Quantum Adder.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import qiskit as qk"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Gate Functions\n",
    "Running this import adds each of the gates to the QuantumCircuit class.\n",
    "* QFT, iQFT\n",
    "* PhiADDa (No control, Single control, double control)\n",
    "* PhiADDaModN\n",
    "* CMULTaModN\n",
    "* Cua"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import customGates"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def init_reg(circ, q, val):\n",
    "    \"\"\"Initializes qubit register to value with NOT gates.\"\"\"\n",
    "    for i in range(len(q)):\n",
    "        if val & (1<<i):\n",
    "            circ.x(q[i])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Create simple 4 bit adder circuit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<qiskit.circuit.instructionset.InstructionSet at 0x7fb6590baa90>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "b = qk.QuantumRegister(5, 'b')\n",
    "res_b = qk.ClassicalRegister(5, 'res\\_b')\n",
    "\n",
    "\n",
    "circ = qk.QuantumCircuit(b, res_b)\n",
    "\n",
    "# Add 20 + 10\n",
    "a = 15\n",
    "init_reg(circ, b, 10)\n",
    "\n",
    "circ.qft(b, 5)\n",
    "circ.PhiADDa(a, b, 5)\n",
    "circ.iqft(b, 5)\n",
    "circ.measure(b, res_b)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Simulate the circuit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAdAAAAFWCAYAAADZtMzFAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDMuMC4zLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvnQurowAAHKpJREFUeJzt3XuYXXV97/H3l4FIcoSQxGkyg0YzqDgH6RASqkaBiMQK9ngUfAAvRbDKAREviBrPsVas6PPEG1SLCNWiaIHipVobCoSkYgGBXNBgbDQUk0ouShKQRmJC/J4/9opuhpnM3r/MZU/m/Xqe/cxev/Vba3/XH+TDuv1+kZlIkqTm7DfSBUiSNBoZoJIkFTBAJUkqYIBKklTAAJUkqYABKklSAQNUkqQCBqgkSQUMUEmSCuw/0gWMpClTpuT06dNHugxJUgu59957H8rM9oH6jekAnT59OosXLx7pMiRJLWTy5MlrG+nnJVxJkgoYoJIkFTBAJUkqYIBKklTAAJUkqYABKklSAQNUkqQCBqgkSQUMUEmSChigkiQVMEAlSSpggEqSVMAAlSSpgAEqSVIBA1SSpAIGqCRJBQxQSZIKGKCSJBUwQCVJKmCASpJUwACVJKmAASpJUgEDVJKkAgaotA96+9vfznOf+1zmzJnT5/rMZP78+cyaNYuXvOQl/PCHP/z9umuvvZbZs2cze/Zsrr322t+333vvvbz4xS9m1qxZzJ8/n8wc8uOQWpkBKu2DXv/613PDDTf0u37RokXcf//9LF26lM985jO85z3vAWDr1q0sWLCAW265hUWLFrFgwQIefvhhAC666CIuvfRSli5dyv3338+iRYuG5VikVmWASvugOXPmMGnSpH7XL1y4kDPOOIOI4JhjjuHXv/41GzduZPHixcydO5dJkyZxyCGHMHfuXG699VY2btzIo48+yjHHHENEcMYZZ7Bw4cJhPCKp9Rig0hi0YcMGDj300N8vd3Z2smHDBtavX/+k9vXr17NhwwY6Ozuf1F8aywxQSZIKGKDSGNTR0cGDDz74++X169fT0dFBZ2fnk9o7Ozvp6Ohg/fr1T+ovjWUGqDQGnXTSSVx33XVkJvfccw8HH3ww06ZN44QTTmDJkiU8/PDDPPzwwyxZsoQTTjiBadOmcdBBB3HPPfeQmVx33XWcfPLJI30Y0ojaf6QLkDT43vKWt3D77bezefNmjjjiCObPn8/jjz8OwNlnn828efO45ZZbmDVrFuPHj+dzn/scAJMmTeKiiy7iZS97GQDvfe97f/8w0ic+8QnOP/98tm/fzoknnsiJJ544MgcntYgYy+9yzZw5MxcvXjzSZUiSWsjkyZOXZebsgfp5CVeSpAIGqCRJBQxQSZIKGKCSJBUwQCVJKmCASpJUwACVJKnAsAZoRBwXEd+JiAcjIiPirAa2OTIivhcRj1XbfSgiolefUyNiVUT8tvr7miE7CEmSGP4z0KcC9wHvBB4bqHNEHAzcAmwCjqm2ey9wYV2fFwHXA18Djqr+3hARLxjs4iVJ2m1Yh/LLzIXAQoCIuLqBTd4ATADelJmPAfdFxPOACyPi01kbRuldwJLMvKTa5pKIeGnV/rrBPgZJkqD174G+CPh+FZ673QR0As+q63Nzr+1uAuYMeXWSpDGr1QeTnwb8olfbprp1D1R/N/XRZ1pfO4yIc4BzoDal0/Lly4HaBMETJkxgzZo1AEycOJGuri5WrFgBQFtbGz09PaxevZpt27YB0N3dzZYtW7hs0fP36iAlSXvv/X+2hrVr1wLQ3t5Oe3s7q1atAmD8+PF0d3ezcuVKdu7cCUBPTw/r1q1j69atAHR1dbFjx46Gf6/VA3TQZeaVwJVQG0z+6KOPfsL6gZYPP/zwJywfeuihQ1ClJKlZU6ZMYcqUKU9o6/1v+JFHHvmE5RkzZjBjxoyi32v1S7gbgam92qbWrdtTn41IkjREWj1A7wSOjYgD69rmAeuBn9f1mddru3nAHUNenSRpzBru90CfGhFHRcRR1W9Pr5anV+s/HhG31m3yD8BvgKsj4vkRcQowH9j9BC7AZcAJETE/Ip4XER8AXgpcOmwHJkkac4b7DHQ2sKL6jAcurr5/pFrfARy2u3NmPkLtbLITWAr8LfAp4NN1fe4AzgDOAn4EnAmcnpl3De2hSJLGsuF+D/TfgNjD+rP6aFsJHDfAfr8OfH0vy5MkqWGtfg9UkqSWZIBKklTAAJUkqYABKklSAQNUkqQCBqgkSQUMUEmSChigkiQVMEAlSSpggEqSVMAAlSSpgAEqSVIBA1SSpAIGqCRJBQxQSZIKGKCSJBUwQCVJKmCASpJUwACVJKmAASpJUgEDVJKkAgaoJEkFDFBJkgoYoJIkFTBAJUkqYIBKklTAAJUkqYABKklSAQNUkqQCBqgkSQUMUEmSChigkiQVMEAlSSpggEqSVMAAlSSpgAEqSVIBA1SSpAIGqCRJBQxQSZIKGKCSJBUwQCVJKmCASpJUwACVJKmAASpJUgEDVJKkAk0FaEScFhEvr1v+UET8IiJuioiOwS9PkqTW1OwZ6Id3f4mIo4H/C/wNcADwqUZ2EBFvi4gHImJ7RCyLiGP30PfqiMg+Ptvq+sztp8/zmjw2SZIatn+T/Z8JrK6+vwb4p8xcEBE3AzcNtHFEnA5cBrwN+Pfq740R8T8zc10fm7wTmN+r7Xbgtj76HgFsqVv+1UD1SJJUqtkz0O3AQdX3lwGLqu+P1LXvyYXA1Zl5VWb+JDMvADYA5/XVOTMfycyNuz/AYUAXcFUf3X9Z3zczdzVxXJIkNaXZAP0+8KmI+EtgNrCwan8u8F972jAixgGzgJt7rboZmNPg778V+HFm3tHHuqURsSEibo2Ilza4P0mSijR7CfftwOeB1wLnZub6qv0kBr6E+zSgDdjUq30TcOJAPxwRE4HTgA/0WrX7DPYeYBzw58CtEXF8Zn6/j/2cA5wD0NHRwfLlywHo7OxkwoQJrFmzBoCJEyfS1dXFihUrAGhra6Onp4fVq1ezbVvtFmx3dzdbtmwBJg1UviRpiG3evJm1a9cC0N7eTnt7O6tWrQJg/PjxdHd3s3LlSnbu3AlAT08P69atY+vWrQB0dXWxY8eOhn8vMnOQD6GfH4roBB4Ejs/M2+raPwS8ITMPH2D786k9qNSZmVsG6LsQeDwzX7WnfjNnzszFixc3egj9et+XDVBJGmkL3rR1UPYzefLkZZk5e6B+Tb8HGhEHRsRrI+L9EXFI1XZYREweYNOHgF3A1F7tU4GNDfz0W4FvDBSelbuA5zTQT5KkIs2+B/ps4D+AK4BLgN2heR6wYE/bZuYOYBkwr9eqeUBf9zTrf/dPgB76fnioL0dRu7QrSdKQaPYe6KXUHvo5D3i4rv07wN83sP2ngWsi4m5qr6OcC3RSC2Qi4isAmXlmr+3OAX6Wmf/We4cR8S7g58CPqd0DfSPwauDUBo9JkqSmNRugc4AXZuauiKhvX0ctCPcoM6+PiCnAB4EO4D7g5MxcW3WZ3nubiDgIOAP4SD+7HQd8Ang68Bi1IH1lZi7sp78kSXut2QCF2qhDvU2n9i7ogDLzcuDyftbN7aPtUeCpe9jfAga4fCxJ0mBr9iGim6kNhrBbRsTBwMXAvwxaVZIktbhmz0AvBJZExGrgQOB64NnU3uU8bZBrkySpZTUVoJm5PiKOAl4HHE3tDPZK4GuZ+dgQ1CdJUktq+h5oFZRfqj6SJI1JAwZoRJwC/HNm7qy+9yszvzlolUmS1MIaOQP9OjAN+GX1vT9JbaxbSZL2eQMGaGbu19d3SZLGsmaH8jsuIp4UuhHRFhHHDV5ZkiS1tmbPKJfwh/Fv6x1SrZMkaUxoNkCD2r3O3qYA2/a+HEmSRoeGXmOJiO9UXxP4akT8tm51G/B8BphRRZKkfUmj74Furv4GsJXaoO277QD+ncanGpMkadRrKEAz82yAiPg58MnM9HKtJGlMa3Yov4uHqhBJkkaTRkYi+hFwfGZujYiV9P0QEQCZ+ceDWZwkSa2qkTPQbwC7Hxra00hEkiSNGY2MRHRxX98lSRrLHJpPkqQCjdwD3eN9z3reA5UkjRWNzsYiSZLqNHUPVJIk1XgPVJKkAr4HKklSAd8DlSSpgO+BSpJUoKmxcHeLiMOA7mrxJ5l5/+CVJElS62sqQCNiCvBF4FXA7/7QHN8F3pyZm/vdWJKkfUizT+H+HfBs4FjgwOpzHDAD5wOVJI0hzV7C/VPgZZl5Z13b7RHxf4BFg1eWJEmtrdkz0F8BfU2m/RvAy7eSpDGj2QD9CHBpRBy6u6H6/qlqnSRJY0LJYPIzgJ9HxIPV8qHAduCPqN0jlSRpn+dg8pIkFXAweUmSCjiYvCRJBZoK0IgYFxEXR8RPI2J7ROyq/wxVkZIktZpmz0D/GngTtadufwe8F/hbaq+wvG1wS5MkqXU1G6CnAedm5heAXcC3M/MdwF8B8wa7OEmSWlWzAToVWFV9/2/gkOr7vwIvH6yiJElqdc0G6Dqgs/q+htrQfgAvAh4brKIkSWp1zQbot4CXVd8vAy6OiAeAq3EQBUnSGNLUYPKZ+YG671+PiF8Ac4CfZuZ3B7s4SZJaVdGE2rtl5g+AHwxSLZIkjRpND6QQEUdHxFciYmn1uSYijh6K4iRJalXNDqTwBuAeoANYWH2mAndHxBsHvzxJklpTs5dwLwH+MjM/Vt8YER8APgp8dbAKkySplTV7Cbcd+Mc+2m+gNp3ZgCLibRHxQDUU4LKIOHYPfedGRPbxeV6vfqdGxKqI+G319zVNHZUkSU1qNkCXAHP7aJ8LfG+gjSPidGqvv3wMmAncAdwYEdMH2PQIapeNd39+VrfPFwHXA18Djqr+3hARLxioHkmSSjUyofYpdYs3Ah+PiNn84enbFwKnAB9u4PcuBK7OzKuq5Qsi4hXAecAH+t+MX2bmQ/2sexewJDMvqZYviYiXVu2va6AmSZKaVjqh9jnVp95ngcv720lEjANmAZ/stepmau+S7snSiHgKtWEEP5qZS+rWvaj67Xo3AW/vp47f197R0cHy5csB6OzsZMKECaxZswaAiRMn0tXVxYoVKwBoa2ujp6eH1atXs23bNgC6u7vZsmULMGmA8iVJQ23z5s2sXbsWgPb2dtrb21m1qjb67Pjx4+nu7mblypXs3LkTgJ6eHtatW8fWrVsB6OrqYseOHQ3/XiMTag/WnKFPA9qATb3aNwEn9rPNBmpnp/cA44A/B26NiOMz8/tVn2n97HNaXzvMzCuBKwFmzpyZRx/9xDdwBlo+/PDDn7B86KGH9lO6JGk4TZkyhSlTpjyhrfe/4UceeeQTlmfMmMGMGTOKfm+vBlIYapm5Glhd13RnRDyL2jRq3+9rG0mShkPJQAqvjIjbIuKhiPhVRHwvIk5uYNOHqE2BNrVX+1RgYxMl3AU8p2554yDsU5KkpjQ7kMJbqA0ofz/wfmA+8ADwrYh48562zcwdwDKePG/oPGpP4zbqKGqXdne7cxD2KUlSU5q9hPt+4MLM/Fxd2xcjYhm1MP3SANt/GrgmIu4GbgfOpTY92hUAEfEVgMw8s1p+F/Bz4MfU7oG+EXg1cGrdPi8DbouI+cA/Aa8BXgq8pMljkySpYc0G6HRqk2f3diNPfrr2STLz+oiYAnyQ2vuc9wEnZ+bauv3XGwd8Ang6tflGfwy8MjMX1u3zjog4g9pISB+hdnZ8embe1cyBSZLUjGYDdB21y6NrerW/HFj75O5PlpmX08/rLpk5t9fyAmBBA/v8On2/biNJ0pBoNkA/CXy2mn1l9z3GF1N7veSCwSxMkqRW1uyE2l+IiF8C76E2+hDAT4DTMvPbg12cJEmtquEAjYj9qV2qvS0zvzV0JUmS1Poafo0lMx8HvgkcNHTlSJI0OjQ7kMIPgWcPRSGSJI0mzQboh4FPRcSrI+IZETG5/jME9UmS1JKafQr3X6q/3wSyrj2q5bbBKEqSpFbXbIC+dEiqkCRplGkoQCNiArURgV4NHAAsAt6xh0muJUnapzV6D/Ri4Cxql3CvpTYa0eeHqCZJklpeo5dwTwH+IjOvA4iIrwG3R0RbZu4asuokSWpRjZ6BPoO6Cawz827gcWozqUiSNOY0GqBtwI5ebY/T/ENIkiTtExoNwAC+GhG/rWs7ELgqIn6zuyEzXzWYxUmS1KoaDdAv99H21cEsRJKk0aShAM3Ms4e6EEmSRpNmh/KTJEkYoJIkFTFAJUkqYIBKklTAAJUkqYABKklSAQNUkqQCBqgkSQUMUEmSChigkiQVMEAlSSpggEqSVMAAlSSpgAEqSVIBA1SSpAIGqCRJBQxQSZIKGKCSJBUwQCVJKmCASpJUwACVJKmAASpJUgEDVJKkAgaoJEkFDFBJkgoYoJIkFTBAJUkqYIBKklTAAJUkqcCwB2hEvC0iHoiI7RGxLCKO3UPfUyLi5oj4VUQ8GhF3RcSrevU5KyKyj8+BQ380kqSxalgDNCJOBy4DPgbMBO4AboyI6f1scjywGHhl1X8h8K0+Qvc3QEf9JzO3D/4RSJJUs/8w/96FwNWZeVW1fEFEvAI4D/hA786Z+c5eTRdHxCuBVwPff2LX3DgUBUuS1JdhOwONiHHALODmXqtuBuY0sauDgK292sZHxNqI+EVEfDciZu5FqZIkDWg4z0CfBrQBm3q1bwJObGQHEXE+8HTgmrrm1cCbgR9SC9d3ArdHRE9m/qyPfZwDnAPQ0dHB8uXLAejs7GTChAmsWbMGgIkTJ9LV1cWKFSsAaGtro6enh9WrV7Nt2zYAuru72bJlCzCpkfIlSUNo8+bNrF27FoD29nba29tZtWoVAOPHj6e7u5uVK1eyc+dOAHp6eli3bh1bt9bOybq6utixY0fDvxeZOciH0M8PRXQCDwLHZ+Ztde0fAt6QmYcPsP2p1ILz9Mz85z30awPuBZZk5jv2tM+ZM2fm4sWLmziKvr3vywaoJI20BW/qfXGyzOTJk5dl5uyB+g3nQ0QPAbuAqb3apwJ7vH8ZEa+lFp5n7ik8ATJzF7AUeE55qZIk7dmwBWhm7gCWAfN6rZpH7WncPkXEadTC86zM/PpAvxMRAfwxsKG8WkmS9my4n8L9NHBNRNwN3A6cC3QCVwBExFcAMvPMavkMauF5EXBbREyr9rMjM7dUff4K+AHwM+Bg4B3UAvS8YTomSdIYNKwBmpnXR8QU4IPU3te8Dzg5M9dWXXq/D3outRovrT67fQ+YW30/BLgSmAY8AqwAjsvMu4fiGCRJguE/AyUzLwcu72fd3D0t97PNu4F3D0ZtkiQ1yrFwJUkqYIBKklTAAJUkqYABKklSAQNUkqQCBqgkSQUMUEmSChigkiQVMEAlSSpggEqSVMAAlSSpgAEqSVIBA1SSpAIGqCRJBQxQSZIKGKCSJBUwQCVJKmCASpJUwACVJKmAASpJUgEDVJKkAgaoJEkFDFBJkgoYoJIkFTBAJUkqYIBKklTAAJUkqYABKklSAQNUkqQCBqgkSQUMUEmSChigkiQVMEAlSSpggEqSVMAAlSSpgAEqSVIBA1SSpAIGqCRJBQxQSZIKGKCSJBUwQCVJKmCASpJUwACVJKmAASpJUgEDVJKkAgaoJEkFhj1AI+JtEfFARGyPiGURcewA/Y+v+m2PiP+MiHP3dp+SJO2tYQ3QiDgduAz4GDATuAO4MSKm99N/BrCw6jcT+Djw2Yg4tXSfkiQNhuE+A70QuDozr8rMn2TmBcAG4Lx++p8LrM/MC6r+VwFfBi7ai31KkrTXhi1AI2IcMAu4udeqm4E5/Wz2oj763wTMjogDCvcpSdJe238Yf+tpQBuwqVf7JuDEfraZBizqo//+1f6i2X1GxDnAOdXif0+ePHl1I8VLY8DTgIdGugip1N+9e9B29cxGOg1ngLaEzLwSuHKk65BaTUQszczZI12HNFoMZ4A+BOwCpvZqnwps7Gebjf30f7zaXxTsU5KkvTZs90AzcwewDJjXa9U8ak/O9uXOfvovzcydhfuUJGmvDfcl3E8D10TE3cDt1J6y7QSuAIiIrwBk5plV/yuAt0fEpcAXgBcDZwGva3SfkhrmrQ2pCcMaoJl5fURMAT4IdAD3ASdn5tqqy/Re/R+IiJOBz1B7LWU98I7M/EYT+5TUgOr5AEkNiswc6RokSRp1HAtXkqQCBqgkSQUMUEmSChigkiQVMEAlSSpggEp6gojw3wWpAf6HIgmAiOgAyMzf1bU96d+IiIjhrEtqVQaoJCLiFcB3IuKjEfGKiDgE/hCmUXNgRBycvjwuAQ6kIAmIiIXA0cBPgXHAfwFLgduoxp6OiJOAyzNzxshVKrUOA1Qa4yJiAvA9auNN30VtLt1jgacDO4CfUZvY4fXALzPztBEqVWopBqg0xkXENOAiYFVmfqlq24/a5A0vB/4E+COgB3hBZt4zUrVKrcQAlURE/A+AzNwWEQdk5s66dROozXr0isx81giVKLWc4Z7OTFILqoIzqu87q+9twK7M/E1EvBj47ogWKbUYn8KVxriIOLh6hSUi4qkRsV/WPJ6ZGREHUrtH+skRLlVqKV7ClcawiHg9cDa1J3AT+AGwELg1M1ePZG1Sq/MMVBqjIuI44GPABuCNwHuoXbb9DLAoIs6v6+u/FVIvnoFKY1RE/CPwcGae06t9AvA+4ALg0sz865GoT2p1PkQkjV3jgF27FyLiKcDvMvM3wIers84zIuKazPz5CNUotSwvy0hj1w3AaRExByAzf1s9gdtWrb8UmAB0jFSBUiszQKUxqHpN5dvAzcDCiPiHiDg1Ig7JzF3V2eefAk/LzDtHtFipRXkPVBrDqgEUzgb+N7XRhh4HHqH2MNFU4LrM/PCIFSi1MANUGsMi4imZ+dtqOL/jgCOAZwBPAT4HLMvMHSNZo9SqDFBpjImIbuBCYCbwn8ADwO3AbZn58EjWJo0mBqg0hkTEYdQGSthELTSfR+0hofHAGuDzmblo5CqURg8DVBpDIuLz1KYpe31mPlq1TQVOAt4MzAYuyMwvjlyV0ujgU7jS2PJMYHlmPhoRbRHRlpmbMvPqzDwO+Dzw1mowBUl7YIBKY8tNwNkR8bzM3FW9sjIuIsZV679I7enbF4xcidLoYIBKY8t3gM3AjRHxZoDM3FH3pO1+wKHAXSNUnzRqeA9UGmMi4iDg48AbgAOoDaawCHg+8BLg3sw8c+QqlEYHA1QaI6rRh/arLtseCBxJ7d3PE6hNZ/YA8FXgm5m5ceQqlUYHA1Qaw6pxb39XTZw9MTMfGemapNHCe6DSPi4iDoiI51azrTxBZu6q+254Sk0wQKV93/nACuCKiPhfETGtbsYVqrPPgyPipIg4YOTKlEYXL+FK+7iIuBPYTm3+3znAOuBbwDeBlZn5SEScC5yVmS8cuUql0cUzUGkfFhHtwE7gqsw8ltpACl8E/gy4DVgcEe8H3oWvrkhN8QxU2odFRAdwBrAqM2/qtW4m8JZq/STgGZn54PBXKY1OBqi0j4uI8dRudW6vXmWBqqFafwlwcmbOHKkapdFo/5EuQNLQyszHdgdn9vo/5mrM21OBvx+J2qTRzDNQaR8VEQcDj/YOzV59DgROB6514mypOQaotI+KiC8Ad1eftZn56z76HOIk2lIZA1TaB0XE64CvAb8GtgC3AP8K/AhYX13WHQ9cB/y/zLxvxIqVRikDVNoHRcRVwC5gAXAK8CbgMGA1sBC4FTgcuCwzx/W3H0n9M0ClfUxE7A+8Dzg4M+fXtR8BvBV4LXAgcAjw5cz8ixEpVBrlDFBpHxQRk4Cpmfkf1WTZO+sfJoqI04FrgaMz896RqlMazXyNRdoHZeZWYGv1fQdAROxH7X+adwEHA9sNT6mcASqNEZn5u7rFg4C/GqlapH2Bl3ClMaiadWVXr1CV1AQDVJKkAs7GIklSAQNUkqQCBqgkSQUMUEmSChigkiQV+P/nStw2qiqokAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from qiskit.tools.visualization import plot_histogram\n",
    "sim_backend = qk.BasicAer.get_backend('qasm_simulator')\n",
    "\n",
    "job = qk.execute(circ, sim_backend)\n",
    "result = job.result()\n",
    "counts = result.get_counts(circ)\n",
    "plot_histogram(counts)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Simulate the circuit with noise"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "qk.IBMQ.load_accounts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from qiskit.providers.aer import noise\n",
    "\n",
    "device = qk.IBMQ.get_backend('ibmqx2')\n",
    "properties = device.properties()\n",
    "coupling_map = device.configuration().coupling_map\n",
    "\n",
    "# Generate an Aer noise model for device\n",
    "noise_model = noise.device.basic_device_noise_model(properties)\n",
    "basis_gates = noise_model.basis_gates\n",
    "\n",
    "\n",
    "# Perform noisy simulation\n",
    "backend = qk.Aer.get_backend('qasm_simulator')\n",
    "job = qk.execute(circ, backend,\n",
    "                  coupling_map=coupling_map,\n",
    "                  noise_model=noise_model,\n",
    "                  basis_gates=basis_gates)\n",
    "result = job.result()\n",
    "counts = result.get_counts(circ)\n",
    "plot_histogram(counts)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Run the circuit on the real device"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Job Status: job is queued (60)      "
     ]
    }
   ],
   "source": [
    "from qiskit.tools.monitor import job_monitor\n",
    "device = qk.IBMQ.get_backend('ibmqx4')\n",
    "\n",
    "job = qk.execute(circ, device)\n",
    "job_monitor(job)\n",
    "result = job.result()\n",
    "counts = result.get_counts(circ)\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": "3.6.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}