520 lines (520 with data), 195.2 kB
{
"cells": [
{
"cell_type": "code",
"execution_count": 96,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 0
},
"id": "eI_d8C3_Tnyu",
"outputId": "f3cee370-eb3f-4985-978c-42d0d1130ea8"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Time in seconds since beginning of run: 1696827990.4356117\n",
"Mon Oct 9 05:06:30 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": 97,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 388
},
"id": "lScQSFsjTnyw",
"outputId": "549b556c-97d8-4ecb-c27f-5c639e6f86a1"
},
"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": 98,
"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": 99,
"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": 100,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 0
},
"id": "NqJGMjbpTnyy",
"outputId": "c5d0699f-c8f8-46a7-80f6-2344cc82e90b"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Epoch: 0 | Cost: 0.415535 | Train accuracy: 0.460000 | Test Accuracy: 0.448500\n",
"Epoch: 1 | Loss: 0.125422 | Train accuracy: 0.840000 | Test accuracy: 0.799000\n",
"Epoch: 2 | Loss: 0.148778 | Train accuracy: 0.815000 | Test accuracy: 0.786000\n",
"Epoch: 3 | Loss: 0.143812 | Train accuracy: 0.800000 | Test accuracy: 0.803000\n",
"Epoch: 4 | Loss: 0.123422 | Train accuracy: 0.820000 | Test accuracy: 0.801500\n",
"Epoch: 5 | Loss: 0.125812 | Train accuracy: 0.835000 | Test accuracy: 0.802000\n",
"Epoch: 6 | Loss: 0.123587 | Train accuracy: 0.840000 | Test accuracy: 0.812000\n",
"Epoch: 7 | Loss: 0.110697 | Train accuracy: 0.840000 | Test accuracy: 0.807000\n",
"Epoch: 8 | Loss: 0.107375 | Train accuracy: 0.905000 | Test accuracy: 0.862000\n",
"Epoch: 9 | Loss: 0.147697 | Train accuracy: 0.755000 | Test accuracy: 0.747000\n",
"Epoch: 10 | Loss: 0.098848 | Train accuracy: 0.925000 | Test accuracy: 0.869500\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 = 0.58\n",
"epochs = 10\n",
"batch_size = 32\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": 101,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 399
},
"id": "ZPszGYA3Tnyy",
"outputId": "e23f07e2-54ad-4a84-a2f7-ca60b3f01d1e"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Cost: 0.098848 | Train accuracy 0.925000 | Test Accuracy : 0.869500\n",
"Learned weights\n",
"Layer 0: [-0.53271344 1.32390017 -0.16621573]\n",
"Layer 1: [0.73986171 0.58321863 0.39605986]\n",
"Layer 2: [ 2.29006351 -1.23394101 0.32099704]\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": "3e1e0fe0-01d7-4a92-d04d-c88bc35deaa8"
},
"execution_count": 102,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Time in seconds since end of run: 1696828271.430586\n",
"Mon Oct 9 05:11:11 2023\n"
]
}
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.18"
},
"colab": {
"provenance": []
}
},
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"nbformat_minor": 0
}