqOABQZZy7kKdZf3pXBQXGaxd2aNtaP3nkAYtSebf0w/XK3HnAMC04KEhTxg5XZERdi1KV7+vcU3pj4XJdX5p+0DVeDz9wtyWZ/IktiBXw/vvva8iQIWrUqJGqVaumVq1a6YknntCOHTusjmaZIrdbH3+aqQt536pmzepWxwGAKqVenXD17dnJMC04OEgP9vd+rJ+VBvXtqdBQ40Wuf9At3rblUJKaRkWqe4Lx2Mga1avp/j7dLErkXxREHxQUFGjUqFEaOnSoduzYoUcffVTPPPOMunTpomXLlunYsWNWR7TM7gOHdfzEad3Xu6utjhkBgKoi8a5OqlNq7809PRIUUa+OhYm8q1O7lvr16lzycc0a1XRf767WBfLRgL7dVS0stOTj++/uplo1KufGEXYx+2DixImaP3++Jk2apOTkZMOtfY4ePaq6deuqdm3vZzj54levvW3KcgAAAK736nPjfZrPOTcxtMiGDRs0f/58DRo0SK+//voNdw/x1+UAAAAArMIWRC8ee+wxLV++XNu2bVOnTp28v6CKKHK79cbC5bpWUKApY4ezexkALHby9Dk1qF/H65nLduJ2u3Xy9Dk1iqxvdZQKyT11VlEOy1xRFEQvateurcjISB06dCgg78cuZgAA4C++7mJ2zp8ZFjh37pzy8vJ0xx13WB0FAAAgYNiCWI6zZ88qIiJCcXFx2rVrl9VxbGPn/kNatGKtHh/SX13iY62OAwAATMYWxHLUr19f0dHR2rNnj9atW3fD8/v27bMglbWKr3sYGVFXCeVcwR8AADgXZzF78dvf/laPP/64Bg8erIcfflht2rTRiRMntGnTJsXFxWnFihVWRwyoS99eVnBQkPpy3UMAACotdjH7YM2aNfrd736njIwMXblyRY0aNVLPnj01efJk3XPPPVbHCzi32y23PPefBAAAlQ8FEQAAAAbsIwQAAIABBREAAAAGFEQAAAAYUBABAABgQEEEAACAAQURAAAABhREAAAAGFAQAQAAYEBBBAAAgAEFEQAAAAYURAAAABhQEAEAAGBAQQQAAIABBREAAAAGFEQAAAAYUBABAABgQEEEAACAAQURAAAABhREAAAAGFAQAQAAYEBBBAAAgAEFEQAAAAYURAAAABhQEAEAAGBAQQQAAIABBREAAAAGFEQAAAAY/H8hVZm4SP43hAAAAABJRU5ErkJggg==\n",
            "text/plain": "<Figure size 840.392x325.08 with 1 Axes>"
          },
          "execution_count": 47,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": "n = 3\nsecretnumber = input(\"Enter the secret number: \")\ncircuit = QuantumCircuit(n+1,n)\nfor i in range(n):\n    circuit.h(i)\ncircuit.x(n)\ncircuit.h(n)\ncircuit.barrier()\nsecretnumber = secretnumber[::-1]\nfor q in range(n):\n    if secretnumber[q] == '0':\n        circuit.i(q)\n    else:\n        circuit.cx(q, n)\ncircuit.barrier()\nfor j in range(n):\n    circuit.h(j)\nfor k in range(n):\n    circuit.measure(k,k)\ncircuit.draw()"
    },
    {
      "cell_type": "code",
      "execution_count": 42,
      "metadata": {
        "trusted": true
      },
      "outputs": [
        {
          "data": {
            "image/png": 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\n",
            "text/plain": "<Figure size 504x360 with 1 Axes>"
          },
          "execution_count": 42,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": "backend = BasicAer.get_backend('qasm_simulator')\nresult = execute(circuit,backend,shots=1).result()\ncounts = result.get_counts()\nplot_histogram(counts)"
    },
    {
      "cell_type": "code",
      "execution_count": 50,
      "metadata": {
        "trusted": true
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": "Job Status: job has successfully run\n"
        }
      ],
      "source": "provider = IBMQ.get_provider(hub='ibm-q')\nprovider.backends()\nreal_device = provider.get_backend('ibmq_london')\nproperties = real_device.properties()\ncoupling_map = real_device.configuration().coupling_map\nfrom qiskit.providers.aer.noise import NoiseModel\n\nnoise_model = NoiseModel.from_backend(properties)\nfrom qiskit.tools.monitor import job_monitor\njob = execute(circuit, backend=backend, shots=1)\njob_monitor(job, interval = 2)"
    },
    {
      "cell_type": "code",
      "execution_count": 51,
      "metadata": {
        "scrolled": true,
        "trusted": true
      },
      "outputs": [
        {
          "data": {
            "image/png": 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\n",
            "text/plain": "<Figure size 504x360 with 1 Axes>"
          },
          "execution_count": 51,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": "\nresults = job.result()\nanswer = results.get_counts()\n\nplot_histogram(answer)"
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "trusted": true
      },
      "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": "3.7.8"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 4
}