crypto.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "from qiskit import *\n",
    "%matplotlib inline\n",
    "import math\n",
    "import numpy as np\n",
    "from IPython.display import display, Markdown, Latex"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "def envio(self, sub_q) :\n",
    "    sub_circ = QuantumCircuit(sub_q, name = 'Canal Cuantico')\n",
    "    \n",
    "    sub_circ.id(0)\n",
    "\n",
    "    sub_inst = sub_circ.to_instruction()\n",
    "    self.append(sub_inst,sub_q)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "def print_ind(Alicia_bases,Bob_bases,resA,resB):\n",
    "    head=\"|   | Base | Resultado | \\n\"\n",
    "    sep=\"|:-:|:-:|:-:| \\n\"\n",
    "    Ali=\"| Alicia | <span style=\\\"color:red\\\"> **\"+ Alicia_bases+\"**</span> | <span style=\\\"color:blue\\\">**\" +str(resA)+\"**</span>  | \\n\" \n",
    "    Bob=\"| Bob | <span style=\\\"color:red\\\"> **\"+Bob_bases+\"**</span> | <span style=\\\"color:blue\\\">**\"+str(resB)+\"**</span>  | \\n\" \n",
    "\n",
    "    output=head+sep+Ali+Bob\n",
    "    display(Markdown(output))    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "def print_llarg(Alicia_bases,Bob_bases,resA,resB):\n",
    "    n=len(Alicia_bases)\n",
    "    head=\"|   |\" \n",
    "    sep=\"|:-:|\"\n",
    "    Ali=\"| Bases Alicia |\"\n",
    "    res_Ali=\"| Resultados Alicia |\"\n",
    "    Bob=\"| Bases Bob |\"\n",
    "    res_Bob=\"| Resultados Bob |\"\n",
    "    for i in range(n):\n",
    "        head = head + str(i+1) + \" |\"\n",
    "        sep=sep+\":-:|\"\n",
    "        Ali=Ali+\"<span style=\\\"color:red\\\"> **\"+ Alicia_bases[i]+\"**</span> |\"\n",
    "        res_Ali=res_Ali + \"<span style=\\\"color:blue\\\">**\" +str(resA[i])+\"**</span>  | \" \n",
    "        Bob=Bob+\"<span style=\\\"color:red\\\"> **\"+Bob_bases[i]+\"**</span> |\"\n",
    "        res_Bob=res_Bob+\"<span style=\\\"color:blue\\\">**\"+str(resB[i])+\"**</span> | \" \n",
    "    head=head + \"\\n\"\n",
    "    sep=sep + \"\\n\"\n",
    "    Ali=Ali + \"\\n\"\n",
    "    res_Ali = res_Ali + \"\\n\"\n",
    "    Bob = Bob + \"\\n\"\n",
    "    res_Bob = res_Bob  + \"\\n\"\n",
    "    output=head+sep+Ali+res_Ali+Bob+res_Bob\n",
    "    display(Markdown(output))    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "def print_clave_secreta(Alicia_bases,Bob_bases,resA,resB):\n",
    "    n=len(Alicia_bases)\n",
    "    head=\"|   |\" \n",
    "    sep=\"|:-:|\"\n",
    "    Ali=\"| Bases Alicia |\"\n",
    "    res_Ali=\"| Resultados Alicia |\"\n",
    "    Bob=\"| Bases Bob |\"\n",
    "    res_Bob=\"| Resultados Bob |\"\n",
    "    C_verd=\"<span style=\\\"color:green\\\"> **\"\n",
    "    C_black=\"<span style=\\\"color:black\\\"> ~~\"\n",
    "    for i in range(n):\n",
    "        head = head + str(i+1) + \" |\"\n",
    "        sep=sep+\":-:|\"\n",
    "        Ali=Ali+\"<span style=\\\"color:red\\\"> **\"+ Alicia_bases[i]+\"**</span> |\"\n",
    "        Bob=Bob+\"<span style=\\\"color:red\\\"> **\"+Bob_bases[i]+\"**</span> |\"\n",
    "        if (Alicia_bases[i] == Bob_bases[i]):\n",
    "            res_Bob=res_Bob+C_verd+str(resB[i])+\"**</span> | \" \n",
    "            res_Ali=res_Ali + C_verd +str(resA[i])+\"**</span>  | \" \n",
    "        else:\n",
    "            res_Bob=res_Bob+C_black+str(resB[i])+\"~~</span> | \" \n",
    "            res_Ali=res_Ali + C_black +str(resA[i])+\"~~</span>  | \" \n",
    "    head=head + \"\\n\"\n",
    "    sep=sep + \"\\n\"\n",
    "    Ali=Ali + \"\\n\"\n",
    "    res_Ali = res_Ali + \"\\n\"\n",
    "    Bob = Bob + \"\\n\"\n",
    "    res_Bob = res_Bob  + \"\\n\"\n",
    "    output=head+sep+Ali+res_Ali+Bob+res_Bob\n",
    "    display(Markdown(output))  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "def print_singular_A(bases,res):\n",
    "    n=len(bases)\n",
    "    head=\"|   |\" \n",
    "    sep=\"|:-:|\"\n",
    "    Ali=\"| Bases Alicia |\"\n",
    "    res_Ali=\"| Resultados Alicia |\"\n",
    "    for i in range(n):\n",
    "        head = head + str(i+1) + \" |\"\n",
    "        sep=sep+\":-:|\"\n",
    "        Ali=Ali+\"<span style=\\\"color:red\\\"> **\"+ bases[i]+\"**</span> |\"\n",
    "        res_Ali=res_Ali + \"<span style=\\\"color:blue\\\">**\" +str(res[i])+\"**</span>  | \" \n",
    "    head=head + \"\\n\"\n",
    "    sep=sep + \"\\n\"\n",
    "    Ali=Ali + \"\\n\"\n",
    "    res_Ali = res_Ali + \"\\n\"\n",
    "    stil=\"<style> table, th, td {padding: 10px; border: 1px solid black; border-collapse: collapse; } </style>\\n\"\n",
    "    \n",
    "    output=stil+head+sep+Ali+res_Ali\n",
    "    display(Markdown(output))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "def print_singular_B(bases,res):\n",
    "    n=len(bases)\n",
    "    head=\"|   |\" \n",
    "    sep=\"|:-:|\"\n",
    "    Ali=\"| Bases Bob |\"\n",
    "    res_Ali=\"| Resultados Bob |\"\n",
    "    for i in range(n):\n",
    "        head = head + str(i+1) + \" |\"\n",
    "        sep=sep+\":-:|\"\n",
    "        Ali=Ali+\"<span style=\\\"color:red\\\"> **\"+ bases[i]+\"**</span> |\"\n",
    "        res_Ali=res_Ali + \"<span style=\\\"color:blue\\\">**\" +str(res[i])+\"**</span>  | \" \n",
    "    head=head + \"\\n\"\n",
    "    sep=sep + \"\\n\"\n",
    "    Ali=Ali + \"\\n\"\n",
    "    res_Ali = res_Ali + \"\\n\"\n",
    "    stil=\"<style> table, th, td {padding: 10px; border: 1px solid black; border-collapse: collapse; } </style>\\n\"\n",
    "    \n",
    "    output=stil+head+sep+Ali+res_Ali\n",
    "    display(Markdown(output))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "def circuit_A(Alicia_bases):\n",
    "    qrA = QuantumRegister(1, 'qubit_A')\n",
    "    qrB = QuantumRegister(1,'qubit_B')\n",
    "    cr = ClassicalRegister(2,'m')\n",
    "\n",
    "    cra = ClassicalRegister(1,'resultado_A')\n",
    "    crb = ClassicalRegister(1,'resultado_B')\n",
    "\n",
    "\n",
    "\n",
    "    circuit = QuantumCircuit(qrA,qrB,cra, crb)\n",
    "\n",
    "    #generem estat entrellaçat\n",
    "\n",
    "    circuit.barrier()\n",
    "    circuit.h(0)\n",
    "    circuit.cx(0,1)\n",
    "\n",
    "    #ALICIA\n",
    "    if (Alicia_bases=='Z'):\n",
    "      circuit.measure(qrA[0],cra)\n",
    "    else:\n",
    "      circuit.h(0)\n",
    "      circuit.measure(qrA[0],cra)\n",
    "      circuit.h(0)\n",
    "\n",
    "    circuit.barrier()\n",
    "    envio(circuit,qrB[0:1])\n",
    "    return circuit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "def circuit_B(Bob_bases,circuit):\n",
    "    circuit.barrier()\n",
    "    #BOB\n",
    "    if (Bob_bases[0]=='Z'):\n",
    "      circuit.measure(1,1)\n",
    "    else:\n",
    "      circuit.h(1)\n",
    "      circuit.measure(1,1)\n",
    "      circuit.h(1)\n",
    "\n",
    "    circuit.barrier()\n",
    "    return circuit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "def resultats_ind(circuit):\n",
    "    simulator = Aer.get_backend('qasm_simulator')\n",
    "    result = execute(circuit, backend = simulator, shots= 1).result()\n",
    "    counts = result.get_counts()\n",
    "    key = [k for k, v in counts.items() if v == 1][0]\n",
    "    resA = int(key[0])\n",
    "    resB = int(key[2])\n",
    "    return resA, resB"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "def resultats_llarga(Alicia_bases,Bob_bases):\n",
    "    if len(Alicia_bases)!=len(Bob_bases):\n",
    "        print(\"No tenemos el mismo numero de bases\")\n",
    "    else:\n",
    "        resA=[]\n",
    "        resB=[]\n",
    "        for k in range(len(Alicia_bases)):\n",
    "            qrA = QuantumRegister(1, 'qubit_A')\n",
    "            qrB = QuantumRegister(1,'qubit_B')\n",
    "\n",
    "            cra = ClassicalRegister(1,'resultado_A')\n",
    "            crb = ClassicalRegister(1,'resultado_B')\n",
    "\n",
    "            circuit = QuantumCircuit(qrA,qrB,cra, crb)\n",
    "            #generem estat entrellaçat\n",
    "            circuit.h(0)\n",
    "            circuit.cx(0,1)\n",
    "            #ALICIA\n",
    "            if (Alicia_bases[k]=='Z'):\n",
    "              circuit.measure(qrA[0],cra)\n",
    "            else:\n",
    "              circuit.h(0)\n",
    "              circuit.measure(qrA[0],cra)\n",
    "              circuit.h(0)\n",
    "            #BOB\n",
    "            if (Bob_bases[k]=='Z'):\n",
    "              circuit.measure(qrB[0],crb)\n",
    "            else:\n",
    "              circuit.h(1)\n",
    "              circuit.measure(qrB[0],crb)\n",
    "              circuit.h(1)\n",
    "            simulator = Aer.get_backend('qasm_simulator')\n",
    "            result = execute(circuit, backend = simulator, shots= 1).result()\n",
    "            counts = result.get_counts()\n",
    "            key = [k for k, v in counts.items() if v == 1][0]\n",
    "            resA.append(int(key[0]))\n",
    "            resB.append(int(key[2]))\n",
    "    return resA, resB"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "# Demo Paso a Paso"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Seccion inputs y circuitos\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "#Inputs:\n",
    "Alicia_bases=\"Z\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
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mJibfdr/99hsmk4m1a9eal129epWxY8eyY8eOIu0zJiYGk8lk8fDy8iIqKopt27bd1fsoTsuXL7d1CXbv3JW7CwM323EYlidYr6YHnfq12BsFgmKW+wFc0Hej+/r6snnzZqKioszLdu7cybhx47h06VKR9rljxw4cHR356aef2Lx5Mz/99BOTJ08mISGBLl26kJ2dXfQ3UoxGjx5t6xLsmmHAki0Fh4HoXjmP/Py6H5KOWa+2B5n6tdgbBYJitm3bNjw8PAgKCsq3nZeXF6GhoZQpU8a8bMeOHZhMJho2bFikfe7YsYOaNWsSFhZGaGgoYWFhvPDCC/Tp04fU1FSOHz9+N2+l2CxdutTWJdi1xCOwN9V621sWnzMxUe6N+nXhfbikP1OXvmDrMu7KE++WI+nQZluXYRUKBLfIzs5mypQp1KhRA1dXVxo0aEBcXBy1atXixRdfBCArKws3NzfGjRtnsW5mZiaurq5MnjzZvCwhIYGmTZuyePFiGjZsyEMPPUTDhg35/vvvLdZt0aIFPXv2ND+vV68ew4YNwzAMKlasiMlkokWLFoV6Dzt27LhtiDh27Bju7u5Urly5sL8OsQM/7bPu9s5egaSSlRmlmO09msCYBV3pMdabp96rQP/JNZm1+nXOXDxh69LMbF1j4h+xtH8r77S7NRMuExzY8r7UUNwUCG4xcOBAPvjgAwYPHsy6det45plnePbZZzl48CBNmjQBIDk5matXr9KoUSOLdffs2UNGRobF8m3btrFnzx7mzp3LuHHjWLJkCQBPPfUUR48eBXICxu7du2ncuLF5vfnz51O7dm2ioqLYvHkzmzdvZtGiRQXWf+TIEc6cOUO9evXIzMwkMzOTY8eOMWHCBL766iuio6NxctJc0tLi7GX4oxjuSx9/0PrblJJp274NDJ8Vhr93Lf7P8J2sHn+RqUPiqPCQF7sOxtm6PMA+aiwN9Mlwk5iYGBYsWEBsbCwREREAtGnThu3bt7NixQrzB/b27dsB8gSC3Ml/ucuPHz9OamoqrVu35rvvvsPR0RGAoKAgQkJC+PrrrxkyZAjJycmkp6dbbK9Ro0YcOXKEXr16ERoaWuj3kFvDO++8wzvvvGNeXrFiRZYuXUq3bt2K9Du5H+Li9A/6bh05UzzbPVxM232Q2Eu//mTlyzze6DkGdf57ZNOrgi+9/zHK/HzTziUs2fhPUs/+iWsZN1oGP8ngJ6dRtowbAL0nBtKpxYvsOPADyUf+H5U9Anm9x2xCAlsBsH3/D8xf9w4paftwdHCiUVBbXu76CR7lHrZajf/zaSSNa0TRK+o987J/vGli+ss/UbdaGH8cT2Tm6lc5nLqHbCOLOlVDGdZ1Bn6VqgM5py2yjSzKOLny466luJZxo3fUaLq0HEzaheO8M6cj2dlZPPFuOQBe6TaTdk37WewDIPGPOBasf4/DqXswmRxoUacLI/97gfm1Od+M5MjpZLzK+/J06+F0aTm40P+viptGCG4yceJEOnToYA4DuYKCgnB2dqZ+/fpATiDw8vKiSpUqFu22b9/OI488gre3N5BzugBg/Pjx5jAAOZcjOTk5cerUKfN6YBkwckchbh41KIzcbW3cuJH4+Hi2bt3KqlWrCAoKYsCAARw8WPIO/fbs2WPrEuzW8fPFs93zV+/tigWxj36dcnofx9MO8HjD5/Jt5+Zakf99bjEr3z/PtJd/YvefP7H4+/EWbdbHz2PoU5+w6oMLNK75Dz78Tz/za2WcXBjWbQbLxpxm9ojdnLl4nFmrX7NqjQUxYaLvP8YSM+oYi/73EK4u5ZgU09uizU+7lhEa/AQrxp1laNd/MWPVME6eO0ylin5MfGEdDg6OrJlwmTUTLtOuab88+zh4fBf/O6c9HZoNZMnoEyx+7yjtm/UH4MTZP3lnTge6tBzCirFneOO/FjBv3f8Sl1hy5ppohOAvKSkp/PbbbwwfPjzPa0eOHCEkJAQXFxcg50P31tEByDk6v/V0gY+PT55bmKalpZGZmYm/v795PT8/P3x8fCzWhbyjEAXZsWMHvr6+tGnTxmK5r68vLVq04Msvv+Ttt98u1LZMJlOR9n07t/t93mr69OkFtps+ffo911Iate41lcYdR1gsK+hKgju9/vq/LZ/7+Ppz+aztLjl4a9JnQE4/vPnnksCe+/WUlzbRoHokAOcv59xN0aviI/mu07x2R/PPj1QK4olWL/P9ts8t2nQOHUxg5RAAOjZ/gRU/RXMl/QJuZSuaj54BPCtU5pnIkUz98vlC1VvYGgvyqF99889lnFzo848xvDi1HteuX8W1zEMANAx6nFYhTwLQut7TlCvrzh/HduLjEVCofXy95f8QGvyEOQQA5t/1ph0xBD3S2PxacEAonUMHs27rHCIa/D1/LC4ulmbPWv79vheGYRS6rQLBX1JScr4P9NYJd+np6cTFxdGx49//IBITE80TDHNdvHiR+Ph4Ro4caV62bds2/Pz88uwrJiYGBwcH2rVrB+QNEpATOipXroyvr2+R3seOHTto0KBBnuWurq4AXLt2rUjbk5ItO7P4DuOzinHbUjK4l8sZzTxz4RgBPnXu2G7bvg0s+v59jp5K5kZmBtnZWbjfMtzvWf7vv1Wuf51KuJpxCbeyFdmXso15697h4PFEMm5cxcAgPeOyVWssyPG0P5j9zZskH/l/pGdcgr/C5YUrp3Etk/OB71nB8u+taxk3rmYU/rLv1HOHCPK7/UHc6fNH8fWsZrHM16s6v+5ZXZS3UawUCP5SqVIlAPbt20enTp3Myz/88ENOnDhhnlB46dIlLly4YD66zxUdHX3bCYUZGRlkZGSYRxfOnTvHpEmT6N27t/mUw86dO/N8M1pSUlKR73R2+vRpUlJS6NUr7yHgsmXLAGjdunWht1eUZHknycnJBbaZPn16noB1q2nTpt1zLaXRlj9y7kFws1uP9HPljgzc6fWblS0DV86fwpYH5G9Png3k9MObfy4J7LlfJyyB8znHP/h718SvUhCbdsbQuGbUbdvfyLzO2AVdeaHzh3Ro/jwuzmVZ9csMlsVNKfQ+J/z7vwmv14NRfZbi5lqBLUlfM2r+E4VatzA1AjzkUp5r16+Yn6ddsLxU5uMVL+FVwY/ZI3ZRwc2LP1N/48Wp9Qrdp0ymgs+wV/YI5Fja/tu+5u1eha3Jay2WnTh7EG93y1PPERGRGJ/app9rDsFfHn30UerXr8/EiRP5/PPP+eGHHxgyZAjz5s0DMAeC8uXL4+fnx7Jlyzh69CiHDx9m3LhxzJw5E/h7iP/YsWOkpqbi7u5Or1692LBhAzExMYSFhVG+fHk+/vhjAA4ePMj58+fzzBXw8PAgKSmJtWvXsmXLFlJTC77QPHdCoYuLC1u2bGHLli2sWbOGl19+mYkTJ9KrVy/atm1rnV+YFd16+aYUXhXP4ttuCRmdt1v20q9f7TaLH3b8m7nr3jF/iJ67dJKYjf9k084lZGZd53pWBuUf8sDFuSyHTybx1S8zirSPq9cu4uZakYdcynPq3BGWbJpk1RoBavg34Zc9qzh/+TRXr11i/rfv5qnBtYwbbmXduXAljYXri3bjKM/ylcnOzuLE2T/v2KZz6GA2J33Fhm1fcD0zg4wb6ST+EQtAm0bPsj9lGxsSPicrK5PkI1v5ZstndGw+sEh1FCcFgr84ODiwdOlSQkJCGDJkCAMGDKBSpUoMHToUR0dH84RCgC+++IK0tDRq1KhBu3btcHFxYeDAgbi7uxMYGAj8PQdg5cqVODk50a1bN1599VXCwsL4+eefcXd3B/JemZBr3LhxVKtWje7du9OyZUu2bLnlMPA2crf1/vvv07JlS1q2bEnv3r3ZvXs3s2fP5osvvrjXX1OxeOaZZ2xdgt3ydYdK5a2/3fpVCm4j+bOXft2k5j+Y/vLPHDmZxIvT6vHke+V5fVYY5y+fosGjkZR1KcdrT3/K//1mJE+8W45/rRxKm0ZFm+A3vPts1m2dw5PvlWfs508TXr9nwSsVoUaA7q2HU/XhOvSbVJ2XpjekRZ3OFtt46cnp7P7zJ7q+V4Hhs1oTWqdLkWrw967JEy2H8Monzek6yp0N2/L+Pa3u14AJA9fy9eZPeWacD70mVOX7v9r5elZjwsC1rP51Bk+P9WLykj70b/8BEQ1KTj8xGSVlDK6E6tOnD4mJiezatcvWpdilwgyt1qlTh99//z3fNrVr17ZWSaXOpt9h9faC2xX2lIGLE4x7Glyd7722e5F7mmDSWy9a/FwS2HO/vvmUgZQ87v7Q9L9ts2+NEBQgISHBfLpApCRqVQMqlbPe9trXs30YEJH7T4EgH5cvX2bfvn1FvhdAccm98+CdHhrseTC5OMGzLcEap/wDK0GkBmNEHki6yiAf5cqVIysry9ZlAHDo0CGqVauWb5v58+fTv3//+1OQFUVGRtq6BLtX/WH479CcKw7uFAsLOlXwcAUYGAEOOkywCvVrsTcKBHbCz8+P+Pj4fNsUFBhKqk8//dTWJZQKLaqDizP8Zwuk3yjaujUrQ9/HoJxr8dT2IFK/FnujQGAnypQpQ9OmTW1dRrEYMmSI/nhaScOqUK0SrNqe87XI2QWcRapYNmfOQMsgXWZoberXYm8UCMTmYmNjbV1CqVLxIegXlvN9BFsPwqHTcOxczncTOJjAq3zOfQaC/aCuPzjqFEGxUL8We6NAIFJKuT8E7eraugoRsRc6NhAREREFArG9gm7eImKP1K/F3uiUgdjcl19+aTe3eRUprJLar8s/XHAbsR1b/v9RIBCbGzNmTIn8wylyL0pqv671uK0rkJJKpwxEREREgUBEREQUCKQEmDVrlq1LELE69WuxNwoEYnMhISG2LkHE6tSvxd4oEIjNRURE2LoEEatTvxZ7o0AgIiIiuuxQilft2rULbDNmzJhCtRMpKdSvpTTSCIHY3NixY21dgojVqV+LvVEgEBEREQUCERERUSAQERERFAhEREQEBQIRERFBgUBERERQIBAREREUCOQuvfbaa/j7++PkpHtbSckTGxtLSEgIQUFBvPDCC2RlZdm6JJEST4FA7krPnj1JSEiwdRkieWRnZ/PCCy+wdOlSDhw4wMWLF1m0aJGtyxIp8RQI5K6EhYVRuXJlW5chkkd8fDx+fn4EBwcDMHDgQJYvX27jqkRKPo33ikiJcOrMeS5eupJn+YFDx277c7Wqvjg65D2mSUlJoUqVKubnVatW5ejRo1auVqT0USAQkRIhMyuL+UvXkZWdbbF8zn++yfNz0/q1CAp85LbbMQyj+IoUKcV0ykBESgS/h71oF960wHaeFcvzxOMt7/h6lSpVLEYEjhw5gr+/v1VqFCnNFAhEpMRo3aw+gf53nptiAp7p0gYXlzJ3bNO0aVNSUlJISkoCYO7cuTz99NPWLlWk1FEguElsbCwmk4nY2FjzsilTprBq1Sqr76t///4EBgZafbs3O3/+PGXLlsVkMpGcnGzVbQ8ePBh/f3+ysrLw9/dn6NChVt2+PJgcHBx4pnMkZco43/b18BYN8g0MAI6OjsyZM4cePXpQvXp1ypUrR58+fYqjXJFSRXMICjBlyhQ6dOhA165dbV1KkcXExHDt2jUAFixYwKRJk6y27c8+++yOr6Wknsa9fDnKuZW12v7kweHpXoEn27Zi2bo4i+W+D3vxj7CCTykAPP744+YRAhEpnBI7QpCRkWHrEuze/Pnz8fX1pXHjxnzxxRf35eYs2dnZLFmzkc9XfFfs+5LSq0m9mgTXCDA/d3R04L+6tMHJydGGVYmUbiUiEIwdOxaTyURiYiJdunShQoUKtG3blmvXrjFq1CiCgoJwcXHB39+fN998M09YmDFjBnXr1sXNzQ13d3caNGjAnDlzzK9HRkYSGRmZZ793Wp4rMDCQkydPsnDhQkwmEyaTif79+wNw4MAB+vXrx6OPPkrZsmUJCAigb9++nDhxIs92Vq5cSd26dXFxcaFmzZoWtd3s1KlTPP/88/j4+ODi4kLt2rWJjo6+q1nTSUlJxMfH07t3bwYMGMDx48f57rvi/5BO/P0P0s5eILx5/WLfl5ReJpOJp9uHU+6hnFGm9uHNqeztaeOqREq3EnXKoGvXrvTv358RI0Zw48YNOnfuTEJCAu+++y5NmjRh9+7djB49mgMHDrBy5UogZ1j89ddf57333iM8PJzr16/z+++/c+7cuXuuZ+XKlURFRREaGsqoUaMA8Pb2BuD48eP4+voybdo0PD09SUlJYerUqYSFhZGUlISLiwsA3377Ld27dycqKoqJEydy5coVxowZQ3p6Oo6Ofx/tXLlyhfDwcE6ePMn48eMJCgriq6++Yvjw4Rw7doyPPvqoSLXPnz8fyJmrULlyZf7nf/6HBQsW0LFjx3v+vdxJdnY2P/y6ncrengTXDCy2/ciDoZxbWZ7uGM7P8bsIa1bP1uWIlHolKhC89NJLvPXWWwAsXryYjRs3sm7dOjp06ABA27Zt8fLyom/fvmzdupXmzZvzyy+/UK9ePcaOHWveTm77e9WoUSOcnZ3x9vYmNDTU4rXw8HDCw8PNzzMzMwkLCyMgIIB169aZ5xyMHj2awMBA1q5da77vf6tWrahRowZ+fn7m9RcuXMjevXst3m/79u25evUq0dHRjBgxAl9f30LVnZmZyaJFi2jWrJn5bm1dunRh9erVnDt3Dg8Pj0Jt5+3JswvV7nbe+fD/3vW6IrdSfxK5O5PeerHQbUvEKYNc3bp1M/+8du1afHx8iIqKIjMz0/xo3749AHFxOROOmjVrRmJiIkOHDmXDhg1cunTpvtSamZnJRx99REhICG5ubjg7OxMQkHPOc+/evUDOUX9CQgLdu3e3+BKggIAAWrVqZbG92NhYvLy88oSZvn37kpmZyS+//FLo2r799ltSU1PNpzcgZ6QgIyODmJiYor5VERF5AJSoEYKbj4BPnjzJyZMncXa+/eVHaWlpQM4H5vXr15k3bx6fffYZDg4OtG3blqlTp5qPjovDO++8w/Tp03n33XcJCwujYsWKZGdnExoaSnp6OgDnzp3DMIzb3vO/cuXKHDp0yPz87Nmztx0ByF125syZQtc2f/58nJ2d6dixI+fPnwegZcuWeHp6smDBAl5++eVCbacoyXLHnv385+tN9O76D+rWqlbo9UREpGQoUYHAZDKZf/by8sLPz4/Vq1fftm3uh6zJZGLQoEEMGjSICxcusHHjRkaOHEmHDh04fPgwJpMJV1dXLly4kGcbZ86cwcvL665qXbx4MX379rU4VfHHH39YtPHw8MBkMpGamppn/VuXeXp6kpiYmKdd7iTFwtZ55swZvv76a27cuMGjjz6a5/WzZ8+SlJRUqLB0N6cMFq3aUOR1RESkeNjtKYObderUidTUVJydnWnatGmex+1uRVqxYkW6devGoEGDOHr0qPnoOCAggP3791tcnbB//37z0H5+XFxczEf8N7t69Wqe0Yt58+ZZPHdzc6Np06YsX76czMxM8/LDhw/z66+/WrSNjIwkLS0tz5UAixYtwsnJiccee6zAWgH+/e9/c/36dT7++GM2bdpk8ViyZAnw94RDERGRXCVqhOBmzz33HJ9//jnt2rVjxIgRNG7cmOzsbA4fPsy6deuYMGECwcHBDBo0iHLlytGqVSt8fHw4dOgQM2fOpHnz5ubJc7169WL27Nn069ePgQMHcuLECSZNmkSlSpUKrCM4OJi4uDi++eYbfHx8qFSpEoGBgXTs2JGFCxcSEhJCnTp1WL9+/W1HM95//306depEp06deOWVV7h8+TJjx47Fx8fHol3//v355JNPePbZZ/nggw8ICgpizZo1zJs3jzfeeKPQEwrnz5+Pv78/w4YNw+E23wQXHR3NokWLmDRpksVVDrdTmGSZnZ3NtLlLcXJ05NUB3XG4aZRHRETsiFECjBkzxgCMS5cuWSzPyMgwJkyYYAQHBxsuLi5GxYoVjQYNGhhvvvmmcfbsWcMwDGPhwoVGZGSk4e3tbZQpU8aoWrWqMXjwYCM1NdViW3PnzjVq1qxpuLq6Go0aNTI2bNhgREREGBEREeY2mzZtMgBj06ZN5mW7du0yWrVqZZQtW9YAjH79+hmGYRhnzpwxevXqZXh6ehrly5c3nnzySePPP/80AGPMmDEW+16+fLkRHBxsODs7G0FBQcacOXOMfv36GQEBARbtTp48aQwYMMDw9vY2nJ2djVq1ahnTpk0zsrOzC/V73LFjhwEYo0aNumObuXPnGoDx9ddfF2qbBdn+2z7jrUmfGbuTD1pleyIiYhsmw9B3hcrdS7+Wwfbf9tOySYhGB0RE7JgCgYiIiJTcOQSSV1ZWVr63MXZwcLjtvAEREZGC6NPDjlSvXh1nZ+c7Pp5//nlblygiInZKIwR2ZM2aNfl+C2RhrpoQERG5Hc0hEBEREZ0yEBEREQUCERERQYFAREREUCAQERERFAhEREQEBQIRERFBgUBERERQIBAREREUCERERAQFAhEREUGBQERERFAgEBERERQIREREBAUCERERQYFAREREUCAQERERFAhEREQEBQIRERFBgUBERERQIBAREREUCOQuvfbaa/j7++Pk5GTrUkRExApMhmEYti5C7M/PP/9MUFAQ/v7+ZGZm2rocERG5RwoEck+cnJwUCERESgGdMhAREREFAhEREVEgEBERERQIREREBAUCC7GxsZhMJmJjY83LpkyZwqpVq6y+r/79+xMYGGj17QIEBgZiMpnMj4ceeojg4GAmTpzI9evXrbKPwYMH4+/vT1ZWFv7+/gwdOtQq2xUREdvQReQFmDJlCh06dKBr1662LqVI2rRpw8SJEwG4fPkymzZtYtSoUZw8eZKPP/74nrf/2Wef3fE1wzAwmUz3vA8REbl/SmwgyMjIwMXFxdZl2C1PT09CQ0PNz6Oiojhw4ABLliyxSiDIz4pvf8LFxZkuj7cs1v2IiIj1lIhTBmPHjsVkMpGYmEiXLl2oUKECbdu25dq1a4waNYqgoCBcXFzw9/fnzTffJCMjw2L9GTNmULduXdzc3HB3d6dBgwbMmTPH/HpkZCSRkZF59nun5bkCAwM5efIkCxcuNA+/9+/fH4ADBw7Qr18/Hn30UcqWLUtAQAB9+/blxIkTebazcuVK6tati4uLCzVr1rSo7WanTp3i+eefx8fHBxcXF2rXrk10dDTWulVEhQoVuHHjhlW2dSdpZy+QsHsvJjRCICJiT0rUCEHXrl3p378/I0aM4MaNG3Tu3JmEhATeffddmjRpwu7duxk9ejQHDhxg5cqVAMTExPD666/z3nvvER4ezvXr1/n99985d+7cPdezcuVKoqKiCA0NZdSoUQB4e3sDcPz4cXx9fZk2bRqenp6kpKQwdepUwsLCSEpKMo9ufPvtt3Tv3p2oqCgmTpzIlStXGDNmDOnp6Tg6Opr3deXKFcLDwzl58iTjx48nKCiIr776iuHDh3Ps2DE++uijItVuGIb5hkFXrlxh48aNxMTEmANNcdm4eTtOjg6Et6hfrPsRERHrKlGB4KWXXuKtt94CYPHixWzcuJF169bRoUMHANq2bYuXlxd9+/Zl69atNG/enF9++YV69eoxduxY83Zy29+rRo0a4ezsjLe3t8XwO0B4eDjh4eHm55mZmYSFhREQEMC6devMcw5Gjx5NYGAga9euNd/3v1WrVtSoUQM/Pz/z+gsXLmTv3r0W77d9+/ZcvXqV6OhoRowYga+vb6FrX7FiBc7OzhbLunXrxrRp0wq9jbcnzy5021tNmLHortcVERHrmPTWi4VuWyJOGeTq1q2b+ee1a9fi4+NDVFQUmZmZ5kf79u0BiIuLA6BZs2YkJiYydOhQNmzYwKVLl+5LrZmZmXz00UeEhITg5uaGs7MzAQEBAOzduxfIOTJPSEige/fuFl8CFBAQQKtWrSy2Fxsbi5eXV54w07dvXzIzM/nll1+KVN/jjz9OfHw88fHx/Pjjj0yZMoXvv/+eHj16WO0UhIiIlB4laoTg5iPgkydPcvLkyTxHubnS0tKAnA/M69evM2/ePD777DMcHBxo27YtU6dOJTg4uNhqfeedd5g+fTrvvvsuYWFhVKxYkezsbEJDQ0lPTwfg3LlzGIZB5cqV86xfuXJlDh06ZH5+9uzZ244A5C47c+ZMkerz8PCgadOm5uetW7cmOzubkSNH8u2339KxY8cCt1GUZJl29gJT53xJWNN6dH48tOAVRESkRClRgeDmS9W8vLzw8/Nj9erVt22b+yFrMpkYNGgQgwYN4sKFC2zcuJGRI0fSoUMHDh8+jMlkwtXVlQsXLuTZxpkzZ/Dy8rqrWhcvXkzfvn0tTlX88ccfFm08PDwwmUykpqbmWf/WZZ6eniQmJuZplztJ8W7rvFlISAgAu3btKlQguJtTBj/F7+Kn+F1FXk9ERKzPbk8Z3KxTp06kpqbi7OxM06ZN8zz8/f3zrFOxYkW6devGoEGDOHr0KOfPnwdyhuj3799vcXXC/v37zUP7+XFxcTEf8d/s6tWreUYv5s2bZ/Hczc2Npk2bsnz5cotvBDx8+DC//vqrRdvIyEjS0tL47rvvLJYvWrQIJycnHnvssQJrLciuXTkf1A8//PA9b0tEREqXEjVCcLPnnnuOzz//nHbt2jFixAgaN25MdnY2hw8fZt26dUyYMIHg4GAGDRpEuXLlaNWqFT4+Phw6dIiZM2fSvHlzPDw8AOjVqxezZ8+mX79+DBw4kBMnTjBp0iQqVapUYB3BwcHExcXxzTff4OPjQ6VKlQgMDKRjx44sXLiQkJAQ6tSpw/r16287mvH+++/TqVMnOnXqxCuvvMLly5cZO3YsPj4+Fu369+/PJ598wrPPPssHH3xAUFAQa9asYd68ebzxxhtFmlAIOacgtmzZAkB6ejpbt25lwoQJ+Pv78/TTTxdqG4VNll9+s4ndyQcZ+dKzlHd7qEh1iohICWGUAGPGjDEA49KlSxbLMzIyjAkTJhjBwcGGi4uLUbFiRaNBgwbGm2++aZw9e9YwDMNYuHChERkZaXh7extlypQxqlatagwePNhITU212NbcuXONmjVrGq6urkajRo2MDRs2GBEREUZERIS5zaZNmwzA2LRpk3nZrl27jFatWhlly5Y1AKNfv36GYRjGmTNnjF69ehmenp5G+fLljSeffNL4888/DcAYM2aMxb6XL19uBAcHG87OzkZQUJAxZ84co1+/fkZAQIBFu5MnTxoDBgwwvL29DWdnZ6NWrVrGtGnTjOzs7CL9PgMCAgzA/ChTpoxRvXp1Y8iQIcaxY8eKtK2CnD5z3nh78mzj6x82W3W7IiJyf5kMQ1PO5e7tPXiUVd/9zMt9ntLogIiIHVMgkHuWnZ2Ng0OJnY4iIiKFoEBgR7KysvK9h4CDg4M+mEVE5K7o08OOVK9eHWdn5zs+nn/+eVuXKCIidqrEXmUgea1ZsybPFzvdrDBXTYiIiNyOThmIiIiIThmIiIiIAoGIiIigQCAiIiIoEIiIiAgKBCIiIoICgYiIiKBAICIiIigQiIiICAoEIiIiggKBiIiIoEAgIiIiKBCIiIgICgQiIiKCAoGIiIigQCAiIiIoEIiIiAgKBCIiIoICgYiIiKBAICIiIigQiIiICAoEIiIiggKBiIiIoEAgIiIiKBCIiIgI8P8BAerEjpig0soAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 664.676x264.88 with 1 Axes>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "circuit=circuit_A(Alicia_bases)\n",
    "circuit.draw(output=\"mpl\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "#Inputs B\n",
    "Bob_bases=\"X\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 965.676x264.88 with 1 Axes>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "circuit = circuit_B(Bob_bases,circuit)\n",
    "circuit.draw(output='mpl')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Sección Resultados\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/markdown": [
       "|   | Base | Resultado | \n",
       "|:-:|:-:|:-:| \n",
       "| Alicia | <span style=\"color:red\"> **Z**</span> | <span style=\"color:blue\">**0**</span>  | \n",
       "| Bob | <span style=\"color:red\"> **X**</span> | <span style=\"color:blue\">**0**</span>  | \n"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "resA, resB = resultats_ind(circuit)\n",
    "print_ind(Alicia_bases,Bob_bases,resA,resB)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "source": [
    "# Demo cadena intermedia"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "Alicia_bases=\"XXZZ\"\n",
    "Bob_bases=\"XXZX\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/markdown": [
       "|   |1 |2 |3 |4 |\n",
       "|:-:|:-:|:-:|:-:|:-:|\n",
       "| Bases Alicia |<span style=\"color:red\"> **X**</span> |<span style=\"color:red\"> **X**</span> |<span style=\"color:red\"> **Z**</span> |<span style=\"color:red\"> **Z**</span> |\n",
       "| Resultados Alicia |<span style=\"color:green\"> **1**</span>  | <span style=\"color:green\"> **0**</span>  | <span style=\"color:green\"> **0**</span>  | <span style=\"color:black\"> ~~1~~</span>  | \n",
       "| Bases Bob |<span style=\"color:red\"> **X**</span> |<span style=\"color:red\"> **X**</span> |<span style=\"color:red\"> **Z**</span> |<span style=\"color:red\"> **X**</span> |\n",
       "| Resultados Bob |<span style=\"color:green\"> **1**</span> | <span style=\"color:green\"> **0**</span> | <span style=\"color:green\"> **0**</span> | <span style=\"color:black\"> ~~0~~</span> | \n"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "resA, resB = resultats_llarga(Alicia_bases,Bob_bases)\n",
    "print_clave_secreta(Alicia_bases,Bob_bases,resA,resB)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "# Demostracion Publico"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Seccion Alicia"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "Alicia_bases=\"XXXXZZZZXXXZ\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "resAL, resBL = resultats_llarga(Alicia_bases,Bob_bases)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/markdown": [
       "<style> table, th, td {padding: 10px; border: 1px solid black; border-collapse: collapse; } </style>\n",
       "|   |1 |2 |3 |4 |5 |6 |7 |8 |9 |10 |11 |12 |\n",
       "|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|\n",
       "| Bases Alicia |<span style=\"color:red\"> **X**</span> |<span style=\"color:red\"> **X**</span> |<span style=\"color:red\"> **X**</span> |<span style=\"color:red\"> **X**</span> |<span style=\"color:red\"> **Z**</span> |<span style=\"color:red\"> **Z**</span> |<span style=\"color:red\"> **Z**</span> |<span style=\"color:red\"> **Z**</span> |<span style=\"color:red\"> **X**</span> |<span style=\"color:red\"> **X**</span> |<span style=\"color:red\"> **X**</span> |<span style=\"color:red\"> **Z**</span> |\n",
       "| Resultados Alicia |<span style=\"color:blue\">**0**</span>  | <span style=\"color:blue\">**1**</span>  | <span style=\"color:blue\">**1**</span>  | <span style=\"color:blue\">**1**</span>  | <span style=\"color:blue\">**0**</span>  | <span style=\"color:blue\">**1**</span>  | <span style=\"color:blue\">**0**</span>  | <span style=\"color:blue\">**0**</span>  | <span style=\"color:blue\">**1**</span>  | <span style=\"color:blue\">**1**</span>  | <span style=\"color:blue\">**0**</span>  | <span style=\"color:blue\">**0**</span>  | \n"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print_singular_A(Alicia_bases,resAL)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![PIPE](quantumchannel.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Seccion Bob"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "Bob_bases=\"XZZZZXXZXXXX\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/markdown": [
       "<style> table, th, td {padding: 10px; border: 1px solid black; border-collapse: collapse; } </style>\n",
       "|   |1 |2 |3 |4 |5 |6 |7 |8 |9 |10 |11 |12 |\n",
       "|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|\n",
       "| Bases Bob |<span style=\"color:red\"> **X**</span> |<span style=\"color:red\"> **Z**</span> |<span style=\"color:red\"> **Z**</span> |<span style=\"color:red\"> **Z**</span> |<span style=\"color:red\"> **Z**</span> |<span style=\"color:red\"> **X**</span> |<span style=\"color:red\"> **X**</span> |<span style=\"color:red\"> **Z**</span> |<span style=\"color:red\"> **X**</span> |<span style=\"color:red\"> **X**</span> |<span style=\"color:red\"> **X**</span> |<span style=\"color:red\"> **X**</span> |\n",
       "| Resultados Bob |<span style=\"color:blue\">**0**</span>  | <span style=\"color:blue\">**0**</span>  | <span style=\"color:blue\">**1**</span>  | <span style=\"color:blue\">**1**</span>  | <span style=\"color:blue\">**0**</span>  | <span style=\"color:blue\">**1**</span>  | <span style=\"color:blue\">**0**</span>  | <span style=\"color:blue\">**0**</span>  | <span style=\"color:blue\">**1**</span>  | <span style=\"color:blue\">**1**</span>  | <span style=\"color:blue\">**0**</span>  | <span style=\"color:blue\">**0**</span>  | \n"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print_singular_B(Bob_bases,resBL)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Comprobando clave secreta"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/markdown": [
       "|   |1 |2 |3 |4 |5 |6 |7 |8 |9 |10 |11 |12 |\n",
       "|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|\n",
       "| Bases Alicia |<span style=\"color:red\"> **X**</span> |<span style=\"color:red\"> **X**</span> |<span style=\"color:red\"> **X**</span> |<span style=\"color:red\"> **X**</span> |<span style=\"color:red\"> **Z**</span> |<span style=\"color:red\"> **Z**</span> |<span style=\"color:red\"> **Z**</span> |<span style=\"color:red\"> **Z**</span> |<span style=\"color:red\"> **X**</span> |<span style=\"color:red\"> **X**</span> |<span style=\"color:red\"> **X**</span> |<span style=\"color:red\"> **Z**</span> |\n",
       "| Resultados Alicia |<span style=\"color:green\"> **0**</span>  | <span style=\"color:black\"> ~~1~~</span>  | <span style=\"color:black\"> ~~1~~</span>  | <span style=\"color:black\"> ~~1~~</span>  | <span style=\"color:green\"> **0**</span>  | <span style=\"color:black\"> ~~1~~</span>  | <span style=\"color:black\"> ~~0~~</span>  | <span style=\"color:green\"> **0**</span>  | <span style=\"color:green\"> **1**</span>  | <span style=\"color:green\"> **1**</span>  | <span style=\"color:green\"> **0**</span>  | <span style=\"color:black\"> ~~0~~</span>  | \n",
       "| Bases Bob |<span style=\"color:red\"> **X**</span> |<span style=\"color:red\"> **Z**</span> |<span style=\"color:red\"> **Z**</span> |<span style=\"color:red\"> **Z**</span> |<span style=\"color:red\"> **Z**</span> |<span style=\"color:red\"> **X**</span> |<span style=\"color:red\"> **X**</span> |<span style=\"color:red\"> **Z**</span> |<span style=\"color:red\"> **X**</span> |<span style=\"color:red\"> **X**</span> |<span style=\"color:red\"> **X**</span> |<span style=\"color:red\"> **X**</span> |\n",
       "| Resultados Bob |<span style=\"color:green\"> **0**</span> | <span style=\"color:black\"> ~~0~~</span> | <span style=\"color:black\"> ~~1~~</span> | <span style=\"color:black\"> ~~1~~</span> | <span style=\"color:green\"> **0**</span> | <span style=\"color:black\"> ~~1~~</span> | <span style=\"color:black\"> ~~0~~</span> | <span style=\"color:green\"> **0**</span> | <span style=\"color:green\"> **1**</span> | <span style=\"color:green\"> **1**</span> | <span style=\"color:green\"> **0**</span> | <span style=\"color:black\"> ~~0~~</span> | \n"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print_clave_secreta(Alicia_bases,Bob_bases,resAL,resBL)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "La clave secreta compartida es: [0, 0, 0, 1, 1, 0]\n"
     ]
    }
   ],
   "source": [
    "clave=[]\n",
    "for k in range(len(Alicia_bases)):\n",
    "    if Alicia_bases[k]==Bob_bases[k]:\n",
    "        clave.append(resAL[k])\n",
    "print(\"La clave secreta compartida es:\",clave)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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