Trabalho_qiskit5.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 279,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import math\n",
    "from numpy.random import randint\n",
    "\n",
    "from qiskit import *\n",
    "from qiskit import QuantumCircuit, QuantumRegister, ClassicalRegister, execute, BasicAer, IBMQ, Aer\n",
    "\n",
    "from qiskit.visualization import plot_histogram, plot_bloch_vector, plot_bloch_multivector\n",
    "from qiskit.extensions import Initialize\n",
    "\n",
    "from qiskit.quantum_info import partial_trace\n",
    "\n",
    "from qiskit.tools.monitor import job_monitor\n",
    "from qiskit.quantum_info.analysis import average_data\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 280,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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iMAWAiMEUACIGUwCIGEwBIGIwBYCIwRQAIgZTAIgYTAEgYjAFgIjBFAAiBlMAiBhMASBiMAWAiMEUACIGUwCIGEwBIGIwBYCIwRQAIgZTAIgYTAEgYjAFgIjBFAAiBlMAiBhMASBiMAWAiMH+D0a+Glepe8p2AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 321.232x204.68 with 1 Axes>"
      ]
     },
     "execution_count": 280,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q = QuantumRegister(2)\n",
    "c = ClassicalRegister(2)\n",
    "qc = QuantumCircuit(2,2)\n",
    "\n",
    "qc.h(0)\n",
    "qc.cx(0,1)\n",
    "qc.z(0)\n",
    "qc.x(1)\n",
    "\n",
    "\n",
    "\n",
    "qc.draw(output='mpl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 281,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 501.832x204.68 with 1 Axes>"
      ]
     },
     "execution_count": 281,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "measureZZ = QuantumCircuit(2, 2)\n",
    "#z  \n",
    "measureZZ.ry(3*math.pi/4,1)\n",
    "measureZZ.measure(0, 0)\n",
    "measureZZ.measure(1, 1)\n",
    "bellZZ = qc+measureZZ\n",
    "\n",
    "bellZZ.draw(output='mpl')\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 282,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYkAAACoCAYAAAAVWhKaAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAZV0lEQVR4nO3de1xUdeL/8dcMIIJAmaxX1LygIQgoaGoqIG5lfisrL1m5fb3RKo9WTWtryTT7WXah1X5rbpq3Lm6/9V5a3+9WK5RpFy1Iza94S9DIvAspAjPz/YMfJMoR0Jk5M/B+Ph7zcDjzmXPewwN4+znnzBmLw+FwICIiUgWr2QFERMRzqSRERMSQSkJERAypJERExJBKQkREDKkkRETEkEpCREQMqSRERMSQSkJERAypJERExJBKQkREDKkkRETEkEpCREQMqSRERMSQSkJERAypJERExJBKQkREDKkkRETEkEpCREQMqSRERMSQSkJERAypJERExJBKQkREDKkkRETEkEpCREQMqSRERMSQr9kB6qM12+DIKXO23aox3BtvzrbNMHXPD2QXFJiy7ZjgYNI7dzFl22aYPHkyWVlZbt9ubGwsc+fOdft26wuVhAmOnIL9v5idon7ILijgs1MnzY5RL2RlZZGZmWl2DHEy7W4SERFDKgkRETGkkhAREUMqCRERMaSSEBERQyoJERExpFNgRcQ0wcHBREVFERQURHFxMTk5OeTn5xuOT0pKoqioiK1bt7oxZf2mkhARt/rd737HmDFj+MMf/kCXLpe/2TA/P581a9awYMECdu3aVbF8wIABfPDBB9hsNuLi4ti7d687Y9dbKglxqcMnYedhKC6F0GDofiM09DM7lZjBarUyadIkZs+eTUBAAAAXLlxg165dnDhxgoCAAKKiomjRogWpqamkpqaydOlSpkyZQlxcHB988AGBgYEsWrSIffv2mfxq6g+PLgm73c6rr77KG2+8QV5eHp07d+a1114jJSWFhIQEFi5caHZEt1j1fxJpEzWQnkOertFyT1BYBMs3w96jlZev3Q53doP+nc3JVR37jp3Y0p65/AGbDUpK8El/CWvXKPcH83IhISGsWbOG5ORkADZu3Mj8+fP55JNPKCkpqRhnsViIjo4mJSWFMWPGMHr0aAYPHkxwcDABAQEsWrSIRx55BIfDYdZLqXc8uiTGjBnD2rVrmT59OnFxcWzZsoWRI0dy7NgxHnvsMbPjiYHiUnj9U8g/ffljJbaya1f5WOCWTu7PVh1r1yis76+ptMxRXIxt6hNw/fVYIuvPtZicJTAwkI8++og+ffrw888/M378eDZs2FDlWIfDQXZ2NqmpqcybN4+1a9dW7JJauXKlCsIEHnt204oVK1i+fDnvv/8+06ZNIykpibS0NHr37k1paSlxcXEAHD16lFtvvZXAwEBiYmL47rvvTE4u3/4IP52GK/0qb8guKwxvYEv/K47iYnyeegKL1WN/ZTzWyy+/TJ8+fTh06BC9evUyLIhLhYWFceONN1Z8HRERgZ+f9lW6m8f+xL/wwgvcfvvtJCQkVFresWNH/Pz86Nq1KwATJkzgpptu4sSJE6SmpjJ06FBsNi/561NHbd0PlmrGnC+GXYfdEuea2N5ZgeO7bHxnzcASGGh2HK/Tv39/Jk6cSHFxMXfddReHDh2q0fPKD1IHBgaydOlS9uzZQ1RUFGlpaS5OLJfyyJI4fPgwO3fuZNiwYZc9lpubS2RkJP7+/hQUFLBx40aeeeYZAgICSElJwWaz8eWXXzolh8ViccktMzOj1lm+Xj+bBSnXV7r9lLO51uvJzMxw2esqv+3ae+SKs4hyYyZMdXmWjIzaf6/L2T/7HPt7/8Rn5nQszZrV+vkZGa7/XnvSraorwD755JMAzJkzh++//75G37eLC2LRokWMHTuWsWPHAjBp0iQaNWpUaXxmZqbpr90bbzXlsSUB0Lx580rLz58/T2ZmZsWupr1799KkSRNCQ0MrxnTt2pUffvjBfWHdpOfdaUxYeLrSrWWnvmbHqlLxuTM47Pbqx50/44Y0V8eek4Pt5VfxmTIJa5cIs+N4pXbt2jFo0CDOnz/PvHnzavScSwui/BjEF198webNm7nuuusYOXKki5PLxTyyJMr/6Ofk5FRa/tJLL5Gfn0/37t0B+PXXXwkJCak0JiQkhMLCQqfkcDgcLrklJCQ6Jd/VSEhIdNnrKr89MKhLtfvurRb48qM3XZ4lMTGx1t8jx/Hj2GY8h/W+e7AmJ13ldxoSE13/vfak26W7hpOSyr53GzZs4OTJ6j/Tw6ggyr399tsAFWdIlUtISDD9tXvjraY88uym9u3bEx0dzfPPP88NN9xAq1atWLVqFR9++CFAxUyiUaNGFFzyqWNnz54lKCjI7ZnlN306QuZuKCoxPnjdpyMENXRrrBpxFBVhmzELS8RNWB8eZXYcr1b+e/r1119XO7a6ggD46quvKq1X3MMjZxJWq5WVK1cSGRnJhAkTGD16NKGhoaSmpuLr60t0dDQA4eHhHD9+nBMnTlQ8d+fOnVW+i1PcJyQAHhkADRtUXl6+F7Rraxjiob/njs1f4Ni7D8c32yi9+z5K7rq30s3+6SazI3qNli1bArB///4rjqtJQQAVb6ArX6+4h0fOJAA6derEpk2VfyFHjRpFRERExbs1g4ODGTx4MM899xxz5szhnXfewWKx0KtXLzMiu8zQpzNqtdwT3BgK0++Crw/Cuu1ly2Lbls0gOjaDWhw3cyvrwGSsA5OrHyjVGjFiBIGBgZw7d+6K45o2bYq/v3+1b5T79ddfadKkCUVFRa6IKwY8tiSqsm3btssKYMGCBTz00EM0btyY8PBwVq9ejY+Pj0kJ5WKB/pB4028l8bBnHmcXFykuLqa4uLjace+99x4HDx7k66+/rnZfeU2ObYhzeU1JFBYWkpOTw8SJEystb9asGR9//LFJqUTEGcqPN4jn8ZqSCAoK0pvkRETczCMPXIuIiGdQSYiIiCGVhIiIGFJJiIiIIZWEiIgYUkmIiIghrzkFti5p1bh+btsMMcHB9XLbZoiNja31cw7k5gPQvk2LSvddvV2pOYujNpcDFLkKk98t+3fug+bmEM/z5Itln1M/588ple6L59DuJhERMaSSEBERQyoJERExpJIQERFDKgkRETGkkhAREUMqCRERMaSSEBERQyoJERExpJIQERFDKgkRETGkkhAREUMqCRERMaRLhUudNnXPD2QXFJiy7ZjgYNI7d6n18/b8Gwp+cUGgGghuCp0HmLNtM0yePJmsrCxTth0bG8vcuXNN2XZtqCSkTssuKOCzUyfNjlErBb/A6cNmp6gfsrKyyMzMNDuGR9PuJhERMaSSEBERQyoJcakz53+7n3cSSmzmZRGR2tMxCXG6I6dgcw7sOgJnLyqJ9I/Aain7nO2e7aFHe2joZ15OEameSkKcprAIVn0DWbnGY+yOshlF3kn4MBvuiYce7cBicV/OumLqgkR2H9qKj48fVqsPzRu344HkNBJihpkdTeoQlYQ4xY/H4c3MsqKoqfMlsGIr/HAEHuoDvj6uy1dXPThwOg8OfBqbrZT1W/7GCyseoGOrbrQK7Wh2NKkjdExCrlnuCVjwae0K4mJZubD0c7DZnZurPvHx8WXQzeOx2UvZ/5M55/2Lseuuu87sCFdNMwm5JkUlZX/gL5Qaj5n7YNm/k981HrPrCHy6C27t6tx89UVJaTEbtiwAICy0k8lp6q5+/foxcOBA4uLiCAsLw2KxcOzYMb799ls+++wzPvroI2y2ymdnDB8+nL///e8MHjyYrVu3mpT86qkk5JpsyIJTvzpnXf+9A7q2hhbXO2d99cGKT2ezMvMVzl8owMfHj8eGvUn7ltEAzH53JIkxI7glaggAM5YNYUjfP9GtYz16S7WT3H///aSlpREVFVXl48nJyTz++OMcPnyYv/71r8ybNw+bzcbw4cN599138fX1JSkpyStLwqN3N9ntdl555RXCw8Np2LAhMTExZGZm0rlzZ1JSUsyOV+8VFMHWfc5bn80Bm3Y7b331wQPJaax77jSrZh6n5013kLXv3xWPTbx7Hm/9awbnigr4fMcaggNvUEHUUpMmTVi3bh3/+Mc/iIqKIj8/n/T0dIYPH063bt2IjY3lzjvv5Nlnn2XPnj2EhYWRnp7O1q1bmTRpUkVBzJo1i+eff97sl3NVPHomMWbMGNauXcv06dOJi4tjy5YtjBw5kmPHjvHYY4+ZHa/e+2q/848jfPsj3N0dGvk7d7015SgpofTRKVi7xeDzyPiK5ba167CvXovvG69jadTInHBXEBzYmMeGvcnDczqwZed6+kTdTeOgptzbbwrz1/+JA/nZvJjyidkxvUrTpk3JyMggIiKCM2fO8Pjjj7Ns2TJKSkoqjcvOzmbDhg3MnDmTwYMH8/rrr9OjRw/i4+OxWCzMmjWLGTNmmPQqrp3HziRWrFjB8uXLef/995k2bRpJSUmkpaXRu3dvSktLiYuLA2DGjBl06dIFq9XKqlWrTE5dv+T87Px1ltrhx2POX29NWfz88H3ycewbPsT+XdkBYMfBH7EvWY7PE9M8siDKhQTewH39HmPJf/0Fu72svW/r8Z8cOb6XIbf8iZDAG0xO6D38/PzYuHEjERER7Nixg6ioKBYtWnRZQVxq48aNPPPMM9jtdiwWC4WFhfztb39zU2rX8NiSeOGFF7j99ttJSEiotLxjx474+fnRtWvZEc7w8HDmzZtHz549zYhZbzkccNhF183LNfl6fJYb22Id8zC2l1/FcfIkpXNewnr3nVijPf+o+j39JnHybD4fb3+rYlnLJh11Smwt/eUvfyE+Pp6DBw+SnJzM4cM1u+Li8OHDefPNN7FarRw6dIigoCDmz5/v4rSu5ZG7mw4fPszOnTuZMmXKZY/l5uYSGRmJv3/Z/oiHHnoIgNmzZzs9h0Xv8DLk6x9I6uLKR6zLz2IyYvT4pWc9pb+2iDsWO+eYk8/Lc7DGRNf6edYhd+P4ehulj6RCaBOsD4+q9ToyMjKw9OhV6+e98sdNxHRIrHZc+oSMy5Y1ahjCmllX37KZmRn0GJl01c+vrT/PeQMo+127+L6ZWrRoQVpaGgCjR4/m2LGaTW0vPkg9a9YsFi9ezM6dOxk2bBgJCQmXXW02MzPT1NfqcDhqNM4jZxLlrd28efNKy8+fP09mZmbFriYxjwUX/nB7QDlbLBYs0V3hzBmsA5Ox+On6IfXFuHHj8PPzY/Xq1TW+jPilBTFjxgxyc3N59dVXAZg4caIrI7uUR84kQkNDAcjJyeGOO+6oWP7SSy+Rn59P9+7d3ZKjpk1bH9kd8OT/g+KLTgk3eh9ETd4ncbFJE8fxyaJx1xbw/xu47aur+jwJx8GD2Fe8h3XEMOzvrMDa7xYsTZvWah2JiYl8chU/Q9vec+7nSTxx/7Iaj01ISMSxwH0/90++uBAo+127+L67JCYmXlYEI0eOBGDBggU1WkdVBVFu4cKFPP3009xzzz00bNiQoqLf3nGakJBARkbGtb8IF/PImUT79u2Jjo7m+eef56233uLTTz9lwoQJLFmyBEAzCQ9gtUArFx0Hbd3ENeutKUdxCaVzXsZ67xB8xo7GcktvbC+l47DrLeF1XVBQEJ07d+bChQt8/vnn1Y6/UkEA/PTTT+zevRs/Pz+io2u/29MTeGRJWK1WVq5cSWRkJBMmTGD06NGEhoaSmpqKr6+v136z65oOtfuPdY1YgHahzl9vbdiXLMXi64t1VNkUyGfiH3H8cgz76rXmBhOXi4iIwGq1snv3boqLi684trqCKFf+8aiRkZFOz+sOHrm7CaBTp05s2rSp0rJRo0YRERFBQEBAxbKSkhJsNht2u52SkhKKiorw9/c3/eBXfdCrQ9mlNJy5cyAyDK4LdOIKa8n+XRb2D/8L3/mvYfEt+/WwBAbi88RUbE89jTW+O5Z27cwLKC519OhRZs6cSX5+/hXHtWrVirfeeqvaggBYtWoVBw4c4Pvvv3d2XLfw2JKoyrZt2+jVq/LZIuPHj2f58uUAFdPDgwcPcuONN7o7Xr0TGgzRrSE7z3nrTIpw3rquhrVbLNb311y+PCoS6weaSdR1ubm5PPvss9WOO3LkCGPGjKFTp07MnDnzimPXr1/P+vXrnZTQ/Txyd1NVCgsLycnJueyg9bJly3A4HJVuKgj3ubcHBDjpxJ8+4a7ZhVWfHD9zhNfXT674elXmq0ye39fERHXXihUrqi2IusBrZhJBQUGXXV1RzHddADzYB5Z8VnbGU1VqclZTWGO4q5tzs9VH23M+Jq7T7wEoLr3AgfxskxOJt/OamYR4rqgw+ENf8LnKn6Y2TeCPA/RRprWVvT+De55pzNQFiTw4uy0zlg0he38G0e3LrlLw0Vdv8vv4h01OKd5OJSFOEdsGpg2C1rU4LdZqgd9Hwp9+D0ENXZetrurarj+dW/ckfUJZMTx6z3wulJwjwD+IUlsJ3x/I1FVf5Zp5ze4m8XwtrofJt8H3ebA5B/b/UvW4hn7Qoz30DYdm3vuBXabLP3mAFje0B+DYmTxOFx6jfcsYAD7Z/jYDuj1gZjypI1QS4lQ+VujWtux2rhiOnITjhWWXFA/wg5aNoVkIWDWHvWaHft5F2+aR2Ow2LBYr23P+RVx42fGIvGN72P9TFhu2/p1DR3exbvP/ZUjfR01OLN5IJSEuE9gAwptDuNlB6qgfj+6iS9velJRe4HThL3y371OGJUwDYPzgFyvGTZ7fVwUhV00lIeKlHkj+S8X9RVN3kJn9T6xVTNHmpm52ZyypYzTpF6kjEmKGmx1B6iDNJKROiwkO9rptB5v4hkIzt22G2NjYq3regdyyy3a0b9Oi0n13bNvdVBJSp6V37mJ2hFrrrLNW3Wbu3LlX9bzyy5rP+XNKpft1kXY3iYiIIZWEiIgYUkmIiIghlYSIiBhSSYiIiCGVhIiIGFJJiIiIIZWEiIgYUkmIiIghlYSIiBhSSYiIiCGVhIiIGFJJiIiIIZWEiIgYUkmIiIghlYQb5OXlkZycTEREBFFRUTz11FNmRxKpEzIyMoiMjKRjx46MGzcOm81mdqRqPfroo4SFheHr6x0f56OScANfX19efPFFdu/ezbfffsuWLVtYv3692bFEvJrdbmfcuHGsXLmSffv2cfbsWd555x2zY1VrxIgRbN++3ewYNaaScIMWLVoQHx8PQIMGDYiOjiY3N9fkVCLe7ZtvvqFly5Z06VL26YNjx45l9erVJqeqXt++fWnWrJnZMWrMO+Y7dciJEydYt24dH3/8sdlRRNzuXNEFlv7zQ0pt9krL5y1dXeX9/xjQmw5tW1a5rsOHD9O6deuKr9u0aUNeXp6TE5f595Zv2bHn4GXLq8rdsmkThg1OdEkOM2gm4UYXLlxg6NChTJ48mZtuusnsOCJuF9jQnw5tW5H/ywnyfzlRsfzS+/m/nMDHx0q7Ni0M1+VwOLBYLJW+dpXuUZ04fvJ0jXLHde3kshxmUEm4ic1m48EHH6Rbt25MnTrV7DgipknqFUtQo4Bqx905oDfWi0rgUq1bt6602zYvL4+wsDCnZLzU9SFB9O8ZU+24qE7taN+m6pmPt1JJuElKSgrBwcGkp6ebHUXEVP7+Dbitf48rjomJ6EDbsOZXHBMfH8+RI0f44YcfAFi8eDH33nuv03JeKuHmGEKCGhk+7uNjZVDSzS7bvllUEm7wxRdfsGTJErZt20a3bt2IjY3ltddeA1w7RRbxVHFRnWjZrEmVj/n6+jAosfo/tj4+PixatIihQ4fSoUMHgoKCGDVqlLOjVmjQwI9BiT0NH+8b35Um14dUu55HHnmEsLAwbDYbYWFhpKamOjOm01kc+itlqvc/2YLNZmPIrX0r7V8VqesO5OWzcMUHly0f0Kc7t/aLNyFR9ewOBwveXkde/rFKy4MaBTBt/Aga+jcwKZnraCZhotNnC/kqq2yqrIKQ+qZ96xZ07dyu0rKQoEASbq5+379ZrBYL/5Hc57Llt/XrUScLAupASezYsYP77ruP0NBQGjZsSHh4OGlpaWbHqpGML7PAAYm9Ys2OImKKQYk34+Pz25+h2xJ64t/Az8RE1WvbqhkxER0qvm7RtEmdO6PpYl69u2n79u3079+ftm3b8sQTT9CmTRsOHjzIli1bWLx48TWv/8kXFzohpYiI55nz55QajfPqN9NNnTqV4OBgvvzyS0JCfjtgNHbsWBNTiYjUHV47kzh37hzBwcE8+uijzJ071+w4tXL6bCEvL3yP+K6duee2fmbHETHd0eOnaBba2OwYtVJcXMKv54tofF2w2VFcymtnEqdOncJut9OqVSuXbcPVu5u+ytrNV1m7XboNEZGq1HR3k9ceuG7cuDFWq5UjR46YHUVEpM7y2t1NAElJSezevZucnJxKxyQ82bp/beab7P9hWsqIOj9NFRHv57UzCYBXXnmFgoICevXqxbJly9i0aRPLly9n3LhxZker0umzhXzz/f8QH91ZBSEiXsFrj0kAxMXFsXXrVqZPn86UKVMoKiqidevW3H///WZHq9KJ02cJbhSo90WIiNfw6t1N3shut2O1evUETkTqEZWEiIgY0n9pRUTEkEpCREQMqSRERMSQSkJERAypJERExJBKQkREDKkkRETEkEpCREQMqSRERMSQSkJERAypJERExJBKQkREDKkkRETEkEpCREQMqSRERMSQSkJERAypJERExJBKQkREDKkkRETEkEpCREQMqSRERMSQSkJERAypJERExJBKQkREDKkkRETEkEpCREQMqSRERMTQ/wKtlQfWTFKsEAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 501.832x204.68 with 1 Axes>"
      ]
     },
     "execution_count": 282,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "measureXX = QuantumCircuit(2, 2)\n",
    "#z\n",
    "measureXX.ry(1*math.pi/4,1)\n",
    "measureXX.measure(0, 0)\n",
    "measureXX.measure(1, 1)\n",
    "bellXX = qc+measureXX\n",
    "\n",
    "bellXX.draw(output='mpl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 283,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 501.832x204.68 with 1 Axes>"
      ]
     },
     "execution_count": 283,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "measureZX = QuantumCircuit(2, 2)\n",
    "measureZX.h(0)\n",
    "measureZX.ry(3*math.pi/4,1)\n",
    "measureZX.measure(0, 0)\n",
    "measureZX.measure(1, 1)\n",
    "bellZX = qc+measureZX\n",
    "\n",
    "bellZX.draw(output='mpl')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 284,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 501.832x204.68 with 1 Axes>"
      ]
     },
     "execution_count": 284,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "measureXZ = QuantumCircuit(2, 2)\n",
    "measureXZ.h(0)\n",
    "measureXZ.ry(1*math.pi/4,1)\n",
    "measureXZ.measure(0, 0)\n",
    "measureXZ.measure(1, 1)\n",
    "bellXZ = qc+measureXZ\n",
    "\n",
    "bellXZ.draw(output='mpl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 285,
   "metadata": {},
   "outputs": [],
   "source": [
    "circuits = [bellZZ,bellXX,bellZX,bellXZ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 286,
   "metadata": {},
   "outputs": [],
   "source": [
    "#observable_first ={'00': 1, '01': -1, '10': 1, '11': -1}\n",
    "#observable_second ={'00': 1, '01': 1, '10': -1, '11': -1}\n",
    "observable_correlated ={'00': 1, '01': -1, '10': -1, '11': 1}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 287,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Job Status: job has successfully run\n"
     ]
    }
   ],
   "source": [
    "job = execute(circuits, backend=Aer.get_backend('qasm_simulator'), shots=10000)\n",
    "job_monitor(job)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 288,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'00': 4272, '01': 760, '10': 734, '11': 4234},\n",
       " {'00': 753, '01': 4235, '10': 4294, '11': 718},\n",
       " {'00': 4336, '01': 739, '10': 694, '11': 4231},\n",
       " {'00': 4314, '01': 743, '10': 747, '11': 4196}]"
      ]
     },
     "execution_count": 288,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result2 = job.result()\n",
    "result2.get_counts() #equivalem aos seguintes resultados\n",
    "#result2.get_counts(bellZZ)\n",
    "#result2.get_counts(bellXX)\n",
    "#result2.get_counts(bellZX)\n",
    "#result2.get_counts(bellXZ)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 289,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "res1 = 0.7012\n",
      "res2 = -0.7058\n",
      "res3 = 0.7134\n",
      "res4 = 0.702\n",
      "s=2.8224\n"
     ]
    }
   ],
   "source": [
    "res1=(average_data(result2.get_counts(bellZZ),observable_correlated))\n",
    "res2=(average_data(result2.get_counts(bellXX),observable_correlated))\n",
    "res3=(average_data(result2.get_counts(bellZX),observable_correlated))\n",
    "res4=(average_data(result2.get_counts(bellXZ),observable_correlated))\n",
    "\n",
    "s= -res2 +res3 +res4 +res1;\n",
    "s=str(s)\n",
    "\n",
    "res1=str(res1)\n",
    "res2=str(res2)\n",
    "res3=str(res3)\n",
    "res4=str(res4)\n",
    "\n",
    "print('res1 = ' + res1)\n",
    "print('res2 = ' + res2)\n",
    "print('res3 = ' + res3)\n",
    "print('res4 = ' + res4)\n",
    "print('s=' + s)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 290,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 501.832x204.68 with 1 Axes>"
      ]
     },
     "execution_count": 290,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "##########################################################################   espiã eva\n",
    "\n",
    "measureZZ2 = QuantumCircuit(2, 2)\n",
    "\n",
    "eva = randint(2, size=1)  #primeiro qubit\n",
    "\n",
    "#if (eva==1):\n",
    "    #nada \n",
    "if (eva==0):\n",
    "        measureZZ2.x(0)\n",
    "        measureZZ2.ry(3*math.pi/4,0)     \n",
    "        \n",
    "eva = randint(2, size=1)  #segundo qubit\n",
    "\n",
    "if (eva==1):\n",
    "    measureZZ2.ry(3*math.pi/4,1)      \n",
    "if (eva==0):\n",
    "    measureZZ2.x(1)\n",
    "\n",
    "\n",
    "measureZZ2.measure(0, 0)\n",
    "measureZZ2.measure(1, 1)\n",
    "bellZZ2 = qc+measureZZ2\n",
    "\n",
    "bellZZ2.draw(output='mpl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 291,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 501.832x204.68 with 1 Axes>"
      ]
     },
     "execution_count": 291,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "measureXX2 = QuantumCircuit(2, 2)\n",
    "\n",
    "eva = randint(2, size=1) #primeiro qubit\n",
    "\n",
    "#if (eva==1):\n",
    "    #nada \n",
    "if (eva==0):\n",
    "        measureXX2.x(0)\n",
    "        measureXX2.ry(1*math.pi/4,0)\n",
    "     \n",
    "        \n",
    "eva = randint(2, size=1) #segundo qubit\n",
    "\n",
    "if (eva==1):\n",
    "    measureXX2.ry(1*math.pi/4,1)      \n",
    "if (eva==0):\n",
    "    measureXX2.x(1)\n",
    "\n",
    "\n",
    "measureXX2.measure(0, 0)\n",
    "measureXX2.measure(1, 1)\n",
    "bellXX2 = qc+measureXX2\n",
    "\n",
    "bellXX2.draw(output='mpl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 292,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 562.032x204.68 with 1 Axes>"
      ]
     },
     "execution_count": 292,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "measureZX2 = QuantumCircuit(2, 2)\n",
    "\n",
    "eva = randint(2, size=1)  #primeiro qubit\n",
    "\n",
    "if (eva==1):\n",
    "    measureZX2.h(0)\n",
    "if (eva==0):\n",
    "    measureZX2.x(0)\n",
    "    measureZX2.ry(3*math.pi/4,0)\n",
    "    \n",
    "    \n",
    "eva = randint(2, size=1)  #segundo qubit\n",
    "\n",
    "if (eva==1):\n",
    "    measureZX2.ry(3*math.pi/4,1)\n",
    "if (eva==0):\n",
    "    measureZX2.x(1)\n",
    "    measureZX2.h(1)\n",
    "    \n",
    "    \n",
    "measureZX2.measure(0, 0)\n",
    "measureZX2.measure(1, 1)\n",
    "bellZX2 = qc+measureZX2\n",
    "\n",
    "bellZX2.draw(output='mpl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 293,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 562.032x204.68 with 1 Axes>"
      ]
     },
     "execution_count": 293,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "measureXZ2 = QuantumCircuit(2, 2)\n",
    "\n",
    "eva = randint(2, size=1)  #primeiro qubit\n",
    "\n",
    "if (eva==1):\n",
    "    measureXZ2.h(0)\n",
    "if (eva==0):\n",
    "    measureXZ2.x(0)\n",
    "    measureXZ2.ry(1*math.pi/4,0)\n",
    "\n",
    "    \n",
    "eva = randint(2, size=1) #segundo qubit\n",
    "    \n",
    "if (eva==1):\n",
    "    measureXZ2.ry(1*math.pi/4,1)\n",
    "if (eva==0):\n",
    "    measureXZ2.x(1)\n",
    "    measureXZ2.h(1)\n",
    "\n",
    "measureXZ2.measure(0, 0)\n",
    "measureXZ2.measure(1, 1)\n",
    "bellXZ2 = qc+measureXZ2\n",
    "\n",
    "bellXZ2.draw(output='mpl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 294,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Job Status: job has successfully run\n"
     ]
    }
   ],
   "source": [
    "circuits2 = [bellZZ2,bellXX2,bellZX2,bellXZ2]\n",
    "job2 = execute(circuits2, backend=Aer.get_backend('qasm_simulator'), shots=10000)\n",
    "job_monitor(job2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 295,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'00': 4311, '01': 745, '10': 699, '11': 4245},\n",
       " {'00': 2539, '01': 2512, '10': 2460, '11': 2489},\n",
       " {'01': 5049, '10': 4951},\n",
       " {'00': 4099, '01': 757, '10': 784, '11': 4360}]"
      ]
     },
     "execution_count": 295,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result22 = job2.result()\n",
    "result22.get_counts() #equivalem aos seguintes resultados\n",
    "#result22.get_counts(bellZZ2)\n",
    "#result22.get_counts(bellXX2)\n",
    "#result22.get_counts(bellZX2)\n",
    "#result22.get_counts(bellXZ2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 296,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "res11 = 0.7111999999999999\n",
      "res22 = 0.005600000000000049\n",
      "res33 = -1.0\n",
      "res44 = 0.6918\n",
      "s2=0.39739999999999986\n"
     ]
    }
   ],
   "source": [
    "res11=(average_data(result22.get_counts(bellZZ2),observable_correlated))\n",
    "res22=(average_data(result22.get_counts(bellXX2),observable_correlated))\n",
    "res33=(average_data(result22.get_counts(bellZX2),observable_correlated))\n",
    "res44=(average_data(result22.get_counts(bellXZ2),observable_correlated))\n",
    "\n",
    "s2= -res22+res33+res44 +res11;\n",
    "s2=str(s2)\n",
    "\n",
    "res11=str(res11)\n",
    "res22=str(res22)\n",
    "res33=str(res33)\n",
    "res44=str(res44)\n",
    "\n",
    "print('res11 = ' + res11)\n",
    "print('res22 = ' + res22)\n",
    "print('res33 = ' + res33)\n",
    "print('res44 = ' + res44)\n",
    "print('s2=' + s2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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