ft-pauli-measurement.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Constructing fault-tolerant weight-6 Pauli measurements\n",
    "\n",
    "The surface code is beautifully simple. We only need to measure weight-4 Pauli operators, and this makes (strictly) fault tolerant circuits relatively easy to find. However, some of the codes we've heard about require higher weight checks, so let's explore some weight-6 Pauli measurement circuits.\n",
    "\n",
    "Our starting point is the circuit proposed by Chamberland, Kubica, Yoder, and Zhu (arXiv:1911.00355) for measuring color code stabilizers (see Figure 3b of their paper). \n",
    "\n",
    "This circuit is 1-fault-tolerant in the sense that if any single location fails, we can examine the flag outcomes and find a local (to the check) correction such that there is at most one error remaining on the data qubits. Our first goal is to verify that fact."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1424.12x1047.48 with 1 Axes>"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from qiskit import QuantumCircuit\n",
    "\n",
    "qc = QuantumCircuit(16, 16)  # 6 extra qubits we'll use later\n",
    "# Prepare aux. system\n",
    "qc.reset(6)\n",
    "qc.reset(7)\n",
    "qc.reset(8)\n",
    "qc.reset(9)\n",
    "qc.h(9)\n",
    "qc.cx(9, 8)\n",
    "qc.cx(9, 7)\n",
    "qc.cx(9, 6)\n",
    "qc.barrier()\n",
    "# Interact with code block\n",
    "qc.cx(6, 0)\n",
    "qc.cx(7, 2)\n",
    "qc.cx(8, 4)\n",
    "qc.cx(6, 1)\n",
    "qc.cx(7, 3)\n",
    "qc.cx(8, 5)\n",
    "qc.barrier()\n",
    "# Measure aux. system\n",
    "qc.cx(9, 6)\n",
    "qc.cx(9, 7)\n",
    "qc.cx(9, 8)\n",
    "qc.h(9)\n",
    "qc.id(6)\n",
    "qc.id(7)\n",
    "qc.id(8)\n",
    "qc.id(9)\n",
    "qc.measure(6, 6)\n",
    "qc.measure(7, 7)\n",
    "qc.measure(8, 8)\n",
    "qc.measure(9, 9)\n",
    "qc.draw(output='mpl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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r3EsFdJOsqKhImzdv1gMPPHDZY4WFhUpISFBEhOee9oMHD9bHH3+sgQMHmh0TQADJz8+3OgJQre+O+nHsI/4bG/bEvAcAgBG1se78dSxZXCKdOe+fsb0F9OWWRUVFkqSWLVsatp8+fVp5eXkaMmRIxbb+/fvX6TVcXHMCBI2xY8dWu09WVla1+2VlZfkqkk888bZnYSrmK+foctMw3fkL44Ky1d0ZqLLHn3zH+PO996fp65UsVhssgnXeAwCgroKxNtrp/cDAh6fphh89Ydjmq+PUmGuv08mj/l2cLKDPJIuJiZEkFRQUGLZPmTJF+/btY9F+AEBQcl8457exS/04NgAAAIJboB+nusrKynx4byxzud1u3XDDDdq3b5+mTp2q1q1bKycnRwsWLFBhYaFWrFihvn37Gp6TkpKiMWPGaNiwYRalBmCVbdu2VbtPXFyctm7dWuU+3bt391Uknyj/hKW6T2gQPL4/Jk36oGb7lv9dXPpJXGWev0tqGV23XLCfYJ33AACoq2CsjXZ6P/DlDum9lTXbtzbHqY0aSP87rPY3mEpJSZEk5ebm1mj/gD6TLCQkRNnZ2UpISFBGRoZGjBihmJgYZWZmKjQ0tGLRfgCoqfHjx1sdAajWtY2lCD8smNAg1DM2nIV5DwAAI2pj3bVp5p9x2zYz5w7sAb0mmSTFxsZq8eLFhm0PP/yw4uPj1bBhQ4tSAQhUaWlpVkcAqhUSIl3fRlr7jW/H7dHWMzachXkPAAAjamPdtW4qNY/yLLTvSz3a+na8ygTlofCaNWsuW4/sxRdfVJs2bfTll19q1KhRatOmjXbu3GlRQgB2FRcXZ3UEoEZuifX9mAO6+n5M2B/zHgAARtTGugsJkfp38e2YEWHSjR19O2Zlgq5JVlJSooKCAvXq1cuwfcKECSoqKtLZs2dVXFysoqIide7c2aKUAADUT4cYz9lkvnJ9G6njNb4bDwAAAM40IFa6+irfjfejHlJkuO/Gq0rAX255qaioKJWWllodAwAAv3K5pLSbpF0HpFP1vNFPowbSAzeZs84DAAAAgltkuDS8nzTjc6m+d4rsECOlmHiPhKBrkgFAfZTf/QQIBE0aSumpngOQsxeuvE91dwuKCJP+M0WKZhlPx2LeAwDAiNpYf7EtpWF9pOzVle9T3XHqNY2lkQPNXTM36C63BID6mDFjhtURgFrpECONuc2zQGptNY+SMm/jMkunY94DAMCI2ugbA2Klh/vX7a7sXVtIvxgkNTb5g1yaZADgJSMjw+oIQK21bS49e6fnVPTw0Or3Dw+Vkrt7ntOuuf/zwd6Y9wAAMKI2+k7vjtLzd0mJbaWarOzRONJzBlrGDz3fm43LLQHAS25urtURgDqJCJPu7S0N6iGt2S3t2C99e1g6ctLz+NWNPM20Li08dwdq1MDavLAP5j0AAIyojb519VXSYwOl4hJp1S7pm0PS3sNSyVnP4y2jpbbNpLjrPM20sBp86OsvNMkAAAgijRpIA7t5vqSLaz2Mu8+6TAAAAEDzKGlI4sWfy49Tn7/LmjxXwuWWAAAAAAAAcDyaZADgZevWrVZHAABTMe8BAGBEbXQummQA4GX27NlWRwAAUzHvAQBgRG10LppkAOBl3LhxVkcAAFMx7wEAYERtdC6aZAAAAAAAAHA8mmQAAAAAAABwPJpkAOBl+vTpVkcAAFMx7wEAYERtdC6aZADgJSEhweoIAGAq5j0AAIyojc5FkwwAvCQnJ1sdAQBMxbwHAIARtdG5aJIBAAAAAADA8WiSAYCXPn36WB0BAEzFvAcAgBG10blokgGAl9WrV1sdAQBMxbwHAIARtdG5aJIBAAAAAADA8WiSAQAAAAAAwPFokgGAl5ycHKsjAICpmPcAADCiNjoXTTIAAAAAAAA4Hk0yAPAybNgwqyMAgKmY9wAAMKI2OhdNMgAAAAAAADgeTTIAAAAAAAA4Hk0yAPCSmZlpdQQAMBXzHgAARtRG56JJBgBexowZY3UEADAV8x4AAEbURueiSQYAXgYOHGh1hKBWViYdOSntPijtOiDtPy653VanApyNeQ8AACNqo3OFWR0AAOzk4MGDVkcIOmVl0q6D0rICafv30smzxscjwqSO10g3d5GubyOF8vENYCrmPQAAjKiNzkWTDADgN4dOSLNWSDsPVL7P2QvStn2er5jG0vB+UudrzcsIAAAAABKXWwKAQXx8vNURgsb6Qmnyh1U3yC516IT0p4XSx5s8Z6AB8D/mPQAAjKiNzkWTDAC8zJkzx+oIQWF9ofSPpdL50to/t0zSxxulBRt8HgvAFTDvAQBgRG10LppkAODlpZdesjpCwDt0QnpnuafZVZlpD3q+qrIwX8rf69NoAK6AeQ8AACNqo3MFRZPM7XZr6tSp6tq1qyIjI5WUlKS8vDx169ZN6enpVscDEECys7OtjhDQyso8a5DV5QyyK3lvpXT6nG/GAnBlzHsAABhRG50rKJpkI0eO1IQJEzRq1Ch99NFHSktL0/Dhw7Vr1y717t3b6ngA4Bi7D9ZuDbLqHD8trdrlu/EAAAAAoDIBf3fLWbNmaebMmcrNzVVycrIkKTU1VevWrdPcuXPVq1cvixMCgHMs+9r3Y35RIA3sJrlcvh8bAAAAAMoF/JlkEydO1ODBgysaZOW6dOmi8PBwJSYm6siRI7rrrrsUGxurpKQkDRo0SDt27LAoMQA7y8vLszpCwCork7bv8/24B09IR0/5flwAHsx7AAAYURudK6CbZEVFRdq8ebMeeOCByx4rLCxUQkKCIiIi5HK59OSTT6qgoEAbNmzQXXfdpREjRliQGIDd5efnWx0hYB09JZWc9c/Y3x72z7gAmPcAALgUtdG5Avpyy6KiIklSy5YtDdtPnz6tvLw8DRkyRJLUtGlT3XbbbRWP9+/fX1OmTKnRa7i4vgcIGmPHjq12n6ysrGr3y8rK8lUkn3jibc99JK2er1p26acf/+ZLw7bq7mBZ2eNPvmP8+eGRY7Rx4Z/rkc657PL3AWsE67wHAEBdBWNtDNTjPTvmDugzyWJiYiRJBQUFhu1TpkzRvn37Kl20f9q0abr33nv9HQ8AHMWfxc3lCuhyBQAAACAAuMrKysqsDlFXbrdbN9xwg/bt26epU6eqdevWysnJ0YIFC1RYWKgVK1aob9++hueMHz9eH330kRYtWqRGjRpZlByAFbZt21btPnFxcdq6dWuV+3Tv3t1XkXyi/Kyr6s7a8rcDx6WJ/67ZvuVZLz1jrDIPD5B6d6hTLMezy98HrBGs8x4AAHUVjLUxUI/3zMidkpIiScrNza3R/gH90XxISIiys7OVkJCgjIwMjRgxQjExMcrMzFRoaKgSExMN+//P//yPPvjgA3388cc0yABc0fjx462OELBiGksRfrqIv00z/4wLgHkPAIBLURudK6DXJJOk2NhYLV682LDt4YcfVnx8vBo2bFixbfz48VqwYIEWLlyopk2bmpwSQKBIS0uzOkLACnFJHa+Rtvn4DpdRkdI1jX07JoCLmPcAADCiNjpXQJ9JVpk1a9YY1iPLz8/Xb37zGxUXFyslJUU9e/ZUz549rQsIwLbi4uKsjhDQ+nf1/Zg3d/Y04AD4B/MeAABG1EbnCvgzyS5VUlKigoICjR49umJbQkKCAnjpNQAIGAmtPWd9HTzhm/HCQ6UBsb4ZCwAAAACqEnRNsqioKJWWllodAwAcKTREGt5P+uNCyRcfTQy9QWrKEpIAAAAATBB0TTIAqI/yu5+g7jpdKw1OlD7aWPk+NbmrZY82nEUGmIF5DwAAI2qjcwXlmmQAUFczZsywOkJQGHS956uuEttKj9zCWmSAGZj3AAAwojY6F00yAPCSkZFhdYSg4HJJdyRJ6SlSdMNqd68QHirdf6P06K1SWKjf4gHwwrwHAIARtdG5uNwSALzk5uZaHSGoxLeW/vtuaeVOadnX0oHjV96vcaTUr7Pn8krWIAPMxbwHAIARtdG5aJIBAPwqMlxK7i4N7CYdOy19Wyy9scTz2M8GSG2aSTGNubQSAAAAgLVokgEATOFyec4S8z5TrFcHy+IAAAAAgAFrkgGAl61bt1odAQBMxbwHAIARtdG5aJIBgJfZs2dbHQEATMW8BwCAEbXRuWiSAYCXcePGWR0BAEzFvAcAgBG10blokgEAAAAAAMDxaJIBAAAAAADA8WiSAYCX6dOnWx0BAEzFvAcAgBG10blokgGAl4SEBKsjAICpmPcAADCiNjoXTTIA8JKcnGx1BAAwFfMeAABG1EbnokkGAAAAAAAAx6NJBgAAAAAAAMejSQYAXvr06WN1BAAwFfMeAABG1EbnokkGAF5Wr15tdQQAMBXzHgAARtRG56JJBgAAAAAAAMejSQYAAAAAAADHo0kGAF5ycnKsjgAApmLeAwDAiNroXDTJAAAAAAAA4Hg0yQDAy7Bhw6yOAACmYt4DAMCI2uhcNMkAAAAAAADgeDTJAAAAAAAA4Hg0yQDAS2ZmptURAMBUzHsAABhRG52LJhkAeBkzZozVEQDAVMx7AAAYURudK8zqAABgJwMHDtSSJUusjgE4TskZaVOR9G2xtP+4dL5UahAmtYqW2jaXrm8jNWpgdcrgxLwHAIARtdG5aJIBgJeDBw9aHQFwlOISacEGaX2hVOq+/PEd+z3/Gx4q3dhRuiNRatzQ3IzBjnkPAAAjaqNz0SQDAACWWP61NG+ddPZC9fueL5W+3CFtLJQeuEnq2d7/+QAAAOAsrEkGAF7i4+OtjgAEvbIy6YP10uxVNWuQeTt5Tpr5hZS3zS/RHIl5DwAAI2qjc9EkAwAvc+bMsToCEPS+KJA+y6/fGO+vldbv8U0ep2PeAwDAiNroXDTJAMDLSy+9ZHUEIKgdPC7N/6rqfaY96PmqTvYq6cRp3+RyMuY9AACMqI3OFRRNMrfbralTp6pr166KjIxUUlKS8vLy1K1bN6Wnp1sdD0AAyc7OtjoCENTmfeVZX8wXTp6TFmz0zVhOxrwHAIARtdG5gqJJNnLkSE2YMEGjRo3SRx99pLS0NA0fPly7du1S7969rY4HAADkuZNlfpFvx1yzWzp1zrdjAgAAwJkC/u6Ws2bN0syZM5Wbm6vk5GRJUmpqqtatW6e5c+eqV69eFicEAACSZw2xMh+Peb5U2lwk3dTJxwMDAADAcQL+TLKJEydq8ODBFQ2ycl26dFF4eLgSExMlSffee68SExN1ww036KabbtJnn31mRVwANpeXl2d1BCBoFR72z7jfFvtnXKdg3gMAwIja6FwBfSZZUVGRNm/erLFjx172WGFhoRISEhQRESFJmjlzppo2bSpJ+uqrr5SSkqLDhw8rNDTUzMgAbC4/P1/XXnut1TGAoLTvqH/G/c5P4zoF8x4AAEbURucK+CaZJLVs2dKw/fTp08rLy9OQIUMqtpU3yCTp2LFjcrlcKiur/qIPl8vlm7AALHelhvqlsrKyqt0vKyvLV5F84om3PXNZIM1XgZg5UNnpd/3YtD1qHNPOsK2qu1hW9tiT7xh/XvblKv1iUN96pgtOwTrvAQBQV8FYG+10vFcbdswd0JdbxsTESJIKCgoM26dMmaJ9+/Zdtmh/ZmamOnXqpPvvv19z5sxRWFhA9wgBAAgoF86f9su4pefP+GVcAAAAOIurrCanU9mU2+3WDTfcoH379mnq1Klq3bq1cnJytGDBAhUWFmrFihXq2/fyT5bz8vI0duxYLVmyRFFRURYkB2CFbdu2VbtPXFyctm7dWuU+3bt391Uknyg/q6aqM3LsJhAzByo7/a7/ludZZL865VkvPWOsMv27SGmcSHZFwTrvAQBQV8FYG+10vFcbZuROSUmRJOXm5tZo/4A+kywkJETZ2dlKSEhQRkaGRowYoZiYGGVmZio0NLRi0f5LJScnKyQkRMuWLTM5MQC7Gz9+vNURgKDVrpl/xm3b3D/jOgXzHgAARtRG5wr46w1jY2O1ePFiw7aHH35Y8fHxatiwoSSppKRExcXFat++vSTPwv07d+5UXFyc6XkB2FtaWprVEYCgldReWrDRt2OGhkjXt/HtmE7DvAcAgBG10bkCvkl2JWvWrFG/fv0qfj558qR+/OMfq6SkRGFhYYqMjNTbb7+tdu3aVTEKACeqyanVAOqmRRMptqVU8L3vxuzZTmoc6bvxnIh5DwAAI2qjcwVdk6ykpEQFBQUaPXp0xbYWLVpoxYoVFqYCAACSNPQG6dWPJbcPVkRtECbdkVT/cQAAAAApCJtkUVFRKi0ttToGAAC4gjbNpEE9pI+ruOyypgv239NLas79dwAAAOAjAb1wPwD4WvndTwD4z6Drpb6d6zfGbQmeu1qi/pj3AAAwojY6V9CdSQYA9TFjxgyrIwBBL8Ql/bivdPVV0qebanfpZVio55LNW2Mll8t/GZ2EeQ8AACNqo3NxJhkAeMnIyLA6AuAIIS5pcA/pqcGexfyr45LnLpbP3SEN7EaDzJeY9wAAMKI2OhdnkgGAl9zcXKsjAI7Sppk0+ofS/mPS+kLp28PS5iLPY9c2kVo1ldo2k25oz/pj/sK8BwCAEbXRuWiSAQAAy7WIln7Uw/N9+cL9v7rbujwAAABwHi63BAAAAAAAgOPRJAMAL1u3brU6AgCYinkPAAAjaqNz0SQDAC+zZ8+2OgIAmIp5DwAAI2qjc9EkAwAv48aNszoCAJiKeQ8AACNqo3PRJAMAAAAAAIDj0SQDAAAAAACA49EkAwAv06dPtzoCAJiKeQ8AACNqo3PRJAMALwkJCVZHAABTMe8BAGBEbXQummQA4CU5OdnqCABgKuY9AACMqI3ORZMMAAAAAAAAjkeTDAC89OnTx+oIAGAq5j0AAIyojc5FkwwAvKxevdrqCABgKuY9AACMqI3ORZMMAAAAAAAAjkeTDAAAAAAAAI5HkwwAvOTk5FgdAQBMxbwHAIARtdG5aJIBAAAAAADA8WiSAYCXYcOGWR0BAEzFvAcAgBG10blokgEAAAAAAMDxaJIBAAAAAADA8WiSAYCXzMxMqyMAgKmY9wAAMKI2OhdNMgDwMmbMGKsjAICpmPcAADCiNjoXTTIA8DJw4ECrI8Bmysqk4hIpv0j6ao+0uUg6eFxyl1mdDPAN5j0AAIyojc4VZnUAALCTgwcPWh0BNrH/uLSsQFr7jXTy7OWPR4ZLPdtJt8RKbZqZHg/wGeY9AACMqI3ORZMMAAAv5y5IH26QlmyTqjpZ7Mx5acVOz1efjtJ9vaVGEabFBAAAAOBjNMkAwEt8fLzVEWChIyelvyzynEVWG6t3S1/vl0alSq2a+iUa4DfMewAAGFEbnYs1yQDAy5w5c6yOAIscPy39+bPaN8jKHT3lef7BOj4fsArzHgAARtRG56JJBgBeXnrpJasjwAJlZdK7K6RDJVXvN+1Bz1dlSs5K/1wmlbp9mw/wJ+Y9AACMqI3OFfBNMrfbralTp6pr166KjIxUUlKS8vLy1K1bN6Wnp1sdD0CAyc7OtjoCLLD2G2nLd74Z69vDUu5W34wFmIF5DwAAI2qjcwV8k2zkyJGaMGGCRo0apY8++khpaWkaPny4du3apd69e1sdDwBgc2Vl0uf5vh0zd5t0odS3YwIAAADwr4BeuH/WrFmaOXOmcnNzlZycLElKTU3VunXrNHfuXPXq1cvihAAAu9t9UNp3zLdjnjgjbS6Serb37bgAAAAA/CegzySbOHGiBg8eXNEgK9elSxeFh4crMTHRsP21116Ty+VSTk6OmTEBBJC8vDyrI8BkOw74adz9/hkX8DXmPQAAjKiNzhWwTbKioiJt3rxZDzzwwGWPFRYWKiEhQRERERXbvv76a/39739Xv379zIwJIMDk5/v4ujvYXtFh/4z7rZ/GBXyNeQ8AACNqo3MF7OWWRUVFkqSWLVsatp8+fVp5eXkaMmRIxbYLFy7oscce04wZM/Tkk0/W6nVcLle9swKwh7Fjx1a7T1ZWVrX7ZWVl+SqSTzzxdpmkwJqv7JT5gZeW6brY/oZtVd3BsrLHn3zH+POm7XvkGtKhfuF8wE6/65oKxMx2FazzHgAAdRWMtTFQj53smDtgzySLiYmRJBUUFBi2T5kyRfv27TMs2j9hwgQNGTJEPXv2NDMiAAAAAAAAAkTAnknWqVMnJSYmauLEiWrWrJlat26tnJwcLViwQJIqmmQrV67UokWLlJubW6fXKSsr81VkABbbtm1btftkZWUpPT29yn1effVVX0XyifIzmAJpvrJT5jeXSBu/NW679KywcuVnkFX2uLce3drb4t9np991TQViZrsK1nkPAIC6CsbaGKjHTmbkTklJqdX+AXsmWUhIiLKzs5WQkKCMjAyNGDFCMTExyszMVGhoaMWi/YsXL9bOnTvVuXNndejQQStWrNDo0aP1yiuvWPwvAGBH48ePtzoCTNammX/GbeuncQFfY94DAMCI2uhcAXsmmSTFxsZq8eLFhm0PP/yw4uPj1bBhQ0nS888/r+eff77i8ZSUFI0ZM0bDhg0zNSuAwJCWlmZ1BJisy7V+GreFf8YFfI15DwAAI2qjcwXsmWSVWbNmjWE9MgCojbi4OKsjwGQdr5FaRft2zMaR0vVtfDsm4C/MewAAGFEbnSuommQlJSUqKChQr169Kt0nNzeXs8gAABVcLumHCb4dMzVOCgv17ZgAAAAA/CugL7e8VFRUlEpLS62OAQAIML07SOu+kbZ8V/+x2jaTkrvXfxwAAAAA5gqqJhkA1Fdt736C4OByScP7Sb//VDpUUvl+1d3VMipC+tkAKTSoztNGsGPeAwDAiNroXBzGA4CXGTNmWB0BFmncUMq8TWpZx/XJmjaSxtwuXdPEt7kAf2PeAwDAiNroXDTJAMBLRkaG1RFgoauvkp4a7Llc0lWL593USXr2jro32AArMe8BAGBEbXQuLrcEAC+5ublWR4DFGoRJ9/WW+neVln8trd0tlZy9fL/IcOmG9tKArlKbZubnBHyFeQ8AACNqo3PRJAMA4ApaNPE0y+7tJR05Ke07Jr2e63nshaFS8ygppDanmwEAAACwNZpkAABUweWSmkV5vspd09i6PAAAAAD8gzXJAMDL1q1brY4AAKZi3gMAwIja6Fw0yQDAy+zZs62OAACmYt4DAMCI2uhcNMkAwMu4ceOsjgAApmLeAwDAiNroXDTJAAAAAAAA4Hg0yQAAAAAAAOB4NMkAwMv06dOtjgAApmLeAwDAiNroXDTJAMBLQkKC1REAwFTMewAAGFEbnYsmGQB4SU5OtjoCAJiKeQ8AACNqo3PRJAMAAAAAAIDj0SQDAAAAAACA49EkAwAvffr0sToCAJiKeQ8AACNqo3PRJAMAL6tXr7Y6AgCYinkPAAAjaqNz0SQDAAAAAACA49EkAwAAAAAAgOPRJAMALzk5OVZHAABTMe8BAGBEbXQummQAAAAAAABwPJpkAOBl2LBhVkcAAFMx7wEAYERtdC6aZAAAAAAAAHA8mmQAAAAAAABwPJpkAOAlMzPT6ggAYCrmPQAAjKiNzkWTDAC8jBkzxuoIAGAq5j0AAIyojc4VZnUAALCTgQMHasmSJVbHABAAzl2QNhRKuw5KRYelkjOSXFLTRlLbZlK3llLcdVKIzT+SZN4DAMCI2uhcNMkAwMvBgwetjgDA5s5dkBZulr4okE6fv/zxIyel3QelJdulqxtJtyVIN3eVQlzmZ60J5j0AAIyojc5FkwwAAKCGig5L/1wmHThes/2PnJKyV0vrC6WH+kvRjfybDwAAAHVn8wsAAMBc8fHxVkcAYFO7D0p/XFjzBpm3r/dLf1joOcvMbpj3AAAwojY6F00yAPAyZ84cqyMAsKEjJ6XXFktnL9R9jOISzxjnS32XyxeY9wAAMKI2OhdNMgDw8tJLL1kdAYDNlJVJ76288vpj3qY96Pmqyr5j0scbfZfNF5j3AAAwojY6V1A0ydxut6ZOnaquXbsqMjJSSUlJysvLU7du3ZSenm51PAABJDs72+oIAGxm63fStn2+G2/xVntddsm8BwCAEbXRuYKiSTZy5EhNmDBBo0aN0kcffaS0tDQNHz5cu3btUu/eva2OBwAAAtiyr307nrtM+nKHb8cEAABA/QX83S1nzZqlmTNnKjc3V8nJyZKk1NRUrVu3TnPnzlWvXr0sTggAAALV2fPSlu98P+5Xe6Q7knw/LgAAAOou4JtkEydO1ODBgysaZOW6dOmi8PBwJSYmSpJSUlK0Z88eRUdHS5IGDx6sSZMmmZ4XgL3l5eVZHQGAjRQd8axJ5msHT0hnzkuR4b4fu7aY9wAAMKI2OldAN8mKioq0efNmjR079rLHCgsLlZCQoIiIiIptv/vd7zRs2LBavYbL5ap3TgD2cKW54lI7d+5U586dq9wnKyvLV5F84om3Pe/gA2m+CsTMUmDmJnP9XJ/6n/rhyNcM26pbnL+yx598x/hzh+59tH/Xmnqkq16wznsAANRVMNZGOx071YYdcwf0mmRFRUWSpJYtWxq2nz59Wnl5eVxqCaDW5s+fb3UEADYSGh4ZkGPXBvMeAABG1EbnCugzyWJiYiRJBQUFuuOOOyq2T5kyRfv27bts0f4XXnhB48ePV6dOnTRhwoSKSzGrUuaPaywAWGLbtm3V7pOVlVXtXXFfffVVX0XyifKzUwJpvgrEzFJg5iZz/Xy5Q3pvpXHbpWeElSs/g6yyxy+1YtlStW1e92w1EazzHgAAdRWMtdFOx061YUbulJSUWu0f0E2yTp06KTExURMnTlSzZs3UunVr5eTkaMGCBZJkaJL985//VNu2beVyufTuu+/qRz/6kXbs2KGrrrrKqvgAAMDmWjX1z7gul9Qi2j9jAwAAoG4C+nLLkJAQZWdnKyEhQRkZGRoxYoRiYmKUmZmp0NBQw5li7dq1q7jO9Sc/+YkaNGig7du3WxUdgE2NHz/e6ggAbOS6plKoH46WWjaRGtjko0rmPQAAjKiNzmWTw7O6i42N1eLFiw3bHn74YcXHx6thw4aSpDNnzqikpKTi8szPP/9cJ06cUJcuXUzPC8De0tLSrI4AwEYahEmJbaWv9vh23N4dfTtefTDvAQBgRG10roBvkl3JmjVr1K9fv4qfjx8/riFDhujcuXMKCQlRkyZNNH/+fDVp0sTClADsKC4uTlu3brU6BgAbuSXWt02ysBCpX9U3zDIV8x4AAEbURucKuiZZSUmJCgoKNHr06Ipt1157rdauXWthKgAAEKg6Xyvd0N53jbIhiVKUPW5sCQAAAC9B1ySLiopSaWmp1TEAAEAQuf9GadcB6djpyvepyV0tO14jpcb5LhcAAAB8J6AX7gcAX6vtLYIBOENUpJTxQ6lxPc4Aa3219HiyFGKzoy/mPQAAjKiNzmWzwzQAsNaMGTOsjgDAplpGS08M8pwNVlu9O0hjbpOuivB5rHpj3gMAwIja6Fw0yQDAS0ZGhtURANhYTGPpv26ThvWRYqKq3799c8/ZYw8PkBo28H++umDeAwDAiNroXEG3JhkA1Edubq7VEQDYXEiI546X/btKO/ZLOw9IRYel/L2ex3u2k9o2k2Jbef7X7pj3AAAwojY6F00yAACAOghxSbEtPV/SxYX7H73VukwAAACoOy63BAAAAAAAgOPRJAMAL1u3brU6AgCYinkPAAAjaqNz0SQDAC+zZ8+2OgIAmIp5DwAAI2qjc9EkAwAv48aNszoCAJiKeQ8AACNqo3PRJAMAAAAAAIDj0SQDAAAAAACA49EkAwAv06dPtzoCAJiKeQ8AACNqo3PRJAMALwkJCVZHAABTMe8BAGBEbXQummQA4CU5OdnqCABgKuY9AACMqI3ORZMMAAAAAAAAjkeTDAC89OnTx+oIAGAq5j0AAIyojc5FkwwAvKxevdrqCABgKuY9AACMqI3ORZMMAAAAAAAAjkeTDAAAAAAAAI5HkwwAvOTk5FgdAQBMxbwHAIARtdG5aJIBAAAAAADA8WiSAYCXYcOGWR0BAEzFvAcAgBG10bnCrA4QLJ588kmtX7/ektfu2bOnpk2bZslrAwAAOMUvt2/RhhMnLHntpMaN9Uq3eEte2wocWwMArECTzEfWr1+vvLw8q2MAAADATzacOKElRw5bHcMROLYGAFiByy0BwEtmZqbVEQDAVMx7AAAYURudiyYZAHgZM2aM1REAwFTMewAAGFEbnYsmGQCfKXVLe49Iq3ZJedukpdulLXulE2esTlZzAwcOtDoCAJgqUOa9Ure076i02qvG5BdJx09bnQwAEGwCpTbC91iTDEC9fX9M+qLA88bl7IUr79OuuXRLrNSrvRQWam6+2jh48KDVEQDAVHaf9w6e8NSYVTul0+evvE/rqz01pncHqQFHtwCAerJ7bYT/cBgBoM4ulEofbZQWbZHKqtm3sFj6vy89+/70Zk/TDACAypS6pc/ypU83SaXVFJm9R6T3Vkqfb5F+2k/qdK05GQEAQHDhcksAdXLyrPSHhZ43JNU1yLx9f0ya9om0cqffotVLfHy81REAwFR2nPfOnJemf+75IKa6Bpm3QyekPy6Ulmz3XzYAQPCzY22EOWiSAai1s+elvyzynB1WF+4y6d0V0rpvfBrLJ+bMmWN1BAAwld3mvQul0muLpZ0H6vb8Mklz10jLv/ZpLASpHj16WB0BgA3ZrTbCPDTJANTav9dL3x6uep9pD3q+KlMmz6UxxSW+TFZ/L730ktURAMBUdpv3Ptkk7apmKZjqaozkaZR9f8x3uWBfjRo10siRIzV79mzt3LlTFy5cUFlZmQ4dOqRPP/1U48aNU7t27S573pgxY7Rx40buYgfgMnarjTBPUDTJ3G63pk6dqq5duyoyMlJJSUnKy8tTt27dlJ6ebnW8Co888ogWL15c4/3XrFmjQYMG+TERUHu7D3oWUPaFsxek7FW+GctXsrOzrY5QKwePX/ze7bYuB+zp1Nkrfw94s9O8990Rz2X8vnDB7Tlruaw2awIgoISFhelXv/qV9u7dq7/97W964IEH1KlTJ4WGeu4Q1Lx5c91+++36zW9+o927d2v27Nlq1aqVJE+D7I9//KMkqbS01LJ/AwB7slNthLmCokk2cuRITZgwQaNGjdJHH32ktLQ0DR8+XLt27VLv3r2tjlepkJAQTZkyRQcOHNDx48eVk5Oj5s0vrmY+b948DR061MKEwOVyt/l2vG37pH1HfTumE+w6IP3+U+l//31x28vzpKXbeUMIz5qB766QXpp7cdtLc6VZKzyPAXa1ZLvnknxf+eaQ58suLjz9nErfmWV1jKDQsWNHrVixQv/7v/+rpk2bavny5UpPT9f111+vBg0aKCQkRG3atNG9996rt99+W+fPn9cDDzyg/Px8vf766xUNstGjR2vGjBkW/2sAAHYR8E2yWbNmaebMmZo/f76efvpppaam6oUXXtDNN9+sCxcuqFevXlZHrNTzzz+ve+65R3379lWbNm0kSW+99VbF4zTJYDcnzkibvvX9uCtsuoi/XW3fJ/3pM+mbSy5HOnpKmrNG+vdX1uSCPZw6J/3hU8/NMS54nV14wS2t2ulprnJWGezo7Hlp7Te+H/fLHb4fE9bq1KmTli5dqt69e2v37t364Q9/qAEDBuj1119Xfn6+zp8/r7KyMu3du1fz5s3Tww8/rM6dO+vDDz/U1Vdfrccff1wSDTIAwOUCvkk2ceJEDR48WMnJyYbtXbp0UXh4uBITEyVJ586d01NPPaWuXbuqR48eGjhwoBVxDdLT0zV58mTt3r1bx48f17PPPqshQ4ZUrJmwceNGlZaW2rrRB2fZc8i3n/CX21XHxZn9IS8vz+oIVSp1S28v95wtVtl/ikVb635TBQS+TzdJ+49f+e+jTNKB49Inm81OBTuzy7z37WHpvB+ueqtufTMElsjISH3wwQdq3bq18vLylJSUpEWLFlX7vL179+rjjz+u+Lm0tFSrV6/2Z1QAAcwutRHmC+gmWVFRkTZv3qwHHnjgsscKCwuVkJCgiIgISdKvfvUrnThxQtu2bdOmTZv03nvvmR3XIDo6Wu3bt9fatWsrtu3atUvHjh1TUlJSxbZ58+bpnnvusSIicJnqFuuvq++Oepo/dpCfn291hCrl7/Wc0VdVr9Il360bh8By7kLNzsxcudOzLyDZZ94r8lONOXRCOn3OP2PDfC+//LLi4uK0ZcsW3XXXXTpx4kSNnue9BtnixYsVGhqqmTNnVrxXAABvdqmNMF+Y1QHqo6ioSJLUsmVLw/bTp08rLy9PQ4YMkSSdOnVKf/3rX/Xtt99WLORZvmhndVwulw8TX9S4cWNJ0rFjxtsuHT16VE2aNKn4+cMPP9Rvf/tbjRs3rtKx8vLy/JYT8JbyyJ+UdHumYVt1dxer7PEn37n4falbioqO0ZkS/57+NHbs2Gr3ycrKqna/rKwsX0WqtX73j9dN975Y5f/nyyR9mLtBD/bvaVqu2nribU+bL9DmLrvnvrpVN/3sd9UvHHjmvNSyfZyOfOfjRQZ9xO6/58rYMXcgzXs3P/A/uumeFwzbfFFjJKlV2846dmBXPdJ5hP5ukkKSEus9Tl3k5ubK1aefJa9tF61atdKTTz6p0tJSPfrooyopqdktsr0bZKNHj9bf//53ffXVV0pISNDDDz+sv/3tb4b9ObYGglsg1caasuMxSE3YMXdAn0kWExMjSSooMJ4yMWXKFO3bt69i0f4dO3YoOjpar776qm666Sb169dPs2fPNj2vt/JPvaKjow3bmzZtquPHL96urn379iosLDQ1G1ApP64IX1Zmk1PJbM5deqHaIlJWViZ3KacJOZHbXfP/7mVu7uYGm6HGoBr/+Z//qfDwcL3//vs1vlTy0gbZjBkzdObMGU2YMEGSlJmZWdXTAQAOE9BnknXq1EmJiYmaOHGimjVrptatWysnJ0cLFiyQpIom2YULF7R37161atVKq1at0jfffKP+/fura9euuuGGG6p8jbIaHrClpKTU6rrlY8eOac+ePerVq5c2bNggyXOXnujoaG3cuLFiv6FDh2rOnDlVjpWcnKzc3NwavzZQV5/lSx+sN2679NP6cuWf7lf2uLeIMOnU8cMK8XPbftu26s+aycrKUnp6epX7vPrqq76KVGs7D0h/XFj1Pi6XS8Pv7K1Zv7bvbS7L/y5qOsfahd1zu92eu5wePVX1ftENpeK9BX7//1xd2f33XBk75g6keW9ZgZR9Sd/DFzUmxCUd/G63GvjgqPe2NSu15IifrgutRkpKij6z0d+Wv13p2Pree++VJL3++us1GuNKDbJyOTk5+uMf/6iePXuqffv22rNnT8VjHFsDwS2QamNN2fEYpCbMyJ2SklKr/W16eFwzISEhys7OVkJCgjIyMjRixAjFxMQoMzNToaGhFYv2ly+E/8gjj0iSOnTooAEDBmjVqlWWZZek1157Tc8995w6dOigxo0ba/Lkyfr4448rinSjRo2UmpqqDz74wNKcQLm2zfwzbuurZZs36+PHj7c6QpU6XSO1aipVdTJZiEvq38W0SLCRkBBpYLfq97u1m33+Pwfr2WXea9vcP+O2jJZPGmSwVkREhK6//nq53W4tW7as2v2rapBJnpt6lb8XKP9gHQDK2aU2wnwBf4gcGxurxYsX6+TJkyosLNSECRO0adMmxcfHq2HDhpI8l2UOHjxYH374oSSpuLhYq1atMiyQb4VJkybp3//+t1avXq29e/cqNDRUDz30UMXjgwYN0ldffaXiYm5TB3toH+M568vXYmu2RKAp0tLSrI5QJZdLevRW6aoGV3js/38N7yfFNDY7Gewiubt0fRvP99691PLvr28tpcaZnQp2Zpd577qm0lV+WEM9tmX1+8D+2rdvr/DwcO3evVsnT56sct/qGmTlNm/23Oo3NjbWt2EBBDy71EaYLyg/V1uzZo369TMubPqXv/xFI0eO1Msvv6yysjI9//zzl+1jNrfbrWeeeUbPPPPMFR8fOnSo5s2bZ3IqoHKR4dKNHaVlX/tuzBCXdHNn341XX3Fxcdq6davVMarUoon09B3S4q3Sih3S2QueBsj1bTzNj07XWp0QVgoNkUbcKn25Q1q6Xdr//5e5vLaJ5wyym7t49gHK2WXeCwuV+nWWPt/i23H7d/XtePURNnWy1REC1r59+3T//ffrzJkzVe7XtGlTvfjii5KqbpBJ0ltvvaWVK1dq06ZNPs0KIPDZpTbCfEHXJCspKVFBQYFGjx5t2N6+fXt99tlnFqWqmz179ig7O9vqGIBBSpy0cpd0wUdrfvftLEU38s1YTtK0kXRfb+meG6TT5z2XEoWHWp0KdhEaIt0SKw3o6mmiSp6zQG104yDgim7t5vkg5sx534x3Q3tPgxiB78SJE5o7d261+x09elQ/+MEP1LdvX7355ptV7rtx40bDWsAAAARdkywqKkqlpfa8Y9f69es1c+bMGu/PddCwo2saS3cmSfPW1X+spo2ke3rVfxwnCwnxz+VJCA4ul+cMUCBQNG0k3dtLendl/ceKipDuv7H+4yDw5OfnKz8/3+oYAIAAFHRNMjvbsGFDxZ0sgUCW3E0qLJa+2lP5PtXdcaxBmOeSMLu9ga/t3U8AINDZbd7r21n65pC0Ymfl+1RXY8JCpEdukaIifZsNAOAMdquNMA9NMgC1FhIiPdTfc3nfql21f35UpPR4sudGAHZT1dolABCM7DbvuVxSWl/PhylLttf++Q0beD6E6cqC/QCAOrJbbYR5WLoXQJ2Ehkg/vdlzp8WoWlzud0N76fk7pQ42bJBJUkZGhtURAMBUdpz3QlzSf9wopadI0Q1r/ryE1tLzd3FHSwBA/dixNsIcnEkGoF56tpPir5PW7ZFW7pS+LZYuuI37NG0kxbeWbukqXXe1NTlrKjc31+oIAGAqO8978a2lF++R1hd6Lr/cc0g6f8nSs9ENpe7XeWpM2+bW5AQABBc710b4F00yAPXWIEzq19nzVeqWDhyXJn/oeex/7mdNGABA3YWFSjd29HyVuqWDJ6RJH3gee/k/pCa1ONMMAACgKlxuCcCnQkOkVk0v/kyDDADgK6EhUsvoiz/TIAMAAL5EkwwAvGzdutXqCABgKuY9AACMqI3ORZMMALzMnj3b6ggAYCrmPQAAjKiNzsWaZD7Ss2dPR742EGzGjRuntLQ0q2MAgGmY92ouqXFjR762Fep6fLurcJ8kqVO7VobvzXhtAMGD2uhcNMl8ZNq0aVZHAAAAgB+90i3e6giOUddj6+cnvyZJmvRcuuF7AABqgsstAQAAAAAA4Hg0yQDAy/Tp062OAACmYt4DAMCI2uhcNMkAwEtCQoLVEQDAVMx7AAAYURudiyYZAHhJTk62OgIAmIp5DwAAI2qjc9EkAwAAAAAAgOPRJAMAAAAAAIDj0SQDAC99+vSxOgIAmIp5DwAAI2qjc9EkAwAvq1evtjoCAJiKeQ8AACNqo3PRJAMAAAAAAIDj0SQDAAAAAACA49EkAwAvOTk5VkcAAFMx7wEAYERtdC6aZAAAAAAAAHA8mmQA4GXYsGFWRwAAUzHvAQBgRG10rjCrAwSLJ598UuvXr7fktXv27Klp06ZZ8toAAACwt19u36INJ06Y/rpJjRvrlW7xpr8uaof3MQBwEU0yH1m/fr3y8vKsjgEAAAAYbDhxQkuOHLY6BmyK9zEAcBGXWwKAl8zMTKsjAICpmPcAADCiNjoXTTIA8DJmzBirIwCAqZj3AAAwojY6F5dbAjZT6pby90qbiqSiYulQiWdbwwbSdU2l9jFSn05SiyZWJw1OAwcO1JIlS6yOAQCmYd7zj1K3tOlbafNeqeiwVOxVz1tfLbVvLt3UWbqmsdVJAQCXojY6F00ywCbKyqRVu6QFG6Rjpy9//ORZ6ev9nq/P8qXuraT7b5SuoVnmUwcPHrQ6AgCYinnPt8rKpC93SB9vlI6fufzxk2elgu89XwvzpYTW0n/cKDWPMj8rAODKqI3ORZMMsIFTZ6W3l0tbvqv5c7btk6YskO7tLQ3o6r9sAACgZkrOSP9c5mmA1VT+Xs8HYMP6SDd18l82AABQPZpkgMVOnZX+/Lm090jtn3u+VMpeJZ0+J92W4PtsThQfz63qATgL855vlJyR/vSZ9P2x2j/33AXp/7701PPk7r7PBgCoHWqjc9EkAyxUVub5xLmqBtm0Bz3/++Q7le/zwXrp2iZSYlufxnOkOXPmWB0BAEzFvFd/7jLp70urbpDVpJ6/v9ZTz+Ou820+wJcaNmyo3r17q3fv3mrdurVcLpcOHDigtWvXavXq1Tpx4sRlz4mLi9PUqVP10EMP6ciROnwyDJiM2uhc3N0SsNCKnZ7LJn1h9irPp9ion5deesnqCABgKua9+lu6Xdp5wDdjvbfSc0YZYDcdO3bUtGnTtG/fPi1dulTTpk3TM888o6efflpTpkzR559/rv379+uNN95Qjx49Kp4XFxenRYsW6Y477tC4ceMs/BcANUdtdK6gaJK53W5NnTpVXbt2VWRkpJKSkpSXl6du3bopPT3d6ngVHnnkES1evLjG+69Zs0aDBg3yYyJY6UKp9OEG341XckZavNV34zlVdna21RGCWnGJNP+riz/PWiEVFluXB/Zy7oK0YsfFn2d8Lq3d7Zkv4T/Me/Vz7oJnkX5fOXpKWrLdd+PV14Wnn1PpO7OsjgELuVwu/eIXv9DmzZv1xBNPKDo6Whs3btRrr72m5557Ts8++6z+9Kc/aeXKlWrYsKEee+wxrVu3ThMmTFBiYqIWLVqkli1bauHChXr++eet/ucANUJtdK6guNxy5MiRmjt3rl588UX17t1by5cv1/Dhw3Xw4EE99dRTVserVEhIiCZNmqRHH31UkZGR+vTTTzVq1CgVF3veMc6bN09Dhw7Vp59+anFS+MOGQt+f+bVypzQkUQoL9e24gC+s2e1Zc8dddnHbqp2ev9sfxEl33yC5XNblg7UOnZCmfy4dPnlxW8H30vbvpc+3SBk/kBo3tC4fUJm130inz/t2zC93eNYaDQ2Kj7MRyMLCwvTWW2/pJz/5iSTp3Xff1aRJk7Rhw5U/6e3cubOeeuop/fznP9evf/1rPfvss2rQoIEWLlyooUOH6swZLnsAYG8BX3pnzZqlmTNnav78+Xr66aeVmpqqF154QTfffLMuXLigXr16WR2xUs8//7zuuece9e3bV23atJEkvfXWWxWPlzfJEJw2Fvl+zJKz0i7uVgwb2nVAeme5sUEmSeU/LtoqLfva9FiwiVK39JfF0pFTxu3lfx/7jkp/y/Os4wjYzaZvfT/m0VPSt4d9Py5QW6+//rp+8pOf6Pjx47r33ns1fPjwShtkkrRz505lZmbqZz/7mUpLS9WgQQMVFxfrvvvuo0EGICAEfJNs4sSJGjx4sJKTkw3bu3TpovDwcCUmJuro0aPq2bNnxVd8fLxcLpc2bdpkUWqP9PR0TZ48Wbt379bx48f17LPPasiQIWrXrp0kaePGjSotLbV1ow91V+Sng19/jesUeXl5VkcISjW5FPizfMnt9n8W2M+mIs+ZZJU1wcok7SmWdvMhgF8w79VdWZn/mlnfcik6LJaWlqZHH31UJSUluu222zRv3rwaPa98kf7Q0FCdPXtWzZs31+jRo/2cFvAtaqNzBfTllkVFRdq8ebPGjh172WOFhYVKSEhQRESEIiIitH79+orH/vnPf+rVV181LChZGZefrv2Jjo5W+/bttXbt2optu3bt0rFjx5SUlKTCwkJJnrPJ7rnnHq1bt67SsfLy8vyWE/7hCgnVL/55QWVlZRX/7crvelWZyh6/9C5ZE7P+ph/+7T99kLJ+nnjb827XTn+bV5orLrVz50517ty5yn2ysrJ8FckRQsMaKPPNU3KFVH0d8NFT0nVdb9L+XatNSlZ7dvy7DgZDxryrLn3uV0ho5YclbnepRvzyj1rydvX/P7aKHf8+gnXes8vvOjwySqP/ZryTn6/q+Yv/+wflvfVEPdJdFPq7SQpJSvTJWLWRm5srV59+pr7mc5P+Ksnzt+H9PWonKipKf/7znyVJTz31lFavrlltLl+kv3wNsj/84Q/697//rZdfflnvvfdexXuccryPgRWCsTbapS7Wlh1zB/SZZEVFnuvVWrZsadh++vRp5eXlVXoG1uuvv275gv6NGzeWJB07ZrxX+NGjR9WkSZOKnz/88EPdeeedpmaD/4WEhkvyz2RQPjbqZv78+VZHCDphDRpV2yAr16Bhk+p3QtBp0LBJ9QvSlZXx9+EnzHt1FxrWwG9jU89hpQcffFAxMTH68ssv9frrr9foOZc2yIYOHaoPPvhA7733niIjI/Xzn//cz6kB36E2OldAn0kWExMjSSooKNAdd9xRsX3KlCnat2+fevfufdlztm3bpnXr1umDDz6o0WuU1XABlJSUlFqdknnihOdTx+joaMP2pk2b6vjx4xU/t2/f/rJPXC6VnJys3NzcGr82rOcuk56eZVyf6dJPkMuVf+Jc2eOXSh/5iD79yyP1C+gD5Xlr+v8hM2zbtq3afbKysqptor/66qu+iuQIbrf0qxzpTA0Wtl6z/DNda+M+iB3/roPB7JWehcqr+q2GhIbpqTGPaeFrj5mWq7bs+PcRrPOeXX7X50ulZ941bvNVPX/yvzK06O8ZdQ/n5bY1K7XkiPnrMaSkpOgzk/8bPT/5NUmevw3v71G5K72PGTlypCTpD3/4Q43GuFKDrHwNst///vf68Y9/rMcee0y/+tWvDM/jfQysEIy10S51sbbMyJ2SklKr/QP6TLJOnTopMTFREydO1D//+U99/vnnysjI0JtvvilJV2ySvfbaa0pLS7usOWW2Y8eOac+ePYaz3Tp27FhxS+VyQ4cOrfH1/wgcIS6pVVP/jH2dn8YF6iokROpb9dnqcknqeI1s3SCD//TrUnWDrFzfTn6PAtRKeKh0TWP/jH3d1f4ZF6hOZGSkbrjhBpWWltbobJqqGmSS9OWXX+r7779XixYt1KkTEzkAewvoJllISIiys7OVkJCgjIwMjRgxQjExMcrMzFRoaKgSE41rL5w9e1b//Oc/Lb/Ustxrr72m5557Th06dFDjxo01efJkffzxx9qzZ48kqVGjRkpNTa3xWW8ILO2b+2fcdn4a1ynGjx9vdYSglBonRUVe+Yo6lzzb7+5pdirYRbvm0g3tq95nYDepWZQ5eZyGea9+2sf4Z1zqOaySkJCgsLAwbdu2TadOnapy3+oaZOXK12G+4YYb/JIZ8DVqo3MF9OWWkhQbG6vFixcbtj388MOKj49Xw4YNDdvff/99tWrVSjfffLOZESs1adIkXX311Vq9erUiIiK0cOFCPfTQQxWPDxo0SF999ZWKi7m9UTDq00lavsO3Y17XVGrNJ8/1kpaWZnWEoNS0kfSL26W/L5X2HTU+FhUpPdRf6nStJdFgEw/eLEWGSyt2Gu9yGeKSUuKku5KsyxbsmPfqp09Hac1u347ZPsY+Z9aGTZ1sdQRYYPny5dqwYUOV+7Rt27ZGDTJJWrlypZo1a1bp44DdUBudK+CbZFeyZs0a9et3+Z10Xn/9df3nf1p/179ybrdbzzzzjJ555pkrPs6llsGtQ4zUpplU5MMlQm7tVv3a16haXFyctm7danWMoHRtE+nZO6TdB6WC7z1r8rVpJiW0lkID+rxm+EJYqPTjvtKPekhf7ZFOnZWaNPScYRYVaXW64Ma8Vz9dW0otmkj7j1e/b03dGuu7sYDaWrt2rQYMGFDtfnv37tUnn3yi6667rsoGmSRNmDBBEyZM8GVMwK+ojc4VdE2ykpISFRQUaPTo0Zc99vnnn1uQqO727Nmj7Oxsq2PAT1wu6YE+0rRParYWT3Xax7BeD+zP5fKcMcZZY6hM00aey3OBQBHikh64SfrTZ74Zr0sLqVcH34wF+JPb7dZjjz2m8PBwnT171uo4AOATQdcki4qKUmlpqdUxrmj9+vWaOXNmjffnOujg1z5GGtRD+mRT5fvU5C5YkeHST/t5FkgHAADm6tJC+kGctKiKkw5qUs8bNZB+0tfTeAMCgdvtpkEGIKgEXZPMzjZs2FDttf1wnsE9PJcVLS2o2/Mjw6X0FKmFtTdsDRq1vUUwAAQ65j3fuOsG6dQ5z7p6ddGwgfTzH0gxfrpbJgCg5qiNzkWTDLCYyyX9x42eJtf8r6RzF2r+3LbNpAf7Sy1pkPnMjBkzrI4AAKZi3vONEJdnXb2WTaUP10vna3FhQ4cY6ac322exfgBwOmqjc3FxFmADLpd0S6z03J3SzV2k8NCq97+msXT/jdKTP6JB5msZGRlWRwAAUzHv+Y7LJaV099yk5KZOnhtSVKVltGc9s1/cToMMAOyE2uhcnEkG2EjzKM+n0HffIH39vfTtYemzfM9jfTpKra/2rGPWIYa7WPpLbm6u1REAwFTMe753TRPPmWH39LpYzz/f4nmsTyepzf+v5+2bU88BwI6ojc5FkwywoUYNpKR2nq/yJtmD/a3NBAAAaueqCKlne89XeZPswZutzQQAACrH5ZYAAAAAAABwPJpkAOBl69atVkcAAFMx7wEAYERtdC4ut/SRnj17OvK1gWAze/ZspaWlWR0DAEzDvBf8kho3dtTronbq+l5iV+E+SVKndq0M35vx2oC/URudiyaZj0ybNs3qCAB8YNy4cRREAI7CvBf8XukWb3UE2Fhd38c8P/k1SdKk59IN3wPBgNroXFxuCQAAAAAAAMejSQYAAAAAAADHo0kGAF6mT59udQQAMBXzHgAARtRG56JJBgBeEhISrI4AAKZi3gMAwIja6Fw0yQDAS3JystURAMBUzHsAABhRG52LJhkAAAAAAAAcjyYZAHjp06eP1REAwFTMewAAGFEbnYsmGQB4Wb16tdURAMBUzHsAABhRG52LJhkAAAAAAAAcjyYZAAAAAAAAHI8mGQB4ycnJsToCAJiKeQ8AACNqo3PRJAMAAAAAAIDj0SQDAC/Dhg2zOgIAmIp5DwAAI2qjc4VZHSBYPPnkk1q/fr0lr92zZ09NmzbNktcGAAAA4PHL7Vu04cQJ0183qXFjvdIt3vTXRe3wnhGwP5pkPrJ+/Xrl5eVZHQMAAACARTacOKElRw5bHQM2xXtGwP643BIAvGRmZlodAQBMxbwHAIARtdG5aJIBgJcxY8ZYHQEATMW8BwCAEbXRubjcEkHv9Dnp28NS0WHp5FkpxCU1vUpq10y67moplFYxvAwcOFBLliyxOgYAmIZ5D5cqOSMVFkt7j0hnznuOlZpHSe2aSy2iPcdSABDMqI3ORZMMQauwWFqyTfqqUCp1X3mfJpFSvy7SrbFS44bm5oM9HTx40OoIAGAq5j2U275PWrJd2vKdVFZ25X1ioqT+XT1fkeHm5gMAs1AbnYsmGYLOuQvShxs8DbJKju8qHD8jfbpZ+qJAuv9GqVcHycWnowAAwEFKzkhz1khf7al+30Ml0vyvpKXbpZ/0k7q18n8+AADMwoVmCConz0p/XCjl1aBB5u3UOemt5dK/1lX+ySmcIT6e26cDcBbmPWc7dEJ69eOaNci8HTklzVjkOeYCgGBDbXQummQIGucuSH9Z5Fl/rK7ytkkLNvguEwLPnDlzrI4AAKZi3nOuE6elP38uHT5Z9zHeXyut2Om7TAAu16BBA7Vo0ULXXnutwsKqvhgsPDxcycnJJiULXtRG56JJhqDx0cbqG2TTHvR8VWVhvrRzv+9yIbC89NJLVkcAAFMx7zlTWZk0e5V0pJoGWU2Oneaslg6e8F02AFJcXJyysrK0bt06lZSU6Pvvv9f+/ftVUlKiVatWadKkSerUqZPhOeHh4crJydHnn3+uYcOGWZQ8OFAbnSsommRut1tTp05V165dFRkZqaSkJOXl5albt25KT0+3Ol6FRx55RIsXL67x/mvWrNGgQYP8mCh47D0i5W713XizVkruShb7R3DLzs62OgJsqNTtWdC63IVS67LAnr4/dvH7o6esy1EXzHvOtLlI2lTkm7HOl0o5q3wzFuB0rVu31vz587VlyxY9+eSTuuGGGxQaGqoDBw7owIEDioiIUJ8+ffTcc8/p66+/1v/93//pmmuuqWiQDR06VEePHtWOHTus/qcENGqjcwVFk2zkyJGaMGGCRo0apY8++khpaWkaPny4du3apd69e1sdr1IhISGaMmWKDhw4oOPHjysnJ0fNmzeveHzevHkaOnSohQkDx9LttVuDrDqHTnju7AQAK3dKL//Ls/ZOuZfmSou2sIYhPM2xP3wqTfrg4rbx/5L+vtSzGDpgV3nbfTve9u+lfUd9O6bTXHj6OZW+M8vqGLDQPffco/z8fN19990qKSnRX//6VyUnJ6tJkyZq0aKFWrRooejoaP3whz/UzJkzde7cOQ0fPlz5+fnKzc3V0KFDVVxcrNtuu03r16+3+p8DBKSAb5LNmjVLM2fO1Pz58/X0008rNTVVL7zwgm6++WZduHBBvXr1sjpipZ5//nndc8896tu3r9q0aSNJeuuttyoep0lWM+cuSGu/8f24rK8BIG+bNGuFdOy0cfupc567u/17vSWxYBP7j0u//0Tafci4vaxM2ljouZHMqXPWZAOqcvCEtMMPS0us5NgJqLMHHnhAc+bMUXR0tObNm6euXbvq5z//uZYsWaKTJy9eF338+HEtWrRII0aMUPfu3bVo0SJdc8016t+/v44fP06DDKingG+STZw4UYMHD75sccIuXbooPDxciYmJkqTc3Fz16dNHPXv2VFxcnKZOnWpFXIP09HRNnjxZu3fv1vHjx/Xss89qyJAhateunSRp48aNKi0ttXWjzw72HvGc5u9r3xzkLBEnysvLszoCbKLkjKcRVpVFWzyNEjjT/HXSmfNXrhVl8vxtLAmAO/8x7znPNwf9M+6lDWMANRMfH6+33npLoaGhevnll3Xvvffq+++/r/Z53333nUpKSip+Dg0N1eHD9biLGSpQG50roJtkRUVF2rx5sx544IHLHissLFRCQoIiIiIkSQ8//LAmT56s9evXa8mSJZo4caK2bvXhIla1FB0drfbt22vt2rUV23bt2qVjx44pKSmpYtu8efN0zz33WBExYBT5qQ6UnL387BEEv/z8fKsjwCZW7/asRVadL7/2fxbYz9FT0pa91V/q/8XXktvmH7gw7zlP0RH/jPvdEfv/vQN2Exoaqr///e+KiIjQm2++qXHjxtXoed5rkBUXF2vRokW66qqr9Prrr/s5sTNQG52r6vvH2lxRkWe10ZYtWxq2nz59Wnl5eRoyZEjFNpfLpaNHj0qSSkpKFBERoWbNmlX7Gi6Xy3eBvTRu3FiSdOzYMcP2o0ePqkmTJhU/f/jhh/rtb39b5WSZl5fnt5yB4KZ7f62bh00wbKvuLkyVPf7kO8afu3TroeKizfVIV39PvO052gy0/8Z2zD127Nhq98nKyqp2v6ysLF9Fgo398PHXFX/rowoJrbxUut2lmvnuJ7rvxjtNTAY7aBOfqvt/taja/UrOSI2irtbZU0f9H+oKgnXes2ONqY6dMt+e/nfFD3zUsM0Xx07nS6WIyEa6cM66Txmfm/RXSZ7fs/f3Zgn93SSFJCWa9nrlcnNz5erTz9TXtPp3HSzuvvtu3XTTTfr222/15JNP1ug5lzbIbrvtNn333XfasmWLBg0apFtvvVVLly41PMfp7xm9BWNttFONqQ075g7oM8liYmIkSQUFBYbtU6ZM0b59+wyL9s+ePVv/9V//pfbt2ys+Pl6/+93v1KJFC1PzejtxwnOf7OjoaMP2pk2b6vjxi9futG/fXoWFhaZmCzRlbv/dZs6fYwOwt9LzZ6UaFOwLF86akAZ2U3q+5v/dS0tZmAz2wrETYB+jR4+WJL3yyisV7xGrcqUG2fr163XgwAFNnz5dkpSZmenXzEAwC+gzyTp16qTExERNnDhRzZo1U+vWrZWTk6MFCxZIUkWTrLS0VOPHj9fMmTN1++23a8eOHUpNTVXPnj11/fXXV/kaZTVclColJaVW1y0fO3ZMe/bsUa9evbRhwwZJUseOHRUdHa2NGzdW7Dd06FDNmTOnyrGSk5OVm5tb49cONmu/kd5aZtx26Rlh5co/Ba3scW8uSd99s0UR4fVJV3/lWWv6t2gXdsy9bVv1iwNlZWUpPT29yn1effVVX0WCjeUXSa9XM62HhITqhcz79EGWff7OYY4LpZ67nFa1ML/LJXWMkc6fOVn5Tn4WrPOeHWtMdeyU+dNN0oKNxm2+OHZq0lC6UIsGsj88P/k1SZ7fs/f3ZrltzUotOWL+mlApKSn6zOS/Lat/14Ho0veMDRs21A9+8ANduHBB//jHP6p9fmUNsnJvvPGGXnzxRQ0ZMkQul8vw38Pp7xm9BWNttFONqQ0zcqekpNRq/4A+kywkJETZ2dlKSEhQRkaGRowYoZiYGGVmZio0NLRi0f7169dr+/btuv322yV5FvXv16/fZaegmu21117Tc889pw4dOqhx48aaPHmyPv74Y+3Zs0eS1KhRI6WmpuqDDz6oZiRna1v9VbN1cm0TWd4gg/nGjx9vdQTYRNx1UkxU5SeTuVxSowZSrw6mxoJNhIVKt3arep+yMiklzpw89cG85zxt/HTs5K9jMiBYJSUlKTQ0VFu2bKlYGqgy1TXIJGnPnj3au3evmjRpoi5duvgvuANQG50roJtkkhQbG6vFixfr5MmTKiws1IQJE7Rp0ybFx8erYcOGkqS2bdtq//79FWdsHThwQCtWrFCPHj2sjK5Jkybp3//+t1avXq29e/cqNDRUDz30UMXjgwYN0ldffaXi4mILU9pfTGPPG1lfi7vO92PC/tLS0qyOAJsICZH+M0WKirjy4w3CpPRUKSKgz8lGfQy6XurRxvO9dzO1/PtB10uJbc3PVVvMe87T6Vr/zF0cOwG106lTJ0mq9oZyNWmQlSsfq3xs1A210bmC8tB+zZo16tfv4sKV1157rf7+97/rZz/7mVwul86dO6ennnpKt9xyi4UpJbfbrWeeeUbPPPPMFR8fOnSo5s2bZ3KqwBPikgbESvPW+XbcAV19Ox4CQ1xcnKV3voW9tIiWnr3Dc4fClTulE6elhhFSn47SrbFSMz806BE4QkOkEbdK6/ZISwukvYc9DbLYltLAblK3VlYnrBnmPeeJDJdu7Cgt8+HdeRuEecZE3YVNnWx1BJjsk08+0YABA3TkSNW3nO3evbt+8IMfVNsgk6Rf/vKXioqK4u6M9URtdK6ga5KVlJSooKCgYgHEcmlpaQHXDd6zZ4+ys7OtjhEQ+nWW8rZJR0/5ZrwbO0jXNKl2NwAO0LihNCTR8wVcKiTE0xigOYBA84N4afVu6dwF34yXGudpvgGoueLiYi1fvrza/TZt2qTBgwfr5MmTVTbIJBnWtwZQe0HXJIuKilJpqT3vqrN+/XrNnDmzxvtzHXTNNWwgpd0kvZZb/7EaR0r33Vj/cQAAAOyqeZR0d09pzpr6j3Xd1dLtCfUfB0Dlli1bVv1OAOot6JpkdrZhw4aKddHge/GtpTuTpA+r+BVXd2emBmHSyGTpqkrWIELwq+3dTwAg0DHvOdctsdLeI9KKnZXvU92xU5OG0mO3em5mAQDBgtroXDTJEFRuv14KD5Pmr5PctbyLbHRDacRAqUOMf7IhMMyYMcPqCABgKuY953K5pLS+nsskc7fV/vktmnhucBLT2OfRAMBS1EbnCvi7WwKXSukuPTW45rchd0m6qZP03J00yCBlZGRYHQEATMW852whLune3tLoH9b8buGhIdIP46Wn76BBBiA4URudizPJEJTaNPM0ynYdkL7cKe0+KBWXXHw8NERq1VTq1lLq39WzLgcgSbm5uVZHAABTMe9B8tyV9Vd3S1u/k1bukvYcko6dvvh4eKjU+mopobXUr4tnDVcACFbURueiSYag5XJJnVt4viTp1DnpV///ZqGT01g7AwAAwFtIiJTQxvMlSSVnpF/P8Xw/Kc3zISMAAMGMUgfHaNTg4vc0yAAAAKoW5XW2GA0yAIATUO4AwMvWrVutjgAApmLeAwDAiNroXDTJAMDL7NmzrY4AAKZi3gMAwIja6FysSeYjPXv2dORrA8Fm3LhxSktLszoGAJiGeQ/wnaTG1tzu06rXRe3U5X3brsJ9kqRO7VoZvjfjtZ2M2uhcNMl8ZNq0aVZHAAAAAGChV7rFWx0BNlaX94zPT35NkjTpuXTD9wD8g8stAQAAAAAA4Hg0yQDAy/Tp062OAACmYt4DAMCI2uhcNMkAwEtCQoLVEQDAVMx7AAAYURudiyYZAHhJTk62OgIAmIp5DwAAI2qjc9EkAwAAAAAAgOPRJAMAAAAAAIDj0SQDAC99+vSxOgIAmIp5DwAAI2qjc9EkAwAvq1evtjoCAJiKeQ8AACNqo3PRJAMAAAAAAIDj0SQDAAAAAACA49EkAwAvOTk5VkcAAFMx7wEAYERtdC6aZAAAAAAAAHC8MKsDBIsnn3xS69evt+S1e/bsqWnTptXpuXPXSHuP+DZPTbS+WvqPG81/XaA6w4YN09atW62OAQCmYd4DfIdja/P8cvsWbThxwvTXTWrcWK90izf9da1k1Xvd+rzPrS9qo3PRJPOR9evXKy8vz+oYtbb3iLTzgNUpAAAAgMDHsbV5Npw4oSVHDlsdwxEC9b0uUBdcbgkAAAAAAADHo0kGAF4yMzOtjgAApmLeAwDAiNroXDTJAMDLmDFjrI4AAKZi3gMAwIja6Fw0yQDAy8CBA62OAACmYt4DAMCI2uhcNMkAwMvBgwetjgAApmLeAwDAiNroXDTJAAAAAAAA4Hg0yQDAS3x8vNURAMBUzHsAAKu5XC6rIxhQG50rzOoAAGAnc+bMsToCAJiKeQ8A4CsNGjTQLbfcohtvvFHdu3dXRESETp48qU2bNmn16tVauXKlysrKDM+JiorSBx98oOnTp2v27NkWJTeiNjoXTTIA8PLSSy/p5ZdftjoGAJiGeQ8AUF9NmzbV008/rccff1wtWrSodL8dO3boz3/+s6ZPn65z584pKipKH3/8sQYMGKC2bdtq3rx5Onv2rInJr4za6FwBf7ml2+3W1KlT1bVrV0VGRiopKUl5eXnq1q2b0tPTrY5n8Mgjj2jx4sU13n/NmjUaNGiQHxPVXs7/pGjVv/6nxtvtwO2WNhRKf/7s4rZ3V0hFh63LVBOHTkj/Wnvx51c/llbslM6XWpepOhdKpdW7pGmfXNw2Z420/7h1mWorOzvb6ggAYKpAmfdK3dK6b6Q/Lry4bfZK6bsjlkWqkQPHpblrLv487RNp1S5PzbSr86XSyp1S1scXt72/1nNsAt8KxGPrYHDh6edU+s4sq2MEjTvuuEP5+fl64YUX1KJFC23evFl/+tOflJ6ergcffFBjxozR3/72NxUWFqpLly7KysrSmjVrdMstt1Q0yAoLC3X77bfbokEmBU5thO8F/JlkI0eO1Ny5c/Xiiy+qd+/eWr58uYYPH66DBw/qqaeesjpelUJCQjRp0iQ9+uijioyM1KeffqpRo0apuLhYkjRv3jwNHTpUn376qcVJA1epW5q5VNpUJHlf5b5yp6fh9MBN0oCulsWr1Ja90ptLpAvui9u+LZbeLZaWfy39/AdSowbW5buSs+elvy6Wdh00/q6XbpeWFUiP3CIltbMsHgAggJ0v9dTFrd9J3svWfLlD+nKnNLyfdFMn6/JVZuO30j+WSqVeVxbtOSR9c0hasUMalSpFhFuX70pOn5NmLJIKi431PG+bp54/NlCKb21ZPAA2M2bMGP3xj3+UJC1btkzPPfecli1bdsV9Q0JCdNddd2nq1Knq0aOHcnNzFRoaqsLCQqWmpmrXrl1mRgeuKKDPJJs1a5Zmzpyp+fPn6+mnn1ZqaqpeeOEF3Xzzzbpw4YJ69epldcQqPf/887rnnnvUt29ftWnTRpL01ltvVTxe3iRD3S3Y4GmQSZL3le/l32evknYdMDtV1Q6XeN4IlLqN28szFxZ7zoSzm5zVngaZZPxdS5K7TPrHF4F1RhkAwD7mf+VpkEmS91I2Zf//51krPB8m2cmB454GmfuSolj+466DnuMQu3l3hedYQ7q8npe6PccoxSWmxwJgQz/96U8rGmS/+tWvNHDgwEobZJLnKrD58+drwIAB2r9/v0JDQ1VWVqaxY8fSIINtBHSTbOLEiRo8eLCSk5MN27t06aLw8HAlJiZKkj799FP16dNHiYmJ6tWrl5YsWWJF3Mukp6dr8uTJ2r17t44fP65nn31WQ4YMUbt2ntNtNm7cqNLSUts3++zq7AXpi4Kq93HJ88monSz72nMG2aUHpt42fmuvA9Rjp6W131S9j7us+v8edpCXl2d1BAAwld3nvVPnPGeMValMWrLdlDg19kWB5wyyqur5uj3SsVOmRapWcYm04dvKHy+T5xhl+demRQJgU23atNH06dMlSU888YR++9vfyu12V/MszyL977//vlq0aKETJ07I5XJp4sSJioyM9HfkWrF7bYT/BOzllkVFRdq8ebPGjh172WOFhYVKSEhQRESEjh49qp/85CdatGiRevbsqfz8fN1xxx3avn17jf6P6K9b0UZHR6t9+/Zau/biolO7du3SsWPHlJSUpMLCQkmes8nuuecerVu3rtKx8vLy6pzz/hcWq01cSq2es2re/2rtgqmGbefPlKjd9bfVeIy8vFz9YlBqrV63tton/kj3PvtxlfuUSVq3+5weS47wa5baeHjKFl3dqnu1/01/8B9jtHHhn01KVbX4gY/q9vS/V7vfguXfalgf6665vNJ8camdO3eqc+fOVe6TlZXlq0gA4FfBMO91vvE+3fXk3Cr3KZP0Rf4xPTSgqSmZauKxaXvUOKbqmucuk/oPeUxbllRfQ82QeNtopT5a9bFFWVmZsj8r0NBe3U1KVTvPTfqrJM8xvPf3ZgnmY+tLWf27Dv3dJIUkJZr2euVyc3Pl6tPPtNez+vdcmalTpyo6Olr/+te/9Ic//KFGz/FepL+wsFA/+tGPlJOTo4SEBD3zzDOaMGGCYf/6vM+tSjDUxks98bbnIxk7/G3Uhh1zB+yZZEVFnmvoWrZsadh++vRp5eXlVZx9tWPHDjVt2lQ9e/aUJCUkJKhJkyb66KOPTM17qcaNG0uSjh07Zth+9OhRNWnSpOLnDz/8UHfeeaep2apz0z0vKOO1o4av62JvsTrWZcIaNKrRfqFhDeQKCfVzmpoLj7iqRpNEeA3/fWao6e86LMI+mSszf/58qyMAgKnsPu/VtHaENWjo5yS1U+PcNqqNNcnicrkUbqPMwSBQjq2Bcq1bt9b999+v8+fPKzMzs0bPubRBlpqaqm3btum//uu/JEkZGRkKC7PPOTx2r43wH/v8FdZSTEyMJKmgoEB33HFHxfYpU6Zo37596t27tyQpNjZWR48e1eLFi5Wamqrly5dr+/bt+uabb2r0OmVlVZ0kf1FKSkqtTsk8ccJze6Do6GjD9qZNm+r48YsLN7Vv377irLLKJCcnKzc3t8av7e2PC6WdFqzJlZycopz/qdnvtq72HZUmf1j9flc3ktylF/yapTamfy59vd+45sqVvDljihLbTjEnVDW27/Ms8lsVl6TuHZrX+P9T/rBtW/XX1mZlZVV7Z9xXX33VV5EAwK+CYd7bc0jK+qTqfVySrmvWwNIac6nff+JZoL+6RO/O/JPirvuTKZmqs+lb6Y1qViVxSeoV31Zv2Oh37e35ya9J8hzDe39vlmA+tr6U1b/r29as1JIj5t+uPiUlRZ+Z+O+0+vcsXf5e98EHH1RYWJhmz56t7777rtrnX6lBVr4G2eLFi5Wfn6+EhAQNGjRICxYsqHhefd7nViUYauOlnnzH8792qoM1YUbulJSUWu0fsGeSderUSYmJiZo4caL++c9/6vPPP1dGRobefPNNSapokjVp0kT/+te/9PLLL6tXr17661//qltvvdXyLvWxY8e0Z88ew3pjHTt2VHR0tDZu3FixbejQoZo3b54VEQNeq6ZS++bGOzNdyYBYM9LU3ICu1TfIoiKlBBvdWaprS0+zsarfdZnseSdRAIC9tWvuqenV1hib1fP+XatukLnkqZ3dWlaxk8niW0uNIwPvdw3AXH379pVUs7OtqmqQlfv3v/9tGBewUsA2yUJCQpSdna2EhARlZGRoxIgRiomJUWZmpkJDQysW7ZekgQMHavHixVq3bp3+8Y9/aO/evUpISLAwvcdrr72m5557Th06dFDjxo01efJkffzxx9qzZ48kqVGjRkpNTdUHH3xgcdLAdd+NUkjIlQ/2XJJaRku32OxA7/o2lR8wl/87ht0ohdro/70hLmlYH8/3lR1Yd7pG6tXetEh1Nn78eKsjAICp7D7vuVzSf9zo+d/Kakzrq6W+VS8dY7ob2kudr73yY+X/jvv7eI5T7CI0xJOpquZebEupRxvTIgGwoaSkJEmqct1sqWYNMu9xyse1A7vXRvhPwF5uKXkupVy8eLFh28MPP6z4+Hg1bHhxXYp9+/apVatWkqQ///nPio6OVmqquQtbXsmkSZN09dVXa/Xq1YqIiNDChQv10EMPVTw+aNAgffXVVyouts89zYf9OrdW263WIUbK/KH07krPrdi9JbSRftJXigy3JltlQkOkkcnS3DXSql3GW8c3aehp/PW0bu37SiW0kR5PlnJWS0e87tQV4pJ6d/A00cLss/RbpdLS0qyOAACmCoR5r2sL6ec/kGavlA553d3ZJSmxnfTjm6QImx3VhoVK6Smeurj2G2M9b9rI04y63obNpp7tpBG3eo5Djp2+uD3EJd3UydOwtNMHdYEu0I6tg0XY1MlWRwhoubm52rJlS7WXWmZnZ1fbIJOk7du3a968edU23cwUCLUR/mGzw4n6W7Nmjfr1M95t5OWXX9aiRYtUWlqqxMREvf/++7a4e4Lb7dYzzzyjZ5555oqPc6mlb3S6Vvrvu6RdBz3rlIWGeD4FbR5ldbLKNQiTftJPurOntGWvdO6CJ2/3Vvb6xPlSCW2kuNbS1997mpINwqTu10nR9lpLuUpxcXHaunWr1TEAwDSBMu/FtpReGCrt2C/tPy6FhUjdWklXX2V1sspFhEsP9pfuukHa9p2nnl/TxPNvCbH+ULRSSe08Z4tt/146dMJTz8svxQSAxx9/vEb7/e///q/atWunu+++u9IGmSRt3LhR9957r4/S+Uag1Eb4XlA1yUpKSlRQUKDRo0cbts+YMcOiRPWzZ88eZWdnWx0jKLhcnkseKrvswa4aR9rv8pHqhLg8b1q6tbI6CQAg2LhcnnUwu9poHa+aiG4YgPU8RIq7zuoUAALZF198oR49esjtdlsdBaixoGqSRUVFqbS01OoYlVq/fr1mzpxZ4/25DhoAAAAAEKhokCHQBFWTzO42bNigDRs2WB0DQBVqe4tgAAh0zHsAABhRG53LxqsbAYD5AvXybACoK+Y9AACMqI3ORZMMALxkZGRYHQEATMW8BwCAEbXRuWiSAYCX3NxcqyMAgKmY9wAAMKI2OhdNMgAAAAAAADgeTTIAAAAAAAA4Hk0yAPCydetWqyMAgKmY9wAAMKI2OleY1QGCRc+ePQPytVtf7bscgfC6QHVmz56ttLQ0q2MAgGmY9wDf4djaPEmNGzvqda1Ul/ebuwr3SZI6tWtl+N7fr+sr1EbnoknmI9OmTbM6Qp38x41WJwDsZdy4cRREAI7CvAf4DsfW5nmlW7zVERyjLu91n5/8miRp0nPphu8DBbXRubjcEgAAAAAAAI5HkwwAAAAAAACOR5MMALxMnz7d6ggAYCrmPQAAjKiNzkWTDAC8JCQkWB0BAEzFvAcAgBG10blokgGAl+TkZKsjAICpmPcAADCiNjoXTTIAAAAAAAA4Hk0yAPDSp08fqyMAgKmY9wAAMKI2OhdNMgDwsnr1aqsjAICpmPcAADCiNjoXTTIAAAAAAAA4Hk0yAAAAAAAAOB5NMgDwkpOTY3UEADAV8x4AAEbURueiSQYAAAAAAADHo0kGAF6GDRtmdQQAMBXzHgAARtRG56JJBgAAAAAAAMejSQYAAAAAAADHo0kGAF4yMzOtjgAApmLeAwDAiNroXDTJAMDLmDFjrI4AAKZi3gMAwIja6Fw0yQDAy8CBA62OAACmYt4DAMCI2uhcNMkAwMvBgwetjgAApmLeAwDAiNroXDTJAAAAAAAA4Hg0yQDAS3x8vNURAMBUzHsAABhRG52LJhkAeJkzZ47VEQDAVMx7AAAYURudiyYZAHh56aWXrI4AAKZi3gMAwIja6FwB0SRzu92aOnWqunbtqsjISCUlJSkvL0/dunVTenq61fEABJHs7GyrIwCAqZj3AAAwCqTaePTUxe/X75EulFqXJRiEWR2gJkaOHKm5c+fqxRdfVO/evbV8+XINHz5cBw8e1FNPPWV1PAAAAAAAANOcvSDNXimt23Nx28wvpEYNpHt6SX07W5ctkNm+STZr1izNnDlTubm5Sk5OliSlpqZq3bp1mjt3rnr16mVxQgAAAAAAAHOUuqW/5Upf77/8sVPnpFkrpDJJ/WiU1ZrtL7ecOHGiBg8eXNEgK9elSxeFh4crMTFRkuea4djYWIWEhCgnJ8ew7zfffKPk5GTFxsaqR48eWrp0qWn5AQSWvLw8qyMAgKmY9wAAMLJ7bdxcdOUGmbd566TzXHpZa7ZukhUVFWnz5s164IEHLnussLBQCQkJioiIkCQNHjxYH3/8sQYOHHjZvqNGjdKPf/xjFRQU6K9//at+8pOf6Ny5c37PDyDw5OfnWx0BAEzFvAcAgJHda+OXOySXq+p9Tp+TNn1rTp5gYuvLLYuKiiRJLVu2NGw/ffq08vLyNGTIkIpt/fv3v+IYhw4d0hdffKH58+dX7Hfddddp8eLF+tGPflRtBld1f3kAAsbYsWOr3ScrK6va/bKysnwVCQD8inkPTvPcpL9K8hzDe38P3+N3bY5A/T3bOXcw1MZHX9mh6BbVX0v58yde0Or5E01IVDdPvF0myT5/G5L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",
      "text/plain": [
       "<Figure size 1604.72x2131.08 with 1 Axes>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from copy import deepcopy\n",
    "from qiskit.circuit.library import HGate\n",
    "\n",
    "qc_1 = deepcopy(qc)\n",
    "# Instrument the code block to detect bit and phase flips\n",
    "qc_1.barrier()\n",
    "for i in range(6):\n",
    "    qc_1.cx(i + 10, i, label=\"inst_cx\")\n",
    "    qc_1.append(HGate(label=\"inst_h\"), [qc.qubits[i+10]])\n",
    "for i in range(6):\n",
    "    qc_1.measure(i, i)\n",
    "    qc_1.measure(i + 10, i + 10)\n",
    "qc_1.draw(output=\"mpl\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Pauli noise model definition"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "from qiskit_qec.noise.paulinoisemodel import PauliNoiseModel\n",
    "\n",
    "model = PauliNoiseModel()\n",
    "model.add_operation(\"cx\", {\"ix\": 1, \"iy\": 1, \"iz\": 1,\n",
    "                        \"xi\": 1, \"xx\": 1, \"xy\": 1, \"xz\": 1,\n",
    "                        \"yi\": 1, \"yx\": 1, \"yy\": 1, \"yz\": 1,\n",
    "                        \"zi\": 1, \"zx\": 1, \"zy\": 1,\n",
    "                        \"zz\": 1})\n",
    "model.add_operation(\"reset\", {\"x\": 1})\n",
    "# model.add_operation(\"measure\", {\"x\": 1})\n",
    "model.add_operation(\"id\", {\"x\": 1})\n",
    "model.add_operation(\"h\", {\"x\": 1, \"y\": 1, \"z\": 1})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Enumerate all single-fault paths"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(0, ['reset'], ['x'], [1, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (1, ['reset'], ['x'], [0, 0, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (2, ['reset'], ['x'], [0, 0, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (3, ['reset'], ['x'], [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (4, ['h'], ['x'], [1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (5, ['h'], ['y'], [1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (6, ['h'], ['z'], [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (7, ['cx'], ['ix'], [0, 0, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (8, ['cx'], ['iy'], [0, 0, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (9, ['cx'], ['iz'], [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (10, ['cx'], ['xi'], [1, 1, 1, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (11, ['cx'], ['xx'], [1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (12, ['cx'], ['xy'], [1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (13, ['cx'], ['xz'], [1, 1, 1, 1, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (14, ['cx'], ['yi'], [1, 1, 1, 1, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (15, ['cx'], ['yx'], [1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (16, ['cx'], ['yy'], [1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (17, ['cx'], ['yz'], [1, 1, 1, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (18, ['cx'], ['zi'], [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (19, ['cx'], ['zx'], [0, 0, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (20, ['cx'], ['zy'], [0, 0, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (21, ['cx'], ['zz'], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (22, ['cx'], ['ix'], [0, 0, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (23, ['cx'], ['iy'], [0, 0, 1, 1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (24, ['cx'], ['iz'], [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (25, ['cx'], ['xi'], [1, 1, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (26, ['cx'], ['xx'], [1, 1, 1, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (27, ['cx'], ['xy'], [1, 1, 1, 1, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (28, ['cx'], ['xz'], [1, 1, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (29, ['cx'], ['yi'], [1, 1, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (30, ['cx'], ['yx'], [1, 1, 1, 1, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (31, ['cx'], ['yy'], [1, 1, 1, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (32, ['cx'], ['yz'], [1, 1, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (33, ['cx'], ['zi'], [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (34, ['cx'], ['zx'], [0, 0, 1, 1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (35, ['cx'], ['zy'], [0, 0, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (36, ['cx'], ['zz'], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (37, ['cx'], ['ix'], [1, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (38, ['cx'], ['iy'], [1, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (39, ['cx'], ['iz'], [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (40, ['cx'], ['xi'], [0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (41, ['cx'], ['xx'], [1, 1, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (42, ['cx'], ['xy'], [1, 1, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (43, ['cx'], ['xz'], [0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (44, ['cx'], ['yi'], [0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (45, ['cx'], ['yx'], [1, 1, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (46, ['cx'], ['yy'], [1, 1, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (47, ['cx'], ['yz'], [0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (48, ['cx'], ['zi'], [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (49, ['cx'], ['zx'], [1, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (50, ['cx'], ['zy'], [1, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (51, ['cx'], ['zz'], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (52, ['cx'], ['ix'], [1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (53, ['cx'], ['iy'], [1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0]),\n",
       " (54, ['cx'], ['iz'], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0]),\n",
       " (55, ['cx'], ['xi'], [0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (56, ['cx'], ['xx'], [1, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (57, ['cx'], ['xy'], [1, 1, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0]),\n",
       " (58, ['cx'], ['xz'], [0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0]),\n",
       " (59, ['cx'], ['yi'], [0, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (60, ['cx'], ['yx'], [1, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (61, ['cx'], ['yy'], [1, 1, 0, 0, 0, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0]),\n",
       " (62, ['cx'], ['yz'], [0, 1, 0, 0, 0, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0]),\n",
       " (63, ['cx'], ['zi'], [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (64, ['cx'], ['zx'], [1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (65, ['cx'], ['zy'], [1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0]),\n",
       " (66, ['cx'], ['zz'], [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0]),\n",
       " (67, ['cx'], ['ix'], [0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (68, ['cx'], ['iy'], [0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0]),\n",
       " (69, ['cx'], ['iz'], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0]),\n",
       " (70, ['cx'], ['xi'], [0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (71, ['cx'], ['xx'], [0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (72, ['cx'], ['xy'], [0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0]),\n",
       " (73, ['cx'], ['xz'], [0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0]),\n",
       " (74, ['cx'], ['yi'], [0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (75, ['cx'], ['yx'], [0, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (76, ['cx'], ['yy'], [0, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 0, 0, 0, 0]),\n",
       " (77, ['cx'], ['yz'], [0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 0, 0, 0, 0]),\n",
       " (78, ['cx'], ['zi'], [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (79, ['cx'], ['zx'], [0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (80, ['cx'], ['zy'], [0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0]),\n",
       " (81, ['cx'], ['zz'], [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0]),\n",
       " (82, ['cx'], ['ix'], [0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (83, ['cx'], ['iy'], [0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0]),\n",
       " (84, ['cx'], ['iz'], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0]),\n",
       " (85, ['cx'], ['xi'], [0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (86, ['cx'], ['xx'], [0, 0, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (87, ['cx'], ['xy'], [0, 0, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0]),\n",
       " (88, ['cx'], ['xz'], [0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0]),\n",
       " (89, ['cx'], ['yi'], [0, 0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (90, ['cx'], ['yx'], [0, 0, 1, 1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (91, ['cx'], ['yy'], [0, 0, 1, 1, 0, 0, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0]),\n",
       " (92, ['cx'], ['yz'], [0, 0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0]),\n",
       " (93, ['cx'], ['zi'], [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (94, ['cx'], ['zx'], [0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (95, ['cx'], ['zy'], [0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0]),\n",
       " (96, ['cx'], ['zz'], [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0]),\n",
       " (97, ['cx'], ['ix'], [0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (98, ['cx'], ['iy'], [0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0]),\n",
       " (99, ['cx'], ['iz'], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0]),\n",
       " (100, ['cx'], ['xi'], [0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (101, ['cx'], ['xx'], [0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (102, ['cx'], ['xy'], [0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0]),\n",
       " (103, ['cx'], ['xz'], [0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0]),\n",
       " (104, ['cx'], ['yi'], [0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (105, ['cx'], ['yx'], [0, 0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (106, ['cx'], ['yy'], [0, 0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 1, 0, 0]),\n",
       " (107, ['cx'], ['yz'], [0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 1, 0, 0]),\n",
       " (108, ['cx'], ['zi'], [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (109, ['cx'], ['zx'], [0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (110, ['cx'], ['zy'], [0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0]),\n",
       " (111, ['cx'], ['zz'], [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0]),\n",
       " (112, ['cx'], ['ix'], [0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (113, ['cx'], ['iy'], [0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0]),\n",
       " (114, ['cx'], ['iz'], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0]),\n",
       " (115, ['cx'], ['xi'], [0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (116, ['cx'], ['xx'], [0, 0, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (117, ['cx'], ['xy'], [0, 0, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0]),\n",
       " (118, ['cx'], ['xz'], [0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0]),\n",
       " (119, ['cx'], ['yi'], [0, 0, 0, 0, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (120, ['cx'], ['yx'], [0, 0, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (121, ['cx'], ['yy'], [0, 0, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 0, 0, 1, 0]),\n",
       " (122, ['cx'], ['yz'], [0, 0, 0, 0, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 1, 0]),\n",
       " (123, ['cx'], ['zi'], [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (124, ['cx'], ['zx'], [0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (125, ['cx'], ['zy'], [0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0]),\n",
       " (126, ['cx'], ['zz'], [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0]),\n",
       " (127, ['cx'], ['ix'], [0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (128, ['cx'], ['iy'], [0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1]),\n",
       " (129, ['cx'], ['iz'], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1]),\n",
       " (130, ['cx'], ['xi'], [0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (131, ['cx'], ['xx'], [0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (132, ['cx'], ['xy'], [0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1]),\n",
       " (133, ['cx'], ['xz'], [0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1]),\n",
       " (134, ['cx'], ['yi'], [0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (135, ['cx'], ['yx'], [0, 0, 0, 0, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (136, ['cx'], ['yy'], [0, 0, 0, 0, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 1]),\n",
       " (137, ['cx'], ['yz'], [0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 1]),\n",
       " (138, ['cx'], ['zi'], [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (139, ['cx'], ['zx'], [0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (140, ['cx'], ['zy'], [0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1]),\n",
       " (141, ['cx'], ['zz'], [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1]),\n",
       " (142, ['cx'], ['ix'], [0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (143, ['cx'], ['iy'], [0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (144, ['cx'], ['iz'], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (145, ['cx'], ['xi'], [0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (146, ['cx'], ['xx'], [0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (147, ['cx'], ['xy'], [0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (148, ['cx'], ['xz'], [0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (149, ['cx'], ['yi'], [0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (150, ['cx'], ['yx'], [0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (151, ['cx'], ['yy'], [0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (152, ['cx'], ['yz'], [0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (153, ['cx'], ['zi'], [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (154, ['cx'], ['zx'], [0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (155, ['cx'], ['zy'], [0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (156, ['cx'], ['zz'], [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (157, ['id'], ['x'], [0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (158, ['cx'], ['ix'], [0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (159, ['cx'], ['iy'], [0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (160, ['cx'], ['iz'], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (161, ['cx'], ['xi'], [0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (162, ['cx'], ['xx'], [0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (163, ['cx'], ['xy'], [0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (164, ['cx'], ['xz'], [0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (165, ['cx'], ['yi'], [0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (166, ['cx'], ['yx'], [0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (167, ['cx'], ['yy'], [0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (168, ['cx'], ['yz'], [0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (169, ['cx'], ['zi'], [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (170, ['cx'], ['zx'], [0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (171, ['cx'], ['zy'], [0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (172, ['cx'], ['zz'], [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (173, ['id'], ['x'], [0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (174, ['cx'], ['ix'], [0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (175, ['cx'], ['iy'], [0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (176, ['cx'], ['iz'], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (177, ['cx'], ['xi'], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (178, ['cx'], ['xx'], [0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (179, ['cx'], ['xy'], [0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (180, ['cx'], ['xz'], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (181, ['cx'], ['yi'], [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (182, ['cx'], ['yx'], [0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (183, ['cx'], ['yy'], [0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (184, ['cx'], ['yz'], [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (185, ['cx'], ['zi'], [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (186, ['cx'], ['zx'], [0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (187, ['cx'], ['zy'], [0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (188, ['cx'], ['zz'], [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (189, ['id'], ['x'], [0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (190, ['h'], ['x'], [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (191, ['h'], ['y'], [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (192, ['h'], ['z'], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (193, ['id'], ['x'], [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0])]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from qiskit_qec.analysis.faultenumerator import FaultEnumerator\n",
    "\n",
    "fe = FaultEnumerator(qc_1, 1, \"propagator\", model=model, sim_seed=0)\n",
    "result = list(fe.generate_blocks())[0]\n",
    "result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "OrderedDict([('cx', 12), ('reset', 4), ('id', 4), ('measure', 4), ('h', 2), ('barrier', 2)])\n",
      "194\n"
     ]
    }
   ],
   "source": [
    "count = qc.count_ops()\n",
    "print(count)\n",
    "num_paths = count['reset'] + count['id'] + count['h']*3 + count['cx']*15\n",
    "print(num_paths)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Apply corrections based on flags ('deflag')\n",
    "# if f_1 (bit 6), apply X_1\n",
    "# if f_2 (bit 7), apply X_3\n",
    "# if f_3 (bit 8), apply X_5\n",
    "# if f_2 and f_3 (bits 7 and 8), apply X_0\n",
    "def process_flags(result):\n",
    "    processed_result = deepcopy(result)\n",
    "    for record in processed_result:\n",
    "        flags = record[3][6:9]\n",
    "        if flags == [1, 0, 0]:\n",
    "            record[3][1] ^= 1\n",
    "        if flags == [0, 1, 0]:\n",
    "            record[3][3] ^= 1\n",
    "        if flags == [0, 0, 1]:\n",
    "            record[3][5] ^= 1\n",
    "        if flags == [0, 1, 1]:\n",
    "            record[3][0] ^= 1\n",
    "    return processed_result\n",
    "processed_result = process_flags(result)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's now check that a 1-good measurement circuit does not produce errors of weight greater than 1 on the data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{1: {(0, 1), (1, 0), (1, 1)}, 0: {(0, 0)}}"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "weights = {}\n",
    "for record in processed_result:\n",
    "    datax = record[3][0:6]\n",
    "    dataz = record[3][10:16]\n",
    "    if sum(datax) > 3:\n",
    "        datax = [(x + 1) % 2 for x in datax]\n",
    "    num_errors = sum([int((x + y) > 0) for x, y in zip(datax, dataz)])\n",
    "    weights.setdefault(num_errors, set([]))\n",
    "    weights[num_errors].add((sum(datax), sum(dataz)))\n",
    "    if num_errors > 1:\n",
    "        print(\"FAILED!\")\n",
    "weights"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "All good!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### How about pairs of faults?\n",
    "\n",
    "The circuit is not designed to be strictly fault-tolerant against multiple faults. Instead, in the paper, the flag outcomes are combined with syndrome information to achieve fault-tolerance. This is a great strategy, since the Pauli measurement circuits might become more complicated if they need to detect higher order error propagations.\n",
    "\n",
    "However, it might also be desirable to have subcircuits that \"work\" regardless of the specific set of correctable errors of the quantum code. Is it possible that we are lucky and the circuit is 2-fault-tolerant?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(0,\n",
       "  ['reset', 'reset'],\n",
       "  ['x', 'x'],\n",
       "  [1, 1, 1, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (1,\n",
       "  ['reset', 'reset'],\n",
       "  ['x', 'x'],\n",
       "  [1, 1, 0, 0, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (2,\n",
       "  ['reset', 'reset'],\n",
       "  ['x', 'x'],\n",
       "  [1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (3,\n",
       "  ['reset', 'h'],\n",
       "  ['x', 'x'],\n",
       "  [0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (4,\n",
       "  ['reset', 'h'],\n",
       "  ['x', 'y'],\n",
       "  [0, 1, 1, 1, 1, 1, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (5,\n",
       "  ['reset', 'h'],\n",
       "  ['x', 'z'],\n",
       "  [1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (6,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'ix'],\n",
       "  [1, 1, 0, 0, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (7,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iy'],\n",
       "  [1, 1, 0, 0, 1, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (8,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iz'],\n",
       "  [1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (9,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xi'],\n",
       "  [0, 0, 1, 1, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (10,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xx'],\n",
       "  [0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (11,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xy'],\n",
       "  [0, 1, 1, 1, 1, 1, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (12,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xz'],\n",
       "  [0, 0, 1, 1, 0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (13,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yi'],\n",
       "  [0, 0, 1, 1, 0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (14,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yx'],\n",
       "  [0, 1, 1, 1, 1, 1, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (15,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yy'],\n",
       "  [0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (16,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yz'],\n",
       "  [0, 0, 1, 1, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (17,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zi'],\n",
       "  [1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (18,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zx'],\n",
       "  [1, 1, 0, 0, 1, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (19,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zy'],\n",
       "  [1, 1, 0, 0, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (20,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zz'],\n",
       "  [1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (21,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'ix'],\n",
       "  [1, 1, 1, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (22,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iy'],\n",
       "  [1, 1, 1, 1, 0, 0, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (23,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iz'],\n",
       "  [1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (24,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xi'],\n",
       "  [0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (25,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xx'],\n",
       "  [0, 0, 1, 1, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (26,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xy'],\n",
       "  [0, 0, 1, 1, 0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (27,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xz'],\n",
       "  [0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (28,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yi'],\n",
       "  [0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (29,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yx'],\n",
       "  [0, 0, 1, 1, 0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (30,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yy'],\n",
       "  [0, 0, 1, 1, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (31,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yz'],\n",
       "  [0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (32,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zi'],\n",
       "  [1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (33,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zx'],\n",
       "  [1, 1, 1, 1, 0, 0, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (34,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zy'],\n",
       "  [1, 1, 1, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (35,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zz'],\n",
       "  [1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (36,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'ix'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (37,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iy'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (38,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iz'],\n",
       "  [1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (39,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xi'],\n",
       "  [0, 1, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (40,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xx'],\n",
       "  [0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (41,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xy'],\n",
       "  [0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (42,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xz'],\n",
       "  [0, 1, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (43,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yi'],\n",
       "  [0, 1, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (44,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yx'],\n",
       "  [0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (45,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yy'],\n",
       "  [0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (46,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yz'],\n",
       "  [0, 1, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (47,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zi'],\n",
       "  [1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (48,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zx'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (49,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zy'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (50,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zz'],\n",
       "  [1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (51,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'ix'],\n",
       "  [0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (52,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iy'],\n",
       "  [0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0]),\n",
       " (53,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iz'],\n",
       "  [1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0]),\n",
       " (54,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xi'],\n",
       "  [1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (55,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xx'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (56,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xy'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0]),\n",
       " (57,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xz'],\n",
       "  [1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0]),\n",
       " (58,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yi'],\n",
       "  [1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (59,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yx'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (60,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yy'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0]),\n",
       " (61,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yz'],\n",
       "  [1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0]),\n",
       " (62,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zi'],\n",
       "  [1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (63,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zx'],\n",
       "  [0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (64,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zy'],\n",
       "  [0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0]),\n",
       " (65,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zz'],\n",
       "  [1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0]),\n",
       " (66,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'ix'],\n",
       "  [1, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (67,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iy'],\n",
       "  [1, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0]),\n",
       " (68,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iz'],\n",
       "  [1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0]),\n",
       " (69,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xi'],\n",
       "  [1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (70,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xx'],\n",
       "  [1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (71,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xy'],\n",
       "  [1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0]),\n",
       " (72,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xz'],\n",
       "  [1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0]),\n",
       " (73,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yi'],\n",
       "  [1, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (74,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yx'],\n",
       "  [1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (75,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yy'],\n",
       "  [1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0]),\n",
       " (76,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yz'],\n",
       "  [1, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0]),\n",
       " (77,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zi'],\n",
       "  [1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (78,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zx'],\n",
       "  [1, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (79,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zy'],\n",
       "  [1, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 0, 0, 0, 0]),\n",
       " (80,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zz'],\n",
       "  [1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 0, 0, 0, 0]),\n",
       " (81,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'ix'],\n",
       "  [1, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (82,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iy'],\n",
       "  [1, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0]),\n",
       " (83,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iz'],\n",
       "  [1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0]),\n",
       " (84,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xi'],\n",
       "  [1, 1, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (85,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xx'],\n",
       "  [1, 1, 1, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (86,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xy'],\n",
       "  [1, 1, 1, 1, 0, 0, 1, 1, 0, 0, 0, 0, 1, 0, 0, 0]),\n",
       " (87,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xz'],\n",
       "  [1, 1, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 1, 0, 0, 0]),\n",
       " (88,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yi'],\n",
       "  [1, 1, 0, 1, 0, 0, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (89,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yx'],\n",
       "  [1, 1, 1, 1, 0, 0, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (90,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yy'],\n",
       "  [1, 1, 1, 1, 0, 0, 1, 1, 0, 1, 0, 0, 1, 0, 0, 0]),\n",
       " (91,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yz'],\n",
       "  [1, 1, 0, 1, 0, 0, 1, 1, 0, 1, 0, 0, 1, 0, 0, 0]),\n",
       " (92,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zi'],\n",
       "  [1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (93,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zx'],\n",
       "  [1, 0, 1, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (94,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zy'],\n",
       "  [1, 0, 1, 0, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 0]),\n",
       " (95,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zz'],\n",
       "  [1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 0]),\n",
       " (96,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'ix'],\n",
       "  [1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (97,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iy'],\n",
       "  [1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0]),\n",
       " (98,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iz'],\n",
       "  [1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0]),\n",
       " (99,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xi'],\n",
       "  [1, 1, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (100,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xx'],\n",
       "  [1, 1, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (101,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xy'],\n",
       "  [1, 1, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 1, 0, 0]),\n",
       " (102,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xz'],\n",
       "  [1, 1, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 1, 0, 0]),\n",
       " (103,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yi'],\n",
       "  [1, 1, 0, 0, 0, 0, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (104,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yx'],\n",
       "  [1, 1, 0, 1, 0, 0, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (105,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yy'],\n",
       "  [1, 1, 0, 1, 0, 0, 1, 1, 0, 1, 0, 0, 0, 1, 0, 0]),\n",
       " (106,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yz'],\n",
       "  [1, 1, 0, 0, 0, 0, 1, 1, 0, 1, 0, 0, 0, 1, 0, 0]),\n",
       " (107,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zi'],\n",
       "  [1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (108,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zx'],\n",
       "  [1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (109,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zy'],\n",
       "  [1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 1, 0, 0]),\n",
       " (110,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zz'],\n",
       "  [1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 1, 0, 0]),\n",
       " (111,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'ix'],\n",
       "  [1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (112,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iy'],\n",
       "  [1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0]),\n",
       " (113,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iz'],\n",
       "  [1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0]),\n",
       " (114,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xi'],\n",
       "  [1, 1, 0, 0, 0, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (115,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xx'],\n",
       "  [1, 1, 0, 0, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (116,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xy'],\n",
       "  [1, 1, 0, 0, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 1, 0]),\n",
       " (117,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xz'],\n",
       "  [1, 1, 0, 0, 0, 1, 1, 0, 1, 0, 0, 0, 0, 0, 1, 0]),\n",
       " (118,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yi'],\n",
       "  [1, 1, 0, 0, 0, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (119,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yx'],\n",
       "  [1, 1, 0, 0, 1, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (120,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yy'],\n",
       "  [1, 1, 0, 0, 1, 1, 1, 0, 1, 1, 0, 0, 0, 0, 1, 0]),\n",
       " (121,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yz'],\n",
       "  [1, 1, 0, 0, 0, 1, 1, 0, 1, 1, 0, 0, 0, 0, 1, 0]),\n",
       " (122,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zi'],\n",
       "  [1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (123,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zx'],\n",
       "  [1, 0, 0, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (124,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zy'],\n",
       "  [1, 0, 0, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 1, 0]),\n",
       " (125,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zz'],\n",
       "  [1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 1, 0]),\n",
       " (126,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'ix'],\n",
       "  [1, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (127,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iy'],\n",
       "  [1, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1]),\n",
       " (128,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iz'],\n",
       "  [1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1]),\n",
       " (129,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xi'],\n",
       "  [1, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (130,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xx'],\n",
       "  [1, 1, 0, 0, 0, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (131,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xy'],\n",
       "  [1, 1, 0, 0, 0, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 1]),\n",
       " (132,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xz'],\n",
       "  [1, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 1]),\n",
       " (133,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yi'],\n",
       "  [1, 1, 0, 0, 0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (134,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yx'],\n",
       "  [1, 1, 0, 0, 0, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (135,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yy'],\n",
       "  [1, 1, 0, 0, 0, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 1]),\n",
       " (136,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yz'],\n",
       "  [1, 1, 0, 0, 0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 0, 1]),\n",
       " (137,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zi'],\n",
       "  [1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (138,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zx'],\n",
       "  [1, 0, 0, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (139,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zy'],\n",
       "  [1, 0, 0, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 0, 0, 1]),\n",
       " (140,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zz'],\n",
       "  [1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 1]),\n",
       " (141,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'ix'],\n",
       "  [1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (142,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iy'],\n",
       "  [1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (143,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iz'],\n",
       "  [1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (144,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xi'],\n",
       "  [1, 1, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (145,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xx'],\n",
       "  [0, 1, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (146,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xy'],\n",
       "  [0, 1, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (147,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xz'],\n",
       "  [1, 1, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (148,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yi'],\n",
       "  [1, 1, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (149,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yx'],\n",
       "  [0, 1, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (150,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yy'],\n",
       "  [0, 1, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (151,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yz'],\n",
       "  [1, 1, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (152,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zi'],\n",
       "  [1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (153,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zx'],\n",
       "  [1, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (154,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zy'],\n",
       "  [1, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (155,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zz'],\n",
       "  [1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (156,\n",
       "  ['reset', 'id'],\n",
       "  ['x', 'x'],\n",
       "  [1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (157,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'ix'],\n",
       "  [1, 1, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (158,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iy'],\n",
       "  [1, 1, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (159,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iz'],\n",
       "  [1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (160,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xi'],\n",
       "  [1, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (161,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xx'],\n",
       "  [1, 1, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (162,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xy'],\n",
       "  [1, 1, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (163,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xz'],\n",
       "  [1, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (164,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yi'],\n",
       "  [1, 1, 0, 0, 0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (165,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yx'],\n",
       "  [1, 1, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (166,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yy'],\n",
       "  [1, 1, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (167,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yz'],\n",
       "  [1, 1, 0, 0, 0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (168,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zi'],\n",
       "  [1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (169,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zx'],\n",
       "  [1, 1, 0, 0, 0, 0, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (170,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zy'],\n",
       "  [1, 1, 0, 0, 0, 0, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (171,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zz'],\n",
       "  [1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (172,\n",
       "  ['reset', 'id'],\n",
       "  ['x', 'x'],\n",
       "  [1, 1, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (173,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'ix'],\n",
       "  [1, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (174,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iy'],\n",
       "  [1, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (175,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iz'],\n",
       "  [1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (176,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xi'],\n",
       "  [1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (177,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xx'],\n",
       "  [1, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (178,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xy'],\n",
       "  [1, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (179,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xz'],\n",
       "  [1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (180,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yi'],\n",
       "  [1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (181,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yx'],\n",
       "  [1, 1, 0, 0, 0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (182,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yy'],\n",
       "  [1, 1, 0, 0, 0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (183,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yz'],\n",
       "  [1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (184,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zi'],\n",
       "  [1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (185,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zx'],\n",
       "  [1, 1, 0, 0, 0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (186,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zy'],\n",
       "  [1, 1, 0, 0, 0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (187,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zz'],\n",
       "  [1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (188,\n",
       "  ['reset', 'id'],\n",
       "  ['x', 'x'],\n",
       "  [1, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (189,\n",
       "  ['reset', 'h'],\n",
       "  ['x', 'x'],\n",
       "  [1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (190,\n",
       "  ['reset', 'h'],\n",
       "  ['x', 'y'],\n",
       "  [1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (191,\n",
       "  ['reset', 'h'],\n",
       "  ['x', 'z'],\n",
       "  [1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (192,\n",
       "  ['reset', 'id'],\n",
       "  ['x', 'x'],\n",
       "  [1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (193,\n",
       "  ['reset', 'reset'],\n",
       "  ['x', 'x'],\n",
       "  [1, 0, 1, 1, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (194,\n",
       "  ['reset', 'reset'],\n",
       "  ['x', 'x'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (195,\n",
       "  ['reset', 'h'],\n",
       "  ['x', 'x'],\n",
       "  [1, 1, 0, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (196,\n",
       "  ['reset', 'h'],\n",
       "  ['x', 'y'],\n",
       "  [1, 1, 0, 1, 1, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (197,\n",
       "  ['reset', 'h'],\n",
       "  ['x', 'z'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (198,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'ix'],\n",
       "  [1, 0, 1, 1, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (199,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iy'],\n",
       "  [1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (200,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iz'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (201,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xi'],\n",
       "  [0, 1, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (202,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xx'],\n",
       "  [1, 1, 0, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (203,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xy'],\n",
       "  [1, 1, 0, 1, 1, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (204,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xz'],\n",
       "  [0, 1, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (205,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yi'],\n",
       "  [0, 1, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (206,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yx'],\n",
       "  [1, 1, 0, 1, 1, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (207,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yy'],\n",
       "  [1, 1, 0, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (208,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yz'],\n",
       "  [0, 1, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (209,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zi'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (210,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zx'],\n",
       "  [1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (211,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zy'],\n",
       "  [1, 0, 1, 1, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (212,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zz'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (213,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'ix'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (214,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iy'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (215,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iz'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (216,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xi'],\n",
       "  [1, 1, 1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (217,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xx'],\n",
       "  [0, 1, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (218,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xy'],\n",
       "  [0, 1, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (219,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xz'],\n",
       "  [1, 1, 1, 1, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (220,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yi'],\n",
       "  [1, 1, 1, 1, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (221,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yx'],\n",
       "  [0, 1, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (222,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yy'],\n",
       "  [0, 1, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (223,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yz'],\n",
       "  [1, 1, 1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (224,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zi'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (225,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zx'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (226,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zy'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (227,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zz'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (228,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'ix'],\n",
       "  [1, 1, 1, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (229,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iy'],\n",
       "  [1, 1, 1, 1, 0, 0, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (230,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iz'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (231,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xi'],\n",
       "  [0, 0, 1, 1, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (232,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xx'],\n",
       "  [1, 1, 1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (233,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xy'],\n",
       "  [1, 1, 1, 1, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (234,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xz'],\n",
       "  [0, 0, 1, 1, 0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (235,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yi'],\n",
       "  [0, 0, 1, 1, 0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (236,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yx'],\n",
       "  [1, 1, 1, 1, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (237,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yy'],\n",
       "  [1, 1, 1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (238,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yz'],\n",
       "  [0, 0, 1, 1, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (239,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zi'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (240,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zx'],\n",
       "  [1, 1, 1, 1, 0, 0, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (241,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zy'],\n",
       "  [1, 1, 1, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (242,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zz'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (243,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'ix'],\n",
       "  [1, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (244,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iy'],\n",
       "  [1, 0, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0]),\n",
       " (245,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iz'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0]),\n",
       " (246,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xi'],\n",
       "  [0, 1, 1, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (247,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xx'],\n",
       "  [1, 1, 1, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (248,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xy'],\n",
       "  [1, 1, 1, 1, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 0, 0]),\n",
       " (249,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xz'],\n",
       "  [0, 1, 1, 1, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 0, 0]),\n",
       " (250,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yi'],\n",
       "  [0, 1, 1, 1, 0, 0, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (251,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yx'],\n",
       "  [1, 1, 1, 1, 0, 0, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (252,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yy'],\n",
       "  [1, 1, 1, 1, 0, 0, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0]),\n",
       " (253,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yz'],\n",
       "  [0, 1, 1, 1, 0, 0, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0]),\n",
       " (254,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zi'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (255,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zx'],\n",
       "  [1, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (256,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zy'],\n",
       "  [1, 0, 1, 0, 0, 0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 0]),\n",
       " (257,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zz'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 0]),\n",
       " (258,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'ix'],\n",
       "  [0, 1, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (259,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iy'],\n",
       "  [0, 1, 1, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0]),\n",
       " (260,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iz'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0]),\n",
       " (261,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xi'],\n",
       "  [0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (262,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xx'],\n",
       "  [0, 1, 1, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (263,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xy'],\n",
       "  [0, 1, 1, 1, 0, 0, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0]),\n",
       " (264,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xz'],\n",
       "  [0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0]),\n",
       " (265,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yi'],\n",
       "  [0, 0, 1, 1, 0, 0, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (266,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yx'],\n",
       "  [0, 1, 1, 1, 0, 0, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (267,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yy'],\n",
       "  [0, 1, 1, 1, 0, 0, 1, 1, 0, 1, 0, 1, 0, 0, 0, 0]),\n",
       " (268,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yz'],\n",
       "  [0, 0, 1, 1, 0, 0, 1, 1, 0, 1, 0, 1, 0, 0, 0, 0]),\n",
       " (269,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zi'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (270,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zx'],\n",
       "  [0, 1, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (271,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zy'],\n",
       "  [0, 1, 1, 0, 0, 0, 0, 1, 0, 1, 0, 1, 0, 0, 0, 0]),\n",
       " (272,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zz'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 1, 0, 0, 0, 0]),\n",
       " (273,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'ix'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (274,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iy'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0]),\n",
       " (275,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iz'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0]),\n",
       " (276,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xi'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (277,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xx'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (278,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xy'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0]),\n",
       " (279,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xz'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0]),\n",
       " (280,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yi'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (281,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yx'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (282,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yy'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0]),\n",
       " (283,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yz'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0]),\n",
       " (284,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zi'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (285,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zx'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (286,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zy'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0]),\n",
       " (287,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zz'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0]),\n",
       " (288,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'ix'],\n",
       "  [0, 0, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (289,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iy'],\n",
       "  [0, 0, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0]),\n",
       " (290,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iz'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0]),\n",
       " (291,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xi'],\n",
       "  [0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (292,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xx'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (293,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xy'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0]),\n",
       " (294,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xz'],\n",
       "  [0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0]),\n",
       " (295,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yi'],\n",
       "  [0, 0, 1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (296,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yx'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (297,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yy'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0]),\n",
       " (298,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yz'],\n",
       "  [0, 0, 1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0]),\n",
       " (299,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zi'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (300,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zx'],\n",
       "  [0, 0, 1, 1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (301,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zy'],\n",
       "  [0, 0, 1, 1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 1, 0, 0]),\n",
       " (302,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zz'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 1, 0, 0]),\n",
       " (303,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'ix'],\n",
       "  [0, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (304,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iy'],\n",
       "  [0, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0]),\n",
       " (305,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iz'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0]),\n",
       " (306,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xi'],\n",
       "  [1, 0, 1, 1, 0, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (307,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xx'],\n",
       "  [1, 0, 1, 1, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (308,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xy'],\n",
       "  [1, 0, 1, 1, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 1, 0]),\n",
       " (309,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xz'],\n",
       "  [1, 0, 1, 1, 0, 1, 0, 1, 1, 0, 0, 0, 0, 0, 1, 0]),\n",
       " (310,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yi'],\n",
       "  [1, 0, 1, 1, 0, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (311,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yx'],\n",
       "  [1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (312,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yy'],\n",
       "  [1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 0, 0, 0, 0, 1, 0]),\n",
       " (313,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yz'],\n",
       "  [1, 0, 1, 1, 0, 1, 0, 1, 1, 1, 0, 0, 0, 0, 1, 0]),\n",
       " (314,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zi'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (315,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zx'],\n",
       "  [0, 0, 1, 0, 1, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (316,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zy'],\n",
       "  [0, 0, 1, 0, 1, 0, 0, 1, 0, 1, 0, 0, 0, 0, 1, 0]),\n",
       " (317,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zz'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 1, 0]),\n",
       " (318,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'ix'],\n",
       "  [0, 0, 1, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (319,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iy'],\n",
       "  [0, 0, 1, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1]),\n",
       " (320,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iz'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1]),\n",
       " (321,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xi'],\n",
       "  [1, 0, 1, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (322,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xx'],\n",
       "  [1, 0, 1, 1, 0, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (323,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xy'],\n",
       "  [1, 0, 1, 1, 0, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0, 1]),\n",
       " (324,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xz'],\n",
       "  [1, 0, 1, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 1]),\n",
       " (325,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yi'],\n",
       "  [1, 0, 1, 1, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (326,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yx'],\n",
       "  [1, 0, 1, 1, 0, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (327,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yy'],\n",
       "  [1, 0, 1, 1, 0, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 1]),\n",
       " (328,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yz'],\n",
       "  [1, 0, 1, 1, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 1]),\n",
       " (329,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zi'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (330,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zx'],\n",
       "  [0, 0, 1, 0, 0, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (331,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zy'],\n",
       "  [0, 0, 1, 0, 0, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 1]),\n",
       " (332,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zz'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 1]),\n",
       " (333,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'ix'],\n",
       "  [0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (334,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iy'],\n",
       "  [0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (335,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iz'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (336,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xi'],\n",
       "  [0, 0, 1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (337,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xx'],\n",
       "  [0, 0, 1, 1, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (338,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xy'],\n",
       "  [0, 0, 1, 1, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (339,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xz'],\n",
       "  [0, 0, 1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (340,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yi'],\n",
       "  [0, 0, 1, 1, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (341,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yx'],\n",
       "  [0, 0, 1, 1, 0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (342,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yy'],\n",
       "  [0, 0, 1, 1, 0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (343,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yz'],\n",
       "  [0, 0, 1, 1, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (344,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zi'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (345,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zx'],\n",
       "  [0, 0, 1, 1, 0, 0, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (346,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zy'],\n",
       "  [0, 0, 1, 1, 0, 0, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (347,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zz'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (348,\n",
       "  ['reset', 'id'],\n",
       "  ['x', 'x'],\n",
       "  [0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (349,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'ix'],\n",
       "  [0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (350,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iy'],\n",
       "  [0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (351,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iz'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (352,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xi'],\n",
       "  [1, 0, 1, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (353,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xx'],\n",
       "  [0, 0, 1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (354,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xy'],\n",
       "  [0, 0, 1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (355,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xz'],\n",
       "  [1, 0, 1, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (356,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yi'],\n",
       "  [1, 0, 1, 1, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (357,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yx'],\n",
       "  [0, 0, 1, 1, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (358,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yy'],\n",
       "  [0, 0, 1, 1, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (359,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yz'],\n",
       "  [1, 0, 1, 1, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (360,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zi'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (361,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zx'],\n",
       "  [0, 0, 1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (362,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zy'],\n",
       "  [0, 0, 1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (363,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zz'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (364,\n",
       "  ['reset', 'id'],\n",
       "  ['x', 'x'],\n",
       "  [0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (365,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'ix'],\n",
       "  [1, 0, 1, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (366,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iy'],\n",
       "  [1, 0, 1, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (367,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iz'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (368,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xi'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (369,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xx'],\n",
       "  [1, 0, 1, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (370,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xy'],\n",
       "  [1, 0, 1, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (371,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xz'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (372,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yi'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (373,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yx'],\n",
       "  [1, 0, 1, 1, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (374,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yy'],\n",
       "  [1, 0, 1, 1, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (375,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yz'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (376,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zi'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (377,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zx'],\n",
       "  [1, 0, 1, 1, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (378,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zy'],\n",
       "  [1, 0, 1, 1, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (379,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zz'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (380,\n",
       "  ['reset', 'id'],\n",
       "  ['x', 'x'],\n",
       "  [1, 0, 1, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (381,\n",
       "  ['reset', 'h'],\n",
       "  ['x', 'x'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (382,\n",
       "  ['reset', 'h'],\n",
       "  ['x', 'y'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (383,\n",
       "  ['reset', 'h'],\n",
       "  ['x', 'z'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (384,\n",
       "  ['reset', 'id'],\n",
       "  ['x', 'x'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (385,\n",
       "  ['reset', 'reset'],\n",
       "  ['x', 'x'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (386,\n",
       "  ['reset', 'h'],\n",
       "  ['x', 'x'],\n",
       "  [1, 1, 1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (387,\n",
       "  ['reset', 'h'],\n",
       "  ['x', 'y'],\n",
       "  [1, 1, 1, 1, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (388,\n",
       "  ['reset', 'h'],\n",
       "  ['x', 'z'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (389,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'ix'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (390,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iy'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (391,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iz'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (392,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xi'],\n",
       "  [1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (393,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xx'],\n",
       "  [1, 1, 1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (394,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xy'],\n",
       "  [1, 1, 1, 1, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (395,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xz'],\n",
       "  [1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (396,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yi'],\n",
       "  [1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (397,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yx'],\n",
       "  [1, 1, 1, 1, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (398,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yy'],\n",
       "  [1, 1, 1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (399,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yz'],\n",
       "  [1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (400,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zi'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (401,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zx'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (402,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zy'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (403,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zz'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (404,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'ix'],\n",
       "  [1, 0, 1, 1, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (405,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iy'],\n",
       "  [1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (406,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iz'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (407,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xi'],\n",
       "  [1, 1, 0, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (408,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xx'],\n",
       "  [1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (409,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xy'],\n",
       "  [1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (410,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xz'],\n",
       "  [1, 1, 0, 1, 1, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (411,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yi'],\n",
       "  [1, 1, 0, 1, 1, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (412,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yx'],\n",
       "  [1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (413,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yy'],\n",
       "  [1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (414,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yz'],\n",
       "  [1, 1, 0, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (415,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zi'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (416,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zx'],\n",
       "  [1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (417,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zy'],\n",
       "  [1, 0, 1, 1, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (418,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zz'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (419,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'ix'],\n",
       "  [1, 1, 0, 0, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (420,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iy'],\n",
       "  [1, 1, 0, 0, 1, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (421,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iz'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (422,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xi'],\n",
       "  [0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (423,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xx'],\n",
       "  [1, 1, 0, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (424,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xy'],\n",
       "  [1, 1, 0, 1, 1, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (425,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xz'],\n",
       "  [0, 0, 0, 0, 1, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (426,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yi'],\n",
       "  [0, 0, 0, 0, 1, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (427,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yx'],\n",
       "  [1, 1, 0, 1, 1, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (428,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yy'],\n",
       "  [1, 1, 0, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (429,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yz'],\n",
       "  [0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (430,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zi'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (431,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zx'],\n",
       "  [1, 1, 0, 0, 1, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (432,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zy'],\n",
       "  [1, 1, 0, 0, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (433,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zz'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (434,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'ix'],\n",
       "  [1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (435,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iy'],\n",
       "  [1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0]),\n",
       " (436,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iz'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0]),\n",
       " (437,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xi'],\n",
       "  [0, 1, 0, 0, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (438,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xx'],\n",
       "  [1, 1, 0, 0, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (439,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xy'],\n",
       "  [1, 1, 0, 0, 1, 1, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0]),\n",
       " (440,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xz'],\n",
       "  [0, 1, 0, 0, 1, 1, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0]),\n",
       " (441,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yi'],\n",
       "  [0, 1, 0, 0, 1, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (442,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yx'],\n",
       "  [1, 1, 0, 0, 1, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (443,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yy'],\n",
       "  [1, 1, 0, 0, 1, 1, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0]),\n",
       " (444,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yz'],\n",
       "  [0, 1, 0, 0, 1, 1, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0]),\n",
       " (445,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zi'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (446,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zx'],\n",
       "  [1, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (447,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zy'],\n",
       "  [1, 0, 0, 0, 1, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0]),\n",
       " (448,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zz'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0]),\n",
       " (449,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'ix'],\n",
       "  [0, 1, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (450,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iy'],\n",
       "  [0, 1, 0, 0, 1, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0]),\n",
       " (451,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iz'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0]),\n",
       " (452,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xi'],\n",
       "  [0, 0, 0, 0, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (453,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xx'],\n",
       "  [0, 1, 0, 0, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (454,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xy'],\n",
       "  [0, 1, 0, 0, 1, 1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0]),\n",
       " (455,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xz'],\n",
       "  [0, 0, 0, 0, 1, 1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0]),\n",
       " (456,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yi'],\n",
       "  [0, 0, 0, 0, 1, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (457,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yx'],\n",
       "  [0, 1, 0, 0, 1, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (458,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yy'],\n",
       "  [0, 1, 0, 0, 1, 1, 1, 0, 1, 1, 0, 1, 0, 0, 0, 0]),\n",
       " (459,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yz'],\n",
       "  [0, 0, 0, 0, 1, 1, 1, 0, 1, 1, 0, 1, 0, 0, 0, 0]),\n",
       " (460,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zi'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (461,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zx'],\n",
       "  [0, 1, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (462,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zy'],\n",
       "  [0, 1, 0, 0, 1, 0, 0, 0, 1, 1, 0, 1, 0, 0, 0, 0]),\n",
       " (463,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zz'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 1, 0, 0, 0, 0]),\n",
       " (464,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'ix'],\n",
       "  [0, 0, 1, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (465,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iy'],\n",
       "  [0, 0, 1, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0]),\n",
       " (466,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iz'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0]),\n",
       " (467,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xi'],\n",
       "  [1, 0, 0, 1, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (468,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xx'],\n",
       "  [1, 0, 1, 1, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (469,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xy'],\n",
       "  [1, 0, 1, 1, 1, 1, 0, 1, 1, 0, 0, 0, 1, 0, 0, 0]),\n",
       " (470,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xz'],\n",
       "  [1, 0, 0, 1, 1, 1, 0, 1, 1, 0, 0, 0, 1, 0, 0, 0]),\n",
       " (471,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yi'],\n",
       "  [1, 0, 0, 1, 1, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (472,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yx'],\n",
       "  [1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (473,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yy'],\n",
       "  [1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 0, 0, 1, 0, 0, 0]),\n",
       " (474,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yz'],\n",
       "  [1, 0, 0, 1, 1, 1, 0, 1, 1, 1, 0, 0, 1, 0, 0, 0]),\n",
       " (475,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zi'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (476,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zx'],\n",
       "  [0, 0, 1, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (477,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zy'],\n",
       "  [0, 0, 1, 0, 1, 0, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0]),\n",
       " (478,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zz'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0]),\n",
       " (479,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'ix'],\n",
       "  [0, 0, 0, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (480,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iy'],\n",
       "  [0, 0, 0, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0]),\n",
       " (481,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iz'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0]),\n",
       " (482,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xi'],\n",
       "  [1, 0, 0, 0, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (483,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xx'],\n",
       "  [1, 0, 0, 1, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (484,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xy'],\n",
       "  [1, 0, 0, 1, 1, 1, 0, 1, 1, 0, 0, 0, 0, 1, 0, 0]),\n",
       " (485,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xz'],\n",
       "  [1, 0, 0, 0, 1, 1, 0, 1, 1, 0, 0, 0, 0, 1, 0, 0]),\n",
       " (486,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yi'],\n",
       "  [1, 0, 0, 0, 1, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (487,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yx'],\n",
       "  [1, 0, 0, 1, 1, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (488,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yy'],\n",
       "  [1, 0, 0, 1, 1, 1, 0, 1, 1, 1, 0, 0, 0, 1, 0, 0]),\n",
       " (489,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yz'],\n",
       "  [1, 0, 0, 0, 1, 1, 0, 1, 1, 1, 0, 0, 0, 1, 0, 0]),\n",
       " (490,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zi'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (491,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zx'],\n",
       "  [0, 0, 0, 1, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (492,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zy'],\n",
       "  [0, 0, 0, 1, 1, 0, 0, 0, 1, 1, 0, 0, 0, 1, 0, 0]),\n",
       " (493,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zz'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 1, 0, 0]),\n",
       " (494,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'ix'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (495,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iy'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0]),\n",
       " (496,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iz'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0]),\n",
       " (497,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xi'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (498,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xx'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (499,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xy'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0]),\n",
       " (500,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xz'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0]),\n",
       " (501,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yi'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (502,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yx'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (503,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yy'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0]),\n",
       " (504,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yz'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0]),\n",
       " (505,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zi'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (506,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zx'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (507,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zy'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 1, 0]),\n",
       " (508,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zz'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 1, 0]),\n",
       " (509,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'ix'],\n",
       "  [0, 0, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (510,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iy'],\n",
       "  [0, 0, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1]),\n",
       " (511,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iz'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1]),\n",
       " (512,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xi'],\n",
       "  [0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (513,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xx'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (514,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xy'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1]),\n",
       " (515,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xz'],\n",
       "  [0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1]),\n",
       " (516,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yi'],\n",
       "  [0, 0, 0, 0, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (517,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yx'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (518,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yy'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1]),\n",
       " (519,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yz'],\n",
       "  [0, 0, 0, 0, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1]),\n",
       " (520,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zi'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (521,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zx'],\n",
       "  [0, 0, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (522,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zy'],\n",
       "  [0, 0, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 1]),\n",
       " (523,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zz'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 1]),\n",
       " (524,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'ix'],\n",
       "  [0, 0, 0, 0, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (525,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iy'],\n",
       "  [0, 0, 0, 0, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (526,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iz'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (527,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xi'],\n",
       "  [0, 0, 0, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (528,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xx'],\n",
       "  [0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (529,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xy'],\n",
       "  [0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (530,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xz'],\n",
       "  [0, 0, 0, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (531,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yi'],\n",
       "  [0, 0, 0, 1, 1, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (532,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yx'],\n",
       "  [0, 0, 0, 0, 1, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (533,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yy'],\n",
       "  [0, 0, 0, 0, 1, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (534,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yz'],\n",
       "  [0, 0, 0, 1, 1, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (535,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zi'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (536,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zx'],\n",
       "  [0, 0, 0, 0, 1, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (537,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zy'],\n",
       "  [0, 0, 0, 0, 1, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (538,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zz'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (539,\n",
       "  ['reset', 'id'],\n",
       "  ['x', 'x'],\n",
       "  [0, 0, 0, 0, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (540,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'ix'],\n",
       "  [1, 0, 0, 0, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (541,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iy'],\n",
       "  [1, 0, 0, 0, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (542,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iz'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (543,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xi'],\n",
       "  [0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (544,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xx'],\n",
       "  [0, 0, 0, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (545,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xy'],\n",
       "  [0, 0, 0, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (546,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xz'],\n",
       "  [0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (547,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yi'],\n",
       "  [0, 0, 0, 0, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (548,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yx'],\n",
       "  [0, 0, 0, 1, 1, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (549,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yy'],\n",
       "  [0, 0, 0, 1, 1, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (550,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yz'],\n",
       "  [0, 0, 0, 0, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (551,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zi'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (552,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zx'],\n",
       "  [1, 0, 0, 0, 1, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (553,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zy'],\n",
       "  [1, 0, 0, 0, 1, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (554,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zz'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (555,\n",
       "  ['reset', 'id'],\n",
       "  ['x', 'x'],\n",
       "  [1, 0, 0, 0, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (556,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'ix'],\n",
       "  [0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (557,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iy'],\n",
       "  [0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (558,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iz'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (559,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xi'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (560,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xx'],\n",
       "  [0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (561,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xy'],\n",
       "  [0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (562,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xz'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (563,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yi'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (564,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yx'],\n",
       "  [0, 0, 0, 0, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (565,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yy'],\n",
       "  [0, 0, 0, 0, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (566,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yz'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (567,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zi'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (568,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zx'],\n",
       "  [0, 0, 0, 0, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (569,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zy'],\n",
       "  [0, 0, 0, 0, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (570,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zz'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (571,\n",
       "  ['reset', 'id'],\n",
       "  ['x', 'x'],\n",
       "  [0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (572,\n",
       "  ['reset', 'h'],\n",
       "  ['x', 'x'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (573,\n",
       "  ['reset', 'h'],\n",
       "  ['x', 'y'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (574,\n",
       "  ['reset', 'h'],\n",
       "  ['x', 'z'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (575,\n",
       "  ['reset', 'id'],\n",
       "  ['x', 'x'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (576,\n",
       "  ['reset', 'h'],\n",
       "  ['x', 'x'],\n",
       "  [1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (577,\n",
       "  ['reset', 'h'],\n",
       "  ['x', 'y'],\n",
       "  [1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (578,\n",
       "  ['reset', 'h'],\n",
       "  ['x', 'z'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (579,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'ix'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (580,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iy'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (581,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iz'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (582,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xi'],\n",
       "  [1, 1, 1, 1, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (583,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xx'],\n",
       "  [1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (584,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xy'],\n",
       "  [1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (585,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xz'],\n",
       "  [1, 1, 1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (586,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yi'],\n",
       "  [1, 1, 1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (587,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yx'],\n",
       "  [1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (588,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yy'],\n",
       "  [1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (589,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yz'],\n",
       "  [1, 1, 1, 1, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (590,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zi'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (591,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zx'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (592,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zy'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (593,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zz'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (594,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'ix'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (595,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iy'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (596,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iz'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (597,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xi'],\n",
       "  [0, 1, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (598,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xx'],\n",
       "  [1, 1, 1, 1, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (599,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xy'],\n",
       "  [1, 1, 1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (600,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xz'],\n",
       "  [0, 1, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (601,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yi'],\n",
       "  [0, 1, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (602,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yx'],\n",
       "  [1, 1, 1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (603,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yy'],\n",
       "  [1, 1, 1, 1, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (604,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yz'],\n",
       "  [0, 1, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (605,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zi'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (606,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zx'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (607,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zy'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (608,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zz'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (609,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'ix'],\n",
       "  [1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (610,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iy'],\n",
       "  [1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (611,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iz'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (612,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xi'],\n",
       "  [0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (613,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xx'],\n",
       "  [0, 1, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (614,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xy'],\n",
       "  [0, 1, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (615,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xz'],\n",
       "  [0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (616,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yi'],\n",
       "  [0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (617,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yx'],\n",
       "  [0, 1, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (618,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yy'],\n",
       "  [0, 1, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (619,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yz'],\n",
       "  [0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (620,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zi'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (621,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zx'],\n",
       "  [1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (622,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zy'],\n",
       "  [1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (623,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zz'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (624,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'ix'],\n",
       "  [1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (625,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iy'],\n",
       "  [1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0]),\n",
       " (626,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iz'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0]),\n",
       " (627,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xi'],\n",
       "  [0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (628,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xx'],\n",
       "  [1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (629,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xy'],\n",
       "  [1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0]),\n",
       " (630,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xz'],\n",
       "  [0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0]),\n",
       " (631,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yi'],\n",
       "  [0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (632,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yx'],\n",
       "  [1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (633,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yy'],\n",
       "  [1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0]),\n",
       " (634,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yz'],\n",
       "  [0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0]),\n",
       " (635,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zi'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (636,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zx'],\n",
       "  [1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (637,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zy'],\n",
       "  [1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0]),\n",
       " (638,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zz'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0]),\n",
       " (639,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'ix'],\n",
       "  [0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (640,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iy'],\n",
       "  [0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0]),\n",
       " (641,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iz'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0]),\n",
       " (642,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xi'],\n",
       "  [0, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (643,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xx'],\n",
       "  [0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (644,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xy'],\n",
       "  [0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 0, 0, 0, 0]),\n",
       " (645,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xz'],\n",
       "  [0, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 0, 0, 0, 0]),\n",
       " (646,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yi'],\n",
       "  [0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (647,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yx'],\n",
       "  [0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (648,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yy'],\n",
       "  [0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0]),\n",
       " (649,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yz'],\n",
       "  [0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0]),\n",
       " (650,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zi'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (651,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zx'],\n",
       "  [0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (652,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zy'],\n",
       "  [0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0]),\n",
       " (653,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zz'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0]),\n",
       " (654,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'ix'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (655,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iy'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0]),\n",
       " (656,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iz'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0]),\n",
       " (657,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xi'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (658,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xx'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (659,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xy'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0]),\n",
       " (660,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xz'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0]),\n",
       " (661,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yi'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (662,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yx'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (663,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yy'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0]),\n",
       " (664,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yz'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0]),\n",
       " (665,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zi'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (666,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zx'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (667,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zy'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0]),\n",
       " (668,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zz'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0]),\n",
       " (669,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'ix'],\n",
       "  [0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (670,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iy'],\n",
       "  [0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0]),\n",
       " (671,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iz'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0]),\n",
       " (672,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xi'],\n",
       "  [0, 0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (673,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xx'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (674,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xy'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 1, 0, 0]),\n",
       " (675,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xz'],\n",
       "  [0, 0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 1, 0, 0]),\n",
       " (676,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yi'],\n",
       "  [0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (677,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yx'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (678,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yy'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0]),\n",
       " (679,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yz'],\n",
       "  [0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0]),\n",
       " (680,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zi'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (681,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zx'],\n",
       "  [0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (682,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zy'],\n",
       "  [0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0]),\n",
       " (683,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zz'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0]),\n",
       " (684,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'ix'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (685,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iy'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0]),\n",
       " (686,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iz'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0]),\n",
       " (687,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xi'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (688,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xx'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (689,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xy'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 1, 0]),\n",
       " (690,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xz'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 1, 0]),\n",
       " (691,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yi'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (692,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yx'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (693,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yy'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0]),\n",
       " (694,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yz'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0]),\n",
       " (695,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zi'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (696,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zx'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (697,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zy'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0]),\n",
       " (698,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zz'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0]),\n",
       " (699,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'ix'],\n",
       "  [0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (700,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iy'],\n",
       "  [0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1]),\n",
       " (701,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iz'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1]),\n",
       " (702,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xi'],\n",
       "  [0, 0, 0, 0, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (703,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xx'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (704,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xy'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 1]),\n",
       " (705,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xz'],\n",
       "  [0, 0, 0, 0, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 1]),\n",
       " (706,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yi'],\n",
       "  [0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (707,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yx'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (708,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yy'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1]),\n",
       " (709,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yz'],\n",
       "  [0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1]),\n",
       " (710,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zi'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (711,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zx'],\n",
       "  [0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (712,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zy'],\n",
       "  [0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1]),\n",
       " (713,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zz'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1]),\n",
       " (714,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'ix'],\n",
       "  [0, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (715,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iy'],\n",
       "  [0, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (716,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iz'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (717,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xi'],\n",
       "  [1, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (718,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xx'],\n",
       "  [0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (719,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xy'],\n",
       "  [0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (720,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xz'],\n",
       "  [1, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (721,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yi'],\n",
       "  [1, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (722,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yx'],\n",
       "  [0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (723,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yy'],\n",
       "  [0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (724,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yz'],\n",
       "  [1, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (725,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zi'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (726,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zx'],\n",
       "  [0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (727,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zy'],\n",
       "  [0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (728,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zz'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (729,\n",
       "  ['reset', 'id'],\n",
       "  ['x', 'x'],\n",
       "  [0, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (730,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'ix'],\n",
       "  [0, 0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (731,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iy'],\n",
       "  [0, 0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (732,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iz'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (733,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xi'],\n",
       "  [0, 0, 0, 0, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (734,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xx'],\n",
       "  [1, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (735,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xy'],\n",
       "  [1, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (736,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xz'],\n",
       "  [0, 0, 0, 0, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (737,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yi'],\n",
       "  [0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (738,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yx'],\n",
       "  [1, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (739,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yy'],\n",
       "  [1, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (740,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yz'],\n",
       "  [0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (741,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zi'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (742,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zx'],\n",
       "  [0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (743,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zy'],\n",
       "  [0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (744,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zz'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (745,\n",
       "  ['reset', 'id'],\n",
       "  ['x', 'x'],\n",
       "  [0, 0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (746,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'ix'],\n",
       "  [0, 0, 0, 0, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (747,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iy'],\n",
       "  [0, 0, 0, 0, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (748,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'iz'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (749,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xi'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (750,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xx'],\n",
       "  [0, 0, 0, 0, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (751,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xy'],\n",
       "  [0, 0, 0, 0, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (752,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'xz'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (753,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yi'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (754,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yx'],\n",
       "  [0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (755,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yy'],\n",
       "  [0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (756,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'yz'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (757,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zi'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (758,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zx'],\n",
       "  [0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (759,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zy'],\n",
       "  [0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (760,\n",
       "  ['reset', 'cx'],\n",
       "  ['x', 'zz'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (761,\n",
       "  ['reset', 'id'],\n",
       "  ['x', 'x'],\n",
       "  [0, 0, 0, 0, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (762,\n",
       "  ['reset', 'h'],\n",
       "  ['x', 'x'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (763,\n",
       "  ['reset', 'h'],\n",
       "  ['x', 'y'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (764,\n",
       "  ['reset', 'h'],\n",
       "  ['x', 'z'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (765,\n",
       "  ['reset', 'id'],\n",
       "  ['x', 'x'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (766,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'ix'],\n",
       "  [1, 1, 1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (767,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'iy'],\n",
       "  [1, 1, 1, 1, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (768,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'iz'],\n",
       "  [1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (769,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'xi'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (770,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'xx'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (771,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'xy'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (772,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'xz'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (773,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'yi'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (774,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'yx'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (775,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'yy'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (776,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'yz'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (777,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'zi'],\n",
       "  [1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (778,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'zx'],\n",
       "  [1, 1, 1, 1, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (779,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'zy'],\n",
       "  [1, 1, 1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (780,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'zz'],\n",
       "  [1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (781,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'ix'],\n",
       "  [1, 1, 1, 1, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (782,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'iy'],\n",
       "  [1, 1, 1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (783,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'iz'],\n",
       "  [1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (784,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'xi'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (785,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'xx'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (786,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'xy'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (787,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'xz'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (788,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'yi'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (789,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'yx'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (790,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'yy'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (791,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'yz'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (792,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'zi'],\n",
       "  [1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (793,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'zx'],\n",
       "  [1, 1, 1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (794,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'zy'],\n",
       "  [1, 1, 1, 1, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (795,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'zz'],\n",
       "  [1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (796,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'ix'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (797,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'iy'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (798,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'iz'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (799,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'xi'],\n",
       "  [1, 1, 1, 1, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (800,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'xx'],\n",
       "  [1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (801,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'xy'],\n",
       "  [1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (802,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'xz'],\n",
       "  [1, 1, 1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (803,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'yi'],\n",
       "  [1, 1, 1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (804,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'yx'],\n",
       "  [1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (805,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'yy'],\n",
       "  [1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (806,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'yz'],\n",
       "  [1, 1, 1, 1, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (807,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'zi'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (808,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'zx'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (809,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'zy'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (810,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'zz'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (811,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'ix'],\n",
       "  [1, 1, 0, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (812,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'iy'],\n",
       "  [1, 1, 0, 1, 1, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (813,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'iz'],\n",
       "  [1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (814,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'xi'],\n",
       "  [1, 0, 1, 1, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (815,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'xx'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (816,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'xy'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (817,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'xz'],\n",
       "  [1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (818,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'yi'],\n",
       "  [1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (819,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'yx'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (820,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'yy'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (821,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'yz'],\n",
       "  [1, 0, 1, 1, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (822,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'zi'],\n",
       "  [1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (823,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'zx'],\n",
       "  [1, 1, 0, 1, 1, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (824,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'zy'],\n",
       "  [1, 1, 0, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (825,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'zz'],\n",
       "  [1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (826,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'ix'],\n",
       "  [1, 1, 0, 1, 1, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (827,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'iy'],\n",
       "  [1, 1, 0, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (828,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'iz'],\n",
       "  [1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (829,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'xi'],\n",
       "  [1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (830,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'xx'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (831,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'xy'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (832,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'xz'],\n",
       "  [1, 0, 1, 1, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (833,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'yi'],\n",
       "  [1, 0, 1, 1, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (834,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'yx'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (835,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'yy'],\n",
       "  [0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (836,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'yz'],\n",
       "  [1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (837,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'zi'],\n",
       "  [1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (838,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'zx'],\n",
       "  [1, 1, 0, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (839,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'zy'],\n",
       "  [1, 1, 0, 1, 1, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (840,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'zz'],\n",
       "  [1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (841,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'ix'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (842,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'iy'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (843,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'iz'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (844,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'xi'],\n",
       "  [0, 1, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (845,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'xx'],\n",
       "  [1, 1, 1, 1, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (846,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'xy'],\n",
       "  [1, 1, 1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (847,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'xz'],\n",
       "  [0, 1, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (848,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'yi'],\n",
       "  [0, 1, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (849,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'yx'],\n",
       "  [1, 1, 1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (850,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'yy'],\n",
       "  [1, 1, 1, 1, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (851,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'yz'],\n",
       "  [0, 1, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (852,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'zi'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (853,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'zx'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (854,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'zy'],\n",
       "  [0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (855,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'zz'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (856,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'ix'],\n",
       "  [0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (857,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'iy'],\n",
       "  [0, 1, 1, 1, 1, 1, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (858,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'iz'],\n",
       "  [1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (859,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'xi'],\n",
       "  [1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (860,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'xx'],\n",
       "  [1, 0, 1, 1, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (861,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'xy'],\n",
       "  [1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (862,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'xz'],\n",
       "  [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (863,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'yi'],\n",
       "  [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (864,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'yx'],\n",
       "  [1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (865,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'yy'],\n",
       "  [1, 0, 1, 1, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (866,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'yz'],\n",
       "  [1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (867,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'zi'],\n",
       "  [1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (868,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'zx'],\n",
       "  [0, 1, 1, 1, 1, 1, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (869,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'zy'],\n",
       "  [0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (870,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'zz'],\n",
       "  [1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (871,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'ix'],\n",
       "  [0, 1, 1, 1, 1, 1, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (872,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'iy'],\n",
       "  [0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (873,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'iz'],\n",
       "  [1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (874,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'xi'],\n",
       "  [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (875,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'xx'],\n",
       "  [1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (876,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'xy'],\n",
       "  [1, 0, 1, 1, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (877,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'xz'],\n",
       "  [1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (878,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'yi'],\n",
       "  [1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (879,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'yx'],\n",
       "  [1, 0, 1, 1, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (880,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'yy'],\n",
       "  [1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (881,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'yz'],\n",
       "  [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (882,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'zi'],\n",
       "  [1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (883,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'zx'],\n",
       "  [0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (884,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'zy'],\n",
       "  [0, 1, 1, 1, 1, 1, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (885,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'zz'],\n",
       "  [1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (886,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'ix'],\n",
       "  [1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (887,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'iy'],\n",
       "  [1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (888,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'iz'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (889,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'xi'],\n",
       "  [0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (890,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'xx'],\n",
       "  [0, 1, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (891,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'xy'],\n",
       "  [0, 1, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (892,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'xz'],\n",
       "  [0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (893,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'yi'],\n",
       "  [0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (894,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'yx'],\n",
       "  [0, 1, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (895,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'yy'],\n",
       "  [0, 1, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (896,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'yz'],\n",
       "  [0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (897,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'zi'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (898,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'zx'],\n",
       "  [1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (899,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'zy'],\n",
       "  [1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (900,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'zz'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (901,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'ix'],\n",
       "  [0, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (902,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'iy'],\n",
       "  [0, 1, 1, 1, 1, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0]),\n",
       " (903,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'iz'],\n",
       "  [1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0]),\n",
       " (904,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'xi'],\n",
       "  [1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (905,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'xx'],\n",
       "  [0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (906,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'xy'],\n",
       "  [0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0]),\n",
       " (907,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'xz'],\n",
       "  [1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0]),\n",
       " (908,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'yi'],\n",
       "  [1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (909,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'yx'],\n",
       "  [0, 1, 1, 1, 1, 1, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (910,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'yy'],\n",
       "  [0, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0]),\n",
       " (911,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'yz'],\n",
       "  [1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0]),\n",
       " (912,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'zi'],\n",
       "  [1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (913,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'zx'],\n",
       "  [0, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (914,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'zy'],\n",
       "  [0, 1, 1, 1, 1, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0]),\n",
       " (915,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'zz'],\n",
       "  [1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0]),\n",
       " (916,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'ix'],\n",
       "  [0, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (917,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'iy'],\n",
       "  [0, 1, 1, 1, 1, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0]),\n",
       " (918,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'iz'],\n",
       "  [1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0]),\n",
       " (919,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'xi'],\n",
       "  [1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (920,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'xx'],\n",
       "  [0, 1, 1, 1, 1, 1, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (921,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'xy'],\n",
       "  [0, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0]),\n",
       " (922,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'xz'],\n",
       "  [1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0]),\n",
       " (923,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'yi'],\n",
       "  [1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (924,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'yx'],\n",
       "  [0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (925,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'yy'],\n",
       "  [0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0]),\n",
       " (926,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'yz'],\n",
       "  [1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0]),\n",
       " (927,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'zi'],\n",
       "  [1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (928,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'zx'],\n",
       "  [0, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (929,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'zy'],\n",
       "  [0, 1, 1, 1, 1, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0]),\n",
       " (930,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'zz'],\n",
       "  [1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0]),\n",
       " (931,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'ix'],\n",
       "  [1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (932,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'iy'],\n",
       "  [1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0]),\n",
       " (933,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'iz'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0]),\n",
       " (934,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'xi'],\n",
       "  [0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (935,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'xx'],\n",
       "  [1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (936,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'xy'],\n",
       "  [1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0]),\n",
       " (937,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'xz'],\n",
       "  [0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0]),\n",
       " (938,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'yi'],\n",
       "  [0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (939,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'yx'],\n",
       "  [1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (940,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'yy'],\n",
       "  [1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0]),\n",
       " (941,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'yz'],\n",
       "  [0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0]),\n",
       " (942,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'zi'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (943,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'zx'],\n",
       "  [1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (944,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'zy'],\n",
       "  [1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0]),\n",
       " (945,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'zz'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0]),\n",
       " (946,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'ix'],\n",
       "  [1, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (947,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'iy'],\n",
       "  [1, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0]),\n",
       " (948,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'iz'],\n",
       "  [1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0]),\n",
       " (949,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'xi'],\n",
       "  [1, 0, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (950,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'xx'],\n",
       "  [1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (951,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'xy'],\n",
       "  [1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0]),\n",
       " (952,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'xz'],\n",
       "  [1, 0, 1, 1, 1, 1, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0]),\n",
       " (953,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'yi'],\n",
       "  [1, 0, 1, 1, 1, 1, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (954,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'yx'],\n",
       "  [1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (955,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'yy'],\n",
       "  [1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 0, 1, 0, 0, 0, 0]),\n",
       " (956,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'yz'],\n",
       "  [1, 0, 1, 1, 1, 1, 1, 0, 0, 1, 0, 1, 0, 0, 0, 0]),\n",
       " (957,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'zi'],\n",
       "  [1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (958,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'zx'],\n",
       "  [1, 0, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (959,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'zy'],\n",
       "  [1, 0, 1, 1, 1, 1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0]),\n",
       " (960,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'zz'],\n",
       "  [1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0]),\n",
       " (961,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'ix'],\n",
       "  [1, 0, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (962,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'iy'],\n",
       "  [1, 0, 1, 1, 1, 1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0]),\n",
       " (963,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'iz'],\n",
       "  [1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0]),\n",
       " (964,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'xi'],\n",
       "  [1, 0, 1, 1, 1, 1, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (965,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'xx'],\n",
       "  [1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (966,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'xy'],\n",
       "  [1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 0, 1, 0, 0, 0, 0]),\n",
       " (967,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'xz'],\n",
       "  [1, 0, 1, 1, 1, 1, 1, 0, 0, 1, 0, 1, 0, 0, 0, 0]),\n",
       " (968,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'yi'],\n",
       "  [1, 0, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (969,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'yx'],\n",
       "  [1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (970,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'yy'],\n",
       "  [1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0]),\n",
       " (971,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'yz'],\n",
       "  [1, 0, 1, 1, 1, 1, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0]),\n",
       " (972,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'zi'],\n",
       "  [1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (973,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'zx'],\n",
       "  [1, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (974,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'zy'],\n",
       "  [1, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0]),\n",
       " (975,\n",
       "  ['h', 'cx'],\n",
       "  ['y', 'zz'],\n",
       "  [1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0]),\n",
       " (976,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'ix'],\n",
       "  [0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (977,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'iy'],\n",
       "  [0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0]),\n",
       " (978,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'iz'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0]),\n",
       " (979,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'xi'],\n",
       "  [0, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (980,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'xx'],\n",
       "  [0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (981,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'xy'],\n",
       "  [0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 0, 0, 0, 0]),\n",
       " (982,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'xz'],\n",
       "  [0, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 0, 0, 0, 0]),\n",
       " (983,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'yi'],\n",
       "  [0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (984,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'yx'],\n",
       "  [0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (985,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'yy'],\n",
       "  [0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0]),\n",
       " (986,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'yz'],\n",
       "  [0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0]),\n",
       " (987,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'zi'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (988,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'zx'],\n",
       "  [0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (989,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'zy'],\n",
       "  [0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0]),\n",
       " (990,\n",
       "  ['h', 'cx'],\n",
       "  ['z', 'zz'],\n",
       "  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0]),\n",
       " (991,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'ix'],\n",
       "  [1, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (992,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'iy'],\n",
       "  [1, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0]),\n",
       " (993,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'iz'],\n",
       "  [1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0]),\n",
       " (994,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'xi'],\n",
       "  [1, 1, 1, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (995,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'xx'],\n",
       "  [1, 1, 0, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0]),\n",
       " (996,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'xy'],\n",
       "  [1, 1, 0, 1, 1, 1, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0]),\n",
       " (997,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'xz'],\n",
       "  [1, 1, 1, 1, 1, 1, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0]),\n",
       " (998,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'yi'],\n",
       "  [1, 1, 1, 1, 1, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " (999,\n",
       "  ['h', 'cx'],\n",
       "  ['x', 'yx'],\n",
       "  [1, 1, 0, 1, 1, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]),\n",
       " ...]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fe2 = FaultEnumerator(qc_1, 2, \"propagator\", model=model, sim_seed=0)\n",
    "result = []\n",
    "for x in fe2.generate_blocks():\n",
    "    result.extend(x)\n",
    "processed_result = process_flags(result)\n",
    "processed_result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "17455\n",
      "17455\n"
     ]
    }
   ],
   "source": [
    "count = qc.count_ops()\n",
    "def choose2(n):\n",
    "    return int(n*(n-1)/2)\n",
    "num_paths = choose2(count['reset']) + choose2(count['id']) + \\\n",
    "    3*3*choose2(count['h']) + 15*15*choose2(count['cx']) + \\\n",
    "    count['reset']*count['id'] + 3*count['reset']*count['h'] + \\\n",
    "    15*count['reset']*count['cx'] + 3*count['id']*count['h'] + \\\n",
    "    15*count['id']*count['cx'] + 3*15*count['h']*count['cx']\n",
    "print(num_paths)\n",
    "print(len(result))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1138\n"
     ]
    }
   ],
   "source": [
    "bad_records = []\n",
    "for record in processed_result:\n",
    "    data = record[3][0:6]  # X errors on the data\n",
    "    num_errors = sum(data)\n",
    "    if num_errors > 3:\n",
    "        num_errors = 6 - num_errors\n",
    "    if num_errors > 2:\n",
    "        bad_records.append(record)\n",
    "print(len(bad_records))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There are some bad fault paths, so we need to try to adapt our flag correction protocol, if possible."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{(1, 1, 0): {(0, 0, 0, 0, 0, 0),\n",
       "  (0, 0, 0, 0, 0, 1),\n",
       "  (0, 0, 0, 0, 1, 1),\n",
       "  (0, 0, 0, 1, 0, 0),\n",
       "  (0, 0, 1, 1, 0, 0),\n",
       "  (0, 1, 0, 0, 0, 0),\n",
       "  (0, 1, 0, 1, 0, 0),\n",
       "  (0, 1, 1, 1, 0, 0),\n",
       "  (1, 1, 0, 0, 0, 0),\n",
       "  (1, 1, 0, 1, 0, 0),\n",
       "  (1, 1, 1, 1, 0, 0)},\n",
       " (1, 0, 1): {(0, 0, 0, 0, 0, 0),\n",
       "  (0, 0, 0, 0, 0, 1),\n",
       "  (0, 0, 0, 0, 1, 1),\n",
       "  (0, 0, 0, 1, 0, 0),\n",
       "  (0, 0, 1, 1, 0, 0),\n",
       "  (0, 1, 0, 0, 0, 0),\n",
       "  (0, 1, 0, 0, 0, 1),\n",
       "  (0, 1, 0, 0, 1, 1),\n",
       "  (1, 0, 1, 1, 0, 0),\n",
       "  (1, 1, 0, 0, 0, 0),\n",
       "  (1, 1, 0, 0, 0, 1),\n",
       "  (1, 1, 0, 0, 1, 1),\n",
       "  (1, 1, 1, 1, 0, 0)},\n",
       " (1, 0, 0): {(0, 0, 0, 0, 0, 0),\n",
       "  (0, 0, 0, 0, 0, 1),\n",
       "  (0, 0, 0, 0, 1, 0),\n",
       "  (0, 0, 0, 1, 0, 0),\n",
       "  (0, 0, 1, 0, 0, 0),\n",
       "  (0, 1, 0, 0, 0, 0),\n",
       "  (0, 1, 0, 0, 0, 1),\n",
       "  (0, 1, 0, 0, 1, 0),\n",
       "  (0, 1, 0, 1, 0, 0),\n",
       "  (0, 1, 1, 0, 0, 0),\n",
       "  (0, 1, 1, 1, 1, 1),\n",
       "  (1, 0, 0, 0, 0, 0),\n",
       "  (1, 0, 0, 0, 0, 1),\n",
       "  (1, 0, 0, 0, 1, 0),\n",
       "  (1, 0, 0, 1, 0, 0),\n",
       "  (1, 0, 1, 0, 0, 0),\n",
       "  (1, 0, 1, 1, 1, 1),\n",
       "  (1, 1, 0, 0, 0, 0),\n",
       "  (1, 1, 1, 1, 1, 1)},\n",
       " (1, 1, 1): {(0, 0, 0, 0, 0, 0),\n",
       "  (0, 0, 0, 0, 0, 1),\n",
       "  (0, 0, 0, 0, 1, 0),\n",
       "  (0, 0, 0, 1, 0, 0),\n",
       "  (0, 0, 1, 0, 0, 0),\n",
       "  (0, 1, 0, 0, 0, 0),\n",
       "  (1, 0, 0, 0, 0, 0),\n",
       "  (1, 1, 0, 0, 0, 0),\n",
       "  (1, 1, 1, 1, 1, 1)},\n",
       " (0, 0, 0): {(0, 0, 0, 0, 0, 0),\n",
       "  (0, 0, 0, 0, 0, 1),\n",
       "  (0, 0, 0, 0, 1, 0),\n",
       "  (0, 0, 0, 0, 1, 1),\n",
       "  (0, 0, 0, 1, 0, 0),\n",
       "  (0, 0, 0, 1, 0, 1),\n",
       "  (0, 0, 0, 1, 1, 0),\n",
       "  (0, 0, 1, 0, 0, 0),\n",
       "  (0, 0, 1, 0, 0, 1),\n",
       "  (0, 0, 1, 0, 1, 0),\n",
       "  (0, 0, 1, 1, 0, 0),\n",
       "  (0, 1, 0, 0, 0, 0),\n",
       "  (0, 1, 0, 0, 0, 1),\n",
       "  (0, 1, 0, 0, 1, 0),\n",
       "  (0, 1, 0, 1, 0, 0),\n",
       "  (0, 1, 1, 0, 0, 0),\n",
       "  (0, 1, 1, 1, 1, 1),\n",
       "  (1, 0, 0, 0, 0, 0),\n",
       "  (1, 0, 0, 0, 0, 1),\n",
       "  (1, 0, 0, 0, 1, 0),\n",
       "  (1, 0, 0, 1, 0, 0),\n",
       "  (1, 0, 1, 0, 0, 0),\n",
       "  (1, 0, 1, 1, 1, 1),\n",
       "  (1, 1, 0, 0, 0, 0),\n",
       "  (1, 1, 0, 1, 1, 1),\n",
       "  (1, 1, 1, 0, 1, 1),\n",
       "  (1, 1, 1, 1, 0, 0),\n",
       "  (1, 1, 1, 1, 0, 1),\n",
       "  (1, 1, 1, 1, 1, 0),\n",
       "  (1, 1, 1, 1, 1, 1)},\n",
       " (0, 1, 1): {(0, 0, 0, 0, 0, 0),\n",
       "  (0, 1, 0, 0, 0, 0),\n",
       "  (0, 1, 0, 0, 0, 1),\n",
       "  (0, 1, 0, 0, 1, 0),\n",
       "  (0, 1, 0, 1, 0, 0),\n",
       "  (0, 1, 1, 0, 0, 0),\n",
       "  (0, 1, 1, 1, 0, 0),\n",
       "  (0, 1, 1, 1, 1, 1),\n",
       "  (1, 0, 0, 0, 0, 0),\n",
       "  (1, 0, 0, 0, 0, 1),\n",
       "  (1, 0, 0, 0, 1, 0),\n",
       "  (1, 0, 0, 0, 1, 1),\n",
       "  (1, 0, 0, 1, 0, 0),\n",
       "  (1, 0, 0, 1, 0, 1),\n",
       "  (1, 0, 0, 1, 1, 1),\n",
       "  (1, 0, 1, 0, 0, 0),\n",
       "  (1, 0, 1, 1, 0, 0),\n",
       "  (1, 0, 1, 1, 0, 1),\n",
       "  (1, 0, 1, 1, 1, 1),\n",
       "  (1, 1, 0, 0, 0, 0)},\n",
       " (0, 1, 0): {(0, 0, 0, 0, 0, 0),\n",
       "  (0, 0, 0, 0, 0, 1),\n",
       "  (0, 0, 0, 0, 1, 0),\n",
       "  (0, 0, 0, 1, 0, 0),\n",
       "  (0, 0, 0, 1, 0, 1),\n",
       "  (0, 0, 0, 1, 1, 0),\n",
       "  (0, 0, 0, 1, 1, 1),\n",
       "  (0, 0, 1, 0, 0, 0),\n",
       "  (0, 0, 1, 0, 0, 1),\n",
       "  (0, 0, 1, 0, 1, 0),\n",
       "  (0, 0, 1, 1, 0, 0),\n",
       "  (0, 1, 0, 0, 0, 0),\n",
       "  (0, 1, 0, 1, 0, 0),\n",
       "  (0, 1, 1, 0, 0, 0),\n",
       "  (1, 0, 0, 0, 0, 0),\n",
       "  (1, 0, 0, 1, 0, 0),\n",
       "  (1, 0, 1, 0, 0, 0),\n",
       "  (1, 1, 0, 1, 0, 0),\n",
       "  (1, 1, 0, 1, 0, 1),\n",
       "  (1, 1, 0, 1, 1, 1),\n",
       "  (1, 1, 1, 0, 0, 0),\n",
       "  (1, 1, 1, 0, 1, 1),\n",
       "  (1, 1, 1, 1, 1, 1)},\n",
       " (0, 0, 1): {(0, 0, 0, 0, 0, 0),\n",
       "  (0, 0, 0, 0, 0, 1),\n",
       "  (0, 0, 0, 0, 1, 0),\n",
       "  (0, 0, 0, 0, 1, 1),\n",
       "  (0, 0, 0, 1, 0, 0),\n",
       "  (0, 0, 0, 1, 0, 1),\n",
       "  (0, 0, 0, 1, 1, 0),\n",
       "  (0, 0, 1, 0, 0, 0),\n",
       "  (0, 0, 1, 0, 0, 1),\n",
       "  (0, 0, 1, 0, 1, 0),\n",
       "  (0, 0, 1, 1, 0, 1),\n",
       "  (0, 1, 0, 0, 0, 0),\n",
       "  (0, 1, 0, 0, 0, 1),\n",
       "  (0, 1, 0, 0, 1, 0),\n",
       "  (0, 1, 1, 1, 0, 1),\n",
       "  (1, 0, 0, 0, 0, 0),\n",
       "  (1, 0, 0, 0, 0, 1),\n",
       "  (1, 0, 0, 0, 1, 0),\n",
       "  (1, 0, 1, 1, 0, 1),\n",
       "  (1, 1, 0, 0, 0, 1),\n",
       "  (1, 1, 0, 1, 0, 1),\n",
       "  (1, 1, 1, 0, 0, 1),\n",
       "  (1, 1, 1, 1, 0, 0),\n",
       "  (1, 1, 1, 1, 0, 1),\n",
       "  (1, 1, 1, 1, 1, 0),\n",
       "  (1, 1, 1, 1, 1, 1)}}"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_by_flag = {}\n",
    "for record in processed_result:\n",
    "    data = tuple(record[3][0:6])\n",
    "    flags = tuple(record[3][6:9])\n",
    "    data_by_flag.setdefault(flags, set([]))\n",
    "    data_by_flag[flags].add(data)\n",
    "data_by_flag"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Can we find a set of ``deflagging'' corrections?\n",
    "\n",
    "The flag outcome (1, 1, 0) only occurs when there are 2 or more faults. Since it can arise without propagating errors to the data, we can apply at most 2 bit flips when we see this outcome. We need to apply some correction (we can't do nothing) because there might have been weight 3 errors on the data. Examining the possible error patterns on the data, we see there is no way to flip the data such that all possible fault paths leave fewer than 3 errors.\n",
    "\n",
    "So, alas, we can't make the (standalone) circuit 2-fault-tolerant by simply changing the classical processing."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Another circuit for weight-6 syndrome measurement"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's construct an alternative circuit that is 2-fault-tolerant, i.e. any two faults in the circuit produce at most two errors on the data.\n",
    "\n",
    "Let's say we want to avoid procedures where we have to test and restart some subcircuits. One approach then is to apply the Aliferis-Divincenzo ancilla-decoding technique (arXiv:quant-ph/0607047).\n",
    "\n",
    "I'll leave it as an exercise to optimize the circuit for whatever your goal is."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<Figure size 1604.72x2371.88 with 1 Axes>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "qc = QuantumCircuit(18, 18)\n",
    "# Prepare aux. system\n",
    "qc.reset(6)\n",
    "qc.reset(7)\n",
    "qc.reset(8)\n",
    "qc.reset(9)\n",
    "qc.reset(10)\n",
    "qc.reset(11)\n",
    "qc.h(9)\n",
    "qc.cx(9, 8)\n",
    "qc.cx(8, 7)\n",
    "qc.cx(7, 6)\n",
    "qc.cx(9, 10)\n",
    "qc.cx(10, 11)\n",
    "qc.barrier()\n",
    "# Interact with code block\n",
    "qc.cx(6, 0)\n",
    "qc.cx(7, 1)\n",
    "qc.cx(8, 2)\n",
    "qc.cx(9, 3)\n",
    "qc.cx(10, 4)\n",
    "qc.cx(11, 5)\n",
    "qc.barrier()\n",
    "# Measure aux. system\n",
    "qc.cx(8, 6)\n",
    "qc.cx(7, 11)\n",
    "qc.cx(10, 8)\n",
    "qc.cx(7, 10)\n",
    "qc.cx(9, 7)\n",
    "qc.h(9)\n",
    "qc.id(6)\n",
    "qc.id(7)\n",
    "qc.id(8)\n",
    "qc.id(9)\n",
    "qc.id(10)\n",
    "qc.id(11)\n",
    "qc.measure(6, 6)\n",
    "qc.measure(7, 7)\n",
    "qc.measure(8, 8)\n",
    "qc.measure(9, 9)\n",
    "qc.measure(10, 10)\n",
    "qc.measure(11, 11)\n",
    "# Instrument the code block to detect bit and phase flips\n",
    "qc.barrier()\n",
    "for i in range(6):\n",
    "    qc.cx(i + 12, i, label=\"inst_cx\")\n",
    "    qc.append(HGate(label=\"inst_h\"), [qc.qubits[i+12]])\n",
    "for i in range(6):\n",
    "    qc.measure(i, i)\n",
    "    qc.measure(i + 12, i + 12)\n",
    "qc.draw(output='mpl')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's build up a list of events first."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "fe = FaultEnumerator(qc, 1, \"propagator\", model=model, sim_seed=0)\n",
    "result1 = list(fe.generate_blocks())[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We will store X errors on the data in a dictionary with flag outcomes as keys."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_by_flag_1 = {}\n",
    "for record in result1:\n",
    "    data = record[3][0:6]\n",
    "    if sum(data) > 3:\n",
    "        data = [(x+1)%2 for x in data]\n",
    "    data = tuple(data)\n",
    "    flags = record[3][6:9]\n",
    "    flags.append(record[3][10])\n",
    "    flags.append(record[3][11])\n",
    "    flags = tuple(flags)\n",
    "    data_by_flag_1.setdefault(flags, set([]))\n",
    "    data_by_flag_1[flags].add(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "fe = FaultEnumerator(qc, 2, \"propagator\", model=model, sim_seed=0)\n",
    "result2 = []\n",
    "for x in fe.generate_blocks():\n",
    "    result2.extend(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_by_flag_2 = {}\n",
    "for record in result2:\n",
    "    data = record[3][0:6]\n",
    "    if sum(data) > 3:\n",
    "        data = [(x+1)%2 for x in data]\n",
    "    data = tuple(data)\n",
    "    flags = record[3][6:9]\n",
    "    flags.append(record[3][10])\n",
    "    flags.append(record[3][11])\n",
    "    flags = tuple(flags)\n",
    "    data_by_flag_2.setdefault(flags, set([]))\n",
    "    data_by_flag_2[flags].add(data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let's search for a candidate set of X corrections to the data such that 1 fault leaves no more than 1 residual X error and 2 faults leave no more than 2 residual X errors."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Apply a correction to a set of errors and test for weights above a cutoff\n",
    "def test_correction(err_iterable, correction, cutoff):\n",
    "    for y in err_iterable:\n",
    "        wt = sum([(u + v) % 2 for u, v in zip(y, correction)])\n",
    "        if wt > 3:\n",
    "            wt = 6 - wt\n",
    "        if wt > cutoff:\n",
    "            return False\n",
    "    return True"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "lookup_table = {}  # store feasible corrections in a lookup table\n",
    "\n",
    "# Iterate over all flag outcomes\n",
    "for x in range(2**5):\n",
    "    flag = \"{0:05b}\".format(x)\n",
    "    tup = tuple(map(int, list(flag)))\n",
    "    err1 = list(data_by_flag_1.get(tup, set()))\n",
    "    err2 = list(data_by_flag_2.get(tup, set()))\n",
    "    # Iterate over all possible corrections for this flag outcome\n",
    "    for corrint in range(2**6):\n",
    "        correction = tuple([int((2**i & corrint)>0) for i in range(6)])\n",
    "        if sum(correction) > 3:\n",
    "            correction = [(u+1) % 2 for u in correction]\n",
    "        if test_correction(err1, correction, 1) and test_correction(err2, correction, 2):\n",
    "            lookup_table[tup] = tuple(correction)\n",
    "            break\n",
    "        if corrint == 2**6 - 1:\n",
    "            print(\"FAIL\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "|00100,11010,11011,11101|100000|\n",
      "|00101,00111|000011|\n",
      "|01001,01110|000100|\n",
      "|01011,11111|010000|\n",
      "|01100,01101|000010|\n",
      "|01111,10011|110000|\n",
      "|10111|011000|\n"
     ]
    }
   ],
   "source": [
    "reverse_table = {}\n",
    "for flag, correction in lookup_table.items():\n",
    "    flagstr = \"\".join(map(str, flag))\n",
    "    corrstr = \"\".join(map(str, correction))\n",
    "    reverse_table.setdefault(corrstr, [])\n",
    "    reverse_table[corrstr].append(flagstr)\n",
    "\n",
    "# Print markdown for the lookup table\n",
    "for correction, flaglist in reverse_table.items():\n",
    "    if correction != \"000000\":\n",
    "        print(\"|\" + \",\".join(flaglist) + \"|\" + correction + \"|\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Lookup table of corrections for each flag outcome\n",
    "\n",
    "Corrections are written modulo {000000,111111}.\n",
    "\n",
    "|flag|correction|\n",
    "|----|----|\n",
    "|00100,11010,11011,11101|100000|\n",
    "|00101,00111|000011|\n",
    "|01001,01110|000100|\n",
    "|01011,11111|010000|\n",
    "|01100,01101|000010|\n",
    "|01111,10011|110000|\n",
    "|10111|011000|"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Testing the deflagging protocol"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "def deflag2(result, lookup_table):\n",
    "    processed_result = deepcopy(result)\n",
    "    for record in processed_result:\n",
    "        flags = record[3][6:9]\n",
    "        flags.extend(record[3][10:12])\n",
    "        for flag_val, correction in lookup_table.items():\n",
    "            if tuple(flags) == flag_val:\n",
    "                for i in range(6):\n",
    "                    record[3][i] = (record[3][i] + correction[i]) % 2\n",
    "    return processed_result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{1: {(0, 1), (1, 0), (1, 1)}, 0: {(0, 0)}}"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "weights = {}\n",
    "for record in deflag2(result1, lookup_table):\n",
    "    datax = record[3][0:6]\n",
    "    dataz = record[3][12:18]\n",
    "    if sum(datax) > 3:\n",
    "        datax = [(x + 1) % 2 for x in datax]\n",
    "    num_errors = sum([int((x + y) > 0) for x, y in zip(datax, dataz)])\n",
    "    weights.setdefault(num_errors, set([]))\n",
    "    weights[num_errors].add((sum(datax), sum(dataz)))\n",
    "    if num_errors > 1:\n",
    "        print(\"FAILED!\")\n",
    "weights"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{0: {(0, 0)},\n",
       " 1: {(0, 1), (1, 0), (1, 1)},\n",
       " 2: {(0, 2), (1, 1), (1, 2), (2, 0), (2, 1), (2, 2)}}"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "weights = {}\n",
    "for record in deflag2(result2, lookup_table):\n",
    "    datax = record[3][0:6]\n",
    "    dataz = record[3][12:18]\n",
    "    if sum(datax) > 3:\n",
    "        datax = [(x + 1) % 2 for x in datax]\n",
    "    num_errors = sum([int((x + y) > 0) for x, y in zip(datax, dataz)])\n",
    "    weights.setdefault(num_errors, set([]))\n",
    "    weights[num_errors].add((sum(datax), sum(dataz)))\n",
    "    if num_errors > 2:\n",
    "        print(\"FAILED!\")\n",
    "weights"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Great! If this weight-6 syndrome measurement circuit is 1- or 2-good (with ideal input), then its output will pass a 1- or 2-filter, respectively.\n",
    "\n",
    "How about 3 faults? Since we can reduce the error on the data to at most 3 X errors, we expect the circuit to be 3-fault-tolerant *in the CSS sense*. Can we remove the qualifier?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "fe = FaultEnumerator(qc, 3, \"propagator\", model=model, sim_seed=0)\n",
    "result3 = []\n",
    "for x in fe.generate_blocks():\n",
    "    result3.extend(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "failed?  True\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{1: {(0, 1), (1, 0), (1, 1)},\n",
       " 0: {(0, 0)},\n",
       " 2: {(0, 2), (1, 1), (1, 2), (2, 0), (2, 1), (2, 2)},\n",
       " 3: {(0, 3),\n",
       "  (1, 2),\n",
       "  (1, 3),\n",
       "  (2, 1),\n",
       "  (2, 2),\n",
       "  (2, 3),\n",
       "  (3, 0),\n",
       "  (3, 1),\n",
       "  (3, 2),\n",
       "  (3, 3)},\n",
       " 4: {(1, 3), (2, 2), (2, 3), (3, 1), (3, 2), (3, 3)},\n",
       " 5: {(2, 3), (3, 2), (3, 3)}}"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "weights = {}\n",
    "failed = False\n",
    "for record in deflag2(result3, lookup_table):\n",
    "    datax = record[3][0:6]\n",
    "    dataz = record[3][12:18]\n",
    "    if sum(datax) > 3:\n",
    "        datax = [(x + 1) % 2 for x in datax]\n",
    "    num_errors = sum([int((x + y) > 0) for x, y in zip(datax, dataz)])\n",
    "    weights.setdefault(num_errors, set([]))\n",
    "    weights[num_errors].add((sum(datax), sum(dataz)))\n",
    "    if num_errors > 3:\n",
    "        failed = True\n",
    "print(\"failed? \", failed)\n",
    "weights"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Nope. The circuit is not 3-fault-tolerant in the strictest sense, so we need to be careful if we plan to measure checks for codes with minimum distance greater than 5.\n",
    "\n",
    "Can you find a less expensive and/or \"more\" fault-tolerant circuit?"
   ]
  }
 ],
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