520 lines (520 with data), 195.2 kB
{
"cells": [
{
"cell_type": "code",
"execution_count": 49,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 0
},
"id": "eI_d8C3_Tnyu",
"outputId": "5abb2e55-b86b-4e8f-8094-2fe4cd31ee1c"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Time in seconds since beginning of run: 1696870354.2684636\n",
"Mon Oct 9 16:52:34 2023\n"
]
}
],
"source": [
"# This cell is added by sphinx-gallery\n",
"# It can be customized to whatever you like\n",
"%matplotlib inline\n",
"# !pip install pennylane\n",
"\n",
"import time\n",
"seconds = time.time()\n",
"print(\"Time in seconds since beginning of run:\", seconds)\n",
"local_time = time.ctime(seconds)\n",
"print(local_time)"
]
},
{
"cell_type": "code",
"execution_count": 50,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 388
},
"id": "lScQSFsjTnyw",
"outputId": "70e28a11-0436-4824-b36d-46ba1d6a7836"
},
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 400x400 with 1 Axes>"
],
"image/png": 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2jK2mnCaS8vJyvOeee1J/d3Z2Yr9+/XD27NlEv//973+PvXr1ws8++yx1rLa2Fm+88UbiNpw6dQo7OjpSn9bWVldEYjb4jSbU888/j3V1dcTpwJkQRQtzArtap5WAoO0nz7xfl9D9S1Lo/kW4GIkdqP1lRI6KEqT2bH5PYyaFXtuboSv2+MQTT+guKm5vb2e2TipnieT06dOYn5+Pq1atSjt+++2344QJE4iuccUVV+CUKVPSjtXW1mIwGMTi4mIcOnQo/uxnP8NPP/3U8BqzZs3KcoU5JRLSwa9OqL///e9ZK45LiorwwIEDtu+tva7IkywTtNN6Wae/tre3Z7mBRMrasgu1v4zcdQAPeCK4ab5H3tUStG1vA+NsSO18Zb1OKmeJ5NChQwgA+Oabb6Ydnz59OpaXl1v+vrGxEQEgK6ayYsUKXL16Ne7atQtXrVqFl112GY4cORLPnDmjex2aFondwV9SVJSVDhxMksm5ABZaJy9N1o+krQcriwTgVSoE7LRdbt6jV7XStG3XS/XluYeLCkkkBpg6dSpeeeWVlue1tLQgAOArr7xC1C6mtbY0g3/dunWm5zp1c/kJrKwH0TJ3zCBCbTE9dx1AHwSoQVbxH5LndvseeS9izbx3MJmcYSUPeCg/OUskblxbn332GRYWFuITTzxBdK++ffviwoULic5lUmtLZ/DW1dWZCtG6ujpH9/cTWE0gP8SM9DKlVBcZb3LRc9cBVCHAQurxHztWgpv36HWMpb29HUcQbCqHyKcaQc4SCWIi2D5t2rTU352dndi/f3/LYPuSJUswEAiYxj5UtLa2Yl5eHq5evZqoTSxqbekNfloWiQgarRuwtB5Edj/pZUopSgiLikp0yYUHmpqaMBwekXX/bdu2UetHJ1aCk/coQqkYUjJT3fTSInGIlStXYiAQwKVLl+KePXtw6tSpGAqF8MiRI4iIOHnyZJwxY0bW7yKRCP7oRz/KOn7ixAl84IEHcMuWLXjw4EF85ZVXMBwO45AhQ/DUqVNEbaJda8tsEKgxEq0QDQJZjMSv2+Nmwg/WA20YxyXKMJF26+2qeXXsbtu2jWpiAU8rwWuLRAWJolRT3bWzauZaGxkjIcT8+fNxwIABWFBQgOXl5bh169bUd9FoFGtra9POf//99w019i+++AKvv/56LC4uxm7duuHAgQNxypQpKWIiAauV7Xo4cOCA46wtL/2/LCCy9UAb+plS5kFv0n6haaHqWU1uiI23lSBCrMxKUVIJ72nIzu5SgN4OpTlPJKKBJ5GoWL9+va11JKJoWxLOoG+RmKfhWglZs5gLvTa6W3zJe9yKZO0aKUoque4yIJJYLEZFOZBEwhleEAkJtIPJjmbn9xhKriI7U+pxV4KblfVAuxyMF1aCyNauSq5lkJ0m3AsA+4ZCVIhQEglniEYkerGQSk0FXyPNLldiKLkKvUypoqISR6vmWVoPXddsTlpNc11ZDyJZCaLAaD6Xgf1tJ4wgiYQzRCMSo1hISVGRqWaXazGUXEVDQ0PKrel01Twr66G6ugYVJYSJJIB0wnMr+EW2EngjFotleRisys3b7TdJJJwhApGo7iiryr5m9XpkDEVsmMU07ApZFhYJYsJ6SKQje59J5hc4cSXrzVercvN2lQNJJJzhJZHouaMUSATijAaTntARIYcekW98xm+xINoxDRbFJFkRVC7CrSs5M3ZktGGdtEh8AqdEQkOQ6bmjgklfqZ3BRGqRsBK+POMzbrOVvCAgFgKaRTFJVi6zXIRbV7Je7MjKfW0Hkkg4wy6R0BKaVsJ/rs3BZJYdw1rQ047PmAl7p5o97XRZO2ApoGnGHqRFQgaarmTt+6OZmCCJhDPsEgktoWnljrI7mMwGIctAPM1JpSfsI5FKjMViGI/HHQk6lZQqKqJUXUt24CcB7ef9V3hZm1Zzd9GiRUTtMGovDeVAEgln2OlwmkLT6lpGOwdaIXMQsg7E04zPpFsbuzAze6irLpS1Zq9HSl4Kcr8IaK/2X3FDArxT363mlFU7eLRXEgln2Olw2kFtVou1nC5mdHovGkSVrbXXYKK0ubbIYZCYENJJaRkxAbGC3zbIYp2uq45RGvW9vEh915u7obw8DID3e5EgSiLhDtYWiZmmRXuxltPFjG5BgxDT4whmriDFUrPXX1wnhmvpXF9PkW0pKpiXF0KnLkfehSHN4hkKJGpombWDV3slkXCG0xiJldC0Y77SEi411dXYMy8PfwCAzwL5Yka3oEGI6cLfPDgdDo801WD1g9uqhSO2a8nvsHJRpVuKm1wTPI/Ud7O5rM7d+vp6onbwStWXRMIZdomEVGjyNrfXr1+P+Zo2AQCWAOD/B+aLGWnCLSF2CRnrOlRm99IPbrdjZsxFZNeS30CSFZf9Xpxns5Eu4uW1p4qdFHxpkeQgnK4jIRFkPFea9y4s1N0Pvlij6YjuVkmPIyiYWGHtzIIwCm5HIlGh+8CvIEnLzrYU7bsc9ayDkqIiDCkKE4vbzlwm9VbwKGQpiYQzWKxs573S3Gr3Rd5xALeIx+MYi8WwoiLq2IJgHdymkWrqt9X5RiBNb9Y/rwYBehMrDGa16FhY3HbmMqm3gkchS0kknMGCSHhbJFb7wQ+55BKq9+MJt1YUbSuMxsJGLxdHsoCdBZfZluJCBAgQ9QWrlHkzOJnLpGOOpYdAEglnsKq1xXMfBiuL5H/+53+o31N0sNL2adTMol13y2vYWXBpZCk2NTVZvi/eln5bWxtWRiKoQPa2uL0hkaUlqjUpiYQzWBEJ730Y3OwHn0tgqe3TWKHup1XudmB3waUTbZy3pV9TXY09FQUBAKs040n7N411WCwUHkkknMG6+i+vALeb/eD9BHvppXS1fRo1s6yuEQ6P8KWLi9eCS16Wvkpac5PPshwA45Ao9x6nQF6sV7dLIuEMEfYjoQm7+8H7Bc7SS+lq+zwsEkUJ+tbFhcheceJl6WvdaDWQ2BY3zbWlKK7Ii/XyAEkknJFrRIKYO9lAWjhLL7VvMZC3w/nCRr1rJBZL1gjv4hJlbPEo4aJaIu1JMtGSV7SiwjF58XDRSSLhjFwiklzdt53EEmhubsZFixYxjz/QcOG0t7dnrc5PkEg7VdKjiVzLNCNBphttLgD2VBSMRiKurssjaUASCWfkEpHk6r7tJHGFLgGn1m4itxicaNluNeIucpyOAHEmpEcTrDPNRLF0tGDlRpMWSQ4iV4gkl/dtJ4krdAm4p5F0XYLXWrZfSsun938zJkqbxKmQntfvgAQs3GhmSQM0SDXnieTJJ5/EgQMHYiAQwPLycmxsbDQ8d8mSJRnmP2AgEEg75+zZszhz5kwsLS3F7t2745gxY2y9AK+JhJYmJsq+7axgJHQTpVT0Caa+vt60X2lo2W7en19Ky3dZhFUZ87HK9diiZemIaNGYQc/aGXvddTiuKr2P5Q6JOli5ciUWFBTgM888g7t378YpU6ZgKBTCo0eP6p6/ZMkSLCwsxMOHD6c+R44cSTtnzpw5GAwG8cUXX8R33nkHJ0yYgBdffDGePHmSqE1eEQnteIYIFgmrydzc3KxbMqUrzuCs6J+beApNTZqWxsuy/xOE3TtN4Cf+Vii495zHtPxg0ZhB++5puqZzmkjKy8vxnnvuSf3d2dmJ/fr1w9mzZ+uev2TJEgwGg4bXO3v2LJaWluLcuXNTx44dO4aBQABXrFhB1CaviIRFPIPnanotWE1m/a13o6623lXhNsNLpNXprIUpq7RqGll2rN4DbwuHtiKYs0Ry+vRpzM/Px1WrVqUdv/3223HChAm6v1myZAnm5+fjgAED8MILL8QJEybge++9l/q+paUFAQB37tyZ9rvKykq89957da956tQp7OjoSH1aW1u5Ewkr64EkOMhigrCazCTXdRpnsBKOZm4x0VansyY1VmnVbvuRxXtgnfloNP9ou6ZzlkgOHTqEAIBvvvlm2vHp06djeXm57m/efPNNXLZsGe7cuRM3bdqE3/3ud7GwsBBbW1sREfGNN95AAMCPP/447Xc333wz3nLLLbrXnDVrVtogUT88iYR1PEPPVcJqgrASqqTXdRNnyCahPyFJoJ7HehVS8CA1lvdwk3DA4j2wyny0mn/SIiGEEyLJxJdffomXXHIJ/uY3v0FEZ0QigkViVWTRzqp0UguD1QRhJVTtXtdJnCGbhMi2fRXJIuFFanYFPum4dKMI0H4PLOOMJPOPpms6Z4nEiWtLDz/84Q/x1ltvRURnrq1MeBEjWbNmDSqQXXahDyQqipJMfjsWBssJopKiVxYJDcTjcduLGUVJ3eXVT6QC32m8xmnCAc33wMpToK3bpdbq0pt/NNet5CyRICaC7dOmTUv93dnZif379zcMtmfizJkzOGzYMPzP//xPROwKts+bNy91TkdHh/DBdnVglWkGjPZvkslkx8KwM0FINcnGxkbNQkB3uxkagaewtqvZi5S6y7OfrAQ+7yQEmu+BlcIVi8VQyZjrNQC4y4CgaGTx5TSRrFy5EgOBAC5duhT37NmDU6dOxVAolErpnTx5Ms6YMSN1fl1dHTY0NGBLSwtu374db731VuzevTvu3r07dc6cOXMwFArh6tWrcdeuXXjjjTf6Iv1XJYK5ALgsqa2QmrF2BzzJ+aSapN55ABUIcAV1ocpTWDvV7EXYvlgUUvPS5UfrPbDIfIxGIlnbYPexqTjaRU4TCSLi/PnzccCAAVhQUIDl5eW4devW1HfRaBRra2tTf993332pc0tKSrCmpgZ37NiRdj11QWJJSQkGAgEcM2YMNjc3E7fHKyJxY8Y6McGtJgipJql3XlfBwbloN8ZDAl7CWhR3lVN4TWoiJSE4Be2yKFZKnNu6XUbIeSIRDV6vbOe1wY/ZBHG353bXeQCv+kZg6EEUzT4Tflm1LVISglvQImUrpS8Wi1FqcTokkXCG10TiBG1tbbo7IpKY4HoThFSTtDoP4AHfCQw9eK3Zq6Cx0JA3CfndqqMNrypOSCLhDD8SSU11NYYUJStYX1JU5CrI6NYi8fumTKLBTeDaq9Iholp1XsKLihOSSDhDRCIx0yIzNRx1+091S1CnGg6pJqm/KVMQAZRzXmA4gdG7dusm8qKEi/ZZRLHqrMDDYuO1q6MWkkg4QyQiIVkbwirXnVST1DsvHB6JTU1Nrp79XIOVxeAmcM07VuHHwolebALHk1wlkXCGSERCsjaEdHGTU5AOdr9onKLCymLgVZCShkbuZQFL0vZnnsdjEzgvkyQkkXCGKERCGpRTA+1aTaoMAEOK4vudEM8F2NkSmFVBSjvrhkiex4tMLTfrniKRKNFcc9M2r7e8lkTCGaIQCanLSk+TCoLzQLsEH+gv5KzCxD7t+hZDS0sLFhWVpP2mqKgEDxw4YHk/KxKiZUV4tXbEzbonRUnso8KqaKoIW15LIuEMUYjEyiJZv369EJtXSTiD/kLO3phYyGllkcxDgGUIMI9Y2JvFvGhaEV5YJLSyDOcxmEeizFFJJJwhCpEg6qcJBgFSdXpGhMNEVovX8MsCOl4gW8j5F2oxEi3crBsiBe+1I7TWPfVUFOopuaJseS2JhDNEIhK9NMEySBR3Ww6AQUURQtsxgh+zd3jAeiEn/awtMyKnbUXwXjtCyyKJRiJpbaa5P4/Xc1QSCWeIRCQqGhoaDE1vJak58d5OlwQibT8rEpzsxuhE2NshchZWBM9MPjfrnrTnsWizV1teayGJhDNEJBIr8/jKb37TlSZFw/W0bt06rKurSxVozKU6SyzgRHDb/Y0dIvf7CnQ3655YP6cXCxAzIYmEM0QkEiPz+E8AWfsaRCsqiAcoDdfT/v37dTOJFi9e7NgVcy7AiUCz8xt9Im9Gq/pnfl8PJPK6Jy/7VhIJZ7glElaBZT3zOACQva+BDZOZhuspQSJBTM8+CmIo1FdaJARwIlxIfpMeU2nDRDZYevUBv1gbEu4hiYQznBIJ60VHeuaxmyAeDdeT1ba6I0aM1K3DVVRUIoUYY6S/3xpM7BHjfaxKZvB5A0kknOGUSHgtOopGIthTUfDHScJwmlZII+Wzrq7O9BozZszAPn2KM8hPQYACrKoaR6tLJAxQXV2DihIUwjKUGXzewo5cU0DCE8TjcVjT0AB/7OyE2wDgIgC4DQD+0NkJaxoaYN++fdTu8+rmzbDw7Fn4VfLYaxnnvJr8d/DgwabXuuSSS0yvYPV7AIBRo0aZXmPo0KHQ3t4GAIUAMD15/M8A8DX4xz82UOsXCX2sWLEcysqGJP+qzPg2CgAA+/fv59KWSZMmwyuvbAWA5QDwIQAsh1de2QoTJ/47l/tL2AAHYst5OLFIeC06yrxPDST2enaaVkgj5bMrRpLtvrKqIVVfX++0KyQIIUL2HM82SNeZPqRF4gOo2r1T68DpfZYDwNUAMBkABiT/PdbZCV999RX861//srzeihXLYezYa9KuMHbsNbBixXLiNjU1bYGiou5p1ygq6g5NTVs0Z+lrwxLsMXToUKiuroH8/HshMWJaAWA55Of/Aqqra2DIkCEWV3CPlpaW5P/YWUXt7e0wfvwNMGzYMKipqYGhQ4fC+PE3EM0DiQxwILach9sYCY1FR2ZaVeZ9ygCwJwBOB8BXdWIzJBoajbTE9evXp60jUe8NAvjnjXCuaK9erxHhMQ7k4ldzyGA7ZzglEhqLjkgyv/TuY5S5VVER9Ty4WVU1DvPyQmmur7y8kKfBdj8GfmmQnpfrGIx20gyF+mIsFqNSGFFUhUUESCLhDLfrSIwmK4kgsJP5FY/HU1lT+rEZJVke21sNzWttWA9+0l79SHp6aG9vz1q4ClCGAIWYyORz/lxela5X4QfLVhIJZ9Be2U66vsRJcTej3zyeupc4GpqX2rB2ovtNe3VKeqIJt65+n4cAaxAgntbvdkriG1+bb+n6WCzGpNAjC0gi4QzaREJqZTjN/NKLzfRMVgU+18uT6Gnz4fAIJn3DQnCzLtTIE9YVj9e4Evy8StfrKYZl0FWRW5SCqZnIeSJ58sknceDAgRgIBLC8vBwbGxsNz120aBFGIhEMhUIYCoVwzJgxWefX1tZmmM+A1TZeLE0isWNlOC03rRczqUxpSf7QulkhW5ufi3l551PtG5aC24nLRlS3nfUeLHFXZE7bhWqkGOgqhgBYCYBrAHCuxXz1CjlNJCtXrsSCggJ85plncPfu3ThlyhQMhUJ49OhR3fMnTZqECxYswJ07d+LevXvxjjvuwGAwiB999FHqnNraWhw/fjwePnw49bEzmGgSiV0rw03mV6briPfmQqIhXXBl1ppSMH3ty+OoKD0xEonavk9XP89Fu7sW2nsGa9IT3W2nH3Dvg127QmbvH8KiDpkZzBQDPWWvLWmRaM9XADAWizm6PyvkNJGUl5fjPffck/q7s7MT+/Xrh7Nnzyb6/ZkzZ7BXr164bNmy1LHa2lq88cYbHbfJK4sEkW65aRGD3DyRrs1n1pp6GgECGlLp6qOKiihxH3UJ7rK0a6h/001rtVYIvA46W0FvTCb6alfac3npnjOz6PQUQ3VRsNZCCUKiCrdIyFkiOX36NObn5+OqVavSjt9+++04YcIEomscP34cu3fvjv/7v/+bOlZbW4vBYBCLi4tx6NCh+LOf/Qw//fRTw2ucOnUKOzo6Up/W1lZqRILozMqgGZj2e1lwp+gS8nNNtPTszDY7RSUTgkXBzIKIib8VKoLbSCHYtm1b1nsV3SJREY/HMRaLYSSin57ulXvOqv/UDeZUxbAZ3BVO5YmcJZJDhw4hAOCbb76Zdnz69OlYXl5OdI27774bBw0ahCdPnkwdW7FiBa5evRp37dqFq1atwssuuwxHjhyJZ86c0b3GrFmzMjQkoEokPDa1ES1DRxQkihb2NNDSN5kKjUgkanl9q+rH2sWZRiB9d6pCsG3bNlNt3W8uzUxFx0syJLHotIrhsmT/e70fOwkkkRhg9uzZ2Lt3b3znnXdMz2tpaUEAwFdeeUX3e9YWiQoWlgHr0vV+R3t7O0YilQaC6QFToUEitNy4kpy6b6y09W3btmE4PNL2dUWBl+45EhKzsyCYZK7zUgJzlkjcuLbmzp2LwWAQm5qaiO7Vt29fXLhwIdG5ou2QSFIuhXXper+joiKadGF1aelW5dVJhJYb7dmJ+8bqfpmVDMLhEcRzRBR47Z4jtehUxTBaUeEoQYa3EpizRIKYCLZPmzYt9XdnZyf279/fNNj+29/+FgsLC3HLli1E92htbcW8vDxcvXo10fmiEInVQHOaLnwuwijOcM01/wezKxf3QTvBcieuJKfC0lxbF6OSgRNkKkteuufsJqk4dV3zVgJzmkhWrlyJgUAAly5dinv27MGpU6diKBTCI0eOICLi5MmTccaMGanz58yZgwUFBfjXv/41Lb33xIkTiIh44sQJfOCBB3DLli148OBBfOWVVzAcDuOQIUPw1KlTRG0ShUisBhqv0vW5hEz3olHZDkUJEQstJ9lxXYTwWwSox65V3ubuG2MCetxTLd4pjNx7Bw4c0F1IytO60o4V2oVPvVACc5pIEBHnz5+PAwYMwIKCAiwvL8etW7emvotGo1hbW5v6e+DAgRmTPvGZNWsWIiJ+8cUXeP3112NxcTF269YNBw4ciFOmTEkREwlYEwnJoCQZaLlmkXiVMJCIo+hnD9kBqSBpa2tLWkLaMawgwDgEWGj57vS0deOEAjHSfo0geryHVRqyF0pgzhOJaGBFJHZ8oqQDjWbpet5QicMqC8npde0SEq806erqmmQ1ZG26cG9MrGsJWFpCehaQcUKBuBYJiXvP61X6rO4vLZJzALSJRBVs0UiE2CdKOtCc+Ge9ThXW0/ISQvRpV5NV1BpTWliXCQFi943fKxlYZWf9/Oc/95QcWQf9eSuBkkg4gxaRGBV3ayfUQOwMNBJtmlTQsiYaPS0voZHXIEAzJor3zbU9Wb3WXklgXbjQuVvDb5UM9AV1G2ZXCfDGXcc6DZnH+jItJJFwBi0iMSruVmPiqtLC7kCzIgArQctDoyfRyLVxA9J6RV6njJKC5PndttVPlQyyragyTGTRLUerBaN+t0hU8Hpfkkg4gwaRWLqmCCwSFVYDjYQARPFHW2vk07HLSgliRUWUynVFCjZ3xUi0KceJGIlI1hMP6Nfe0o7RmmTfeOOuY+EuzNwbhxfpSyLhDBpEohcsb4aukgrLLFxVdkBCAFaCdtGiRVy0L7JS4vbv7ReLBDEhPKuqxmUITwWrqsYJ6YbiIey0u32mj9F2BKgyVZJYgqa7MNPVrWRY4KwrUkgi4QzaFkkbJNxZ2kGjUBo8pALU6rz6+npuGr3R3t0JgeH83n4LNsfjcayvr8f6+nqhiE6FkaWrVyySBkjGqFf9RMP9pHV1VwFgbwCuFSkkkXAG7RhJGWSXme6tKFTKTNtx6ZgJWp4avb47Q8FE1pbze/st2Cw69CzdhEtOYda/flMGSKHOr+kA2JDsO97rvySRcAYtImlvb0/tVMhq0NghACtBy3sSa7U8mvd2oz16nRptByzbau2CfBVZxNDslMz3C9ra2nBkOJz2TAoktubVdi7rihSSSDjDyx0SncCuENYTtM3NzRiLxbKK/vHS6L22JvywBkUFj7aS7a/OLgZFUjLfDpF6qSDUVFdjb0XJ2viqzKFy6fRZJJFwhpc7JGb+lmTAuBHCekIpEoliLBbjMukyn9Gr1FU/rEFRwaOt5EkRbLPi9J5VUUJZ9dGMxrvXCkJjY6Pp/J8L5IsR3VYLlkTCGbRXtpMsLNQKVKcDxokQ9kqAej3BtfBTxhfPtuonRagLR9n3kfGzateamI9ZrxWEEUmXlpFHws4cd1stWBIJZ9AmErOFhXqkUVJUxKW8tJcC1OsJrgXNNSisXSg818voJ0UEMFFYkn0MTf9Zyces1wpC1/2NLZL169cTjRcatbkkkXAGq6KNehZDppYx12Lg0Rz8Xi3i83qCa9uxZs2a1D7cbtqjZ2GFwyOplz33ou/UcdvU1GTLinRLqvrPSj5mvV6kqt6/ChJZm1qPRBAAR4bDtq/lJtYqiYQzeO1HoqdlrEkOjMwBsyl5vL6+nvr9eQqltrY2DIdHmE7wcHgEUxeXntAvKipxlTWmXz8siABKzqXI0qi0QIrsZyXfd4X1+LYiSvX+T4P+OjI7Soa0SHwIXkRitPpdO2D0FjPSXAHLWyhVV9dYbnGrKEGmQtFtADcTVgKL9vPwyHBzY03QdFvqPasd0mcxvu0QpTY++ioAPgCAQUVx5KZ2Wy1YEglneGmRICTSAoPJgcJ6BSzPtNt0gVuDiS1tM7e4rWFqEVkJfVKftRbWqbIPED2PXeFNM8ON1t4wVv3r1NWnfVY7Y5bF+LZDlDQr/Lq9liQSzuBBJGqQXdGQhqplhBQFS4qKUoOFR7yER9ptusBtT5KG1toamTzOzofNwm9OtnjP+NpeZrDR3hvGqn/D4RHU2m5nzNIa307dZTTnl9NrSSLhDB5EopqpTyetDj0tQ61/tQkSsRO1YrBf92TXn4TxlMbetTaha1LSzoJi5TfXT5Uls7C8zGAz3xvGvG/03g2PMvlegkcAP7Nfac0BSSScwWPP9kxLIw4J/6l2ojU2NmZXCAXAhQQTUtRSH8YFG8tQ68OuqhqnkwU1gkoWFAu/uX6qbBUCLDS9tpcZbE4XHVpZUIk91oM6pFrlSwVIC5bvy2gpAK34qCQSzmBNJHb2Yw/l5aUXewTAQHJA6YF3xVa7MAqeZra3qmpcUtgvRNplxFnGhZqamjRZadbX9jJF1WkZFCsLatu2bagt7Jj41CTfpf8skkyljFWCSuZSgDJIuL1pxUclkXCGFxYJQnrsw+ocI82cVcVW2hZOpp9X+7d+UJ6+24dlXIj02mJbJK9mCUnS9nZl5z2gex0/wEgpO3DgAHVFJHO+Z2Zv6skIu5BEwhluiIRU4Fql8jlZgMSiYqsXgeAuTXmTZ0KWJ7xcF6J3bzPFg9SC8roIJw1YWV40FZHM+W60nsxNfJQ5kXzxxRf40UcfZR1/7733nFzO93BCJHbrY1ml8jlZgMSiYqsXgeAuQpye8TzNyWcwz4LyG7wUukb3bmpq0hWSdi0or4pwugVvS9H3Fsnzzz+P/fv3x+HDh+OVV16JW7duTX131VVX2b1cTsAJkTgtqGY20ewuQKJdsdXrWlxdCxcXYnaqsEK9/IjX4C10tdaznXvzsKCculJpuWC9iF1lznc1RuJ0AWImmBLJ8OHD8ciRI4iI+NZbb+Hll1+Ozz77LCIilpWV2b2cIzz55JM4cOBADAQCWF5ejo2NjabnP/fcczhs2DAMBAJ4xRVX4N/+9re078+ePYszZ87E0tJS7N69O44ZM8bWwLJLJDTKF+jByQIkmhVbvQwEd2nKCibWNfTGzLiPn/ztJOCVaefWXcnSgnLatsbGRltJDlbwQonSm+++ydr65je/mfZ3W1sbVlZWYl1dHReLZOXKlVhQUIDPPPMM7t69G6dMmYKhUAiPHj2qe/4bb7yB+fn5+Pjjj+OePXvwN7/5DXbr1g3ffffd1Dlz5szBYDCIL774Ir7zzjs4YcIEvPjii/HkyZNEbbJLJKw3r7KjLW7bti2Zfpm5wMx+xVYRiiv+9a9/9bwNrME7DkXLXUlzkV/2TplkbdNfUFmFAE+7tpK8il2ZJaK4AVMiufbaa/Gdd95JO3b69Gm89dZbMT8/3+7lbKO8vBzvueee1N+dnZ3Yr18/nD17tu75t9xyC95www1px0aNGoU//elPETFhjZSWluLcuXNT3x87dgwDgQCuWLGCqE2iWCRG9zLa3TASiaZNqHB4BG7YsMGVkPK6QKDXFVx5gEUcysi6EUE5UKFPAgomVtUbt82KeGiV2smFhAEtmBDJ8ePHERGxtbUVDx8+rHvO5s2bSS/nCKdPn8b8/HxctWpV2vHbb78dJ0yYoPubiy66CH//+9+nHXv44YfxW9/6FiIitrS0IADgzp07086prKzEe++9V/eap06dwo6OjtSntbXVFpEgui+oZgW9YP7Y667DqqpxGROxDAF2ZQmjeDyOixYtwvr6elsTy+vJJJLgYwHaz2dl3YhEzMYVk6t02xaLxXSIxypL0f0zNTQ0YF1dHa5fv57Sk3sDJkQyfPhwQwLhhUOHDiEA4Jtvvpl2fPr06VheXq77m27duuF///d/px1bsGABfv3rX0fEhOsLAPDjjz9OO+fmm2/GW265Rfeas2bN0hmc9oiEZnE2PegF88+D/GSqpp421jWh3BbiQ/Q2+4aWVSTian/agt3KuhGFmMkTQ7qORSLRjGfLzOrLzFIkK5ZpBJF28aQBJkRyxx134IABA3Dv3r1px3fu3Inf+c537LfSAUQhEhoWiQoWAlfPddYMVtpYPDWhwuGROmXTgxgOjxBKqBrBrVUkskCgKdjtLBb00l2JSFoxuattkUhU59nYlu/3sgYaCzCLkTz88MNYVFSEr7/+OjY3N+PNN9+MiqLgd7/7XceNtQNRXFuZ4FVGnhR6wXx1wZL5mpGuQnldk60NM1NpRRGqVnBK0qILBFqC3U+LBUmKO2rbFovFDJ6tCrPregXR7YZiolhuNME02P7YY49h9+7dsVu3bjh+/HjL1FvaKC8vx2nTpqX+7uzsxP79+5sG2zOJbvTo0VnB9nnz5qW+7+joYBpsZw1nFslczM/vo7MbIbuSIyJCRIGQ6WKjJdjXrVuX/P08omf1erGgGYFmts34PS7EzLpeNLY4tuNyFNFlqgcmRHLkyBG89957sUePHhgOh/H888/HlStXumqoE6xcuRIDgQAuXboU9+zZg1OnTsVQKJRa2zJ58mScMWNG6vw33ngDzzvvPJw3bx7u3bsXZ82apZv+GwqFcPXq1bhr1y688cYbmab/2oHTQacXzO+KkWRrY6owShTQUyegeEKVNUQKLlu52JwKdv3sJzXpQtwaV3YJ1A7xuIWVAtLQ0ICxWAwrKqLE7fcaTIikR48eWFZWhi+//DIiIq5duxYLCwvx8ccfd95Sh5g/fz4OGDAACwoKsLy8PG11fTQaxdra2rTzn3vuORw6dCgWFBTg5ZdfbrggsaSkBAOBAI4ZMwabm5uJ2+OWSPTIwm4JlUzoBfPHVVVlZW1VVEQxFoul3btrAqr7fngvVHlBJIuElYvNOPupS6EQVbghkhMoC5ecmWJnRFxd1aqVZD/7w7pnQiR6bp7t27fjBRdcgP/xH/9hr4U5BqdEYkYWTkuoZEJv0llNxOwJ6L1Q5QkRgsusCI1k6+BcAw3rgyQBw2jLA0UJIcBc380lrtV/Dx48iJdeeqnby/gaTonEiCwqIxHMjHEg8FuwqCIej2syuLwTqrwhQnCZlYtNJNedn2DHOlSJq6GhQUMe/ut37mXkRTaDecAJkVitbs/MukKgu2UuaYqrCELVK3gZXPbKIhFRM/YaTvssnbT91+9yPxLOcEIkVvW2WFskdv3vLIKTfshc8RKsXGwiuO5owM4YcjPenFpx2QSkZkD6o98lkXAGC4skWlHBrISKl1qpyIv9RAMra5D2dXkrBXbGEI3x5ma+pJP2Lkxkx/lj7Esi4Qy3MRI9smBVQqW5uRnr6uocaVg0IPpiPxHBysXm9rpeKQV2xhCt8ebUitMj7UgkO1OSFDxJWxIJZzglEhKyoCVEjNcOtHOzSKR/PrfghVJgZwzRHG9urTgapM2yNp8eJJFwhtt1JDyCusZrB8q4+WtlxhBb8NRWaQlpu222M4ZYjDevEjBoLQewA0kknCFaiZRMkNYpYu2WyBWLRLREAVIXE812uxXSem2ORKKW488ri8RL8Ny/SAtJJJwhOpFYTfq6ujpu/lo/ZwyJmihg5WJi0W63Qrq6uia5UC89+FxUVGLZLjtjyM/jTQXrHVWNIImEM0QnEt6bIZnBz+tSREwUIHm37Eut2BPSXW0uw8yCoABBrKiImv7ezhjiNd5YWqnSIjlHIDqRINLVzNwIJq+0ercTXVQ3iXG59IS1uWjRImbtdiqkuyxkd+2yE69gFdvgNZ5Z76iqB0kknOEHIqGlmdFwafDU6mlNdFETBSKRStP3UV9fz7zddoV01xgSrz/tgtd4Zr2jqh4kkXCGH4hEhVvNzI1A9UKrpzXRRbBIMq2qbBdR+vYAFRVR6u2m5cKxIkA/BMK9GBM8s8YkkXCGn4jELoyFl/3Jw1urpz3RvQrcGllVXW6tXZi5iyWAgrFYjFq7abtw2tvbk+XVg9z7kxZEtVJpQRIJZ+QikZgJDvdBVj4aHO2JziNwq6fxG1lVkUg0oz/jmKgyOzetP2m0W68NihLEcHiE4/fW3t7uq42eMiGClWrVPjfWiyQSzshFIjFzCbkRTDy1elYTnYV7wYi403eszH6GSCRK3J9O253dj21ZFpD2/dsVYF5v4esGIqYX01oFL4mEM3KNSEgFsBMBwDv9V8SJrgcj4g6HR5haVbFYjHl/Zlt2ahXb9LZWVY3zbWq3U5iNZ68WrtJaBS+JhDNyjUh4+H55aaF+WLdCVnmAPqkbtUXdlEm9Xnr7zNuqKEFdKzbXoe1/Lxeu0lxzIomEM/xIJHpBdH3BIZ7v1wm0u9aJ5kaxIm4eu1SmCz8lSwhWVY1LtuEB07YCTM+ZMaOFHevCy4WrNFfBSyLhDD8RiZ7/tG/R100Eh9guIVKIWt4E0doiaWpqYt72LuGXvdpc321lZD29ysyK9QJ2x41XSpjWkpQWiU/hJyLJ9J9eCQomUjC993ez9CmLWN5EC5JYDit3YJfwm2spBOPxuKGFlLBkcseKRbQ/bninBOsphiVFRVRWwUsi4Qy/EEmm/7TZQrtUBQdrV5Bba8GKgPzgqvMyltMl/JYRCUGjtrqxYkWrqIzobNywGGtmfaMXWA8pCpYUFaW9H5m15QP4hUgy/adrUgPN2wVVTq0FUgLyYiGkU6HoRSqsHYvErK1OyFBkl6PTcUMrU9AqjdcqsL5+/Xq5jsRP8AuROLFIeLXJrFaUmgBAulAvc8LyskhEFopWyI6RpJdbISnvrsIOGYrscnQ6bmhZl1ZpvKzLy+cskbS1teGkSZOwV69eGAwG8a677sITJ06Ynj9t2jQcOnQodu/eHS+66CL8+c9/jseOHUs7T/vC1c+KFSuI2+UXIkHMriLaFSPxJqhupfV1fZS0SWm1UC9zkvNYT2IlFEV036hIF35KRt+XoaKEqI8JP7gc3YwbN9YlSRrvunXrEABwnsk5bpCzRDJ+/HgcPnw4bt26FV9//XUcPHgwTpw40fD8d999F//t3/4NX3rpJdy/fz9u2LABhwwZgj/4wQ/SzgMAXLJkCR4+fDj1OXnyJHG7/EQkelVE9bK2eGnR1msoXk1+1xsBqlLCORweaUpAmdqYUy2RVPhbPUckEvWFpaJm/QA8iIlyK3Fmwt0Ptaq82s/EytoYGQ6ntakMAHcB3fLyOUkke/bsQYBEKqSKtWvXYl5eHh46dIj4Os899xwWFBTgV199lToGALhq1SrHbROZSIwEYaa25GWZCj2tL0EcNTrEEtf83742S/qcdt1UVkJRUXoaWioigUS407Ks/GCRqGC5n4leHES1uPUsEiVJFlqXVzB53GlgXQ85SSSLFy/GUCiUduyrr77C/Px8fOGFF4ivU19fj3379k07BgDYr18/LCoqwpEjR+LixYvx7Nmzhtc4deoUdnR0pD6tra3CEQmtejtuQSJ09LS+hPXRniXIElpy4v+XXDIkuZKavrvKru/e2rKaJ7ywRLR+DtpFFv1SwoYVzOIgeptZBRXFkGDUADst5CSRPPbYYzh06NCs48XFxfjUU08RXeP//b//hwMGDMBf//rXaccfeeQR3Lx5M+7YsQPnzJmDgUAA//CHPxheZ9asWRlCD4QjElr1dpzCSeA5Ho9b7ugHsA0z9/nW+vSLikrwwIEDrtruVFPWE4qK0jvZPnHdN5kwEu5FRSXUA+Mil7BhHdPSxkGaIZFFGdeQQlNTU5YyOCLp0uKxf7uviOTBBx/UFcraz969e10TSUdHB5aXl+P48ePxyy+/ND135syZeOGFFxp+L7pF4tUez1q4ycYxdnVVJUkkmHbdxHfDEWAeFW3Wqe9eTyhGIqoGL777RoX+c7DdiEqkCsB6SlA4PDLNrU4D6jirypB36t/qONP2Dc+57Ssi+eSTT3Dv3r2mn9OnT7tybR0/fhxHjx6NY8aMIQqiv/zyywgAeOrUKaJnEC1Gwjot0Apufd/6ri5tJpH2us3YVf8pTnwPlu3PFIpW7htRs7m0z+GHwDgt6ClBCeVFoWotNTc3owKAvZPEoHoOekMi3mE0Hnjt3+4rIiGFGmx/6623UscaGhosg+0dHR14zTXXYDQaxc8//5zoXo8++ij27t2buG2iEYnXFgktoaMVZPF4HOvq6jTXzd4TA2AkJnYLtL6HlfCm6bs3ct+0tLQI69bJhJ8C425g9ZyKEqQWv3E6T3nt356TRIKYSP+96qqrsLGxETdv3oxDhgxJS//96KOPcNiwYdjY2IiIiY4YNWoUXnnllbh///609N4zZ84gIuJLL72E9fX1+O677+K+ffvwqaeewvPPPx8ffvhh4naJRiSI/LQWRLrb8epdT3u867rZe2Ik/i4zvYe+22JEltuChe/e2FIRP5sr0fcKJtyImS5HJWeIxHpd0wPUiFONBzr1HLB2B+YskbS1teHEiROxZ8+eWFhYiHfeeWfagsSDBw8iAODGjRsREXHjxo0ZGmvX5+DBg4iYSCEuKyvDnj174te+9jUcPnw4Lly4EDs7O4nbJSKR8NBaaG/HSxKgr66uSWZqma/ZMEJXuxZiIuZiThTsCyX6Q8PvErDpfab+nSuurfRyMdnraBLrmtw9b2ZGpZexTDPkLJGIChGJRAVLrcVMo3ai0ZNo6O3t7US7BurByqIRaUW/aII5ve/UveHpxKREQltbGxYVlWSQZRkChJJjxv3zajMqqyARE+HhObALSSScwZtIaAZnnV6L9na8djR0p9p8l/De5Lk14DeLBNEovTmI4fAIIdvrBMaB9mIEWOhK2Whubk65s1QrpB0AazK8JV6s99KDJBLO4EUkNBcZur0WbY3a7vWcuM66hPd0IawBvy3Gy7Yy02tyiZooQAqSLY+dPKPeXMuMi7yaPF5fX8/o6exDEgln8CISmosM3V7LrkZNe88QPddZRUXUcpKTxFh4add23H8ipQinb24lfqIAKayUGadCXjvXNoHYcREtJJFwBg8ioZnSS+taJBq1nRXudjX0trY2w2KIRoK3S3h7W/VYCzP3n4il6f3oliMBq02pMudaDYgbF9FCEgln0CISI+HX1tZGtTQCrQWLJBq1nRRXuwF6o2tnBkv1rtHU1KSpICyGgNaDiKXp/ZYoYAe03Y16c60dslezW7mVvXjPkkg4wy2RWMUraqqrLYu1NTQ0EA802gsWjTRqpxoeSYCerEiitctFpNIcmRC1NH2uWiSI9pUZUpet0VxTN24zgpfFVyWRcIZbIjGLV2gHYg0A9sk0iR3uz8xjwSJLzdV64dga3ws4kUvT+y1RwC6sFAw7Lkc3c83L4quSSDjDDZGQaCyqaayXKti7sBBDimJ7oNlZsMg6RdgJrC2SuOaYP10uIpemF7lqLw/Yddk6sSq8LnUkiYQz3BCJVbwiM+8cIVFq+gHNoHQz0FgHellqrvpVgoOYWECWGy4X0UvTi+waZAWWLlstvC6+KomEM1haJPF43NA0Zr03AY1aUCw1V71rFxWVoKKEmBCXF8iV0vS5BF7JBtIiOcdAK0Zi5EM1Mo3NtuNk7TqiFZCnAe21/ehyIXEdqpt+qcHZXI9RiAyeyQY8i69mQhIJZ7glElIfqp4wZjXQ/J7i6QeXC6nrUO+8qqpxWFU1zleE6QYiLchE5JdswKtkvB4kkXAGrXUkToQfq4GWyymeZuApsEhdh2bn+YEw3UDEBZmI/JMNvHjPkkg4Q4TqvywG2rnkPmElsMj2VjEm6nOV0FWIvmdLLhO5JBLOEIFIWID24iyRQVtgWRETqevQ7y5GNzjXSdRrSCLhjFwlEhU0F2eJCBYCi6S0ibRIzOEVifpZIaIJSSScwYtI1P0MrMoq8IB2sonufrACbYFFKvxJXYcsXYw8hKaIC1r14HeFiDYkkXAGayJpa2vDcVXpW5wqAPjta67BWCzGlVT0JpvfNWbaAouUmEhdhywCuzyEpugLWo3v5U+FiDYkkXAGayKpqa7GUF5eqgzKQgAMZAhyXimB2ZNNjE2i3MJIYEUilWnaNEmRPrUaASkxkQZsaQZ2eQhN0Re0Ina9z4aGBt8rRLQhiYQzWBKJ2X4GvAu56WvuueHDN1olb/a3VqDpW2oBBFjIXJO2CysLzE4laaf38HpBq7Fl7W+FiCYkkXAGSyLJrLfTDO7ra7ltS/Zkq0JRNolyC1VgVVREDfbuLtPVrvW077y8EGq3oxXF3278Hnchre1zRc82y35fc3NCIaIJSSScwYpItG4SlTjWJCe4F4Xc1q1bZzDZFlITQCKAvLJwlwZvdr4IyRFaGD9fWZIs3bu7RM42s35+/ytENGBHrp0HEsKhvb0dJk+aBGsaGlLHfgwAnwHApcm/XwOA2zS/eTX57+DBg5m16+zZswCgQD7cA52AABAFgFchHx6ETgCor6+H/v37w+DBg2HIkCHM2sEaLS0tyf9VZnwTTf67HwCGpP7eunWr6fn9+/d33R/xeBxaWlqo9O3QoUOhuroGXnnlXujsVN/jSgB4GwCWQ9fIug06OxEaGibDvn37TO+b2T79e7wK+fm/gLFjazwdH8bv988AUAYAk1NHRo+OwooVy/k0zM/gQGw5D9oWid5mNiFIZGpB8t8g8N/zWdXkrsywPtS/RdK63YC2ReKmX1hlV+nFhMCBK8qsfaIW0LR6vyNGlAvXZi+Qs66ttrY2nDRpEvbq1QuDwSDeddddeOLECdPfRKPRrMny05/+NO2cDz74AGtqarBHjx5YXFyMDzzwAH711VfE7aJJJFalox999FF84oknMFpRkfZMrLO21OyWaEUF9snPx7kAuAwA53IiMd4w3+sk2+3BKk2VdXaVGhNySoYk7ROxjIjR+yoqKuGaAuxmHQ/rNUA5SyTjx4/H4cOH49atW/H111/HwYMH48SJE01/E41GccqUKXj48OHUR9sxZ86cwSuuuALHjh2LO3fuxDVr1mDfvn3xoYceIm4XTSKx2swmFoulzuUxQfX2jHayta/fQJLFpdVU9c6vqIi66hfecQa7ZChyHMQK+vu8VNp6HjeC3M1e7Lz2cc9JItmzZw8CADY1NaWOrV27FvPy8vDQoUOGv4tGo/iLX/zC8Ps1a9agoih45MiR1LE//elPWFhYiKdPnyZqG0+LJBqJOL6uk0FvtGd0NBLhpmV6WbIik6ytdpSMRNItYDduEavMp7q6Ot12OO0vu64o0TOzSKB9n6TPQ0OQu9mLndc+7jlJJIsXL8ZQKJR27KuvvsL8/Hx84YUXDH8XjUaxb9++WFRUhJdffjnOmDEDP//889T3M2fOxOHDh6f95sCBAwgAuGPHDt1rnjp1Cjs6OlKf1tZWakSCiBiNRLJjIABYBvZTfN0Meq93aPNbyQrabih9jb8NE+617D6hRWSklq6fLRI9kD6PW0GunVfNkMjEjBPOK9I5SUP5ykkieeyxx3Do0KFZx4uLi/Gpp54y/N3TTz+N69atw127duHy5cuxf//++P3vfz/1/ZQpU/D6669P+83nn39uqlHNmjUrbbKqH1pEEovFUoH1lPAHwF1gP8XXzaD3es9oP5WsYCVUs91N+im6VVXjkq43Oum7es+nJ5iqqsYl18t0ucPy8kJYVTWOijDjbY1aufdoKFfqvKrKmONVBPOKxPVNy+3lKyJ58MEHdYWy9rN3717HRJKJDRs2IADg/v37EdEZkbC2SNTBOk+jrTixBNwOei8tEr9pu6zcPPrZVUbZZPT7y8oqTOzSGMhoXwB79y42/A2N+7KClXuPhnLV3NyMCmRXp+gNiYxMNxaJmgxDw+3lKyL55JNPcO/evaaf06dPO3ZtZeKzzz5DAMB169YhojPXViZYLEiksYUujUHv1Z7RfvO/sya+eDyOdXV1pn3Cor/MrML0Z44jwJrkv/pWkx3LyGtr1Mi9R0O5cnsNozlZGYlQVfx8RSSkUIPtb731VupYQ0ODZbA9E5s3b0YAwHfeeQcRu4LtR48eTZ3z9NNPY2FhIZ46dYromiyIhMYWujQGvVd7RvvNIkFkX6nWen0L3f6yul99fb0Oebl/b6K/e7fKlVsFz2hOxmIxV9fNRE4SCWIi/feqq67CxsZG3Lx5Mw4ZMiQt/fejjz7CYcOGYWNjIyIi7t+/Hx955BF866238ODBg7h69WocNGgQVlZWpn6jpv9ef/31+Pbbb+O6deuwuLjYs/RfxHS/sNsUX1oWhRdrAfy21W97ezvVrC09GK9vUZKWQPZ3FRVRR/eysgr1qxy7tyRFt0bdKle0XMaZc5K2KzpniaStrQ0nTpyIPXv2xMLCQrzzzjvTFiQePHgQAQA3btyIiIgffvghVlZWYp8+fTAQCODgwYNx+vTpWR3zz3/+E7/zne9gjx49sG/fvvjLX/7SkwWJLPLDvbIoaEDUldF60PPpRyLu1pHoob29PWs9S4JAChCgEDMzuoqKShy3gcQyyCa2x3PeIlHhRrli5TKmed2cJRJRQYtIWOaHi7i6mBR+aDsvn36XkJ2HXTEJRL3CmZGIeyKzsgr1yL5btx6YWfwQIIhFRSXU7msnm0vErXNZKXg0ryuJhDNoEInXazYknIOnBm3l9qmvr6cqNEmtwuxSK+mWkfo3abu2bduG4fCIrPu2tLQQW6k0M79YkRErJYnGdSWRcAYNIvF6zYZbiKj18QJPn75Xbh9SwZTeF9pMLrK+0BP+4fDIVEULO5YfDSuRVzkSESGJhDPOZYvkXJ5oKkSvicUTbndfJE83Nu9nWu+EVzkSESGJhDNox0h4r9lwg3N5omnBU7iLnoSg1xeKEjIteonoNN1Y3/KjYSX6VbmjBUkknEGLSGgH4Fi7m871iaaFF8Jd1CQEo8rJVm4mZ+nG7CwSv7ub3UISCWfQXkfiVkDwcjed6xNND6IKdy9gd68TZ+nGxpafWR0wEpzripIkEs5gtWe7U/ByN5FMtHM5CC+RgB03k5N0YyPLb1xVFZ4H+Wnnngf5OK6qirjtfnQ304IkEs4QiUh4a1FGE23sddcxs4rskpMkM29hx81kN93Y6J2q95wLgPXJj1mpdqMx4ucFvW4hiYQzRCISVu4ms4kWTRaL0060cVVV1K0iu+sC/LafCSuIQKR2kxHcughJt2IgdQOfiy5LSSScIRKR0LZIzCaa3nfRSAS3bdvGxCqyuy7A6wqyXkMkIuWdjKBuDpemyED25nA11dUYVBScDoCvMnQDO4WXSoAkEs4QiUgQ6fh11QFstr+BUSxmRDhM3Sqym4Xjl3pNLOEVkZoJPx6aPel21Y2NjbpWy0KXCg8NiLA+SxIJZ4hGJG78unoD2GhCOv3OyQS1CtjGYjFb59POKBPBfaSFF0RqZQHx6iOSXQQREUeGw7pWC8lOhawhwvosSSScIRqRqHCi/WkH8LLkhDKakGbfjQyHqWa7WAnGSCRq63xawkwk95EWtImUhAS60m27LKC8vBBWVFzLtY9IswmtFCGvlAJR0o4lkXCGqERiF5kDuNmF1dHU1ETdNI9EophdVbYPGhUE5LHaXNQ4DC0iJSVK8/sp3PvIyr1rZbWMCIeZtc0KoqzPkkTCGU6JRDR3iN4AroGEua83Ia0ma3NzM9bX12N9fT2VVN3EDnDppdIBahBgl+4EYx3gFT0OQ4NISYmya9V5pgW0ybSPrGpvOYWVe9dK61eLRHoBaZGco7BLJCIE0vSgN4DboSvTJbOtRpO1paXF9vOR9InxXhxd7i29e7AK8PphJz83RGqHKPXLl7QhwCDTPmLt7jJ79yIvNhShbZJIOMMukVgF0ry0VIwG8Mirr8a6ujpcv3591m8yJ6uTQCHpb/S3mk24t3i7lES3SFQ4JVI7RJnoCwUBemveTRkC9DTto4RS4I1LUOTFhiK0TRIJZ9jpcMvUxIoKZoPHjKDU7/RiGyVFRcRtcmKW2/mN3r7oCfdWuycCXOSS7m5hlyirqsYhQCDj3SxPvh+9febLTK/LQ6Fy4n7lCadKAI2+k0TCGXY63CyQpgBgb0WhnvJnd1FhTXU1NjU1JdaRRCK2rAsngUK7v+nSlJdhl3vLG5eS6CXd3cIOUer1ReI37Uky0R5XMBHbyrZ0YrEYc21cVPeyW9B8LkkknEHDInkc6K+9UGHmNjL7jrV14fQ3IrqUcrWEhhOijMfjBjGTOAI8kGGtZL8/u8qLE4iwToMFaD6XJBLOcBoj0cYheiqKbU2eBCT58kbfqRsJ2W2Tk0Ch3d/ksktJRGhLwpMSptk7MvouEolSU6iM3DuiZEXRBu3nkkTCGXaJRC+QVpksfEh7cFu5jcy+U7VKu21yEii0+5tcdymJBicLL83ekdF3iRRvdwqVlXtHlHUaWpiRHilx034uSSSc4XQdiVG2E82UPzcWSTwed9UmJ+4eu79xcg/R1u/4AW4WXpq9o8zvaGjVJFmRolgkRqTnJIVeWiQ+hyhb7RoJSDMysCIKEdIQaUGkAKufyIx3TMqN8kIqTEVYp6FtRybplRQVOYp10HwuSSSc4fVWu1YC0owMSIkiF4LJXgRYMwlD1NpcZuC98NKN8kLq3hFBQbIivXkOLAuaz5WzRNLW1oaTJk3CXr16YTAYxLvuugtPnDhheP7BgwfTOlT7ee6551Ln6X2/YsUK4nZ5XWuLVEDacTHkGni7M4wIo6pqnJC1uczgVZacU7elnffs5bi3Ir1lFmRoBhrPlbNEMn78eBw+fDhu3boVX3/9dRw8eDBOnDjR8PwzZ87g4cOH0z51dXXYs2fPNAICAFyyZEnaeSdPniRulxdEomq6DQ0NXAWkX8E7wGoUU0isnxAnbZkUfsqSE8VtZQUWFglN5CSR7NmzBwHSi6mtXbsW8/Ly8NChQ8TXKSsrw7vuuivtGADgqlWriK9x6tQp7OjoSH1aW1tdEwmpz1zPjSVaBoqIsJq06spmGrELKw0e4NWM42LU5jKDn7LkRHBbkcKI9NQYiay1RRmLFy/GUCiUduyrr77C/Px8fOGFF4iu8dZbbyEA4BtvvJF2HACwX79+WFRUhCNHjsTFixfj2bNnDa8za9YsXXeYEyKxGwDOdGPNBXYLGXMNepM2CJC2S55C+B7MYBVTAJiOAM3YVXhSfItEhZ9coH5oqxHpHThwwHMyzEkieeyxx3Do0KFZx4uLi/Gpp54iusbdd9+Nl112WdbxRx55BDdv3ow7duzAOXPmYCAQwD/84Q+G16FpkRjFN0aGw8QLqcqSAlF0U94LaC0MvUkbAMCnNX3fGxI75LkJxFtbJJn1qAJYVTWOwdNL+AVGpOclGfqKSB588EFd7V772bt3r2si+eKLLzAYDOK8efMsz505cyZeeOGFxM/gZj8SLTE0A+AajZWRqYUY+fl3ZWjSIpvyvGBm6UUjETw/L8/cknNp1RnFFPr0+bruLoKSSCREg6+I5JNPPsG9e/eafk6fPu3atfXnP/8Zu3Xrhp988onluS+//DICAJ46dYroGZwSiUoMuyCxgZRW6CkA+HOwt5Bq/fr1wpvyvGBk6akVBKaDRWwJ3MWZ9GIKkUilqaXil/fmpzUwEs7hKyIhhRpsf+utt1LHGhoaiIPt0WgUf/CDHxDd69FHH8XevXsTt82tRVIGiV0ItUIvCIBRHa3YLxkpXqG5udmytAsA4CawiC25tEhUaF0TJOsxeAtpO/cTaUGnBHvkJJEgJtJ/r7rqKmxsbMTNmzfjkCFD0tJ/P/roIxw2bBg2Njam/W7fvn2Yl5eHa9euzbrmSy+9hPX19fjuu+/ivn378KmnnsLzzz8fH374YeJ2uUn/taqx9WqGVuynjBSe0BNyZvXFloP+NsJqjEQl6MpIhJpgt4qdRJNjgcd7dUIKuVoxV0IfOUskbW1tOHHiROzZsycWFhbinXfembYeRF2AuHHjxrTfPfTQQ3jRRRdhZ2dn1jXXrl2LZWVl2LNnT/za176Gw4cPx4ULF+qeawQ3RGJVpO4BA63YDxkpPKEVclbWRrSiAvvk5+PCJGlohWme5v92NvQihVHspG/R17kKabukIFJ9qlyB6C7CnCUSUeGGSKwmaFBRhNb4RJgMen1Yk7Qu9FyAelZd2be+hf/nmmvSjmVmdNEQ7PqxkyhXIe2EFESsmOtX+MVFKImEM9yubK+MRLCnouBcyF7fIOIAQxRrMugJuXYdayOzfVqrTk9D750kpMxsOhqCXS92wktIO7kfKfmIoFiIDr+4CCWRcIZTItETxmoa78hwOG0Vv2gQaTKQrlp3+vvM9xOLxbi2XwSLBNFgQzZIuAO/fc01OK6qippikauE5CcXoSQSznBKJLpasKJgtKKCUUvpTFBak4GmsHCTzWaloU+HjGw6B+/H6ll5Z+MZ3c8suSDTJZi5duk8cO8KFMnSZQE/uQglkXCGEyLxohotrQnqdjKwEBZustks34WL90P6rLyz8fTuR5JcoPbVJWCcsu5mLLOwdEWybqRFImEIJ0TCWzOhOUGtJoPVvt4s3WJOs9mM6nBVuXw/dp+Vdzaeej81k82qnV1rYayJ125f0Rayolo3flkLJomEM0S3SFjcy6xqqdnEFVUj09PQFUi4apy2U9RnVdumEpaddnathTGvCuDkOWkrVyLF8bTwy1owSSSc4TZGwlozYWH9GLlGQopiOnG99hFbuTn0Mrmcvh+vn1UPelr6yHDYVjtJFtE6Gcs0iVdkElch+lowSSSc4ZRIeGkmLCeVOhlIN9jyaoI7cXO4fT8iCjMjLV2x0c729nYsKSrKqjgdAvdl+GkpVyKSuN8giYQz3K4j4aGZsLZ+7ExcL3zEbtwcbt6PSP5wksWvpO1sb2/HaEVFFsk2NTW5Gsu0lCsRSdxvkETCGV7v2U4C1taPnYnL20fspVDxwh9u5L6zIvsRSReX+qmMRDAWi5n2DysliMZ1RSJxP0ISCWf4gUhUsLR+7E5cXj5iEdwcLJ9VJY5t27aZkhYJocbjcYzFYrrWhmjBYCv4JagtKiSRcIafiIQlRJ24uerm0Iv7WNUHIyF7J25AkdZqZEL0oLaokETCGbyIROTJqqK5uRnr6+sty5LwRi66OczqgxmRpRXZNzY22iJdUddqSLiHJBLOYEEkWtLww2T1oo12iFVUa8kpSFfjG7nvjLT0ETZTgUVdqyHhHpJIOIMmkegJ5JKiIuEnK0+B4oa0csXNYRn3sem+0+4sSWqR5KrLUCIBSSScQZNIMgXyXBsT2yvwFihSC7buc9JFgXqkXAzZO0cGIbFwUQsRkhgk2EESCWfQIhI94bAGuspRqPtixBlOVidxGCuBsmjRIurb1YpMrLygF/cJ5eXZWhSoR8pBACzRXAMgsdAwc1sD+S5yG5JIOIMWkegJ5ObkpCzLmNhllCerG3eRkUD5E2SXGncbl1D7aJOGVEXVglknRxjFfUgXBVoRwbOQ2OrZbJfOXExiIIEfEl/cQhIJZ7C0SBASpSeCkF2yu6SoyNa1WVbk1RMogaSGTNMF1djYmE1OALhQIC2Yd+KB07iPlSVJ0vZcS2Kwgh8SX2hBEglnsIiRqAL5cXAXIyEZ+DRcFHoChYXbo6a6OouceidJSxQt2C8xHLc7S2phl8z8qtH75d3SgCQSzqBJJEYC2WlAk2TgazVTt3EYVaDU19e7arcerASfCFsT+y1uwNs15WeN3m/v1i0kkXAGi3Ukdqvq6oF04Kvn0YzDqNecC+mxDDeTToQsIStNWoQ22gGpa4qWBeFnjd5v79YtJJFwBuuV7U61RjsDXy0L7iYOo0VbW1vWJldlABgyCdxawUuNkFST9qvWauSaomlBiNw3JEQpcvtZQBIJZ7AmEqcBTbsWCYsdFPWIyY0bw6ssITuadC5lMtG0IETU6O0SZS69WyvkJJE8+uijOHr0aOzRowcGg0Gi35w9exZnzpyJpaWl2L17dxwzZoyuxjVp0iTs1asXBoNBvOuuu/DEiRO22sar1paT7BySgU97grPU3Lwqy27neXIlk4n2exRRo7dLlLnybkmQk0Ty8MMP4+9+9zu8//77iYlkzpw5GAwG8cUXX8R33nkHJ0yYgBdffDGePHkydc748eNx+PDhuHXrVnz99ddx8ODBOHHiRFttE7n6L8nApz3BeWiePEudOH0ev5djYfEeRdLo3Yx7v79bEuQkkahYsmQJEZGcPXsWS0tLce7cualjx44dw0AggCtWrEBExD179mBmts/atWsxLy8PDx06RNwmkYlEhdXApznBRdQ83SDXnocULJ5bJI1eRFebSJBEgogtLS0IALhz586045WVlXjvvfciIuLixYsxFAqlff/VV19hfn4+vvDCC4bXPnXqFHZ0dKQ+ra2twhOJFWhPcJE0TxrItechBavnFkGjP1cVBFJIIkHEN954AwEAP/7447TjN998M95yyy2IiPjYY4/h0KFDs35bXFyMTz31lOG1Z82alSZw1Y+fiUQFrQkukuZJA7n2PKTI9ec+VxUEEtghkvPAQ8yYMQN++9vfmp6zd+9euPTSSzm1iAwPPfQQ3H///am/jx8/DhdddJGHLaKHIUOGwJAhQ1xfp3fv3vC3detg3759sH//fhg8eDCV63qFXHseUuT6cy9fsQL+feJEmNzQkDpWM3YsLF+xwsNW+Q+eEskvf/lLuOOOO0zPGTRokKNrl5aWAgDA0aNH4YILLkgdP3r0KJSVlaXO+eSTT9J+d+bMGWhvb0/9Xg+BQAACgYCjdp1roEVMoiDXnocUufrcuU6UvOApkRQXF0NxcTGTa1988cVQWloKGzZsSBHH8ePHobGxEe6++24AABg9ejQcO3YMtm/fDldffTUAAPzjH/+As2fPwqhRo5i0S0JCQjzkKlHyguJ1A0jx4Ycfwttvvw0ffvghdHZ2wttvvw1vv/02fPbZZ6lzLr30Uli1ahUAAOTl5cF9990Hjz76KLz00kvw7rvvwu233w79+vWDm266CQAALrvsMhg/fjxMmTIFtm3bBm+88QZMmzYNbr31VujXr58XjykhISHhO3hqkdjBww8/DMuWLUv9fdVVVwEAwMaNG+Haa68FAIDm5mbo6OhInfOrX/0KPv/8c5g6dSocO3YMIpEIrFu3Drp3754659lnn4Vp06bBmDFjQFEU+MEPfgB//OMf+TyUhISERA4gDxHR60b4HcePH4dgMAgdHR1QWFjodXMkJCQkXMOOXPONa0tCQkJCQkxIIpGQkJCQcAVJJBISEhISriCJREJCQkLCFXyTtSUy1HyF48ePe9wSCQkJCTpQ5RlJPpYkEgo4ceIEAEDOlEmRkJCQUHHixAkIBoOm58j0Xwo4e/YsfPzxx9CrVy/Iy8sj+o1an6u1tVWmDGdA9o0xZN8YQ/aNMZz0DSLCiRMnoF+/fqAo5lEQaZFQgKIocOGFFzr6bWFhoRz0BpB9YwzZN8aQfWMMu31jZYmokMF2CQkJCQlXkEQiISEhIeEKkkg8QiAQgFmzZsly9DqQfWMM2TfGkH1jDNZ9I4PtEhISEhKuIC0SCQkJCQlXkEQiISEhIeEKkkgkJCQkJFxBEomEhISEhCtIIpGQkJCQcAVJJJzw2GOPwbe//W04//zzIRQKEf0GEeHhhx+GCy64AHr06AFjx46Fffv2sW2oB2hvb4fbbrsNCgsLIRQKwY9//GP47LPPTH9z7bXXQl5eXtrnZz/7GacWs8WCBQvgG9/4BnTv3h1GjRoF27ZtMz3/+eefh0svvRS6d+8OV155JaxZs4ZTS/nDTt8sXbo0a4xot9nOFbz22mvwve99D/r16wd5eXnw4osvWv5m06ZNEA6HIRAIwODBg2Hp0qWu2iCJhBO+/PJLuPnmm+Huu+8m/s3jjz8Of/zjH2HhwoXQ2NgIX/va16C6uhpOnTrFsKX8cdttt8Hu3bvh73//O7z88svw2muvwdSpUy1/N2XKFDh8+HDq8/jjj3NoLVvEYjG4//77YdasWbBjxw4YPnw4VFdXwyeffKJ7/ptvvgkTJ06EH//4x7Bz50646aab4KabboL33nuPc8vZw27fACRKgmjHyAcffMCxxXzw+eefw/Dhw2HBggVE5x88eBBuuOEGuO666+Dtt9+G++67D37yk59AQ0OD80agBFcsWbIEg8Gg5Xlnz57F0tJSnDt3burYsWPHMBAI4IoVKxi2kC/27NmDAIBNTU2pY2vXrsW8vDw8dOiQ4e+i0Sj+4he/4NBCvigvL8d77rkn9XdnZyf269cPZ8+erXv+LbfcgjfccEPasVGjRuFPf/pTpu30Anb7hnSu5RIAAFetWmV6zq9+9Su8/PLL04796Ec/wurqasf3lRaJoDh48CAcOXIExo4dmzoWDAZh1KhRsGXLFg9bRhdbtmyBUCgEI0aMSB0bO3YsKIoCjY2Npr999tlnoW/fvnDFFVfAQw89BF988QXr5jLFl19+Cdu3b09754qiwNixYw3f+ZYtW9LOBwCorq7OqTEC4KxvAAA+++wzGDhwIFx00UVw4403wu7du3k0V2iwGDOy+q+gOHLkCAAAlJSUpB0vKSlJfZcLOHLkCHz9619PO3beeedBnz59TJ9z0qRJMHDgQOjXrx/s2rULHnzwQWhuboYXXniBdZOZ4dNPP4XOzk7dd/7+++/r/ubIkSM5P0YAnPXNsGHD4JlnnoFvfetb0NHRAfPmzYNvf/vbsHv3bsfVunMBRmPm+PHjcPLkSejRo4fta0qLxAVmzJiRFczL/BgN8lwH676ZOnUqVFdXw5VXXgm33XYb/PnPf4ZVq1ZBS0sLxaeQ8DNGjx4Nt99+O5SVlUE0GoUXXngBiouL4emnn/a6aTkHaZG4wC9/+Uu44447TM8ZNGiQo2uXlpYCAMDRo0fhggsuSB0/evQolJWVObomT5D2TWlpaVaw9MyZM9De3p7qAxKMGjUKAAD2798Pl1xyie32ioC+fftCfn4+HD16NO340aNHDfuitLTU1vl+hZO+yUS3bt3gqquugv3797Noom9gNGYKCwsdWSMAkkhcobi4GIqLi5lc++KLL4bS0lLYsGFDijiOHz8OjY2NtjK/vAJp34wePRqOHTsG27dvh6uvvhoAAP7xj3/A2bNnU+RAgrfffhsAII10/YaCggK4+uqrYcOGDXDTTTcBQGL3zQ0bNsC0adN0fzN69GjYsGED3Hfffaljf//732H06NEcWswPTvomE52dnfDuu+9CTU0Nw5aKj9GjR2eliLseM47D9BK28MEHH+DOnTuxrq4Oe/bsiTt37sSdO3fiiRMnUucMGzYMX3jhhdTfc+bMwVAohKtXr8Zdu3bhjTfeiBdffDGePHnSi0dghvHjx+NVV12FjY2NuHnzZhwyZAhOnDgx9f1HH32Ew4YNw8bGRkRE3L9/Pz7yyCP41ltv4cGDB3H16tU4aNAgrKys9OoRqGHlypUYCARw6dKluGfPHpw6dSqGQiE8cuQIIiJOnjwZZ8yYkTr/jTfewPPOOw/nzZuHe/fuxVmzZmG3bt3w3Xff9eoRmMFu39TV1WFDQwO2tLTg9u3b8dZbb8Xu3bvj7t27vXoEJjhx4kRKngAA/u53v8OdO3fiBx98gIiIM2bMwMmTJ6fOP3DgAJ5//vk4ffp03Lt3Ly5YsADz8/Nx3bp1jtsgiYQTamtrEQCyPhs3bkydAwC4ZMmS1N9nz57FmTNnYklJCQYCARwzZgw2NzfzbzxjtLW14cSJE7Fnz55YWFiId955ZxrBHjx4MK2vPvzwQ6ysrMQ+ffpgIBDAwYMH4/Tp07Gjo8OjJ6CL+fPn44ABA7CgoADLy8tx69atqe+i0SjW1tamnf/cc8/h0KFDsaCgAC+//HL829/+xrnF/GCnb+67777UuSUlJVhTU4M7duzwoNVssXHjRl3ZovZFbW0tRqPRrN+UlZVhQUEBDho0KE3uOIHcj0RCQkJCwhVk1paEhISEhCtIIpGQkJCQcAVJJBISEhISriCJREJCQkLCFSSRSEhISEi4giQSCQkJCQlXkEQiISEhIeEKkkgkJCQkJFxBEomEhISEhCtIIpGQEBQrVqyAHj16wOHDh1PH7rzzztT+GhISokCWSJGQEBSICGVlZVBZWQnz58+HWbNmwTPPPANbt26F/v37e908CYkUZBl5CQlBkZeXB4899hj88Ic/hNLSUpg/fz68/vrrKRL5/ve/D5s2bYIxY8bAX//6V49bK3EuQ1okEhKCIxwOw+7du2H9+vUQjUZTxzdt2gQnTpyAZcuWSSKR8BQyRiIhITDWrVsH77//vu5+5ddeey306tXLo5ZJSHRBEomEhKDYsWMH3HLLLbB48WIYM2YMzJw50+smSUjoQsZIJCQExD//+U+44YYb4Ne//jVMnDgRBg0aBKNHj4YdO3ZAOBz2unkSEmmQFomEhGBob2+H8ePHw4033ggzZswAAIBRo0bBd77zHfj1r3/tceskJLIhLRIJCcHQp08feP/997OO/+1vf/OgNRIS1pBZWxISPsXYsWPhnXfegc8//xz69OkDzz//PIwePdrrZkmcg5BEIiEhISHhCjJGIiEhISHhCpJIJCQkJCRcQRKJhISEhIQrSCKRkJCQkHAFSSQSEhISEq4giURCQkJCwhUkkUhISEhIuIIkEgkJCQkJV5BEIiEhISHhCpJIJCQkJCRcQRKJhISEhIQr/P+Hbb38tIDSMAAAAABJRU5ErkJggg==\n"
},
"metadata": {}
}
],
"source": [
"import pennylane as qml\n",
"from pennylane import numpy as np\n",
"from pennylane.optimize import AdamOptimizer, GradientDescentOptimizer\n",
"\n",
"import matplotlib.pyplot as plt\n",
"\n",
"\n",
"# Set a random seed\n",
"np.random.seed(42)\n",
"\n",
"\n",
"# Make a dataset of points inside and outside of a circle\n",
"def circle(samples, center=[0.0, 0.0], radius=np.sqrt(2 / np.pi)):\n",
" \"\"\"\n",
" Generates a dataset of points with 1/0 labels inside a given radius.\n",
"\n",
" Args:\n",
" samples (int): number of samples to generate\n",
" center (tuple): center of the circle\n",
" radius (float: radius of the circle\n",
"\n",
" Returns:\n",
" Xvals (array[tuple]): coordinates of points\n",
" yvals (array[int]): classification labels\n",
" \"\"\"\n",
" Xvals, yvals = [], []\n",
"\n",
" for i in range(samples):\n",
" x = 2 * (np.random.rand(2)) - 1\n",
" y = 0\n",
" if np.linalg.norm(x - center) < radius:\n",
" y = 1\n",
" Xvals.append(x)\n",
" yvals.append(y)\n",
" return np.array(Xvals, requires_grad=False), np.array(yvals, requires_grad=False)\n",
"\n",
"\n",
"def plot_data(x, y, fig=None, ax=None):\n",
" \"\"\"\n",
" Plot data with red/blue values for a binary classification.\n",
"\n",
" Args:\n",
" x (array[tuple]): array of data points as tuples\n",
" y (array[int]): array of data points as tuples\n",
" \"\"\"\n",
" if fig == None:\n",
" fig, ax = plt.subplots(1, 1, figsize=(5, 5))\n",
" reds = y == 0\n",
" blues = y == 1\n",
" ax.scatter(x[reds, 0], x[reds, 1], c=\"red\", s=20, edgecolor=\"k\")\n",
" ax.scatter(x[blues, 0], x[blues, 1], c=\"blue\", s=20, edgecolor=\"k\")\n",
" ax.set_xlabel(\"$x_1$\")\n",
" ax.set_ylabel(\"$x_2$\")\n",
"\n",
"\n",
"Xdata, ydata = circle(500)\n",
"fig, ax = plt.subplots(1, 1, figsize=(4, 4))\n",
"plot_data(Xdata, ydata, fig=fig, ax=ax)\n",
"plt.show()\n",
"\n",
"\n",
"# Define output labels as quantum state vectors\n",
"def density_matrix(state):\n",
" \"\"\"Calculates the density matrix representation of a state.\n",
"\n",
" Args:\n",
" state (array[complex]): array representing a quantum state vector\n",
"\n",
" Returns:\n",
" dm: (array[complex]): array representing the density matrix\n",
" \"\"\"\n",
" return state * np.conj(state).T\n",
"\n",
"\n",
"label_0 = [[1], [0]]\n",
"label_1 = [[0], [1]]\n",
"state_labels = np.array([label_0, label_1], requires_grad=False)"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "NqAg65FbTnyx"
},
"source": [
"Simple classifier with data reloading and fidelity loss\n",
"=======================================================\n"
]
},
{
"cell_type": "code",
"execution_count": 51,
"metadata": {
"id": "ZyKIWD9bTnyx"
},
"outputs": [],
"source": [
"dev = qml.device(\"lightning.qubit\", wires=1)\n",
"# Install any pennylane-plugin to run on some particular backend\n",
"\n",
"\n",
"@qml.qnode(dev, interface=\"autograd\")\n",
"def qcircuit(params, x, y):\n",
" \"\"\"A variational quantum circuit representing the Universal classifier.\n",
"\n",
" Args:\n",
" params (array[float]): array of parameters\n",
" x (array[float]): single input vector\n",
" y (array[float]): single output state density matrix\n",
"\n",
" Returns:\n",
" float: fidelity between output state and input\n",
" \"\"\"\n",
" for p in params:\n",
" qml.Rot(*x, wires=0)\n",
" qml.Rot(*p, wires=0)\n",
" return qml.expval(qml.Hermitian(y, wires=[0]))\n",
"\n",
"\n",
"def cost(params, x, y, state_labels=None):\n",
" \"\"\"Cost function to be minimized.\n",
"\n",
" Args:\n",
" params (array[float]): array of parameters\n",
" x (array[float]): 2-d array of input vectors\n",
" y (array[float]): 1-d array of targets\n",
" state_labels (array[float]): array of state representations for labels\n",
"\n",
" Returns:\n",
" float: loss value to be minimized\n",
" \"\"\"\n",
" # Compute prediction for each input in data batch\n",
" loss = 0.0\n",
" dm_labels = [density_matrix(s) for s in state_labels]\n",
" for i in range(len(x)):\n",
" f = qcircuit(params, x[i], dm_labels[y[i]])\n",
" loss = loss + (1 - f) ** 2\n",
" return loss / len(x)"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "3Bz83H0xTnyx"
},
"source": [
"Utility functions for testing and creating batches\n",
"==================================================\n"
]
},
{
"cell_type": "code",
"execution_count": 52,
"metadata": {
"id": "i1-TLseuTnyx"
},
"outputs": [],
"source": [
"def test(params, x, y, state_labels=None):\n",
" \"\"\"\n",
" Tests on a given set of data.\n",
"\n",
" Args:\n",
" params (array[float]): array of parameters\n",
" x (array[float]): 2-d array of input vectors\n",
" y (array[float]): 1-d array of targets\n",
" state_labels (array[float]): 1-d array of state representations for labels\n",
"\n",
" Returns:\n",
" predicted (array([int]): predicted labels for test data\n",
" output_states (array[float]): output quantum states from the circuit\n",
" \"\"\"\n",
" fidelity_values = []\n",
" dm_labels = [density_matrix(s) for s in state_labels]\n",
" predicted = []\n",
"\n",
" for i in range(len(x)):\n",
" fidel_function = lambda y: qcircuit(params, x[i], y)\n",
" fidelities = [fidel_function(dm) for dm in dm_labels]\n",
" best_fidel = np.argmax(fidelities)\n",
"\n",
" predicted.append(best_fidel)\n",
" fidelity_values.append(fidelities)\n",
"\n",
" return np.array(predicted), np.array(fidelity_values)\n",
"\n",
"\n",
"def accuracy_score(y_true, y_pred):\n",
" \"\"\"Accuracy score.\n",
"\n",
" Args:\n",
" y_true (array[float]): 1-d array of targets\n",
" y_predicted (array[float]): 1-d array of predictions\n",
" state_labels (array[float]): 1-d array of state representations for labels\n",
"\n",
" Returns:\n",
" score (float): the fraction of correctly classified samples\n",
" \"\"\"\n",
" score = y_true == y_pred\n",
" return score.sum() / len(y_true)\n",
"\n",
"\n",
"def iterate_minibatches(inputs, targets, batch_size):\n",
" \"\"\"\n",
" A generator for batches of the input data\n",
"\n",
" Args:\n",
" inputs (array[float]): input data\n",
" targets (array[float]): targets\n",
"\n",
" Returns:\n",
" inputs (array[float]): one batch of input data of length `batch_size`\n",
" targets (array[float]): one batch of targets of length `batch_size`\n",
" \"\"\"\n",
" for start_idx in range(0, inputs.shape[0] - batch_size + 1, batch_size):\n",
" idxs = slice(start_idx, start_idx + batch_size)\n",
" yield inputs[idxs], targets[idxs]"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "B5s1nRL2Tnyy"
},
"source": [
"Train a quantum classifier on the circle dataset\n",
"================================================\n"
]
},
{
"cell_type": "code",
"execution_count": 53,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 0
},
"id": "NqJGMjbpTnyy",
"outputId": "c84d6bf7-1e45-4232-f122-3f16597dd269"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Epoch: 0 | Cost: 0.415535 | Train accuracy: 0.460000 | Test Accuracy: 0.448500\n",
"Epoch: 1 | Loss: 0.162864 | Train accuracy: 0.785000 | Test accuracy: 0.741000\n",
"Epoch: 2 | Loss: 0.156189 | Train accuracy: 0.760000 | Test accuracy: 0.778000\n",
"Epoch: 3 | Loss: 0.141870 | Train accuracy: 0.790000 | Test accuracy: 0.794500\n",
"Epoch: 4 | Loss: 0.139086 | Train accuracy: 0.790000 | Test accuracy: 0.774000\n",
"Epoch: 5 | Loss: 0.134667 | Train accuracy: 0.830000 | Test accuracy: 0.806500\n",
"Epoch: 6 | Loss: 0.109524 | Train accuracy: 0.865000 | Test accuracy: 0.825000\n",
"Epoch: 7 | Loss: 0.136898 | Train accuracy: 0.820000 | Test accuracy: 0.808500\n",
"Epoch: 8 | Loss: 0.147579 | Train accuracy: 0.755000 | Test accuracy: 0.747500\n",
"Epoch: 9 | Loss: 0.101547 | Train accuracy: 0.920000 | Test accuracy: 0.861500\n",
"Epoch: 10 | Loss: 0.109776 | Train accuracy: 0.890000 | Test accuracy: 0.865000\n"
]
}
],
"source": [
"# Generate training and test data\n",
"num_training = 200\n",
"num_test = 2000\n",
"\n",
"Xdata, y_train = circle(num_training)\n",
"X_train = np.hstack((Xdata, np.zeros((Xdata.shape[0], 1), requires_grad=False)))\n",
"\n",
"Xtest, y_test = circle(num_test)\n",
"X_test = np.hstack((Xtest, np.zeros((Xtest.shape[0], 1), requires_grad=False)))\n",
"\n",
"\n",
"# Train using Adam optimizer and evaluate the classifier\n",
"num_layers = 3\n",
"learning_rate = 0.6\n",
"epochs = 10\n",
"batch_size = 29\n",
"\n",
"opt = AdamOptimizer(learning_rate, beta1=0.9, beta2=0.999)\n",
"\n",
"# initialize random weights\n",
"params = np.random.uniform(size=(num_layers, 3), requires_grad=True)\n",
"\n",
"predicted_train, fidel_train = test(params, X_train, y_train, state_labels)\n",
"accuracy_train = accuracy_score(y_train, predicted_train)\n",
"\n",
"predicted_test, fidel_test = test(params, X_test, y_test, state_labels)\n",
"accuracy_test = accuracy_score(y_test, predicted_test)\n",
"\n",
"# save predictions with random weights for comparison\n",
"initial_predictions = predicted_test\n",
"\n",
"loss = cost(params, X_test, y_test, state_labels)\n",
"\n",
"print(\n",
" \"Epoch: {:2d} | Cost: {:3f} | Train accuracy: {:3f} | Test Accuracy: {:3f}\".format(\n",
" 0, loss, accuracy_train, accuracy_test\n",
" )\n",
")\n",
"\n",
"for it in range(epochs):\n",
" for Xbatch, ybatch in iterate_minibatches(X_train, y_train, batch_size=batch_size):\n",
" params, _, _, _ = opt.step(cost, params, Xbatch, ybatch, state_labels)\n",
"\n",
" predicted_train, fidel_train = test(params, X_train, y_train, state_labels)\n",
" accuracy_train = accuracy_score(y_train, predicted_train)\n",
" loss = cost(params, X_train, y_train, state_labels)\n",
"\n",
" predicted_test, fidel_test = test(params, X_test, y_test, state_labels)\n",
" accuracy_test = accuracy_score(y_test, predicted_test)\n",
" res = [it + 1, loss, accuracy_train, accuracy_test]\n",
" print(\n",
" \"Epoch: {:2d} | Loss: {:3f} | Train accuracy: {:3f} | Test accuracy: {:3f}\".format(\n",
" *res\n",
" )\n",
" )"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "YWspC-9BTnyy"
},
"source": [
"Results\n",
"=======\n"
]
},
{
"cell_type": "code",
"execution_count": 54,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 399
},
"id": "ZPszGYA3Tnyy",
"outputId": "1594d9f6-3995-40fb-830b-dd5ffcd5e890"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Cost: 0.109776 | Train accuracy 0.890000 | Test Accuracy : 0.865000\n",
"Learned weights\n",
"Layer 0: [ 0.42324588 1.92028565 -0.23067514]\n",
"Layer 1: [ 0.39551242 -0.17149491 0.58010746]\n",
"Layer 2: [-0.65227841 1.52176168 0.32099705]\n"
]
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 1000x300 with 3 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
}
],
"source": [
"print(\n",
" \"Cost: {:3f} | Train accuracy {:3f} | Test Accuracy : {:3f}\".format(\n",
" loss, accuracy_train, accuracy_test\n",
" )\n",
")\n",
"\n",
"print(\"Learned weights\")\n",
"for i in range(num_layers):\n",
" print(\"Layer {}: {}\".format(i, params[i]))\n",
"\n",
"\n",
"fig, axes = plt.subplots(1, 3, figsize=(10, 3))\n",
"plot_data(X_test, initial_predictions, fig, axes[0])\n",
"plot_data(X_test, predicted_test, fig, axes[1])\n",
"plot_data(X_test, y_test, fig, axes[2])\n",
"axes[0].set_title(\"Predictions with random weights\")\n",
"axes[1].set_title(\"Predictions after training\")\n",
"axes[2].set_title(\"True test data\")\n",
"plt.tight_layout()\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "sYQWz6IdTnyy"
},
"source": [
"References\n",
"==========\n",
"\n",
"\\[1\\] Pérez-Salinas, Adrián, et al. \\\"Data re-uploading for a universal\n",
"quantum classifier.\\\" arXiv preprint arXiv:1907.02085 (2019).\n",
"\n",
"\\[2\\] Kingma, Diederik P., and Ba, J. \\\"Adam: A method for stochastic\n",
"optimization.\\\" arXiv preprint arXiv:1412.6980 (2014).\n",
"\n",
"\\[3\\] Liu, Dong C., and Nocedal, J. \\\"On the limited memory BFGS method\n",
"for large scale optimization.\\\" Mathematical programming 45.1-3 (1989):\n",
"503-528.\n",
"\n",
"About the author\n",
"================\n"
]
},
{
"cell_type": "code",
"source": [
"seconds = time.time()\n",
"print(\"Time in seconds since end of run:\", seconds)\n",
"local_time = time.ctime(seconds)\n",
"print(local_time)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 0
},
"id": "8FGVwF_QUYza",
"outputId": "c9045120-1cda-425a-bca6-2086010ef565"
},
"execution_count": 55,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Time in seconds since end of run: 1696870625.844115\n",
"Mon Oct 9 16:57:05 2023\n"
]
}
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"name": "python3"
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"name": "ipython",
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"name": "python",
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