520 lines (520 with data), 195.5 kB
{
"cells": [
{
"cell_type": "code",
"execution_count": 103,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 0
},
"id": "eI_d8C3_Tnyu",
"outputId": "c56556bc-ce04-4dce-8b24-f98bf21610c8"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Time in seconds since beginning of run: 1696828991.8390205\n",
"Mon Oct 9 05:23:11 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": 104,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 388
},
"id": "lScQSFsjTnyw",
"outputId": "f3d03b75-d40b-459f-a578-5c29e8b940d4"
},
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 400x400 with 1 Axes>"
],
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAZIAAAFzCAYAAAAUmo/dAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAAA9hAAAPYQGoP6dpAABotklEQVR4nO29f3gU1b0//s5EsmAhuxDSRFCoyA+tWuIKQfrZZDWAobFFe1ut4MWoLbReqfVaqdinyCdefaDCt7VFLJIHgRYvrPaKeC0QKgUVhRABRQGzEKhGBPyYlIAKKOH9/WN3NrO78+PMzDlnzizn9Tz7QGZnZ86cOef9ev8675OHiAgSEhISEhIOoXjdAAkJCQkJf0MSiYSEhISEK0gikZCQkJBwBUkkEhISEhKuIIlEQkJCQsIVJJFISEhISLiCJBIJCQkJCVc4z+sG5ALOnj0LH3/8MfTq1Qvy8vK8bo6EhISEayAinDhxAvr16weKYm5zSCKhgI8//hguuugir5shISEhQR2tra1w4YUXmp4jiYQCevXqBQCJDi8sLPS4NRISEhLucfz4cbjoootS8s0MkkgoQHVnFRYWSiKRkJDIKZC462WwXUJCQkLCFSSRSEhISEi4giQSCQkJCQlXkEQiISEhIeEKkkgkJCQkJFxBEomEhISEhCtIIpGQkJCQcAVfEclrr70G3/ve96Bfv36Ql5cHL774ouVvNm3aBOFwGAKBAAwePBiWLl2adc6CBQvgG9/4BnTv3h1GjRoF27Zto994CQkJXyAej8PatWth3759XjfFN/AVkXz++ecwfPhwWLBgAdH5Bw8ehBtuuAGuu+46ePvtt+G+++6Dn/zkJ9DQ0JA6JxaLwf333w+zZs2CHTt2wPDhw6G6uho++eQTVo/BBXIySEjYQ3t7O9wwfjwMGzYMampqYOjQoXDD+PHwr3/9y+umiQ/0KQAAV61aZXrOr371K7z88svTjv3oRz/C6urq1N/l5eV4zz33pP7u7OzEfv364ezZs4nb0tHRgQCAHR0dxL9hhba2NqyprkYASH1qqquxvb3d66ZJcEBzczOuWbMG4/G4103xHWqqq7FPfj4uB8APAXA5APbJz8cajbw4l2BHrvnKIrGLLVu2wNixY9OOVVdXw5YtWwAA4Msvv4Tt27ennaMoCowdOzZ1jh5Onz4Nx48fT/t4hUzLY/KkSbD1lVdgOQB8CADLAWDrK6/Av0+c6FkbJdiDlzadq5ZuPB6HNQ0N8MfOTrgNAC4CgNsA4A+dnbCmoSHnnpc2cppIjhw5AiUlJWnHSkpK4Pjx43Dy5En49NNPobOzU/ecI0eOGF539uzZEAwGUx8vKv/qCY7yESPkZHABPwtJ1gpErrt9WlpaAACgMuN4NPnv/v37ubbHCbwcvzlNJKzw0EMPQUdHR+rT2trKvQ16gmP39u0A4O/J4AVoCEkvJzEPbTrXLd1LLrkEAABeyzj+avLfwYMHc22PHYhA8jlNJKWlpXD06NG0Y0ePHoXCwkLo0aMH9O3bF/Lz83XPKS0tNbxuIBBIVfr1ouKvkeD4v8nv/TgZvIQbIel2EtMgINba9Lng9hk6dCjUVFfDvfn5sBwAWiExDn6Rnw811dUwZMgQj1toDCFInkPMhgmAMNh+xRVXpB2bOHFiVrB92rRpqb87Ozuxf//+Qgfb16xZg5AMCKLm8yEAKgAYAsC/JP/+CwD2Th6XAdhsNDc3IyQDq9q+/EsyUcGqz5wGaGkmRbh9BiuYjTcAwDVr1ri6vh2wTCZob2/3XaIKy3dvR675ikhOnDiBO3fuxJ07dyIA4O9+9zvcuXMnfvDBB4iIOGPGDJw8eXLq/AMHDuD555+P06dPx7179+KCBQswPz8f161blzpn5cqVGAgEcOnSpbhnzx6cOnUqhkIhPHLkCHG7eBOJ1eC5RjMRAACrPJjwfoEbIelmEtPOEFKvp1UgaGUcsSYqEvDMRozH477JfGNJ8jlLJBs3bkwbSOqntrYWERFra2sxGo1m/aasrAwLCgpw0KBBuGTJkqzrzp8/HwcMGIAFBQVYXl6OW7dutdUut0Si1bJINS5dwZG0PJYDYBwA1yT/5Tnh/QYrIRmNRAyFldNJzEIws9amWRKVnfvL1Nx0SIskh+CUSPS0LIVQEOgJjjIArICEK8urCe9HGJFymUXfWU3ihoYGXaWApRbJSpv20u0jgkUk8vocViQviYQznBKJnpbVGxKuqekAGFQUy8EQj8cxFothNBLRJSPWE97JBBNtUra3t6f1HwBgDQC2Ewgro0lcUlRk+A5EEIxO4YXbx8sYjR8W+LIieUkknOGESKyEiZYUmpqaiK6pneSsJ7yTCSbypFSF1TJIuANJhZXeJC4pKsKQopi6Ybx2FfkJXhKvn1xqtOe8JBLOcEIkVlrWsuSgDQLgyHCYYeudwckEE3lSuhVW6iRuaGgguo4fM4S8hBfEK4rl6JUFL4mEM1hYJHGPBi0JnEwwryalnUloJKxGhsPE7bPrhvFThpCX8IJ47b5L2gLfawteEglnuI2RZAZ5a2y4VrzQVpz4rFn6ufX6wMkk1BNWpMkP2rY4IVlJJmTgQbzq+yC1LlkJfK8teEkknOGUSIwyr9oJBJCX2oooFolZH7iZhPF4HEeEwxi0iHMYgdQN47XGeS7ADknrvY+SoiLLdzn2uuswoPkNAGAAAMdVVblqt9duNUkknOF2HYmqZUUjEWI/MA1txY0m7MRnTdvPbdQHagaW00nodhKTumG81jhzGU5IWu99hBTFMgNPgUS2ZWb2pZtqEiJUE5BEwhm0VraTCiC3go6GJuzEZ03Tz02S9eZ0EtKaxGZuGBE0Tp7g7b6zS9JW72P9+vW67V+0aJHp7+rr6x21X4TxIYmEM2iXSLHyA7sVdDQ1YSc+axp+bqs+8NIiodH+XCln44X7zsn7c/o+VCIx+p1TIkH0PkVcEgln0CASOxqbG0EngqZDAySlTawmoTaomtn3rCdxrrwHK3jhvnNCCk7fB8v36HWKuCQSznBDJE41NqeCzuuURpow6wOzSajtc6MqADwmsdcaJ2t4mfLt5L5O38e4qioM5eWl/S6Ul+cq2K4+x5o1awzdaqwhiYQz3BCJU43NqaAjnWR+yCgi6QM9N5ra52WQSLc263uW6aZea5wkcKNIOLUMaPS3E1Jw+j5ov0dR5p4kEs5wSiQ0NDYngi5zkj0OgD0VBaORSNY5fsgostMHap/PBXdxFJpgQVZuBTINYWZnfNMWnm6Eu9P3of0djYxIr+eeJBLOcEokmRpbMyRKv79qorHRgHaS6bl2tm3bRiwARHZ96UFbUysXg920BDItYUZqGbASnrwrB7jtf5FiZ5JIOMOtRbIQEqvZtYPPTrFGp4hWVGBvnUV3I8NhSyErivltFyJaJDRBa30Rrb4hsQxEEp5uEY1EdOcUaf+LlM0niYQz3MZIApC9oCmUl4fRSISZNkWyDsNsYotifjtBZowkV4LdtAQyC2FmZhmIJDydoq2tDStdLoRFFItUJZFwhhsisXIjsdL2rSbviHDY0CVhNdhZW1JuYeXao9HPfqmBpgfewkwk4ekUNdXV2FNRqPQ/qTuQ9RiTRMIZboiEtJw8DU05c0tfs8n7xBNPZG/2lBSyJCTkB6haMs30Sr/VQNO7ht1yPTTg51Ro2u5SK3cgrzEmiYQz3BAJ63Lyzc3NiR0UKyqyBt64qqq0yfsngKzic9GKCozFYqn7Njc3W5aFsBOQp6FViRTw99rl51QgGxUs5EWIdsoDsXT3Orm2VrGqgWx3aW+CnU71YOQO5DXGJJFwhtuV7bqTH+yVk89E5qK7IGSvlxhXVZU2eRVIxGb0BmimoFGvmdnmKk07zTQnGloV6TV4EY1WM11DQQlwAqdpr0bCKVpRwZWkM4Wn+u62bdvGTAunmWnVDtmJM9GKClfttONJoPmeJJFwhlsiISkn/3jy+Pr164muqQoGK3O7oaEB6+vr8b/+679Mz1NdHcuTZNELdOILkMhAUwe0meZEQ6uyugZvN1MsFtPtk102lQAacLK2RqQYhd67CwDg0y7GixFojkVVsZoL2Wuz7EKvD6745jcRILFEQPuuWCQmSCLhDFpFG/XKye9KkoodYagVDGtAf73ELh0iMIt7qNdr1vy/BhJWyQPJgW0nIE/Dl291Dd5upmgkkm35ad6fXk0vESBi1pTeu+sN6VY6DaKjRaIsqhRo+0BXDkCXsiktkhwA7eq/mVlFWcLJQhhqBYNW8GsnSlnGda0sF/V6WmLSM+NHhsNEAXm3gsvq+lZxHN6ZR71D6fGG6uoaYdbciGaRkMYNaRAdbRKltQAysw/U2EsmsVYBu8QESSScQZtIVJBu9ZkJo0GoLYliRi6ZgVrtRlF6xBSHhFWibZPXFkl9fT1XLdtcICmoKL0RYDkCfIgAyzE/vw9WV9dQbYMbiJQ1ZSncKRKdaCSqgkQZ1M4lmbWVA2BFJG60Ja1g0DOLSd1d6gDVXq8KEtoQadkLvfNoCC6za7gpC+5EozS63+OpvlyO6V/9xVNBlQk3RUBZ1Akze3eZblS37RKJRBGzMyON3NOqHHCz54kZcp5InnzySRw4cCAGAgEsLy/HxsZGw3Oj0WiWAAUArKnp0gZra2uzvq+2MYhoEUnm4HejLekJhmgkgrFYzNLS0VtXkXk9koV8ZsKJhk/Z6hp2BASNwLze/dRFaglLRNvdHzKxjNyC1DXT1taG1dU1af0VDo+kthhVry9DeXlp407v/Th5j6JUYTZKMKgD9xa8E+Q0kaxcuRILCgrwmWeewd27d+OUKVMwFArh0aNHdc9va2vDw4cPpz7vvfce5ufn45IlS1Ln1NbW4vjx49POszOI3BKJ2eB3qy1Z5aLbva72eqRCx+w8Nz5lq/0a7AgIGoF5vftVphZ1im2R2EV1dQ3m5/dBrbsOIIgACpX4j9G7a2pqMh0vbt4j7wKPmdBru0qeuun2jK2mnCaS8vJyvOeee1J/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": 105,
"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": 106,
"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": 107,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 0
},
"id": "NqJGMjbpTnyy",
"outputId": "dff7bf79-d8f0-4b14-c106-4ba9a2d64286"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Epoch: 0 | Cost: 0.415535 | Train accuracy: 0.460000 | Test Accuracy: 0.448500\n",
"Epoch: 1 | Loss: 0.125657 | Train accuracy: 0.830000 | Test accuracy: 0.793000\n",
"Epoch: 2 | Loss: 0.142989 | Train accuracy: 0.820000 | Test accuracy: 0.796000\n",
"Epoch: 3 | Loss: 0.139200 | Train accuracy: 0.810000 | Test accuracy: 0.805000\n",
"Epoch: 4 | Loss: 0.122949 | Train accuracy: 0.830000 | Test accuracy: 0.817000\n",
"Epoch: 5 | Loss: 0.127595 | Train accuracy: 0.830000 | Test accuracy: 0.801500\n",
"Epoch: 6 | Loss: 0.119071 | Train accuracy: 0.840000 | Test accuracy: 0.815500\n",
"Epoch: 7 | Loss: 0.108056 | Train accuracy: 0.845000 | Test accuracy: 0.815000\n",
"Epoch: 8 | Loss: 0.107607 | Train accuracy: 0.885000 | Test accuracy: 0.857500\n",
"Epoch: 9 | Loss: 0.140646 | Train accuracy: 0.770000 | Test accuracy: 0.769500\n",
"Epoch: 10 | Loss: 0.099717 | Train accuracy: 0.925000 | Test accuracy: 0.884500\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 = 0.56\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": 108,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 399
},
"id": "ZPszGYA3Tnyy",
"outputId": "f7e5da56-9a6a-40bc-de0b-932ec8546478"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Cost: 0.099717 | Train accuracy 0.925000 | Test Accuracy : 0.884500\n",
"Learned weights\n",
"Layer 0: [-0.73444648 1.44692601 -0.1343184 ]\n",
"Layer 1: [0.80982997 0.47242158 0.29914995]\n",
"Layer 2: [ 2.25988775 -1.2766224 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": "10754378-8e0c-4b7c-fe7c-4da117eefdea"
},
"execution_count": 109,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Time in seconds since end of run: 1696829264.3950837\n",
"Mon Oct 9 05:27:44 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": []
}
},
"nbformat": 4,
"nbformat_minor": 0
}