{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "e5ba8253-2492-453f-834f-b1d8089d391c",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "\n",
    "# Importing standard Qiskit libraries\n",
    "from qiskit import QuantumCircuit, transpile, execute, 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",
    "from qiskit.providers.ibmq import least_busy  #Para verificar qual é o QComputer mais disponível\n",
    "\n",
    "# IBMQ.get_provider(hub='ibm-q-education', group='uni-sao-paulo-M', project='Quantum-Informat')\n",
    "\n",
    "# Loading your IBM Quantum account(s)\n",
    "provider = IBMQ.load_account()\n",
    "#provider = IBMQ.get_provider(hub='ibm-q-education', group='uni-sao-paulo-M', project='Quantum-Informat')\n",
    "#provider = IBMQ.get_provider(hub='ibm-q-education', group='uni-sao-paulo-M', project='qinfo-7600074-21')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "049410c3-91e6-4857-b7d7-bb062fe2a3d6",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Função para implementar a caixa secreta\n",
    "def secretBox(secret):\n",
    "    for k, bit in enumerate(reversed(secret)):\n",
    "        if bit == '1':\n",
    "            circ.cx(k,len(secret))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "b9b10ab5-f04a-4143-8dc9-dd0f5a2c40ab",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Código secreto\n",
    "secretNum = '100100'\n",
    "#secretNum = '00100'\n",
    "n = len(secretNum)  # número de bits"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "efb707c4-36a4-4bfa-9801-9b2b94c26efa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 869.197x505.68 with 1 Axes>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "circ = QuantumCircuit(n+1,n)\n",
    "\n",
    "circ.h(range(n))\n",
    "circ.x(n)\n",
    "circ.h(n)\n",
    "circ.barrier()\n",
    "secretBox(secretNum)\n",
    "circ.barrier()\n",
    "circ.h(range(n))\n",
    "circ.measure(range(n),range(n))\n",
    "circ.draw()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "92214744-08ac-40e9-9027-09a63ce6f819",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Resultado obtido em 1-shot: \n",
      " {'1011': 1}\n",
      "Código secreto na caixa: \n",
      " 1011\n"
     ]
    }
   ],
   "source": [
    "# Rodando o código no simulador\n",
    "simulador = Aer.get_backend('qasm_simulator')\n",
    "resultado = execute(circ, backend = simulador, shots = 1).result()\n",
    "contagem  = resultado.get_counts()\n",
    "\n",
    "print(\"Resultado obtido em 1-shot: \\n\",contagem)\n",
    "print(\"Código secreto na caixa: \\n\", secretNum)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cc063b1f-1379-4b2e-a214-c8e8c78fc02a",
   "metadata": {},
   "source": [
    "# Testando Bernstein-Vazirani no computador quântico"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "7cf4749e-3deb-4d8c-a2a7-ede4aa4409bd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Backend menos ocupado:  ibmq_quito\n"
     ]
    }
   ],
   "source": [
    "# Rodando o código em hardware \n",
    "hardware = least_busy(provider.backends(filters=lambda x: x.configuration().n_qubits >= (n+1) and not x.configuration().simulator and x.status().operational==True))\n",
    "print(\"Backend menos ocupado: \", hardware)\n",
    "\n",
    "#%qiskit_job_watcher\n",
    "#job = execute(circ, backend=hardware, shots=1, optimization_level=3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ffe71b4e-d5a2-49b7-a2f0-32b56e1fc4fb",
   "metadata": {},
   "outputs": [],
   "source": [
    "results = job.result()\n",
    "resposta = results.get_counts()\n",
    "plot_histogram(resposta)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "874febf1-a994-44ca-bf0c-54c20df15b6a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Carreganodo um resultado anterior (rodado no 7-qbit hardware Casablanca)\n",
    "#ATENÇÃO: Este bloco de código só vai funcionar na minha conta pessoal (SRM) \n",
    "provedor = IBMQ.get_provider(hub='ibm-q-education', group='uni-sao-paulo-M', project='Quantum-Informat')\n",
    "bck2 = provedor.get_backend('ibmq_casablanca')\n",
    "old_job = bck2.retrieve_job(\"61d2968dfa27f646d137ed4e\")\n",
    "old_result = old_job.result()\n",
    "resposta2 = old_result.get_counts()\n",
    "plot_histogram(resposta2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2a97697a-d1dc-44d1-a636-69d9c73a5161",
   "metadata": {},
   "source": [
    "# Rodando num computador Quântico de 7-qbit \n",
    "Observe, neste caso, como o número de erros aumenta significativamente!!  (Porque?)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "329c19f2-72c8-4ac9-9cdf-21c1f719c9ad",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "47d65328c68043d4ad489b5887a6e8f5",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Accordion(children=(VBox(layout=Layout(max_width='710px', min_width='710px')),), layout=Layout(max_height='500…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "\n",
       "        const isLab = window['Jupyter'] === undefined;\n",
       "        const notebook = document.querySelector( isLab ? 'div.jp-Notebook' : '#site');\n",
       "        const jobWidget = document.querySelector('div.job_widget');\n",
       "        notebook.prepend(jobWidget);\n",
       "        jobWidget.style.zIndex = '999';\n",
       "        jobWidget.style.position = isLab ? 'sticky' : 'fixed';\n",
       "        jobWidget.style.boxShadow = '5px 5px 5px -3px black';\n",
       "        jobWidget.style.opacity = '0.95';\n",
       "        if (isLab) {\n",
       "            jobWidget.style.top = '0';\n",
       "            jobWidget.style.left = '0';\n",
       "        }\n",
       "        "
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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o5N4XJbdMdwJ373QiERGRFGhybxERETQwX0REBMh92AVm1g04AegPdMhc5+435CmXiIhIQeVUEM3scOB3QB0xBGMFMUi/DlgGqCCKiEhJyrXJ9GbgF0BfYCPwCeJIsRr4fn6jiYiIFE6uBfFg4C53d6AeKHf3VcDVaNiFiIiUsFwL4qaMn1cB+yU/vwf0yUsiERGRFOTaqWYecBiwGJgBfMfMegJfBP6a32giIiKFk+sR4n8Aryc/Xwu8SQzI78ZHB+qLiIiUjJyOEN29OuPnN4nhFyIiIiUv53GIAGa2P3BgcneRuy/JXyQREZHCy3UcYg/gXmAi8OHWxfZb4Hx3X5PnfCIiIgWR6znEnwKDgaOAjsltPDAQmJzfaCIiIoWTa5Pp8cAn3X1OxrLnzOwrwB/yF0tERKSwcj1CfBN4P8vyfwJqLhURkZKVa0G8AbjdzPo2LEh+vpUWzmNqZpea2VIz22hmc83sqBY+bpyZbTazBTlmFhER2a7tNpma2d8Az1g0EFhmZiuS+w3zmu5LnGNs7rnOAO4ALgVmJ/8+YWbD3P21Zh7XDZgCPJ38fyIiInnVknOID+fx/7sKuM/dGzrgXGFmnwYuAa5p5nH3Aj8HDDgtj3lERESAFhREd/92Pv4jM+sAHArc0mjVk8ARzTzuUqAn8B3gW9v5Py4imTGnT58+zJgxA4BBgwbRpUsX5s+fD0CPHj0YPnw4s2bNAqCsrIxx48Yxb9481q1bB0BlZSWrVq1i+fLlABxwwAGUl5ezYEG02O67774MGTKE2bNnA1BeXs7YsWOprq7mvffeA2DMmDHU1tayYkUcTA8dOpT27duzaNEiAHr16sXAgQOZMyf6KHXq1IkxY8ZQVVXFhg0bABg7dixLly5l5cqVAAwbNoz6+npefvllAPr27UtFRQVVVVUAdO7cmcrKSubMmUNdXR0A48aNY/HixaxevRqAESNGUFdXR01NDQD9+vWjZ8+eVFfHvAtdu3Zl9OjRzJ49m82bNwMwfvx4Fi5cyJo1cap45MiRrF+/niVLYgjqgAED6N69O/PmzQOgW7dujBw5kpkzZ+LumBkTJkxg/vz5rF27FoDRo0fz9ttvs2zZMr1PO/A+wdHk28yZM/U+6fPUqt+n5lhcuCI3ZvYJYBjRlLrQ3We04DF9iOsnTnD3WRnLrwPOdvehWR5zENF79XB3X2pm1wOnufuI7f1/lZWVvvWLQ6T1ufD2/D/n5Cvz/5wixcTM5rp7ZbZ1uQ7M7wv8mjjSa5jTtI+ZVQOnuPvrTT44R2ZWDjwEfM3dl+breUVERLLJtZfpD4nrIA52937u3g84IFn2w+089q1ku56NlvcEVmbZvjcxPdzPkt6lm4HrgOHJ/U/lmF1ERKRJuQ7MPw44OvOIzd2XmNkkogdok9x9k5nNTZ7jV42e85EsD1kBHNRo2aXJ9qcAy3LMLiIi0qQdmdw720nHlp6IvA2438xeAJ4DLiYuLHwPgJlNAXD3c939A2CbMYdmthqoc3eNRRQRkbzKtSA+DdxpZme5+3IAM+sP3M52jhAB3P2hZILwa4km0QXAie7+arJJ/xzziIiI5EWuBXES8BtgiZlt6VQD/A04qyVP4O53A3c3se7o7Tz2euD6lkUVERFpuVwL4hrg48QAqI8ly15yd03sLSIiJa3FBdHM2gPvAiPd/SngqV2WSkREpMBaPOzC3euBV4EOuy6OiIhIOnIdh3gjcJOZ7b0rwoiIiKQl13OIXyOudrHCzGppdG1Edz84X8FEREQKKdeC+DAx5tB2QRYREZHUtKggmtnuwM3AycBuxJjDK9z9rV0XTUREpHBaeg7x28B5wO+AB4FjgR/tokwiIiIF19Im01OBC9x9KoCZ/QJ4zszaJ71PRURESlpLjxD7Ac823HH3F4DNxCw1IiIiJa+lBbE9sKnRss3s2OTgIiIiRaelBc2AB8ysLmNZR2Cymf2zYYG7T8xnOBERkUJpaUH8eZZlD+QziIiISJpaVBDd/V92dRAREZE05Tp1m4iISKukgigiIoIKooiICKCCKCIiAqggioiIACqIIiIigAqiiIgIoIIoIiICqCCKiIgAKogiIiKACqKIiAiggigiIgKoIIqIiAAqiCIiIoAKooiICKCCKCIiAqggioiIACqIIiIigAqiiIgIoIIoIiICqCCKiIgAKogiIiKACqKIiAiggigiIgKoIIqIiAAqiCIiIoAKooiICKCCKCIiAqggioiIACqIIiIigAqiiIgIkEJBNLNLzWypmW00s7lmdlQz255qZk+a2Ztmtt7MqsxsYiHziohI21DQgmhmZwB3AN8FRgF/Ap4ws/5NPGQC8AzwmWT7x4FfN1dERUREdkRZgf+/q4D73H1ycv8KM/s0cAlwTeON3f1fGy36tpl9BjgZeHZXBhURkbalYAXRzDoAhwK3NFr1JHBEDk/VBVjbxP9xEXARQJ8+fZgxYwYAgwYNokuXLsyfPx+AHj16MHz4cGbNmgVAWVkZ48aNY968eaxbtw6AyspKVq1axfLlywE44IADKC8vZ8GCBQDsu+++DBkyhNmzZwNQXl7O2LFjqa6u5r333gNgzJgx1NbWsmLFCgCGDh1K+/btWbRoEQC9evVi4MCBzJkzB4BOnToxZswYqqqq2LBhAwBjx45l6dKlrFy5EoBhw4ZRX1/Pyy+/DEDfvn2pqKigqqoKgM6dO1NZWcmcOXOoq6sDYNy4cSxevJjVq1cDMGLECOrq6qipqQGgX79+9OzZk+rqagC6du3K6NGjmT17Nps3bwZg/PjxLFy4kDVr1gAwcuRI1q9fz5IlSwAYMGAA3bt3Z968eQB069aNkSNHMnPmTNwdM2PChAnMnz+ftWvj7Rs9ejRvv/02y5Yt0/u0A+8THE2+zZw5U++TPk+t+n1qjrl7sxvki5n1AVYAE9x9Vsby64Cz3X1oC57jMuAmYIS7v9rctpWVlb71i0Ok9bnw9vw/5+Qr8/+cIsXEzOa6e2W2dYVuMt1hZvZ54GbgjO0VQxERkVwVslPNW0A90LPR8p7AyuYeaGanAfcD57r7Y7smnoiItGUFK4juvgmYCxzXaNVxRG/TrMzsdKIYnufuD++6hCIi0pYVusn0NuB+M3sBeA64GOgD3ANgZlMA3P3c5P6ZRDH8GjDLzHolz7PJ3d8ucHYREWnFCloQ3f0hM+sBXAv0BhYAJ2acE2w8HvFiIuPtya3BTHZFFzsREWmzCt6pxt3vBu5uYt3Rzd0XERHZVTSXqYiICCqIIiIigAqiiIgIoIIoIiICqCCKiIgAKogiIiKACqKIiAiggigiIgKoIIqIiAAqiCIiIoAKooiICKCCKCIiAqggioiIACqIIiIigAqiiIgIoIIoIiICqCCKiIgAKogiIiKACqLIFtOnT2fo0KEMHjyYm2666SPr6+rqOOOMMxg8eDBjxoxh2bJlAPziF7/gkEMO2XJr164dL774IgBz587loIMOYvDgwUyaNAl3L+BvJCK5UEEUAerr67nssst44oknWLRoEQ8++CCLFi3aZpt7772Xbt268corr/DVr36Vq6++GoCzzz6bF198kRdffJH777+fgQMHcsghhwBwySWXMHnyZGpqaqipqWH69OmF/tVEpIVUEEWAF154gcGDBzNo0CA6dOjAmWeeyaOPPrrNNo8++ihf+tKXADjttNN4+umnP3LE9+CDD3LmmWcC8MYbb7Bu3ToOP/xwzIxzzz2XadOmFeT3EZHcqSCKACtWrKBfv35b7ldUVLBixYomtykrK2PPPfdkzZo122zz0EMPcdZZZ23ZvqKiotnnFJHioYIokidVVVXsvvvujBgxIu0oIrIDVBBFgL59+7J8+fIt92tra+nbt2+T22zevJl3332XHj16bFk/derULUeHDdvX1tY2+5wiUjxUEEvcjvaMXLZsGZ06ddrSM/Liiy/e8pi22DPysMMOo6amhqVLl7Jp0yamTp3KxIkTt9lm4sSJ/PznPwfg4Ycf5hOf+ARmBsCHH37IL3/5yy3nDwF69+5N165def7553F3pkyZwkknnVS4X0pEcqKCWMJ2pmckwP7777+ld+Q999yzZXlb7BlZVlbGXXfdxfHHH8+BBx7I6aefzvDhw7nuuuv4zW9+A8AFF1zAmjVrGDx4MLfddts2OyCzZs2iX79+DBo0aJvnvfvuu/nyl7/M4MGD2X///TnhhBMK+nuJSMtZa937r6ys9Orq6rRj7FJz5szh+uuv5/e//z0A3/ve9wC45pprtmxz/PHHc/311zN27Fg2b95Mr169ePPNN3n11Vf57Gc/y4IFC7Z5zjfeeINjjjmGv//970D0mpwxYwY//vGPC/RbSUtdeHv+n3Pylfl/TpFiYmZz3b0y2zodIZawne0ZuXTpUkaNGsWECRN49tlnt2yvnpEi0haVpR1A0tG7d29ee+01evTowdy5czn55JNZuHBh2rFERFKjgljCcukZWVFRsU3PSDOjvLwcgEMPPZT999+fxYsXq2ckaooUaavUZFrCdqZn5Jtvvkl9fT0AS5YsoaamhkGDBqlnpIi0WTpCLGGZPSPr6+s5//zzt/SMrKysZOLEiVxwwQWcc845DB48mO7duzN16lQgekVed9117LbbbrRr14577rmH7t27A9Ez8rzzzmPDhg2ccMIJ6hkpIm2CepmKNFIqTaalklOkmKiXqYiI7HI7OlHIU089xaGHHspBBx3EoYceyjPPPLPlMYWcKERNpq2EjhZEJE0NE4U89dRTVFRUcNhhhzFx4kSGDRu2ZZvMiUKmTp3K1VdfzUMPPcTee+/NY489Rp8+fViwYAHHH3/8luFeDROFjBkzhhNPPJHp06fvstM4OkIUEZGdtjOXUBs1ahR9+vQBYPjw4WzYsIG6urqCX0JNBbEJO3rov2bNGo455hg6d+7M5Zdfvs1j2uIcoQ30erY9pfKel0LOUsiYr0uoPfLII4wePZry8vKCTxSigpjFzswR2rFjR2688UZuueWWjzxvW5wjFPR6tkWl8p6XQs5SyJgvCxcu5Oqrr05tqkgVxCx25tB/jz32YNy4cXTs2HGb7dvy1dP1erY9pfKel0LOUsgIO38JtdraWk455RSmTJnC/vvvv2X7Qk4UooKYRb4O/Rtv31bnCNXr2faUynteCjlLISPs3EQh77zzDp/5zGe46aabOPLII7dsX+iJQlQQRURkp+3MJdTuuusuXnnlFW644YYt12hdvXo1UNhLqGnYRRY7M0doc8/ZVucI1evZ9pTKe14KOUshY4MTTzyRE088cZtlN9xww5afO3bsyK9+9auPPO7aa6/l2muvzfqclZWVH7lM3a6iI8Qsdvbq6dm05TlC9Xq2PaXynpdCzlLI2FroCDGLnZkjFGDAgAGsW7eOTZs2MW3aNJ588kmGDRvWZucI1evZ9pTKe14KOUshY2OlOlFIwecyNbNLgX8HegMLgSvd/dlmtp8A3AYMB14H/svd79ne/9PW5jIt1T/AYlQqr2Wp5JS2p5j/NotmLlMzOwO4A/guMAr4E/CEmfVvYvuBwOPJdqOA7wF3mtnnC5NYRETaikI3mV4F3Ofuk5P7V5jZp4FLgGuybH8x8Lq7X5Hcf8nMxgBfAx7Z5Wkp7j2dUqTXs+0plfe8rebU52ergh0hmlkH4FDgyUarngSOaOJhY7Ns/3ug0sx2y29CERFpywp2DtHM+gArgAnuPitj+XXA2e4+NMtjFgMPuPsNGcvGAzOBPu7+RqPtLwIuSu4OBV7O+y/SvL2Btwr8f+aqFDKCcuZbKeQshYygnPlW6Jz7ufs+2Va0ql6m7v4T4Cdp/f9mVt3UydpiUQoZQTnzrRRylkJGUM58K6achexU8xZQD/RstLwnsLKJx6xsYvvNlMaej4iIlIiCFUR33wTMBY5rtOo4ohdpNnOa2L7a3T/Ib0IREWnLCj1TzW3AeWb2ZTM70MzuAPoA9wCY2RQzm5Kx/T1AXzO7Pdn+y8B5wEevZVIcUmuuzUEpZATlzLdSyFkKGUE5861ocqY1MP/rxMD8BcBXGzrZmNkMAHc/OmP7CcAP2Dow//stGZgvIiKSi4IXRBERkWKkyb1FRERQQRQREQFUEKXEWHPXtBER2QkqiFJSPDnpbWbtirk4FnO2TKWSs9hZKPrvU+Xczv+rTjX5Z2bdgR7AHoADi919Q7qpPiq5ykjv5LYe+LO7r0s31UeZ2XBgEDCY6Gn8lLu/nW6qljGzdu7+Ydo5tif58nEvoi8EM7NiytOUxjmL8bUE5WzR/11kr0XJM7OzgK8A44nZdP4OLAWeBZ5w9xXF8CVpZl8h5n0dBbwKvAn8E5gF/NLdFxTDF5KZfZ0YezoQWATsBnQmXs/J7j67GHICmNmRwJ7EztCrwJxim0AimWT/eKBXcvsrMN3d61INVoKSHd+Tib/NPsBsYGqx7fwqZw4ZiuB7pNUws72AGuAXwH8D+wHHAGOIKef+AnzN3VenlRG25FwG/BdwN3AAcSWSw4ADgXeJnAtTighsyVkLfBW4j/igDCayHgV0Bb7l7k+lFBEAM9sduBU4Eygn/gY+IHaIphM7GK+nvSNkZp2BycAJwDvAcmBfohXjt8BP3f3vae9gJFeyGQn8w93XNlpXLDs/XYAHic/2y8TreSjQHZgG3OruL6SVr4Fy5sjddcvTDZgEvJBleSfgLOAVoih2TTnnpcT0d42XdwA+RUyZt4K4okiaOS8E/pJleVnyYfkV0dT7sZRz/jtx9Pqp5P5RwJXEB3wu8FNgtzQzJrm+TkyGMSq5PwI4hdgxeg74DdCrCHJeDKwmZjA5HRgC7N5omz2Bz6X1ugJXA/OJKydAHNGMAi4HniG5qHkRvJbKmUuOtF+I1nRLvhj/DPRL7ncEyjLWH0gcPZyYcs4Lki/G4cn99kC7jPXdgBeBL6Scc2Lyeh3ZxPrdiKbTy1LOWQVMyrJ8L+ALwNvAg2lmTPLMAr6RZfkewLHJa/102sU7+fJ7HqgmmvH/BtxMHNn2IzoD/gswL8WM04H/zLJ8N+Bg4hJ184AuKb+WypnDreh7G5WYXxLnj74M4O4b3X2zmZUl918C1hCFMU2PElce+aqZVbh7vbt/2NDj0KOZ6n2iiTJNM4gj1W+a2RFmVp650uP8nBPNfqlIMi0GjjGzPZJl7ZOmvXfc/X+Iv4ePmdkBKeZsTxytfjY5V7OFu7/v7n8giszexDSJqTCzvYEPgds8Lgl0EPA74DTi8/U/xJHuN4lzTGmZAZxiZr0zF7r7B+7+V+ASonCPTCFbphkoZ8uluVfQ2m7JGzaJOH/0CvA1oEeyrgfRHPk+sH8RZP0/REea1cT5r1FJxv2JZqr1RZLzCKLjx/vEl+EpyYfi48mH5J20crL1HPwJxPm4fwX2yLLdQGAdUJHya3k4cRR4G3EB7faN1u+XvM79U8y4T/K+fqQVBTgSmEIccX9I0ryWUs6PEa0ojxBX4OnBtq0sA4ANwICU33PlzOGmTjW7gJkNJvZiJxJ73EuJL+6ewCPu/tX00m1lZp2Iov1FomPN68QXdxeig8W3U4y3DTM7mzi3dARRxN8nmnpvdfe7Us62B/AN4jzIq0QHoP8F1hKF5/PA0e5+cFoZYctR4oXAfxItBA8DjxE7RvsBnwVGuvvo1EKypYPFh+7+fpLZ3H1zxvr/C5zs7qNSCxk5TgS+QzTjPkc0+73J1p3fCnc/PL2Ewcw+B3wb6E/kfALlzJ5BBTF/ki7t+7l7TXK/L9H54xDiPM2vgL96XBsyrYy7EU2MfT2j15aZHUQUmzLg98AST39oSMO5zQ8ylnUFPgnUER1u3kgrX2NmNojoEXsKMbbzNWB3YCFwg7vPSC/dVsnf6STgS0Tz6FKix+6zwE1eBL0OG2T2Kk3Go3Uizin+zN1vTDVcIhlqdQnR+ect4ij3MeAHnnJP7UxmdgaR80Ci0Chn4/9bBXHnJcXk34hmvHeBzUQHhv8psj+0I4FriD+0TcSR4B+Bu919TprZMplZV280QUBSHD3tIt1YUqCHENnmJsvaE+e+Komj7j96ymO+zKwCGA2syyzMZtYLGAssAV5Kc2ctyVNB7ECudffnMpYbYEQni88Cv/UUx05m9AvIPHLdk9jBeAVY4+71KcVr2HkYTvR4foOYdKM2WbcX0VHl78rZKI8K4s4zsxrgJWK4QhnRNPpxomv4dOIajq+nlzCY2WvAU0TODUQz2eeIAjkb+KbHCexUmdnPiPOGVcAid38nY50R52p3d/f16STckuUrwPVE0+juRBPur4kdjL832ja18XNm9i3iyPUNojnKiOaoO9w9zY4p28iSE+BxIuefUguWwcx6Z7ZKJF/ouwH1mcUxbWZ2J3A20SmtP3Fk/QLwY3e/P81smYouZ5onUlvDjehW/w8yxhYSR16VwLXJup8AHVLOeSbRNNYpY9luQAXxBzmbOO+Vdvfr04gOE38n+WAQvR8PBjom23QghgekNn6KGFe6lDh3+Fmik9J3iea8VcAdwJ5pvpZJzrOTv8HziYkXDiPOxc4kWjIeJcXOKdvJ+ZWMnL8mGc6UYsZPE8OqvpP8vFej9e2JL/S0xxmfQxylnkTs9PZM8v4K2EgMXxhdBO950eXUEeJOMrNvEIf7n/UsL6aZnUQUxM95iudmkqOZLwAnuPs/s6w/mujFeYG7P1HYdNvkuIeY7eUe4kT6iUTHpFriy2gOMWj3VnfvmGLOPxKTMFydsayc+GCfREyL9zN3/25KERsyPUmct/5ao+Vdid58/wHMcvcrU4iXmafoc5rZ40Sz82Jip2w5MVZyFjHRxQdmdgLRQpDakCUze4yY5efK5H7medjRRK/yN9z9C2llTLIUXU6NQ9x5M4BPAF9Pesc19hviA3RsIUNlMZPo4HOzmfVrGHPYwOO80t+Iru2pSM69vUacP6py9xvdfSxx1LCQ2Hu8EbgFmJpyzlWNl7t7nbsvdvebieEBn086VqUiac5bSuxQbMPd17n7I8TO2nFmltrY2FLImUzPtw/R6nMZ8BBxRPh5YtKAn5jZRURP4z+nkTHJacSsSUMalrm7J2Nj27v7POBOoNLMjlDORtI+bG4NN2LvdRnwI2Iuvq5AebJuP2LIxRFFkPMsorD8EjiDGBLQME7yYKJDUKo5iWaTA5Kfd2u0rpwYNvAhcGjKOb9CNOVdAOydZX1/YnjIsJRzfj55vW4ABmVZ34PoyXewcjabrxexI3Z+xrJ2ROvQjUTP7L8kv8NhKb+WxyQ5fgYckmX9HkRv2FSnbCvGnGoy3QmWTNacDGW4CLiK+CJcQIyj6UfsAf3D3T+bXtKQ7ImfQvSIPZw4cl1ADBzvBlS5+1npJcwus4epmV1AdLLonHKmMuAm4vzhTLa2BLxBTMxwOfBv7t4ntZAJM5tEFO7FRPPeX4kdozpivOx57t4vvYSh2HMmR4nmMT6yzLftYbo7MeHBp919QFoZG5jZqcRr9k+iUFcTU+JtJnqaf8ZTbNZtUGw5VRB3kpl1dPeNGffHE0dflWztGPKIu69MKWLW64mZ2QCiI8Nwosv9IuAxT7HnZlL4PvQm/iiTZpZ/J2aD+b8FDbdtjoYdoT2Bc4niN5iYaWMl0UqwDLjH3X+aVs4GZtaRmCTiAqJH8SriHNiBxN/n3R5TzKWqVHJmyvxsmdnfgJnufnnKmYxozj2K6Ew3kjia7U+MQX4a+G93n5ZWRijOnCqIOygZv3UacZK94QP7kGd0D29cLNOWfHjLiC7iqY092p6GMWfexJjDNIcwJP//bkBnz7g0kZkdTEx5txexIzQTWNjU71AI2XYwzGwIMbFBJ2JWnWp3fzWliA2Zij5ncl6ryc9MUsxvAW5x92UFC/bRHNley/7E91Q7oglyobuvSSliQ6aizKmCuIPM7HfEUcFLxODrI9l6tHUz0cNws6V/DbzLiGanKs8YHJ58qeNFcgHbZnIW1VW9zezTxDCQkcQ5zZlEC8BjqQZrRtK82w74oPHrmPbORaZSyJn8PZLmZ7olSuG1hOLLqV6mO8DMPkEMvP+ku59MnDscn9xmEm3fkyDdD46ZjSN6at0ATDazSWY2Msn1gUc38XIzu84azTJfRDk/TJqjGnKmdk4uyXkHcb71h8D/I1oHppnZSxZTeKXOzA4ys7vN7NiGc13uvil5HTskX0JA7GkoZ04ZP2z4TCc9Im17z1EIZlZpZr81s9PMbLdifC1LIaeOEHeAmV0PjHf3T2RZ1xW4giiK4z26D6fCzH5AnM/6A9EU0RN4j+i08BzRcaEnMbavq7u/p5zN5nyYGBJyYaPlHyN2ij4DXOPuU9LIl5Hn50Tz7QKi5/Bs4DeZf4tmNhY4D7g4xWJT9DlLIWNGzrOIc9ftiSkZ73f3mRnbHEHsqJ+d1imTYs+pgrgDkiOFXwPnuPv0LOvLiCmnnnD3HxQ6X0aO+4kv8EkWEzp/ghjkPIqYTWcVcdmVpe5+nHJuN+czwHPu/q3kfhlxHuTD5BzSj4im1E+7++oUc84jpgysJTp3DSWmlnsNeJKYKPkaYIK7D1PO0s6Y5JyT5KwmWq/GE6d01hI9oO8niswEdx+hnE3wFMehlOqNONE/hZh26BvEgPc9MtbvRXyATk055whiZprGy/cl9tLuI8YBfeTac8qZNeckohfpkEbLG3Ys+yV/E6lNi0VcxmsmyXg5YofiKGLA+C+Jzl/Vyet5knKWdsYk1wDgt8Alyf2OROE+nWji/zMxq86HwETlbPqmI8QdZGb9iD3DY4m9mz8TX5b1xNUDhrr70PQShoZzM0lngHYkRzTJus8BD7j7nqmGpDRymtk+xPR2g4iZcn5PXIJqfbL+VODn7p5txqKCsbgeZzt3X9xoeU+iSforxPUZ90ohXmaeos9ZChkz8uzh7ksaLe9C/L1eCpyhnM1TQdxJSXf7L7L1WoLdiIGlt7n739LM1pSkI4ARF4jt6u5pTyuXVTHmTL4gLwUmEIOHa4lBxXsQzbq/dfevp5dwW5b9ArvTgPfd/ezUgjVSCjlLIWODxj00k5x17n5Geqm21czrmVrOsu1vIg0sJm8+GDgVWE/MpFHd8AVoZkOJk8WbPMU9jYycpxAdARYSTXnL3f19kjF+ZnY6cYkq5Wwhd38FuMrMhhGXzhoGdCea0f+d6CRQNDyjU0Jy9N2NuFbjuamFyqIUcpZCxgaNiuFexHSSVzf5gAIysy7uvj7L69mVlHPqCDEHZvZDohi+QXwJDiCaSR8lrnmY6gDnBlly7keMlZwG3N64uSItJZSzHzHB+MeJSagXAn9y9/nJXm4nT6nna6aMnIcRl1J6mcj6V3df23DUYGad08xbCjlLJGPm1SG2dPBqYtvdPctVbgrFYlL2q4iOcq8QnZJeBJ519+UZ23XyFC+mrYLYQskRwfPE7DRz3X1Nck7pAuI8Qi/gSuAnKR8dtiTnvwKTIdXxXaWScyDwCFsvXHoQMQTkHaIL/vc8xZlJGjSRc1/gbSLnre7+j4ztUxmcXQo5SyFj8v/uQ0wenzlkoWE6tPqMYtne3etTzLk/0et+FTGM6mPE57ucKI4/dfcnM3+H1L5Dd2WPndZ0A75JXI+t4X5Zo/XfJabs6qOcrSrnPUTX+l4Zy/oTzTqvElNMnZRmxhbmfFM5W0/GJNN/Ez0yVyY/D2u0vmFe0P/T+PNV4Jw/Sl7PLhnLehJjN2cB7xPXYU319XR3zVSTg5eA3kmnCjx6RJYl488gjmT+SRzxpEk582s4MWHzSjPbLekN+5q7f9/d9wOeAi42s3bJ3nmx5vyDcraqjBDNufcQBWccsMDMXjGzb5pZd4/m0y8Rp3M2N/dEu9h+wDx3X29br3e4yt3vc/fxye9wocUVQ1Klgthys4hehb81s9PNrNxj2qGNAO6+lGiqqEszJMqZb08DX0w6AnyQFO7dzKxTsv6/iUt8fdyTXd+UKGcbymhm+xHDvV4grsd4InACMRToYuAtM3sO+CoxLWKafg/8i5l9zN3rPZpvO1hMwgFwL3HEOCa9iIm0D1FL6Qb0Ia6UvYiYpeI7xKwqQ4iBpW+SMUBfOUs/JzHpwuvAPLIMFibOh2wEdlfO1pGzRDJ2JY7+JjRa3gnYnxjsPoPY6eyU8ns+kLjW4VIyLrCcsX4EsCntv013DczPmZn1IC4KexwxkHQo0f16JvBjd5+aYrwtlDMv2Rp6Eg4G/ou4qPIa4FngCWLIxWnElHKnK2fp5yyFjI01dKTxRs2iZvYLoK+7H51KsG2zdAG+R1yDdTdiB/gPRDEcB7zo7qkPX1FBbAEzqyDm24M4AbwI2EB8gXcmznW95e5vp5MwKOeuk5zbPJYo3B8nzjO9TZzrfMCLZ8iNcuZJKWTMlNnDlDhSnEX0gn4k5UztPJpJOxI9dscTLUGjiaPGB4D/9RQvot5ABXE7zOwSYjzSSOKLegkxO8kfgYc9YwxNmpQzvywGCp8E7EN8ufyDGDP1bvLBdqLX3FspxlTONpYRPpJzd2AF0QlodcY25cCx7v67dFI2zTIuDmxme7r7u2lnaqCC2IykOe8V4FaiJ9c+xB7j0UTTyevAJHdflObYGeXMe84uxIn+Y4hu7SuIKeT+STTzPODuNcm2qV0AWjnbVsYmctYShXojcZrhfnf/exrZMllcgHwg8Kq7f6RjXJqf72alfRKzmG/EdQ2rmlg3jjivsATYWzlbVc7/AOYDhyX3P0bMV/sjYC4xpmqfNDMqZ9vL2IKcfyYuoVQMOa8kTof8jJjisBdxnjNzm65Ez9jd0s67JVPaAYr5RsyYsggYkdwvBzpkrO+frP+CcraqnM8CV2VZ3p44/1EDTE8zo3K2vYwllnMOcRrkWeKc5lLgNmLHd89km4uB59POmnnTOMTmPUw0S1yZjEmqc/dNSRs+7v4aMYVXRYoZQTnzxmJOyAXA5y2mxiIZTNzOYwzVLOKDXGFmI5Wz9HOWQsYSy7kP8AEw2d2PIgbm30v0Jp8FPGNmVxNHkVVp5cwq7YpcrDfi/IEBJxPTNa0n3tRD2Tol0heT5QOUs3XkTLIeTnSo+D7QM8v6fsB7RJd25WwFOUshY6nkBHoTEwIcn2XdKGJigzXEznGqr2fjmzrVbIfFpVP6E9c7PAU4Mlm1kviCv9/dr08lXAblzA/beoHifyHmUy0jJnp+iJih/2BiT3eYux+mnKWfsxQyllJOiKtWEHPyb0yGXgBbJ+k3s/8ETnT3UWllzEYFMQsz2xc4B/g3YvLmDWy9usHzxMDSwURb/eImnmaXU85dKyne5wFfAA4hjl43Ep0XvufuRdHco5z5UwoZoTRyNtWT1GLO0nnAz9z9+4VP1jQVxCzM7D5iEO5jxEDc7sSA0iHAauDaIvmDuw/lzBsz6wqsz/wQJ3vlHYkJA0YQV0dPNaty5k8pZEwylWzOLNt0BM4AHnT3TQUL1wIqiI0kh/fricP5WRnL+hOTz36ZmFHldHefp5ytI2eS68fEZMkvEOOn1mXZpptnXCC24CFRzraWMcnQmnLu5e7vFDpbi6R9ErPYbsSRzN+Aw5tYXw5UE80Sytl6cp5FnOR/hxgL+WPgVKIpt1OyTWdgGnCQcpZ+zlLI2ApynkJMNt6QsxPwKMnQq2K76QixkeRk8G+JKZHOBf7hjWalMLMriAtaHlL4hFsyKGcemdlkYrzUfxFfNl8iPsgvE1f7fpqYePwOd+/Q1PMoZ+nkLIWMyllgaVfkYrwRXZtfJAaXnkd0Ze6crNudGE/3gHK2jpxEb71vAjc1Wj4cuJ2YHust4lI69ypn6ecshYzKmcLvkXaAYr0RJ6kfInpEvkV0CPl/RPfmKlJsmlDOXZKvG/Cx5OcOJOfXM9afQTQHHaKcrSNnKWRUzsLeypCs3H0BcEYyZOAzxIDyPYhLv/zKi2ACXVDOfHH3tcQVyPGk51vSi8/cvZ6Yd3Gju7+YWkiUs61lTLIpZ4HoHGIOLMVZ7nOhnPlnZlcRkxPfnHaW5ihn/pRCRlDOfFJBFGkBi8vZ1Bd7AVfO/CmFjKCc+aSCKCIiArrahYiICKggioiIACqIIiIigAqiiIgIoIIoIiICqCCKiIgA8P8BKtplcIw3yLsAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Rodando num computador de 7-qbit\n",
    "#device = provider.get_backend('ibmq_casablanca')\n",
    "provedor = IBMQ.get_provider(hub='ibm-q-education', group='uni-sao-paulo-M', project='Quantum-Informat')\n",
    "device = provedor.get_backend('ibmq_casablanca')\n",
    "\n",
    "%qiskit_job_watcher\n",
    "job = execute(circ, backend=device, shots=100, optimization_level=3)\n",
    "\n",
    "results = job.result()\n",
    "resposta = results.get_counts()\n",
    "plot_histogram(resposta)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fbb77666-55f3-4edd-b825-cb9f6c1c9822",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Qiskit v0.34.0 (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": "3.8.10"
  },
  "widgets": {
   "application/vnd.jupyter.widget-state+json": {
    "state": {
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