{"id":3217,"date":"2022-03-24T12:49:19","date_gmt":"2022-03-24T03:49:19","guid":{"rendered":"https:\/\/qard.is.tohoku.ac.jp\/T-Wave\/?p=3217"},"modified":"2022-03-24T12:49:19","modified_gmt":"2022-03-24T03:49:19","slug":"%e9%87%8f%e5%ad%90%e3%82%a2%e3%83%8b%e3%83%bc%e3%83%aa%e3%83%b3%e3%82%b0%e3%82%92%e7%94%a8%e3%81%84%e3%81%9f%e3%82%b0%e3%83%a9%e3%83%95%e5%bd%a9%e8%89%b2%e5%ae%9f%e8%b7%b5%e7%b7%a8","status":"publish","type":"post","link":"https:\/\/qard.is.tohoku.ac.jp\/T-Wave\/2022\/03\/24\/%e9%87%8f%e5%ad%90%e3%82%a2%e3%83%8b%e3%83%bc%e3%83%aa%e3%83%b3%e3%82%b0%e3%82%92%e7%94%a8%e3%81%84%e3%81%9f%e3%82%b0%e3%83%a9%e3%83%95%e5%bd%a9%e8%89%b2%e5%ae%9f%e8%b7%b5%e7%b7%a8\/","title":{"rendered":"\u91cf\u5b50\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u3092\u7528\u3044\u305f\u30b0\u30e9\u30d5\u5f69\u8272(\u5b9f\u8df5\u7de8)"},"content":{"rendered":"<p><a href=\"https:\/\/colab.research.google.com\/github\/T-QARD\/t-wave\/blob\/main\/notebooks\/graph_coloring\/graph_coloring.ipynb\" target=\"_blank\" rel=\"noopener noreferrer\"><img decoding=\"async\" src=\"https:\/\/colab.research.google.com\/assets\/colab-badge.svg\" alt=\"Open in Colab\" \/><\/a><\/p>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\"><\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">\n<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_82_2 counter-hierarchy ez-toc-counter ez-toc-white ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\">\n<p class=\"ez-toc-title ez-toc-toggle\" style=\"cursor:pointer\">Table of Contents<\/p>\n<span class=\"ez-toc-title-toggle\"><a href=\"#\" class=\"ez-toc-pull-right ez-toc-btn ez-toc-btn-xs ez-toc-btn-default ez-toc-toggle\" aria-label=\"Toggle Table of Content\"><span class=\"ez-toc-js-icon-con\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #999;color:#999\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewBox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #999;color:#999\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewBox=\"0 0 24 24\" version=\"1.2\" baseProfile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/span><\/a><\/span><\/div>\n<nav><ul class='ez-toc-list ez-toc-list-level-1 ' ><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/qard.is.tohoku.ac.jp\/T-Wave\/2022\/03\/24\/%e9%87%8f%e5%ad%90%e3%82%a2%e3%83%8b%e3%83%bc%e3%83%aa%e3%83%b3%e3%82%b0%e3%82%92%e7%94%a8%e3%81%84%e3%81%9f%e3%82%b0%e3%83%a9%e3%83%95%e5%bd%a9%e8%89%b2%e5%ae%9f%e8%b7%b5%e7%b7%a8\/#%E6%A6%82%E8%A6%81\" >\u6982\u8981<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/qard.is.tohoku.ac.jp\/T-Wave\/2022\/03\/24\/%e9%87%8f%e5%ad%90%e3%82%a2%e3%83%8b%e3%83%bc%e3%83%aa%e3%83%b3%e3%82%b0%e3%82%92%e7%94%a8%e3%81%84%e3%81%9f%e3%82%b0%e3%83%a9%e3%83%95%e5%bd%a9%e8%89%b2%e5%ae%9f%e8%b7%b5%e7%b7%a8\/#%E6%96%87%E7%8C%AE%E6%83%85%E5%A0%B1\" >\u6587\u732e\u60c5\u5831<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/qard.is.tohoku.ac.jp\/T-Wave\/2022\/03\/24\/%e9%87%8f%e5%ad%90%e3%82%a2%e3%83%8b%e3%83%bc%e3%83%aa%e3%83%b3%e3%82%b0%e3%82%92%e7%94%a8%e3%81%84%e3%81%9f%e3%82%b0%e3%83%a9%e3%83%95%e5%bd%a9%e8%89%b2%e5%ae%9f%e8%b7%b5%e7%b7%a8\/#%E5%95%8F%E9%A1%8C\" >\u554f\u984c<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/qard.is.tohoku.ac.jp\/T-Wave\/2022\/03\/24\/%e9%87%8f%e5%ad%90%e3%82%a2%e3%83%8b%e3%83%bc%e3%83%aa%e3%83%b3%e3%82%b0%e3%82%92%e7%94%a8%e3%81%84%e3%81%9f%e3%82%b0%e3%83%a9%e3%83%95%e5%bd%a9%e8%89%b2%e5%ae%9f%e8%b7%b5%e7%b7%a8\/#%E5%AE%9F%E9%A8%93\" >\u5b9f\u9a13<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/qard.is.tohoku.ac.jp\/T-Wave\/2022\/03\/24\/%e9%87%8f%e5%ad%90%e3%82%a2%e3%83%8b%e3%83%bc%e3%83%aa%e3%83%b3%e3%82%b0%e3%82%92%e7%94%a8%e3%81%84%e3%81%9f%e3%82%b0%e3%83%a9%e3%83%95%e5%bd%a9%e8%89%b2%e5%ae%9f%e8%b7%b5%e7%b7%a8\/#%E7%B5%90%E8%AB%96\" >\u7d50\u8ad6<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/qard.is.tohoku.ac.jp\/T-Wave\/2022\/03\/24\/%e9%87%8f%e5%ad%90%e3%82%a2%e3%83%8b%e3%83%bc%e3%83%aa%e3%83%b3%e3%82%b0%e3%82%92%e7%94%a8%e3%81%84%e3%81%9f%e3%82%b0%e3%83%a9%e3%83%95%e5%bd%a9%e8%89%b2%e5%ae%9f%e8%b7%b5%e7%b7%a8\/#%E3%81%82%E3%81%A8%E3%81%8C%E3%81%8D\" >\u3042\u3068\u304c\u304d<\/a><\/li><\/ul><\/nav><\/div>\n<h2 id=\"\u6982\u8981\"><span class=\"ez-toc-section\" id=\"%E6%A6%82%E8%A6%81\"><\/span>\u6982\u8981<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">\n<p>\u8a18\u4e8b<a href=\"\/T-Wave\/?p=2510\">\u300c\u91cf\u5b50\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u3092\u7528\u3044\u305f\u30b0\u30e9\u30d5\u5f69\u8272\u300d<\/a>\u3067\u306f\u8caa\u6b32\u6cd5\u3067\u30b0\u30e9\u30d5\u5f69\u8272\u3092\u884c\u3046\u3068\u304d\u306b\u72ec\u7acb\u70b9\u96c6\u5408\u3092\u91cf\u5b50\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u3067\u6c42\u3081\u305f\u3068\u304d\u3068\u53e4\u5178\u30b3\u30f3\u30d4\u30e5\u30fc\u30bf\u3067\u6c42\u3081\u305f\u3068\u304d\u3068\u3067\u6700\u9069\u5316\u6027\u80fd\u306e\u6bd4\u8f03\u3092\u884c\u3063\u305f\u8ad6\u6587\u3092\u7d39\u4ecb\u3057\u307e\u3057\u305f\u3002\u672c\u8a18\u4e8b\u3067\u306f\u3053\u306e\u624b\u6cd5\u3092\u7528\u3044\u3066\u5b9f\u969b\u306b\u30b0\u30e9\u30d5\u5f69\u8272\u3092\u884c\u3044\u307e\u3059\u3002\u307e\u305f\u8ad6\u6587\u3067\u306f\u9802\u70b9\u6570\u304c20\u300140\u300160\u306e\u3068\u304d\u3067\u5b9f\u9a13\u3092\u884c\u3044\u3001\u3053\u308c\u3088\u308a\u9802\u70b9\u6570\u304c\u591a\u3044\u30b0\u30e9\u30d5\u306b\u3064\u3044\u3066\u306f\u91cf\u5b50\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u306e\u512a\u4f4d\u6027\u306f\u4e0d\u660e\u3067\u3057\u305f\u3002\u672c\u8a18\u4e8b\u3067\u306f\u9802\u70b9\u6570\u309280\u3001100\u3068\u3057\u305f\u3068\u304d\u3067\u3082\u6027\u80fd\u6bd4\u8f03\u3092\u884c\u3044\u307e\u3059\u3002<\/p>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">\n<h2 id=\"\u6587\u732e\u60c5\u5831\"><span class=\"ez-toc-section\" id=\"%E6%96%87%E7%8C%AE%E6%83%85%E5%A0%B1\"><\/span>\u6587\u732e\u60c5\u5831<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">\n<ul>\n<li>\u30bf\u30a4\u30c8\u30eb\uff1aGraph Coloring with Quantum Annealing<\/li>\n<li>\u8457\u8005\uff1aJulia Kwok, Kristen Pudenz<\/li>\n<li>\u66f8\u8a8c\u60c5\u5831\uff1a<a href=\"https:\/\/arxiv.org\/abs\/2012.04470\">https:\/\/arxiv.org\/abs\/2012.04470<\/a><\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">\n<h2 id=\"\u554f\u984c\"><span class=\"ez-toc-section\" id=\"%E5%95%8F%E9%A1%8C\"><\/span>\u554f\u984c<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">\n<p>\u30b0\u30e9\u30d5\u5f69\u8272\u306b\u304a\u3051\u308b\u8caa\u6b32\u6cd5\u306f\u72ec\u7acb\u70b9\u96c6\u5408\u306b1\u8272\u305a\u3064\u5272\u308a\u5f53\u3066\u308b\u3053\u3068\u3092\u7e70\u308a\u8fd4\u3057\u3066\u30b0\u30e9\u30d5\u5f69\u8272\u3092\u884c\u3044\u307e\u3059\u3002\u8a73\u7d30\u306f<a href=\"\/T-Wave\/?p=2510\">\u300c\u91cf\u5b50\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u3092\u7528\u3044\u305f\u30b0\u30e9\u30d5\u5f69\u8272\u300d<\/a>\u3092\u53c2\u7167\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/p>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">\n<h2 id=\"\u5b9f\u9a13\"><span class=\"ez-toc-section\" id=\"%E5%AE%9F%E9%A8%93\"><\/span>\u5b9f\u9a13<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">\n<p>\u307e\u305a\u306f\u5fc5\u8981\u306a\u30e9\u30a4\u30d6\u30e9\u30ea\u3092\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3057\u307e\u3059\u3002<\/p>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing code_cell rendered\">\n<div class=\"input\">\n<div class=\"inner_cell\">\n<div class=\"input_area\">\n<div class=\" highlight hl-python\">\n<pre><span class=\"err\">!<\/span><span class=\"n\">pip<\/span> <span class=\"n\">install<\/span> <span class=\"n\">dwave<\/span><span class=\"o\">-<\/span><span class=\"n\">ocean<\/span><span class=\"o\">-<\/span><span class=\"n\">sdk<\/span>\n<span class=\"err\">!<\/span><span class=\"n\">pip<\/span> <span class=\"n\">install<\/span> <span class=\"n\">openjij<\/span>\n<span class=\"err\">!<\/span><span class=\"n\">pip<\/span> <span class=\"n\">install<\/span> <span class=\"n\">numpy<\/span>\n<span class=\"err\">!<\/span><span class=\"n\">pip<\/span> <span class=\"n\">install<\/span> <span class=\"n\">matplotlib<\/span>\n<span class=\"err\">!<\/span><span class=\"n\">pip<\/span> <span class=\"n\">install<\/span> <span class=\"n\">networkx<\/span>\n<\/pre>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing code_cell rendered\">\n<div class=\"input\">\n<div class=\"inner_cell\">\n<div class=\"input_area\">\n<div class=\" highlight hl-python\">\n<pre><span class=\"kn\">import<\/span> <span class=\"nn\">numpy<\/span> <span class=\"k\">as<\/span> <span class=\"nn\">np<\/span>\n<span class=\"kn\">import<\/span> <span class=\"nn\">matplotlib.pyplot<\/span> <span class=\"k\">as<\/span> <span class=\"nn\">plt<\/span>\n<span class=\"kn\">import<\/span> <span class=\"nn\">networkx<\/span> <span class=\"k\">as<\/span> <span class=\"nn\">nx<\/span>\n<span class=\"kn\">import<\/span> <span class=\"nn\">random<\/span>\n<span class=\"kn\">from<\/span> <span class=\"nn\">itertools<\/span> <span class=\"kn\">import<\/span> <span class=\"n\">product<\/span><span class=\"p\">,<\/span> <span class=\"n\">combinations<\/span>\n<span class=\"kn\">from<\/span> <span class=\"nn\">networkx.algorithms.approximation<\/span> <span class=\"kn\">import<\/span> <span class=\"n\">clique<\/span>\n\n<span class=\"c1\"># D-wave\u30de\u30b7\u30f3\u306e\u5834\u5408<\/span>\n<span class=\"kn\">from<\/span> <span class=\"nn\">dwave.system<\/span> <span class=\"kn\">import<\/span> <span class=\"n\">DWaveSampler<\/span><span class=\"p\">,<\/span> <span class=\"n\">EmbeddingComposite<\/span>\n\n<span class=\"c1\"># SA\u306e\u5834\u5408<\/span>\n<span class=\"kn\">from<\/span> <span class=\"nn\">openjij<\/span> <span class=\"kn\">import<\/span> <span class=\"n\">SASampler<\/span>\n<\/pre>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">\n<p>\u53e4\u5178\u30b3\u30f3\u30d4\u30e5\u30fc\u30bf\u3067\u72ec\u7acb\u70b9\u96c6\u5408\u3092\u6c42\u3081\u307e\u3059\u3002\u5177\u4f53\u7684\u306b\u306fSampleIS\u3068\u3044\u3046\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u306b\u3088\u3063\u3066\u6700\u5927\u72ec\u7acb\u70b9\u96c6\u5408\u3092\u6c42\u3081\u307e\u3059\u3002SampleIS\u306b\u3064\u3044\u3066\u306f<a href=\"\/T-Wave\/?p=2827\">\u300c\u6700\u5927\u72ec\u7acb\u70b9\u96c6\u5408\u554f\u984c\u306b\u304a\u3051\u308b\u8caa\u6b32\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u306e\u7d39\u4ecb\u300d<\/a>\u3092\u53c2\u7167\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/p>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing code_cell rendered\">\n<div class=\"input\">\n<div class=\"inner_cell\">\n<div class=\"input_area\">\n<div class=\" highlight hl-python\">\n<pre><span class=\"k\">def<\/span> <span class=\"nf\">independent_set_classical<\/span><span class=\"p\">(<\/span><span class=\"n\">g<\/span><span class=\"p\">,<\/span> <span class=\"n\">k<\/span><span class=\"p\">):<\/span>\n    <span class=\"c1\"># \u9802\u70b9\u6570\u304c1\u4ee5\u4e0b\u306e\u6642\u306f\u30b0\u30e9\u30d5\u306e\u9802\u70b9\u3092\u8fd4\u3059<\/span>\n    <span class=\"k\">if<\/span> <span class=\"n\">g<\/span><span class=\"o\">.<\/span><span class=\"n\">number_of_nodes<\/span><span class=\"p\">()<\/span> <span class=\"o\">&lt;=<\/span> <span class=\"mi\">1<\/span><span class=\"p\">:<\/span>\n        <span class=\"k\">return<\/span> <span class=\"nb\">set<\/span><span class=\"p\">(<\/span><span class=\"n\">g<\/span><span class=\"o\">.<\/span><span class=\"n\">nodes<\/span><span class=\"p\">())<\/span>\n\n    <span class=\"c1\"># n:\u30b0\u30e9\u30d5\u306e\u9802\u70b9\u6570<\/span>\n    <span class=\"n\">n<\/span> <span class=\"o\">=<\/span> <span class=\"n\">g<\/span><span class=\"o\">.<\/span><span class=\"n\">number_of_nodes<\/span><span class=\"p\">()<\/span>\n\n    <span class=\"k\">while<\/span> <span class=\"kc\">True<\/span><span class=\"p\">:<\/span>\n        <span class=\"c1\"># log_{k}^{n}\u500b\u9802\u70b9\u3092\u30e9\u30f3\u30c0\u30e0\u306b\u9078\u3076(i)<\/span>\n        <span class=\"n\">i<\/span> <span class=\"o\">=<\/span> <span class=\"nb\">set<\/span><span class=\"p\">(<\/span>\n            <span class=\"n\">random<\/span><span class=\"o\">.<\/span><span class=\"n\">sample<\/span><span class=\"p\">(<\/span>\n                <span class=\"nb\">list<\/span><span class=\"p\">(<\/span><span class=\"n\">g<\/span><span class=\"o\">.<\/span><span class=\"n\">nodes<\/span><span class=\"p\">()),<\/span> <span class=\"n\">np<\/span><span class=\"o\">.<\/span><span class=\"n\">floor<\/span><span class=\"p\">(<\/span><span class=\"nb\">max<\/span><span class=\"p\">(<\/span><span class=\"mi\">1<\/span><span class=\"p\">,<\/span> <span class=\"n\">np<\/span><span class=\"o\">.<\/span><span class=\"n\">log<\/span><span class=\"p\">(<\/span><span class=\"n\">n<\/span><span class=\"p\">)<\/span> <span class=\"o\">\/<\/span> <span class=\"n\">np<\/span><span class=\"o\">.<\/span><span class=\"n\">log<\/span><span class=\"p\">(<\/span><span class=\"n\">k<\/span><span class=\"p\">)))<\/span><span class=\"o\">.<\/span><span class=\"n\">astype<\/span><span class=\"p\">(<\/span><span class=\"nb\">int<\/span><span class=\"p\">)<\/span>\n            <span class=\"p\">)<\/span>\n        <span class=\"p\">)<\/span>\n\n        <span class=\"c1\"># I\u304c\u72ec\u7acb\u70b9\u96c6\u5408\u304b\u3069\u3046\u304b\u5224\u5b9a<\/span>\n        <span class=\"n\">is_independent<\/span> <span class=\"o\">=<\/span> <span class=\"kc\">True<\/span>\n        <span class=\"k\">for<\/span> <span class=\"n\">u<\/span><span class=\"p\">,<\/span> <span class=\"n\">v<\/span> <span class=\"ow\">in<\/span> <span class=\"n\">product<\/span><span class=\"p\">(<\/span><span class=\"n\">i<\/span><span class=\"p\">,<\/span> <span class=\"n\">i<\/span><span class=\"p\">):<\/span>\n            <span class=\"k\">if<\/span> <span class=\"p\">(<\/span><span class=\"n\">u<\/span><span class=\"p\">,<\/span> <span class=\"n\">v<\/span><span class=\"p\">)<\/span> <span class=\"ow\">in<\/span> <span class=\"nb\">list<\/span><span class=\"p\">(<\/span><span class=\"n\">g<\/span><span class=\"o\">.<\/span><span class=\"n\">edges<\/span><span class=\"p\">()):<\/span>\n                <span class=\"n\">is_independent<\/span> <span class=\"o\">=<\/span> <span class=\"kc\">False<\/span>\n\n        <span class=\"c1\"># I\u304c\u72ec\u7acb\u70b9\u96c6\u5408\u306e\u6642<\/span>\n        <span class=\"k\">if<\/span> <span class=\"n\">is_independent<\/span> <span class=\"o\">==<\/span> <span class=\"kc\">True<\/span><span class=\"p\">:<\/span>\n            <span class=\"c1\"># I\u306b\u542b\u307e\u308c\u308b\u9802\u70b9\u3068I\u3068\u96a3\u63a5\u3057\u3066\u3044\u308b\u9802\u70b9<\/span>\n            <span class=\"n\">node_neighbors<\/span> <span class=\"o\">=<\/span> <span class=\"n\">i<\/span>\n            <span class=\"k\">for<\/span> <span class=\"n\">v<\/span> <span class=\"ow\">in<\/span> <span class=\"n\">i<\/span><span class=\"p\">:<\/span>\n                <span class=\"n\">node_neighbors<\/span> <span class=\"o\">=<\/span> <span class=\"n\">node_neighbors<\/span> <span class=\"o\">|<\/span> <span class=\"nb\">set<\/span><span class=\"p\">(<\/span><span class=\"n\">g<\/span><span class=\"o\">.<\/span><span class=\"n\">neighbors<\/span><span class=\"p\">(<\/span><span class=\"n\">v<\/span><span class=\"p\">))<\/span>\n\n            <span class=\"c1\"># I\u306e\u3069\u306e\u9802\u70b9\u3068\u3082\u96a3\u63a5\u3057\u3066\u3044\u306a\u3044\u9802\u70b9\u306e\u90e8\u5206\u30b0\u30e9\u30d5<\/span>\n            <span class=\"n\">non_neighbors<\/span> <span class=\"o\">=<\/span> <span class=\"n\">g<\/span><span class=\"o\">.<\/span><span class=\"n\">subgraph<\/span><span class=\"p\">(<\/span><span class=\"nb\">set<\/span><span class=\"p\">(<\/span><span class=\"n\">g<\/span><span class=\"o\">.<\/span><span class=\"n\">nodes<\/span><span class=\"p\">()<\/span> <span class=\"o\">-<\/span> <span class=\"n\">node_neighbors<\/span><span class=\"p\">))<\/span><span class=\"o\">.<\/span><span class=\"n\">copy<\/span><span class=\"p\">()<\/span>\n\n            <span class=\"k\">if<\/span> <span class=\"n\">non_neighbors<\/span><span class=\"o\">.<\/span><span class=\"n\">number_of_nodes<\/span><span class=\"p\">()<\/span> <span class=\"o\">&gt;=<\/span> <span class=\"p\">(<\/span><span class=\"n\">n<\/span> <span class=\"o\">\/<\/span> <span class=\"n\">k<\/span><span class=\"p\">)<\/span> <span class=\"o\">*<\/span> <span class=\"n\">np<\/span><span class=\"o\">.<\/span><span class=\"n\">log<\/span><span class=\"p\">(<\/span><span class=\"n\">n<\/span><span class=\"p\">)<\/span> <span class=\"o\">\/<\/span> <span class=\"p\">(<\/span>\n                <span class=\"mi\">2<\/span> <span class=\"o\">*<\/span> <span class=\"n\">np<\/span><span class=\"o\">.<\/span><span class=\"n\">log<\/span><span class=\"p\">(<\/span><span class=\"n\">np<\/span><span class=\"o\">.<\/span><span class=\"n\">log<\/span><span class=\"p\">(<\/span><span class=\"n\">n<\/span><span class=\"p\">))<\/span>\n            <span class=\"p\">):<\/span>\n                <span class=\"k\">return<\/span> <span class=\"n\">i<\/span> <span class=\"o\">|<\/span> <span class=\"n\">independent_set_classical<\/span><span class=\"p\">(<\/span><span class=\"n\">non_neighbors<\/span><span class=\"p\">,<\/span> <span class=\"n\">k<\/span><span class=\"p\">)<\/span>\n\n            <span class=\"k\">else<\/span><span class=\"p\">:<\/span>\n                <span class=\"c1\"># clique_removal\u3067\u6c42\u307e\u3063\u305f\u72ec\u7acb\u70b9\u96c6\u5408<\/span>\n                <span class=\"n\">i2<\/span> <span class=\"o\">=<\/span> <span class=\"n\">clique<\/span><span class=\"o\">.<\/span><span class=\"n\">clique_removal<\/span><span class=\"p\">(<\/span><span class=\"n\">non_neighbors<\/span><span class=\"p\">)[<\/span><span class=\"mi\">0<\/span><span class=\"p\">]<\/span> <span class=\"o\">|<\/span> <span class=\"n\">i<\/span>\n\n                <span class=\"c1\"># I_2\u306b\u542b\u307e\u308c\u308b\u9802\u70b9\u306e\u6570\u304c(np.power(np.log(n), 3)\/(6*np.log(np.log(n))))\u3088\u308a\u5927\u304d\u3044\u306a\u3089\u7d50\u679c\u3092\u8fd4\u3059<\/span>\n                <span class=\"k\">if<\/span> <span class=\"nb\">len<\/span><span class=\"p\">(<\/span><span class=\"n\">i2<\/span><span class=\"p\">)<\/span> <span class=\"o\">&gt;=<\/span> <span class=\"n\">np<\/span><span class=\"o\">.<\/span><span class=\"n\">floor<\/span><span class=\"p\">(<\/span>\n                    <span class=\"n\">np<\/span><span class=\"o\">.<\/span><span class=\"n\">power<\/span><span class=\"p\">(<\/span><span class=\"n\">np<\/span><span class=\"o\">.<\/span><span class=\"n\">log<\/span><span class=\"p\">(<\/span><span class=\"n\">n<\/span><span class=\"p\">),<\/span> <span class=\"mi\">3<\/span><span class=\"p\">)<\/span> <span class=\"o\">\/<\/span> <span class=\"p\">(<\/span><span class=\"mi\">6<\/span> <span class=\"o\">*<\/span> <span class=\"n\">np<\/span><span class=\"o\">.<\/span><span class=\"n\">log<\/span><span class=\"p\">(<\/span><span class=\"n\">np<\/span><span class=\"o\">.<\/span><span class=\"n\">log<\/span><span class=\"p\">(<\/span><span class=\"n\">n<\/span><span class=\"p\">)))<\/span>\n                <span class=\"p\">)<\/span><span class=\"o\">.<\/span><span class=\"n\">astype<\/span><span class=\"p\">(<\/span><span class=\"nb\">int<\/span><span class=\"p\">):<\/span>\n                    <span class=\"k\">return<\/span> <span class=\"n\">i2<\/span> <span class=\"o\">|<\/span> <span class=\"n\">i<\/span>\n<\/pre>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">\n<p>\u5b9f\u969b\u306bSampleIS\u3067\u72ec\u7acb\u70b9\u96c6\u5408\u3092\u6c42\u3081\u3066\u307f\u307e\u3059\u3002<\/p>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing code_cell rendered\">\n<div class=\"input\">\n<div class=\"inner_cell\">\n<div class=\"input_area\">\n<div class=\" highlight hl-python\">\n<pre><span class=\"n\">g<\/span> <span class=\"o\">=<\/span> <span class=\"n\">nx<\/span><span class=\"o\">.<\/span><span class=\"n\">fast_gnp_random_graph<\/span><span class=\"p\">(<\/span><span class=\"mi\">5<\/span><span class=\"p\">,<\/span> <span class=\"mf\">0.3<\/span><span class=\"p\">)<\/span>\n<span class=\"n\">independent_set<\/span> <span class=\"o\">=<\/span> <span class=\"n\">independent_set_classical<\/span><span class=\"p\">(<\/span><span class=\"n\">g<\/span><span class=\"p\">,<\/span> <span class=\"mi\">3<\/span><span class=\"p\">)<\/span>\n<span class=\"n\">nx<\/span><span class=\"o\">.<\/span><span class=\"n\">draw_networkx<\/span><span class=\"p\">(<\/span><span class=\"n\">g<\/span><span class=\"p\">)<\/span>\n<span class=\"n\">plt<\/span><span class=\"o\">.<\/span><span class=\"n\">show<\/span><span class=\"p\">()<\/span>\n<span class=\"nb\">print<\/span><span class=\"p\">(<\/span><span class=\"sa\">f<\/span><span class=\"s2\">\"\u72ec\u7acb\u70b9\u96c6\u5408:<\/span><span class=\"si\">{<\/span><span class=\"n\">independent_set<\/span><span class=\"si\">}<\/span><span class=\"s2\">\"<\/span><span class=\"p\">)<\/span>\n<\/pre>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"output_wrapper\">\n<div class=\"output\">\n<div class=\"output_area\">\n<div class=\"prompt\"><\/div>\n<div class=\"output_png output_subarea \"><img decoding=\"async\" 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\" \/><\/div>\n<\/div>\n<div class=\"output_area\">\n<div class=\"prompt\"><\/div>\n<div class=\"output_subarea output_stream output_stdout output_text\">\n<pre>\u72ec\u7acb\u70b9\u96c6\u5408:{1, 2}\n<\/pre>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">\n<p>\u6b21\u306b\u91cf\u5b50\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u3092\u4f7f\u3063\u3066\u72ec\u7acb\u70b9\u96c6\u5408\u3092\u6c42\u3081\u307e\u3059\u3002\u5b9a\u5f0f\u5316\u306f\u4ee5\u4e0b\u306e\u901a\u308a\u3067\u3059\u3002<\/p>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">\n<p>[latex]f_{MIS}(x) = &#8211; \\sum_{i}^{n}x_{i} + \\alpha \\sum_{i, j \\in E}x_{i}x_{j}[\/latex]<\/p>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing code_cell rendered\">\n<div class=\"input\">\n<div class=\"inner_cell\">\n<div class=\"input_area\">\n<div class=\" highlight hl-python\">\n<pre><span class=\"k\">def<\/span> <span class=\"nf\">independent_set_quantum<\/span><span class=\"p\">(<\/span><span class=\"n\">g<\/span><span class=\"p\">,<\/span> <span class=\"n\">sampler<\/span><span class=\"p\">,<\/span> <span class=\"o\">**<\/span><span class=\"n\">sampler_params<\/span><span class=\"p\">):<\/span>\n    <span class=\"c1\"># \u9802\u70b9\u6570<\/span>\n    <span class=\"n\">n<\/span> <span class=\"o\">=<\/span> <span class=\"n\">g<\/span><span class=\"o\">.<\/span><span class=\"n\">number_of_nodes<\/span><span class=\"p\">()<\/span>\n\n    <span class=\"c1\"># \u30b0\u30e9\u30d5\u306e\u9802\u70b9\u756a\u53f7<\/span>\n    <span class=\"n\">nodes<\/span> <span class=\"o\">=<\/span> <span class=\"nb\">list<\/span><span class=\"p\">(<\/span><span class=\"n\">g<\/span><span class=\"o\">.<\/span><span class=\"n\">nodes<\/span><span class=\"p\">())<\/span>\n\n    <span class=\"c1\"># QUBO\u3092\u4f5c\u6210<\/span>\n    <span class=\"n\">qubo<\/span> <span class=\"o\">=<\/span> <span class=\"p\">{}<\/span>\n\n    <span class=\"c1\"># \u9802\u70b9\u6570\u3092\u591a\u304f\u3059\u308b\u305f\u3081\u306e\u9805<\/span>\n    <span class=\"k\">for<\/span> <span class=\"n\">i<\/span> <span class=\"ow\">in<\/span> <span class=\"nb\">range<\/span><span class=\"p\">(<\/span><span class=\"n\">n<\/span><span class=\"p\">):<\/span>\n        <span class=\"n\">qubo<\/span><span class=\"p\">[(<\/span><span class=\"n\">i<\/span><span class=\"p\">,<\/span> <span class=\"n\">i<\/span><span class=\"p\">)]<\/span> <span class=\"o\">=<\/span> <span class=\"o\">-<\/span><span class=\"mi\">1<\/span>\n\n    <span class=\"c1\"># \u72ec\u7acb\u70b9\u96c6\u5408\u306b\u3059\u308b\u305f\u3081\u306e\u9805<\/span>\n    <span class=\"k\">for<\/span> <span class=\"p\">(<\/span><span class=\"n\">u<\/span><span class=\"p\">,<\/span> <span class=\"n\">v<\/span><span class=\"p\">)<\/span> <span class=\"ow\">in<\/span> <span class=\"n\">g<\/span><span class=\"o\">.<\/span><span class=\"n\">edges<\/span><span class=\"p\">():<\/span>\n        <span class=\"n\">qubo<\/span><span class=\"p\">[(<\/span><span class=\"n\">nodes<\/span><span class=\"o\">.<\/span><span class=\"n\">index<\/span><span class=\"p\">(<\/span><span class=\"n\">u<\/span><span class=\"p\">),<\/span> <span class=\"n\">nodes<\/span><span class=\"o\">.<\/span><span class=\"n\">index<\/span><span class=\"p\">(<\/span><span class=\"n\">v<\/span><span class=\"p\">))]<\/span> <span class=\"o\">=<\/span> <span class=\"n\">qubo<\/span><span class=\"p\">[<\/span>\n            <span class=\"p\">(<\/span><span class=\"n\">nodes<\/span><span class=\"o\">.<\/span><span class=\"n\">index<\/span><span class=\"p\">(<\/span><span class=\"n\">v<\/span><span class=\"p\">),<\/span> <span class=\"n\">nodes<\/span><span class=\"o\">.<\/span><span class=\"n\">index<\/span><span class=\"p\">(<\/span><span class=\"n\">u<\/span><span class=\"p\">))<\/span>\n        <span class=\"p\">]<\/span> <span class=\"o\">=<\/span> <span class=\"mi\">2<\/span>\n\n    <span class=\"c1\"># \u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u306e\u5b9f\u884c<\/span>\n    <span class=\"n\">sampleset<\/span> <span class=\"o\">=<\/span> <span class=\"n\">sampler<\/span><span class=\"o\">.<\/span><span class=\"n\">sample_qubo<\/span><span class=\"p\">(<\/span><span class=\"n\">qubo<\/span><span class=\"p\">,<\/span> <span class=\"o\">**<\/span><span class=\"n\">sampler_params<\/span><span class=\"p\">)<\/span>\n\n    <span class=\"c1\"># \u6700\u3082\u9802\u70b9\u6570\u306e\u591a\u3044\u72ec\u7acb\u70b9\u96c6\u5408<\/span>\n    <span class=\"n\">max_independent_set<\/span> <span class=\"o\">=<\/span> <span class=\"p\">{}<\/span>\n\n    <span class=\"k\">for<\/span> <span class=\"n\">sample<\/span> <span class=\"ow\">in<\/span> <span class=\"n\">sampleset<\/span><span class=\"o\">.<\/span><span class=\"n\">record<\/span><span class=\"o\">.<\/span><span class=\"n\">sample<\/span><span class=\"p\">:<\/span>\n        <span class=\"c1\"># \u72ec\u7acb\u70b9\u96c6\u5408\u304b\u5224\u5b9a<\/span>\n        <span class=\"n\">is_independent<\/span> <span class=\"o\">=<\/span> <span class=\"kc\">True<\/span>\n\n        <span class=\"k\">for<\/span> <span class=\"p\">(<\/span><span class=\"n\">u<\/span><span class=\"p\">,<\/span> <span class=\"n\">v<\/span><span class=\"p\">)<\/span> <span class=\"ow\">in<\/span> <span class=\"n\">g<\/span><span class=\"o\">.<\/span><span class=\"n\">edges<\/span><span class=\"p\">():<\/span>\n            <span class=\"k\">if<\/span> <span class=\"n\">sample<\/span><span class=\"p\">[<\/span><span class=\"n\">nodes<\/span><span class=\"o\">.<\/span><span class=\"n\">index<\/span><span class=\"p\">(<\/span><span class=\"n\">u<\/span><span class=\"p\">)]<\/span> <span class=\"o\">==<\/span> <span class=\"mi\">1<\/span> <span class=\"ow\">and<\/span> <span class=\"n\">sample<\/span><span class=\"p\">[<\/span><span class=\"n\">nodes<\/span><span class=\"o\">.<\/span><span class=\"n\">index<\/span><span class=\"p\">(<\/span><span class=\"n\">v<\/span><span class=\"p\">)]<\/span> <span class=\"o\">==<\/span> <span class=\"mi\">1<\/span><span class=\"p\">:<\/span>\n                <span class=\"n\">is_independent<\/span> <span class=\"o\">=<\/span> <span class=\"kc\">False<\/span>\n\n        <span class=\"k\">if<\/span> <span class=\"n\">is_independent<\/span><span class=\"p\">:<\/span>\n            <span class=\"n\">independent_set<\/span> <span class=\"o\">=<\/span> <span class=\"nb\">set<\/span><span class=\"p\">([<\/span><span class=\"n\">nodes<\/span><span class=\"p\">[<\/span><span class=\"n\">i<\/span><span class=\"p\">]<\/span> <span class=\"k\">for<\/span> <span class=\"n\">i<\/span> <span class=\"ow\">in<\/span> <span class=\"nb\">range<\/span><span class=\"p\">(<\/span><span class=\"n\">n<\/span><span class=\"p\">)<\/span> <span class=\"k\">if<\/span> <span class=\"n\">sample<\/span><span class=\"p\">[<\/span><span class=\"n\">i<\/span><span class=\"p\">]<\/span> <span class=\"o\">==<\/span> <span class=\"mi\">1<\/span><span class=\"p\">])<\/span>\n\n            <span class=\"c1\"># \u9802\u70b9\u6570\u304c\u591a\u3044\u65b9\u306e\u72ec\u7acb\u70b9\u96c6\u5408\u3092\u6c42\u3081\u308b<\/span>\n            <span class=\"k\">if<\/span> <span class=\"nb\">len<\/span><span class=\"p\">(<\/span><span class=\"n\">independent_set<\/span><span class=\"p\">)<\/span> <span class=\"o\">&gt;<\/span> <span class=\"nb\">len<\/span><span class=\"p\">(<\/span><span class=\"n\">max_independent_set<\/span><span class=\"p\">):<\/span>\n                <span class=\"n\">max_independent_set<\/span> <span class=\"o\">=<\/span> <span class=\"n\">independent_set<\/span>\n\n    <span class=\"k\">return<\/span> <span class=\"n\">max_independent_set<\/span>\n<\/pre>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">\n<p>\u91cf\u5b50\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u3067\u72ec\u7acb\u70b9\u96c6\u5408\u3092\u6c42\u3081\u3066\u307f\u307e\u3059\u3002<\/p>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing code_cell rendered\">\n<div class=\"input\">\n<div class=\"inner_cell\">\n<div class=\"input_area\">\n<div class=\" highlight hl-python\">\n<pre><span class=\"c1\"># \u30b5\u30f3\u30d7\u30e9\u30fc\u306e\u8a2d\u5b9a<\/span>\n<span class=\"c1\"># SA\u306e\u5834\u5408<\/span>\n<span class=\"c1\"># sampler = SASampler()<\/span>\n\n<span class=\"c1\"># D-wave\u30de\u30b7\u30f3\u306e\u5834\u5408<\/span>\n<span class=\"n\">sampler_config<\/span> <span class=\"o\">=<\/span> <span class=\"p\">{<\/span><span class=\"s2\">\"solver\"<\/span><span class=\"p\">:<\/span> <span class=\"s2\">\"DW_2000Q_6\"<\/span><span class=\"p\">,<\/span> <span class=\"s2\">\"token\"<\/span><span class=\"p\">:<\/span> <span class=\"s2\">\"YOUR_TOKEN\"<\/span><span class=\"p\">}<\/span>\n<span class=\"n\">sampler<\/span> <span class=\"o\">=<\/span> <span class=\"n\">EmbeddingComposite<\/span><span class=\"p\">(<\/span><span class=\"n\">DWaveSampler<\/span><span class=\"p\">(<\/span><span class=\"o\">**<\/span><span class=\"n\">sampler_config<\/span><span class=\"p\">))<\/span>\n\n<span class=\"n\">g<\/span> <span class=\"o\">=<\/span> <span class=\"n\">nx<\/span><span class=\"o\">.<\/span><span class=\"n\">fast_gnp_random_graph<\/span><span class=\"p\">(<\/span><span class=\"mi\">5<\/span><span class=\"p\">,<\/span> <span class=\"mf\">0.3<\/span><span class=\"p\">)<\/span>\n<span class=\"n\">independent_set<\/span> <span class=\"o\">=<\/span> <span class=\"n\">independent_set_quantum<\/span><span class=\"p\">(<\/span><span class=\"n\">g<\/span><span class=\"p\">,<\/span> <span class=\"n\">sampler<\/span><span class=\"o\">=<\/span><span class=\"n\">sampler<\/span><span class=\"p\">,<\/span> <span class=\"n\">num_reads<\/span><span class=\"o\">=<\/span><span class=\"mi\">30<\/span><span class=\"p\">)<\/span>\n<span class=\"n\">nx<\/span><span class=\"o\">.<\/span><span class=\"n\">draw_networkx<\/span><span class=\"p\">(<\/span><span class=\"n\">g<\/span><span class=\"p\">)<\/span>\n<span class=\"n\">plt<\/span><span class=\"o\">.<\/span><span class=\"n\">show<\/span><span class=\"p\">()<\/span>\n<span class=\"nb\">print<\/span><span class=\"p\">(<\/span><span class=\"sa\">f<\/span><span class=\"s2\">\"\u72ec\u7acb\u70b9\u96c6\u5408:<\/span><span class=\"si\">{<\/span><span class=\"n\">independent_set<\/span><span class=\"si\">}<\/span><span class=\"s2\">\"<\/span><span class=\"p\">)<\/span>\n<\/pre>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"output_wrapper\">\n<div class=\"output\">\n<div class=\"output_area\">\n<div class=\"prompt\"><\/div>\n<div class=\"output_png output_subarea \"><img decoding=\"async\" src=\"data:image\/png;base64,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\" \/><\/div>\n<\/div>\n<div class=\"output_area\">\n<div class=\"prompt\"><\/div>\n<div class=\"output_subarea output_stream output_stdout output_text\">\n<pre>\u72ec\u7acb\u70b9\u96c6\u5408:{0, 2, 3, 4}\n<\/pre>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">\n<p>\u4e0a\u8a18\u306e\u95a2\u6570\u3092\u7528\u3044\u3066\u30b0\u30e9\u30d5\u5f69\u8272\u306e\u95a2\u6570\u3092\u4f5c\u6210\u3057\u307e\u3059\u3002<\/p>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing code_cell rendered\">\n<div class=\"input\">\n<div class=\"inner_cell\">\n<div class=\"input_area\">\n<div class=\" highlight hl-python\">\n<pre><span class=\"k\">def<\/span> <span class=\"nf\">graph_coloring_classical<\/span><span class=\"p\">(<\/span><span class=\"n\">g<\/span><span class=\"p\">):<\/span>\n    <span class=\"c1\"># \u73fe\u5728\u306e\u8272<\/span>\n    <span class=\"n\">color<\/span> <span class=\"o\">=<\/span> <span class=\"mi\">0<\/span>\n\n    <span class=\"c1\"># \u5f69\u8272\u3059\u308b\u305f\u3081\u306e\u30b0\u30e9\u30d5<\/span>\n    <span class=\"n\">coloring_graph<\/span> <span class=\"o\">=<\/span> <span class=\"n\">g<\/span><span class=\"o\">.<\/span><span class=\"n\">copy<\/span><span class=\"p\">()<\/span>\n\n    <span class=\"c1\"># \u9802\u70b9\u306e\u8272<\/span>\n    <span class=\"n\">node_color<\/span> <span class=\"o\">=<\/span> <span class=\"p\">[<\/span><span class=\"kc\">None<\/span><span class=\"p\">]<\/span> <span class=\"o\">*<\/span> <span class=\"n\">coloring_graph<\/span><span class=\"o\">.<\/span><span class=\"n\">number_of_nodes<\/span><span class=\"p\">()<\/span>\n\n    <span class=\"k\">while<\/span> <span class=\"n\">coloring_graph<\/span><span class=\"o\">.<\/span><span class=\"n\">number_of_nodes<\/span><span class=\"p\">()<\/span> <span class=\"o\">&gt;<\/span> <span class=\"mi\">0<\/span><span class=\"p\">:<\/span>\n        <span class=\"c1\"># \u72ec\u7acb\u70b9\u96c6\u5408\u3092\u6c42\u3081\u308b<\/span>\n        <span class=\"n\">max_independent_set<\/span> <span class=\"o\">=<\/span> <span class=\"p\">{}<\/span>\n        <span class=\"n\">independent_set<\/span> <span class=\"o\">=<\/span> <span class=\"n\">independent_set_classical<\/span><span class=\"p\">(<\/span><span class=\"n\">coloring_graph<\/span><span class=\"o\">.<\/span><span class=\"n\">copy<\/span><span class=\"p\">(),<\/span> <span class=\"mi\">3<\/span><span class=\"p\">)<\/span>\n\n        <span class=\"n\">s<\/span> <span class=\"o\">=<\/span> <span class=\"mi\">1<\/span>\n        <span class=\"k\">for<\/span> <span class=\"n\">i<\/span> <span class=\"ow\">in<\/span> <span class=\"nb\">range<\/span><span class=\"p\">(<\/span><span class=\"n\">s<\/span><span class=\"p\">):<\/span>\n            <span class=\"k\">if<\/span> <span class=\"nb\">len<\/span><span class=\"p\">(<\/span><span class=\"n\">independent_set<\/span><span class=\"p\">)<\/span> <span class=\"o\">&gt;<\/span> <span class=\"nb\">len<\/span><span class=\"p\">(<\/span><span class=\"n\">max_independent_set<\/span><span class=\"p\">):<\/span>\n                <span class=\"n\">max_independent_set<\/span> <span class=\"o\">=<\/span> <span class=\"n\">independent_set<\/span>\n\n        <span class=\"c1\"># \u6c42\u3081\u305f\u72ec\u7acb\u70b9\u96c6\u5408\u306b1\u8272\u5272\u308a\u5f53\u3066\u308b<\/span>\n        <span class=\"k\">for<\/span> <span class=\"n\">v<\/span> <span class=\"ow\">in<\/span> <span class=\"n\">max_independent_set<\/span><span class=\"p\">:<\/span>\n            <span class=\"n\">node_color<\/span><span class=\"p\">[<\/span><span class=\"n\">v<\/span><span class=\"p\">]<\/span> <span class=\"o\">=<\/span> <span class=\"n\">color<\/span>\n\n        <span class=\"k\">if<\/span> <span class=\"nb\">len<\/span><span class=\"p\">(<\/span><span class=\"n\">max_independent_set<\/span><span class=\"p\">)<\/span> <span class=\"o\">&gt;<\/span> <span class=\"mi\">0<\/span><span class=\"p\">:<\/span>\n            <span class=\"c1\"># \u30b0\u30e9\u30d5\u304b\u3089\u9802\u70b9\u3092\u524a\u9664<\/span>\n            <span class=\"n\">coloring_graph<\/span><span class=\"o\">.<\/span><span class=\"n\">remove_nodes_from<\/span><span class=\"p\">(<\/span><span class=\"n\">max_independent_set<\/span><span class=\"p\">)<\/span>\n            <span class=\"n\">color<\/span> <span class=\"o\">+=<\/span> <span class=\"mi\">1<\/span>\n\n    <span class=\"k\">return<\/span> <span class=\"n\">node_color<\/span>\n<\/pre>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing code_cell rendered\">\n<div class=\"input\">\n<div class=\"inner_cell\">\n<div class=\"input_area\">\n<div class=\" highlight hl-python\">\n<pre><span class=\"k\">def<\/span> <span class=\"nf\">graph_coloring_quantum<\/span><span class=\"p\">(<\/span><span class=\"n\">g<\/span><span class=\"p\">,<\/span> <span class=\"n\">sampler<\/span><span class=\"p\">,<\/span> <span class=\"o\">**<\/span><span class=\"n\">sampler_params<\/span><span class=\"p\">):<\/span>\n    <span class=\"c1\"># \u73fe\u5728\u306e\u8272<\/span>\n    <span class=\"n\">color<\/span> <span class=\"o\">=<\/span> <span class=\"mi\">0<\/span>\n\n    <span class=\"c1\"># \u5f69\u8272\u3057\u305f\u3044\u30b0\u30e9\u30d5<\/span>\n    <span class=\"n\">coloring_graph<\/span> <span class=\"o\">=<\/span> <span class=\"n\">g<\/span><span class=\"o\">.<\/span><span class=\"n\">copy<\/span><span class=\"p\">()<\/span>\n\n    <span class=\"c1\"># \u9802\u70b9\u306e\u8272<\/span>\n    <span class=\"n\">node_color<\/span> <span class=\"o\">=<\/span> <span class=\"p\">[<\/span><span class=\"kc\">None<\/span><span class=\"p\">]<\/span> <span class=\"o\">*<\/span> <span class=\"n\">coloring_graph<\/span><span class=\"o\">.<\/span><span class=\"n\">number_of_nodes<\/span><span class=\"p\">()<\/span>\n\n    <span class=\"k\">while<\/span> <span class=\"n\">coloring_graph<\/span><span class=\"o\">.<\/span><span class=\"n\">number_of_nodes<\/span><span class=\"p\">()<\/span> <span class=\"o\">&gt;<\/span> <span class=\"mi\">0<\/span><span class=\"p\">:<\/span>\n        <span class=\"c1\"># \u72ec\u7acb\u70b9\u96c6\u5408\u3092\u6c42\u3081\u308b<\/span>\n        <span class=\"n\">max_independent_set<\/span> <span class=\"o\">=<\/span> <span class=\"n\">independent_set_quantum<\/span><span class=\"p\">(<\/span>\n            <span class=\"n\">coloring_graph<\/span><span class=\"o\">.<\/span><span class=\"n\">copy<\/span><span class=\"p\">(),<\/span> <span class=\"n\">sampler<\/span><span class=\"o\">=<\/span><span class=\"n\">sampler<\/span><span class=\"p\">,<\/span> <span class=\"o\">**<\/span><span class=\"n\">sampler_params<\/span>\n        <span class=\"p\">)<\/span>\n\n        <span class=\"c1\"># \u6c42\u3081\u305f\u72ec\u7acb\u70b9\u96c6\u5408\u306b1\u8272\u5272\u308a\u5f53\u3066\u308b<\/span>\n        <span class=\"k\">for<\/span> <span class=\"n\">v<\/span> <span class=\"ow\">in<\/span> <span class=\"n\">max_independent_set<\/span><span class=\"p\">:<\/span>\n            <span class=\"n\">node_color<\/span><span class=\"p\">[<\/span><span class=\"n\">v<\/span><span class=\"p\">]<\/span> <span class=\"o\">=<\/span> <span class=\"n\">color<\/span>\n\n        <span class=\"k\">if<\/span> <span class=\"nb\">len<\/span><span class=\"p\">(<\/span><span class=\"n\">max_independent_set<\/span><span class=\"p\">)<\/span> <span class=\"o\">&gt;<\/span> <span class=\"mi\">0<\/span><span class=\"p\">:<\/span>\n            <span class=\"c1\"># \u30b0\u30e9\u30d5\u304b\u3089\u9802\u70b9\u3092\u524a\u9664<\/span>\n            <span class=\"n\">coloring_graph<\/span><span class=\"o\">.<\/span><span class=\"n\">remove_nodes_from<\/span><span class=\"p\">(<\/span><span class=\"n\">max_independent_set<\/span><span class=\"p\">)<\/span>\n            <span class=\"n\">color<\/span> <span class=\"o\">+=<\/span> <span class=\"mi\">1<\/span>\n\n    <span class=\"k\">return<\/span> <span class=\"n\">node_color<\/span>\n<\/pre>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">\n<p>\u8ad6\u6587\u3067\u306f\u5f69\u8272\u3092\u884c\u3046\u30b0\u30e9\u30d5\u306f3\u8272\u3067\u5f69\u8272\u53ef\u80fd\u306a\u3082\u306e\u3092\u7528\u3044\u3066\u5b9f\u9a13\u3092\u884c\u3044\u307e\u3057\u305f\u3002\u672c\u8a18\u4e8b\u3067\u306f\u8fba\u304c\u5b58\u5728\u3057\u306a\u3044\u30b0\u30e9\u30d5\u306e\u9802\u70b9\u306b\u3042\u3089\u304b\u3058\u30813\u8272\u306e\u3046\u3061\u3069\u308c\u304b\u306e\u8272\u3092\u5272\u308a\u5f53\u3066\u3001\u7570\u306a\u308b\u8272\u306e2\u9802\u70b9\u306e\u9593\u306b\u30e9\u30f3\u30c0\u30e0\u306b\u8fba\u3092\u751f\u6210\u3059\u308b\u3053\u3068\u3067\u30b0\u30e9\u30d5\u3092\u4f5c\u6210\u3057\u307e\u3059\u3002<\/p>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing code_cell rendered\">\n<div class=\"input\">\n<div class=\"inner_cell\">\n<div class=\"input_area\">\n<div class=\" highlight hl-python\">\n<pre><span class=\"k\">def<\/span> <span class=\"nf\">make_random_graph<\/span><span class=\"p\">(<\/span><span class=\"n\">node_num<\/span><span class=\"o\">=<\/span><span class=\"mi\">20<\/span><span class=\"p\">,<\/span> <span class=\"n\">color_num<\/span><span class=\"o\">=<\/span><span class=\"mi\">3<\/span><span class=\"p\">,<\/span> <span class=\"n\">p<\/span><span class=\"o\">=<\/span><span class=\"mf\">0.5<\/span><span class=\"p\">):<\/span>\n    <span class=\"c1\"># \u9802\u70b9\u756a\u53f7<\/span>\n    <span class=\"n\">num<\/span> <span class=\"o\">=<\/span> <span class=\"p\">[<\/span><span class=\"n\">i<\/span> <span class=\"k\">for<\/span> <span class=\"n\">i<\/span> <span class=\"ow\">in<\/span> <span class=\"nb\">range<\/span><span class=\"p\">(<\/span><span class=\"n\">node_num<\/span><span class=\"p\">)]<\/span>\n\n    <span class=\"c1\"># \u7a7a\u30b0\u30e9\u30d5\u3092\u4f5c\u6210<\/span>\n    <span class=\"n\">g<\/span> <span class=\"o\">=<\/span> <span class=\"n\">nx<\/span><span class=\"o\">.<\/span><span class=\"n\">empty_graph<\/span><span class=\"p\">(<\/span><span class=\"n\">node_num<\/span><span class=\"p\">)<\/span>\n\n    <span class=\"c1\"># \u30e9\u30f3\u30c0\u30e0\u306b\u8272\u3092\u5272\u308a\u5f53\u3066\u308b<\/span>\n    <span class=\"n\">color<\/span> <span class=\"o\">=<\/span> <span class=\"p\">[<\/span><span class=\"n\">random<\/span><span class=\"o\">.<\/span><span class=\"n\">randint<\/span><span class=\"p\">(<\/span><span class=\"mi\">0<\/span><span class=\"p\">,<\/span> <span class=\"n\">color_num<\/span> <span class=\"o\">-<\/span> <span class=\"mi\">1<\/span><span class=\"p\">)<\/span> <span class=\"k\">for<\/span> <span class=\"n\">i<\/span> <span class=\"ow\">in<\/span> <span class=\"nb\">range<\/span><span class=\"p\">(<\/span><span class=\"n\">node_num<\/span><span class=\"p\">)]<\/span>\n\n    <span class=\"c1\"># \u8272\u304c\u7570\u306a\u308b\u9802\u70b9\u306e\u9593\u306b\u30e9\u30f3\u30c0\u30e0\u306b\u8fba\u3092\u751f\u6210<\/span>\n    <span class=\"k\">for<\/span> <span class=\"p\">(<\/span><span class=\"n\">u<\/span><span class=\"p\">,<\/span> <span class=\"n\">v<\/span><span class=\"p\">)<\/span> <span class=\"ow\">in<\/span> <span class=\"n\">combinations<\/span><span class=\"p\">(<\/span><span class=\"n\">num<\/span><span class=\"p\">,<\/span> <span class=\"mi\">2<\/span><span class=\"p\">):<\/span>\n        <span class=\"k\">if<\/span> <span class=\"n\">color<\/span><span class=\"p\">[<\/span><span class=\"n\">u<\/span><span class=\"p\">]<\/span> <span class=\"o\">!=<\/span> <span class=\"n\">color<\/span><span class=\"p\">[<\/span><span class=\"n\">v<\/span><span class=\"p\">]<\/span> <span class=\"ow\">and<\/span> <span class=\"n\">random<\/span><span class=\"o\">.<\/span><span class=\"n\">random<\/span><span class=\"p\">()<\/span> <span class=\"o\">&lt;<\/span> <span class=\"n\">p<\/span><span class=\"p\">:<\/span>\n            <span class=\"n\">g<\/span><span class=\"o\">.<\/span><span class=\"n\">add_edge<\/span><span class=\"p\">(<\/span><span class=\"n\">u<\/span><span class=\"p\">,<\/span> <span class=\"n\">v<\/span><span class=\"p\">)<\/span>\n\n    <span class=\"k\">return<\/span> <span class=\"n\">g<\/span>\n<\/pre>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">\n<p>\u5b9f\u969b\u306b\u30b0\u30e9\u30d5\u5f69\u8272\u3092\u884c\u3044\u307e\u3059\u3002\u4eca\u56de\u306f\u9802\u70b9\u6570\u309210\u3068\u3057\u3066\u30b0\u30e9\u30d5\u5f69\u8272\u3092\u884c\u3044\u307e\u3059\u3002<\/p>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing code_cell rendered\">\n<div class=\"input\">\n<div class=\"inner_cell\">\n<div class=\"input_area\">\n<div class=\" highlight hl-python\">\n<pre><span class=\"n\">g<\/span> <span class=\"o\">=<\/span> <span class=\"n\">make_random_graph<\/span><span class=\"p\">(<\/span><span class=\"n\">node_num<\/span><span class=\"o\">=<\/span><span class=\"mi\">10<\/span><span class=\"p\">,<\/span> <span class=\"n\">color_num<\/span><span class=\"o\">=<\/span><span class=\"mi\">3<\/span><span class=\"p\">,<\/span> <span class=\"n\">p<\/span><span class=\"o\">=<\/span><span class=\"mf\">0.5<\/span><span class=\"p\">)<\/span>\n<span class=\"n\">nx<\/span><span class=\"o\">.<\/span><span class=\"n\">draw_networkx<\/span><span class=\"p\">(<\/span><span class=\"n\">g<\/span><span class=\"p\">)<\/span>\n<span class=\"n\">plt<\/span><span class=\"o\">.<\/span><span class=\"n\">show<\/span><span class=\"p\">()<\/span>\n<\/pre>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"output_wrapper\">\n<div class=\"output\">\n<div class=\"output_area\">\n<div class=\"prompt\"><\/div>\n<div class=\"output_png output_subarea \"><img decoding=\"async\" src=\"data:image\/png;base64,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\" \/><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing code_cell rendered\">\n<div class=\"input\">\n<div class=\"inner_cell\">\n<div class=\"input_area\">\n<div class=\" highlight hl-python\">\n<pre><span class=\"c1\"># \u30b5\u30f3\u30d7\u30e9\u30fc\u306e\u8a2d\u5b9a<\/span>\n<span class=\"c1\"># SA\u306e\u5834\u5408<\/span>\n<span class=\"c1\"># sampler = SASampler()<\/span>\n\n<span class=\"c1\"># D-wave\u30de\u30b7\u30f3\u306e\u5834\u5408<\/span>\n<span class=\"n\">sampler_config<\/span> <span class=\"o\">=<\/span> <span class=\"p\">{<\/span><span class=\"s2\">\"solver\"<\/span><span class=\"p\">:<\/span> <span class=\"s2\">\"DW_2000Q_6\"<\/span><span class=\"p\">,<\/span> <span class=\"s2\">\"token\"<\/span><span class=\"p\">:<\/span> <span class=\"s2\">\"YOUR_TOKEN\"<\/span><span class=\"p\">}<\/span>\n<span class=\"n\">sampler<\/span> <span class=\"o\">=<\/span> <span class=\"n\">EmbeddingComposite<\/span><span class=\"p\">(<\/span><span class=\"n\">DWaveSampler<\/span><span class=\"p\">(<\/span><span class=\"o\">**<\/span><span class=\"n\">sampler_config<\/span><span class=\"p\">))<\/span>\n\n<span class=\"n\">color_quantum<\/span> <span class=\"o\">=<\/span> <span class=\"n\">graph_coloring_quantum<\/span><span class=\"p\">(<\/span><span class=\"n\">g<\/span><span class=\"p\">,<\/span> <span class=\"n\">sampler<\/span><span class=\"o\">=<\/span><span class=\"n\">sampler<\/span><span class=\"p\">,<\/span> <span class=\"n\">num_reads<\/span><span class=\"o\">=<\/span><span class=\"mi\">30<\/span><span class=\"p\">)<\/span>\n<span class=\"nb\">print<\/span><span class=\"p\">(<\/span><span class=\"n\">color_quantum<\/span><span class=\"p\">)<\/span>\n<span class=\"n\">nx<\/span><span class=\"o\">.<\/span><span class=\"n\">draw_networkx<\/span><span class=\"p\">(<\/span><span class=\"n\">g<\/span><span class=\"p\">,<\/span> <span class=\"n\">node_color<\/span><span class=\"o\">=<\/span><span class=\"n\">color_quantum<\/span><span class=\"p\">)<\/span>\n<span class=\"n\">plt<\/span><span class=\"o\">.<\/span><span class=\"n\">title<\/span><span class=\"p\">(<\/span><span class=\"s2\">\"Quantum Graph Coloring\"<\/span><span class=\"p\">)<\/span>\n<span class=\"n\">plt<\/span><span class=\"o\">.<\/span><span class=\"n\">show<\/span><span class=\"p\">()<\/span>\n<\/pre>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"output_wrapper\">\n<div class=\"output\">\n<div class=\"output_area\">\n<div class=\"prompt\"><\/div>\n<div class=\"output_subarea output_stream output_stdout output_text\">\n<pre>[1, 0, 0, 0, 1, 2, 0, 1, 0, 2]\n<\/pre>\n<\/div>\n<\/div>\n<div class=\"output_area\">\n<div class=\"prompt\"><\/div>\n<div class=\"output_png output_subarea \"><img decoding=\"async\" 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hUZBhjWLVqFWbOnIkuXbrg7NmzGp9foizBiemSLAPI+gdA\/u1E\/n2UA5+5yYiMFsHMRAvLfzWFW6+8SxVlgOwtkHMN0OtYYBvlsfdaFGFhYRg9ejScnZ0RExOjtMGQL8MLANC5c2e8f\/8eUVFRaNOmjVLaUSVnz56Ft7c3+vXrh6ioKI1KwaiJMMawYsUKzJ49+5PxmpqW79wa6oIb0xUGAQp2KpBICG4jX2Pc8GoIOWiFi+FC9PV8jcjQ2mhYL8+KM8oCZW4DyzXd8t57LYr09HT8\/PPPOHXqFLZu3YoePXootf7s7OzPwguAfI7nyJEjsWPHDo02XaFQiDlz5iAgIAD+\/v5wcXHhWlKZgTGGZcuWQSAQoEuXLggLC+ONVwlwE17I2glFA2cPHufgdaIEU8cZgTGGzh0r49t2+tgb8AGLZn3+80acdQNjJvfExcv3y3XvtSjOnDmDMWPGwMXFBffu3VPJHEtFPV0A8PLyQqtWrbB69WqN3A4mKioKw4YNQ4sWLRAdHc3HJksBYwxLliyRfx87d0ZYWJjCud08xYcb05UmFLsogRDzIH\/cVyrVgveIbpj\/24Zy2Xstivfv32PGjBk4e\/Ystm\/fjm7duqmsrYJMt3bt2mjXrh0OHz6MYcOGqaz9kiKRSLBixQqsXbsWa9euxZAhQ8pM3FkTYYxh8eLFEAgEn4zX3Nyca1llFrU7FZEMQP4UggDQqJ4uzE21sGpzKsRiwpkLmbgULkSWMP+quUqV9OD4fRvUr1+\/whnuyZMn0bx5c+jo6ODevXsqNVxAcXjhI6NGjcKOHTtU2n5JePLkCRwdHREWFobIyEj8+OOPvOEqAcYYfv\/9d7i5uaFz585ITk7mWlKZRe1uJZ9xoLiDraPDcGRnTZw8m4Wa9k+x5s80DOhtgFo1FZVnACuf+VsLIjU1FV5eXpg0aRJ2796NLVu2qCUtX0E9XQDo06cPYmNj8eTJE5XrKAwiwvbt29GhQwcMGDAAoaGhsLa25lRTeYMxhkWLFsHDwwPOzs5ISkriWlKZhJsuolbByyztmurh\/NFaeHO\/Hk4fsEJcvBjtWubvZUklQmRkVZylisePH0eLFi1gYGCA6OhodO5c+E4OyqQw09XT08PQoUPh7++vNj1fkpSUhL59+2LTpk24cOFCmU0yXlb47bffMHDgQDg7OyMxMZFrOWUObj6Zlb0ApnjgJfq+CNnZMmRlybB6SyoSkiTwGpS\/Nxf7nw6sareGq6srtm\/fXm5\/7qSkpGDYsGGYNm0a9u3bhw0bNqg9239h4QVAHmLYtWsXJBxsTHns2DG0bNkSzZo1w40bN9CsWTO1a6iILFiwAEOGDIGzszMSEoo\/RsPDkekyfTeAZAqP7Q1Ih1XLOFi0eIqwy1kIOWgFPb0vZLLKsHdYj5cvX2L48OEIDQ1Fw4YN4ejoiHXr1iE+Pl4NV6F6AgMD0aJFC5iamuLu3btwdHTkREdhPV0AaN68OWrVqoWQkBC1afrw4QNGjx6NqVOn4p9\/\/sHSpUvLbSJ7TeXXX3\/FsGHD4OzsjNevX3Mtp8zAWWpH2fv5gDAQihZIFI4A0KoJZnr2sxVp2dnZCA0NxdGjR3Hs2DHY2trC3d0dbm5uaNKkiVK1q5q3b9\/Cx8cHkZGR8Pf3R8eOBS8CUTVEBC0tLYjFYmgVksZx69atOH36NI4cOaJyTVevXoWnpyecnZ3h6+vLbzfDMUuWLMGuXbtw\/vx5WFmVvx1ESkNhqR05C3wxw18AnYYAStI7kQ+eMeNd+ZYAV6pUCb1794a\/vz8SExOxcuVKJCQkoFu3bmjSpAnmzZuHiIgIFHaT0QQCAgLQokULWFlZ4c6dO5waLoBPZluY4QLA4MGDcf78eZUOruTk5GDu3Lnw8PDAmjVrsH37dt5wNYC5c+fC29sbTk5OePnyJddyNB7uTJfpghnvAnTsARRnYr0uIKgOZnIQTLvwra+1tbXh7OyMDRs2ID4+Hrt374ZUKsWPP\/4IW1tbTJ06FRcvXoRUKlXGpSiF5ORkDBw4EL\/88guOHDmCVatWacRS1aJCCx8xNDREv379sGfPHpXoiI2NRfv27XHv3j3cuXOn1BnTeFTD7NmzMWbMGDg7O\/PGWxREVOCjTZs2pGpkshySZR4kaXJXkibYkTShEUkTGnx6pD9pQNkv7Uiavppk0pSvbEtGMTExtGjRImrVqhWZmZnRqFGj6MSJE5Sdna2kKyq5pgMHDlCNGjVo5syZlJWVxYmOgnjz5g2ZmJgUq+zly5epcePGJJPJlNa+VColX19fMjU1pW3btim1bh7ls3LlSqpXrx7Fx8dzLYVTAERQAb7Kuel+RCaTkUx0h6RpC+lycEt6\/W9fkqbNpsN\/jyYfn\/EqafPp06e0Zs0a6tixIxkZGdHgwYPp0KFD9OHDB5W09yUJCQnk5uZGTZs2pRs3bqilzZLy4sULqlmzZrHKymQyatSoEV29elUpbcfHx1Pnzp3JwcGB\/vvvP6XUyaN6Vq9eTXXr1qXnz59zLYUzyoTp5sXJyYnCwsKIiOjBgwdUs2ZNkkqlKm0zMTGR\/Pz8qHv37mRgYEC9e\/emnTt30tu3b5Xelkwmo71795K5uTnNnTuXs152cXj8+DHVqVOn2OWXL19O3t7eX93uvn37yMzMjP744w8Si8VfXR+PevH19aU6derQs2fPuJbCCWXOdNu3b0\/h4eGf\/m7WrJnSek\/FITU1lfbu3Uv9+\/cnQ0ND6ty5M23cuJFevnz51XW\/fv2a+vTpQ82bN6eIiAglqFUtsbGx1KRJk2KXT0hIICMjI0pPTy9VeykpKTR48GBq3LhxmXh9eApm3bp1ZGtrS3FxcVxLUTuFma5GLtvJysr6bBCpf\/\/+OHz4sNraNzIywtChQxEQEICEhAT4+Pjg5s2bsLOzQ4cOHbB8+XL8999\/JaqTiLB7927Y29vD3t4ekZGRGp0S8SOKEpgXhoWFBRwdHXHo0KEStxUaGgp7e3uYm5uXmTy9PAUzefJkTJ8+Hc7OzoiLi+NajuZQkBsThz3devXq0aNHjz79fffuXbKxseF8ECUnJ4fOnDlD48ePJwsLC2revDn9+uuvdPv27UK1vXz5knr16kX29vYUFRWlRsVfz7Vr16h9+\/YlOufYsWPk4OBQ7PKZmZnk4+NDtWrVotDQ0JJK5NFwNm7cSDY2NvTkyROupagNlPWebosWLaCjo4OoqCgOVQE6Ojro1q0bNm\/ejFevXmHr1q0QCoXo378\/6tatixkzZuDq1auQyeSr7YgI\/v7+aNWqFdq3b4+bN2+iVatWnF5DSSlqCbAievbsiWfPnuH+\/ftFlv3Y43\/z5g2io6PRtWvX0krl0VAmTpyImTNnwtnZmfPESJqARu7I96XpMsY+hRg05SenQCCAg4MDHBwcsGLFCty7dw9HjhzBhAkTkJSUhC5duuDhw4eQyWQ4e\/Ys7OzsuJZcKoo7Tzcv2traGDFiBHbs2IHVq1crLCORSLBs2TKsX78e69atw5AhQ5Qhl0dDmTBhAgQCAZydnXHu3LmKvftyQV1g4jC8oKurm29E\/+bNm9SwYUPOQwxFIZPJ6I8\/\/qAqVaqQtbU1GRkZ0bBhw+jw4cOUkZHBtbwSExgYSL179y7xeY8ePSIzMzMSiUT5jv3333\/k4OBAXbp0qfDzOSsafn5+ZG1t\/Vn4sDyCshRekEgkkEgk+ZKXtG3bFtnZ2YiNjeVIWdE8e\/YMLi4uCAwMxPXr1xEfH4\/Y2Fg4ODhgy5YtqFmzJtzd3bFnzx6kpqZyLbdYlCa8AAANGjRAkyZNcPz48U\/PERG2bduGDh06YNCgQThz5gyf87aCMXbsWMyfPx+dO3cu8WB0eUHjTFcoFEJfXz9ftn\/GGNzd3dU6i6G4yGQybNmyBW3btkXXrl0RHh6O5s2bAwBq1qyJCRMmIDQ0FHFxcejXrx8OHz4MGxsbuLi44M8\/\/9To1HilCS98JO+uEklJSejTpw+2bNmCS5cuYcqUKXzO2wrK6NGjsXDhQnTu3BkPHz7kWo76KagLTByFFxITE8nMzEzhscuXL1OLFi3UrKhwnjx5Qk5OTtS+fXu6f\/9+sc\/LyMiggIAA+vHHH8nIyIi+\/fZbWrVqlcaN8G7dupVGjRpVqnMzMzPJ2NiYtm3bRhYWFjR37lyF4Qaeiom\/vz9ZWVnRv\/\/+y7UUpYOytDji6dOnZGNjo\/CYVColCwsLjYgHSaVSWr9+PZmYmNDKlStJIpGUui6RSESnTp2iMWPGkLm5Odnb29PChQspOjqa8xj2+vXraeLEiaU69\/3799SoUSMyNjamK1euKFkZT3lg586dVLNmzRJ1WMoChZmuxv2+EwqFBWbXEggEcHNz4zzE8PjxYzg7O+PAgQO4evUqfvrppyJTHxaGrq4uevToga1bt+L169fYsGED0tLS0Lt3bzRs2BCzZs3C9evXP01FUyelDS9cvnwZLVu2ROPGjVGtWjU4ODioQB1PWcfLywtLly5F165dizXFsDygcab75XSxL1H36rS8SKVSrF27Fh06dICbmxsuXbqERo0aKbUNLS0tdOrUCWvWrEFcXBwOHToEXV1djBo1CtbW1pg4cSLCwsIgFiveUVlZSMQSJMQl4W1cKiiDIT3lQ7HOy8nJwZw5czBw4ECsXbsWR48ehaGhIS5cuKBSvTxlF09PTyxfvhxdu3bV6IFyZaFx83SzsrKgr19wfl1HR0c8e\/YMz58\/h42Njdp0PXz4EN7e3tDS0sL169fVMs+QMYZWrVqhVatW+P333\/Hw4UMcPXoUc+fOxZMnT\/DDDz\/A3d0d3bp1K\/Q1KwlvX6Xg2OYQHNsSAqlYCrFEDBAwePdYNGpfH4Nn9kPbHi0V9uxjYmIwbNgw2NjY4O7duzA3NwfwvwE1dW6myVO2GDZsGBhj6NatG86cOfNpILpcUlDcgTiK6Z46dYpcXFwKLePt7U1r1qxRix6JREIrV64kExMTWr9+vcqznRWX+Ph4Wr9+PTk7O5OhoSF5eHjQ33\/\/TWlpaaWqTyKW0OrRW6in\/hDqWWkIdWUeCh+9DYfRAMvR9O+N\/8XVpVIprVmzhkxNTWn79u354tBv376latWq0bt3777qmnnKP3\/\/\/TdZWFhQdHQ011K+CpSlmG5R4QVAfSGGf\/\/9Fx07dsSJEydw8+ZN+Pj4aMw0J2tra\/j4+ODcuXN48uQJevbsib\/\/\/hvW1tbo1atXiXZIFueIMcvld5zbfxnibDHEooJDF8IP2UhNTMNPnRci6mw04uPj0bVrVwQEBOD69esYNWpUvul+JiYm6NGjB\/7++++vumae8s+QIUOwdu1auLi4IDo6mms5KkEzHCQPhQ2kfaRLly6IjY1V2fxWiUSC5cuXo1OnTvD09ERYWBjq1q2rkraUgampKby9vXH8+HG8evUKXl5eOHv27KcdkteuXYvnz58XeP6KERvx4OZ\/EGXlFLtNUZYI83ovQceWjujWrRsuXbqEevXqFVg+75xdHp7CGDRoENatWwcXFxfcvXuXazlKRyNjukWZrp6eHlxdXXH06FFMmDBBqe3HxMTA29sbhoaGiIiIgK2trVLrVzUGBgYYOHAgBg4ciOzsbISFheHIkSNYvHgxbGxs4ObmBnd39087JD+89RjhxyPzGa6MpHiA23iHZIiRA31UQX00hymz\/FRGLJKgZ3N3zJkzp0hdXbp0wbt373D79u0yl\/SHR\/0MHDgQjDF0794dp0+fRsuWLbmWpDQ0rqdb1EDaR5QdYhCLxVi8eDGcnZ0xevRohIaGljnD\/ZJKlSrB1dUVO3bsQEJCAlatWoWkpCS4uLigcePGmDt3Lrb+shvi7Pw9XAJBD\/poA0c4oS\/qoRnu4QaElPmpDAPDy9gEJD4rOowhEAgwcuRIvrfLU2wGDBiATZs2oUePHpxnGFQmGmm6xdkFt3v37oiIiMDbt2+\/us3o6Gh06NABly5dQmRkJMaOHZsvLlnW0dbWhpOTE9avX4\/4+Hjs2bMH4iwJ7py9D5ks\/7b0Wkwb9Vgz6LMqYIzBjNWEPqogHZ\/njJDJCIEbTxVLw8iRI7F\/\/34IhUKlXBNP+ad\/\/\/7YvHkzevbsicjISK7lKIUya7qVK1eGi4sLgoKCSt1WTk4OFi5ciC5dumDixIk4ffo0atcufHv38gBjDO3atUM\/Jw9UNahSrHNElI0sfEBVGH72vCRHgqtHbxarjtq1a6Nt27Y4evRoiTXzVFzc3d3h5+eHXr16ISIigms5X43GmW5xBtI+8jUhhjt37uCbb77BzZs3cfv2bXh7e5e73m1RfHiXAZm06FVuMpIhFjdhCRtUYYb5jme+zyp2m\/yAGk9p6NevH7Zu3QpXV1fcunWLazlfhcaZbnF7ugDg6uqKK1euIC0trdj15+TkYP78+XBxccH06dMRHByMWrVqlVZumYYJir7JEBFicRMMAjSC4gGwktys+vbti+joaDx9+rTY5\/DwAPLPzvbt2+Hq6oobN25wLafUaKTpFnd1lYGBAZycnBAcHFys8pGRkWjbti3u3LmDO3fuwNPTs8L1bvNiaGIAgVbBHwEiwn1EIAci2MEBAqa4bFWj4oUoAPnMk6FDh8Lf37\/Eenl4evfuDX9\/f\/Tu3RvXr1\/nWk6p0EjTLW5PFyheiEEkEmHevHno1asXZs2ahaCgINSsWfNrpZZ57J2aQSqWFnj8AW4jEx9gj++gxRQn9NGtpIPOQzuWqN1Ro0Zh165dkEoLbpuHpyB++OEH7Ny5E3369EF4eLjCMjKZDK8eJ+DBzf\/wMOIJEp8ly9MqagBlcp5uXvr06YPJkycjIyMDVatWzXf85s2bGDlyJBo2bIi7d+\/CwsJCmXLLNJUN9OH8Y0eE7r4AqeTz2K6QMvEKTyGAAJdxHMj9vDZGG1iy\/w02EgE\/jHMpUbstWrSAlZUVQkJC0KtXr6++Dp6Kh6urK3bv3o2+ffsiMDAQ3377LQAg\/d0HnPY\/j8NrjiMrXQgtHXlnQZIjQXVLYwz8uS+6DO0I\/arKyVVSGjTOdEsykAYAxsbG6NChA06dOoUBAwZ8ej47OxsLFizA7t27sXbtWgwaNKhChxIKov\/UH3Du7yuQSj6fq6vPqqArPAo9VyBgaNWlOUwsjUvc7scBNd50eUpLz5498ddff6Ffv344cuQIXlx5g72L\/gETMIWrKxOeJsHvp934c8ZuTN48Gi6eTuoXjXIQXgDyhxjCw8PRsmVLxMXFITo6GoMHD+YNtwBsm1mj56jOYKW4\/eob6GPShlGlanfw4MEICwsrdn4I0R+WZwAAHHtJREFUHh5F9OjRA3v27IFPt5nYs+gQcrLFhS5nz84UQZQlwvoJ23BgOTdTFzXSdEuaprBfv344ffo03r17hxkzZsDd3R2\/\/\/47Dh069Cm9II9iZDIZojKuQmwkhF5l3aJPAMAYIGUSDFnRG5Z1apSqXUNDQ\/Tr1w979uwp1fk8PB9JvSOEJWwgzpYU+xxRVg72\/h6Ac\/svq1CZYjTSdEva0zU3N0edOnXQokULvH79GtHR0Z+FGngUI5VK4e3tjadPn+LYk\/0Y+HNf6OnrolIVxTtFCLQE0KusB9vmtTFu+4+Y\/MtE\/Pvvv6Vu\/2OIQVMGOHjKHhlpmdiz8BDEos8N9wU9xg0KQxgdQSwpntcrysrBhok7IBEX36yVgUbEdIkIjyKfIuX1O2il6CMu4gXMjWvAyKxakedmZmZi3rx5ePr0KVq3bo39+\/erQXHZRyKRwMvLCwkJCThx4gSqVKkCzwUDMWBGb4Ttu4KDKwKR\/PwNtHW1Py0T\/t6jAzym90aD1vKMayItIXr27Ilr166VajZIx44dIZVKcf36dX47H55SEbLrvML55nrQRx00RgqSIEPBs2SkUinCj0WgU\/8OqpT5GaywXkbbtm1JlcvuMtIyEbLrPAJWH0fm+ywwLQE+vE+HgaEBxDkSfNOjFQb81AdNHRoqjMlevHgRo0aNgoODA2bNmgVHR0ckJCRAV7d4P5MrKhKJBMOHD0dKSgoCAwML\/GWRk52DzPdZ0NHTQWVDfYW5hBcvXoyAgABcunQJBgYGJdayfPly\/Pfff9i+fXuJz+Wp2BARhliPQ8rr1ALLPKYYiCBEM9auwDKN2tXDxhvLlKqNMRZJRG0VHuPKdK8G3sTSYevBAGRniRSWYYxBr7IuGrSui9+Pz0YVQ7k5ZGRkYPbs2Th69Ci2bNmCPn36AAAcHBzw22+\/oXv37irRXB4Qi8UYOnQoPnz4gCNHjnz1Nj9EhPHjxyMuLg7BwcHQ0dEp0fmJiYlo0qQJXrx4oXDKHw9PQSTHv4F3k6kQCQseOCuO6TIBw6ns\/dDSLv3msvnqLMR0OYnphuw6j6VD10GUJSrQcAH5Fzo7U4QHN\/\/DxHazkfk+E+fOnYOdnR0yMjIQExPzyXABbjetLAvk5ORg0KBByMrKwtGjR5WyrxpjDBs3boSuri7GjBlT4vishYUFvv\/+exw6dOirtfBULNLfZXyah\/s1aOtoIyMts+iCSkLtpnv3YizWT9xe6N3pS8QiCZLj32Bw49EY4TkCGzZswK5du2Bs\/Pn80P79+yMwMJBf6aQAkUiEAQMGQCqV4vDhw6hUqZLS6tbW1saBAwdw\/\/59LFiwoMTn80lweEqD0rbOIipWHhJlofaBtC1TdyGnAMNNpBd4ivvIRhb0UAlN0RbGzAyA3HglKcDf\/xxCJ1fFgy516tRBrVq1cPnyZTg5OanqEsoc2dnZ8PDwgK6uLg4cOKCSmHeVKlUQHByMb7\/9FtbW1hjz\/+3de1xU9b7\/8dfiNiBqCpKiKCI3xQEUBBIHTTAzUjQvqF0szcqy1E6nTNun9FHtdpmPrTu3v73d2XFv7eb5WduT19S0Dbp1RtAEFVS8gJAiiIAKDDOzzh\/G5DQDggwzg\/N9Ph78w1pr1nemeLvm870991yzr01NTWXOnDmcPHnSuKOFIFhiMBjIy8tDrVZzYO+\/uVF9A6mVz456vQHv+1o2Yqo1bPqkey7nAhdPlVg8Vi5f5gw5DGQII5lALA\/ihWmNT9bBtv+3p8l7iBKDqdraWh577DG8vLz4+uuv27ST8f7772fHjh28\/fbbbN26tdnXubm5MWPGDLEIjmCmuLiYb7\/9lkWLFpGSkkLXrl1JS0tj165dDIyJwK9PN4vXGWQDelnPrT1QZPSyHoNseRnTmJRIXF2tV8+9E5t2pH387Gp2\/eNHi2u4auQf6EkQvaSgJl\/DXeHO309\/gl+Ar8XjeXl5pKSkUFRU5DA799pLTU0N48ePx9fXl\/Xr1+PmZpsvNocOHWLs2LFs27aNuLjGOzBud+rUKYYPH05RUVGLO+OEe0NVVRWHDx9GrVajVqs5dOgQWq2WhIQE4uPjiY+PJy4uDl\/fX\/\/2v\/\/7Pla9spaa67Umr1UgH+ccpmPIgxhAsDTQ5HdeHT1Z8u0bxKREWvW9NNWRZtPywpE9ORYDV5ZlqqjAj57sl7djwIAfPQklymx1KzcPN\/IOnW40dPv370+XLl04dOiQU4\/9vHnzJuPGjcPf359169bZLHABEhISWLt2LePHjycjI6PJXYIbhIWFERYWxpYtW3jsscds0ErBnrRaLTk5OSYBW1hYyODBg4mPj2fq1KksX76cvn37NjmFf0T6UFa9Yt4fECwNJJiBFq4w5d2lA4OTla16Ly1l09C9WW15bywttcjIXKaYITyIhAs\/cYBznCQE0w9E1huormi6p7GhxOCsoXv9+nXGjh1LYGAgn332mU2\/OjVIS0ujpKSERx55hP379+Pn53fHaxo61ETo3ltkWaagoMAYrmq1mmPHjhEcHEx8fDxDhw5l\/vz5KJXKFj8cKLwUvLb2JZbNXNXkmguWr\/Vg0Yb5Nl+Xxaah29g4OBdu\/b43wSikW8OY+sihnCPPLHT1Bj3Xb1Yjy3KjH9akSZOYMGECy5Ytc7qFbqqrq0lNTSUsLIw1a9bYJXAbzJkzh8LCQtLS0tizZ88dp3dPnjyZV199leLiYnr16mWjVgrWVlpaikajMQasRqOhY8eOxhLBxIkTiY2Ntdq47BFThlJx+RqfLtzQ7FFRCi8PFv7jFaKGR1ilDS1h05rubOWrXDhx0eKxDHkrwSjpKQUCUCoXc5aTPCCNMjlPdjVwzjuXCpcrKJVK409kZCQDBw7Ex8cHWZYJDQ1l48aNxMTEWK39jq6qqooxY8agVCr5y1\/+4hA1bVmWmTFjBtXV1WzatOmO\/wjMmTOHPn36sHjxYhu1UGiNmzdvkp2dbQxYtVrNtWvXiIuLM6nD+vv7t3lb9v9TzR9f+CvaGq1ZjRduLdSk8PakU1dv3lw\/r00D12FmpH2zciv\/\/daXFidEFMjHKecSgxj2S3lhP13xI1gyfdLt0NmL\/7m8lmuVFeTm5pr9dOrUCaVSydWrV+nevTvvvPMOEREReHs3f0uZ9ujatWuMGTOGmJgYVq1a5RCB20Cr1ZKamkp4eDirVq1q8tuHRqNh2rRpnD592qHeg3BrnYITJ06YBOzp06dRKpXGgI2Pjyc0NNRu\/+30ej2Hdxzl6482k7s\/D1dXF2RANsgMeXgQ6a+nETU8os2\/ATtM6F6\/doOpPZ9DW1tvdswgGzjFUS5RhAsudKc3IUSadKS5e7gxYV4qz3\/0lMXXl2WZoqIicnJy2L59O+vXr6dfv37k5+fTs2dPkydjpVJJWFjYPbFOQ0VFBaNHjyYxMZEVK1Y4ZEmlsrKS4cOH8\/jjj7Nw4cJGz5NlmejoaFauXMnIkSNt2ELhdg1\/S7cHbHZ2Nr169TKGa0JCAlFRUSgUllelszeDwUBNdQ2SiwteHT1t+nfhMKEL8IcZn\/Djxv3otC2fNebh6c5nJ1fSPfDOnTKyLBMYGMj27dsJDw+noKDA+DSck5NDbm4uFy5cIDg4mMjISJMwDgoKajdPWeXl5Tz00EM8+OCDLF++3CEDt0FxcTGJiYn8\/ve\/54knnmj0vJUrV6LRaNiwYYMNW+fcKioq0Gg0xoBVq9UAxuFaCQkJDBkyhC5duti5pe2DQ4VuVXk1Lwz+T66WVBiXDGwORQcFs96fzsT5jzb7mgULFuDj48Pbb79t8XhtbS15eXlmJYqysjIGDBhgVjP29\/d3qFArKytj1KhRjB49mg8\/\/NCh2taY3NxckpOT+eqrr0hOTrZ4Tnl5OcHBwZw\/f178kbeBuro6jh49ahKwJSUlxMbGGgM2Pj6egICAdvH\/lCNyqNAFuHS+lAVJ\/0VlaSW6JnajbaDo4MGU19J4eunUFt0nIyODl19+mZ9++qlF11VVVXH8+HGzMK6vrzcrUSiVSnx8fFr0+tZQWlrKqFGjGDt2LO+\/\/367+uPYt28f6enp7N69m6ioKIvnTJ06lREjRvDSSy\/ZuHX3FoPBwKlTp0wC9vjx44SFhZkE7IABA+w60uVe43ChC1BZVsWKF9ZwaFs2kotkcT0Gz46eeHf24vmPZ5A8rWXbfMOtonqvXr3IzMwkJCSk1W0uLS3l+PHjxvJEw0\/Hjh3NShRt2Xl3+fJlkpOTmTRpEkuXLm1Xgdvgq6++4vXXX+fAgQP07t3b7Pj333\/PokWLyMrKskPr2q+ff\/7ZJGA1Gg0+Pj4mATt48OAW784itIxDhm6Da1cq2fbpHrau2UXllWr0Oj2eHRSEx4eQ\/vp4BicrWxUqL774In379m2y86Y1Gjocbg\/hnJwc8vPz8ff3N5YmrNV59\/PPP5OcnMz06dMbLZu0Fx9\/\/DHr1q0jMzPTrIxgMBgICgpi8+bNDBo0yE4tdGzV1dVkZWWZzOq6efOmScDGxcU1a2KKYF0OHbptbffu3SxevNjYMWArOp3OpPOu4ef8+fMEBweb1Yub03lXXFxMcnIyM2bM4K233rLRO2k7siwzf\/58cnJy2LFjh1kv+JIlSygvL+eTTz6xUwsdR319Pbm5uSYBe+7cOaKjo03WJujXr1+7\/OZzr3Hq0K2vr8ff35\/s7Gz69Olj7+a0qPNOqVTSs2dPJEmiqKiI5ORkZs+e3WZP7fag1+tJT09HoVCwYcMGk394Lly4QGxsLBcvXrTq+r+OTpZlzp07Z1ImOHr0KIGBgSYBGxkZKRYHclBOHboAs2bNIioqigULFti7KY2qqqrixIkTZvXi+vp6QkNDjaunLViwwG6dd22lpqaGUaNGoVKp+PDDD02OjR49mpkzZzJ9+nQ7ta7tlZWVmQ3XUigUJgEbGxtL586d7d1UoZmcPnS3bt3KH\/7wBzIybL\/HfWtpNBrGjRvHsGHD8PX1Nem8+229uD3PvCsvLycxMZFXXnmFl19+2fj7r7\/+mr\/97W\/s3r3bjq2znpqaGo4cOWJSJigrKzObNivWnmjfnD506+rq6NGjBydPnqRHjx72bk6zFRQUkJyczBtvvMHcuXONv7fUeZebm0teXp6x8+72n\/Dw8HYx8+7cuXOoVCpWrVplXGmsrq6OgIAA1Go1QUFNr7XsaPR6vXGXg4aZXfn5+URERJhMmw0PD283k3GE5nH60AV44oknUKlUvPjii\/ZuSrOcPn2alJQUFi9ezJw5c5p1TUs67xpm3jna2MysrCzGjBnD5s2bSUxMBGD+\/PkEBriyYE4v0J0Gww1w6QTuSiSvKUiu9u+dl2WZ4uJik4DNysqiR48eJgE7aNAgp6pPOysRusA333zD6tWr28XX1Pz8fFJSUliyZAmzZ89u9evV1taSn59vVi++cuUKERERjXbe2cv27duZOXMmP\/74I2F9y7h+eRmuhuMoPD2QuH3dDgUgg8cwpI4vIXlE26yNlZWVHD582GRtAp1OZ7bLwb1UexeaT4Qut5ag8\/f35+zZsybbfTiaEydO8NBDD\/Hee+8xc+bMNr1XQ+fdb9ek0Gq1JsPZ7DHzbu3aT7lR+gFzZ3ojYb5MnykJUECnxbh4T7N6W7RaLceOHTN5ii0qKiImJsbkKTYwMFAM1xIAEbpGkydPJjU1lVmzZtm7KRbl5uYa11F46inLK6nZQsPMu9+WKby9vc3GF7dV552h+o9or63Bw70lCyN5Que3cekw+a7vK8syZ86cMXmCzcnJISQkxCRgBw4caNMtkIT2RYTuL7788ks2bNjQop1qbeXYsWM8\/PDDLF++nMcff9zezTFjy847uS4TuWIuYHl7p6Z5Ivn+D5J7eLPOvnz5stm02c6dO5ssXxgTE9NuR4UI9iFC9xdVVVUEBARQVFTEfffdZ+\/mGB05coRHHnmEP\/3pT6Snp9u7OS2i0+k4e\/asSXmitZ13hvJpUJ9t8VjyxIsczK6lYeenXv5unMzse9sZruCZhkuXD82uvXHjhsm0WbVaTWVlpUnAxsXF0b1797v8NAThFhG6txk3bhzTpk1rcj1XW8rKyiI1NZXVq1czadIkezfHaho6735bL75y5YrJzLuGmnFD552sK0QuexQw310EboXu45M6MfuJpv7RVGDw+RfHTxaaBOyZM2eIjIw0CdmQkBBRhxWszmG2YHcEDTsFO0LoqtVqxo0bx5o1axg\/fry9m2NVnp6eREdHEx1tOqLgt513O3bsIDc3l7q6OpRKJW8tUJDyQD2tGclWU6tl0dz+7Mr0MQbsCy+8QFRUVLsYryzc25zuSffq1asEBQVRUlJi1zrdwYMHSUtL47PPPmPs2LF2a4ejuHLlCrm5ufTt8j6B\/oWNnpc88SLH87XIskx4iAfvvunLg4nmyxRqXafj6be0LZssCI1q6knX6abB+Pj4kJCQwPbt2+3Whv3795OWlsa6detE4P7Cz8+PkSNHEtinW5PnffC7bpw51JeiI0HMfvI+xs8ooeC8+VrMHh53GmYmCPbhdKELv5YY7OFf\/\/oXEyZMYP369aSmptqlDY5MpmOTxxNiPOnU0QWFwoWn0zuTGOfF9j03zU+UxKQEwTE5XU0XYMKECSxcuJDa2lqbTsncu3cv6enpfPnll4waNcpm93VktbW1aDQaMjIyyMzMZMSQo8yb3RFFM0uvkgTmFbIOSG6t3ylEENqCUz7pdu\/enejoaHbt2mWze+7evZv09HQ2btzo1IFbUVHBli1bePPNN40rp7322muUl5fz3HPP8ezcnSga6ey6Vqln594b1NYa0OlkPt9URcbBGh4e+duargyej7T9mxGEu+CUT7rwa4lh3LhxbX6vnTt38uSTT7Jp0yaGDx\/e5vdzJIWFhWRmZhqfZC9cuEBCQgIqlYp3332XhIQEsw5Nw9UhoD1g9lr19TJvf1hO3hktrq4S\/UM8+Oa\/\/QkLvj2k3cBrApKL2ANMcExON3qhwcWLF4mOjubSpUttuvr+tm3beOaZZ\/j2228ZNmxYm93HERgMBk6cOGEM2MzMTGpqakhKSkKlUpGUlER0dPQdP29Zexj56iy445oLlngidftfJLe+d\/MWBMEqxDhdCwICAggNDWXv3r2MHj26Te7x3Xff8eyzz7J582aGDh3aJvewp7q6Og4fPmwM2P379+Pr64tKpSIlJYV33nmH0NDQFk8+kDyGIHf6D7j+R5BbMhXYE6nLchG4gkNz2tAFmDhxIps2bWqT0P3nP\/\/J888\/z5YtW4iPj7f669tDZWUlBw4cMJYLsrOzCQ8PJykpiaeffpo1a9bg7+9vlXu5eD+DAVeoXgZoAUMTZ7sC7khdPkbyfMgq9xeEtuK05QW4tTNDYmIiJSUlVl3Me9OmTbz00kts27aN2NhYq72urRUXF5vUYwsKCoiLi0OlUqFSqRg6dCidOnVq0zbI9ceRr6+Buh+4tYTj7SWHDoABvNKQvGchufVr07YIQnOJ8kIjgoOD8ff3vzVUacQIq7zmxo0bmTdvHjt27GDw4MFWeU1bkGWZvLw8k3psVVWVMWCfeuopBg8ebPNptJL7QKSuK5ENFcg134HuLMhVIHVBcu8Pno8iuYgVwIT2w6lDF34dxWCN0P3iiy947bXX2Llzp9maA45Gq9WSnZ1tDNjMzEw6d+5s7PBatGgR\/fv3d5jFYCSXrkjeM+zdDEFoNacuL8CtnRpGjx5NYWFhqzYHXL9+PQsXLuT7779HqVRasYXWUV1dzb\/\/\/W9juUCj0RASEmIcWaBSqcQOtIJgJaK80ISIiAg6deqEWq3mgQceuKvXWLduHW+99RZ79uxhwIABVm7h3bl06ZJJPTY\/P5\/Y2FhUKhULFy5k6NChDrWmsCA4C6cPXfi1xHA3ofvpp5+ydOlSfvjhB8LDm7dbgbXJsszp06eNAZuRkcHVq1cZNmwYSUlJfPLJJ8TGxqJQKOzSPkEQfuX05QW4tXPDpEmTKCgoaFEN869\/\/Svvv\/8+e\/bsITQ0tA1baEqn03HkyBGTJ1kvLy+TUkFERESryiWCINw9UV64g0GDBgGgyc6mW78gquvq8HBzw6+DN906WJ5O+uc\/\/5mPPvqIvXv3Ehwc3Kbtu379OocOHTIGrFqtpm\/fvqhUKiZPnsyKFSvo06dPm7ZBEATrEKELXKyqIuTZZ3gyYy8e6v24ShIyoNXriby\/Oy\/ExjGybz9cf3lyXLFiBStXrmTfvn0EBQVZvT2lpaUmowpOnDjBoEGDUKlUvPrqqyQmJtK1a1er31cQhLbn1OWFOp2ON3bv5PuC0+gNBnSNfBbe7u54urnzadpj7N7wOatXr+aHH34gMDCw1W2QZZmCggJjwGZkZHD58mUSExON5YK4uDibLkEpCELriPKCBbW6eqZv2kh+eRl1en2T596or+dGfT1TvtqA\/rvv2LdvH717976r++p0Oo4dO2ZSj3V1dTUG7Lx58xg4cKBVZ8gJguA4nDJ0ZVlm7rbvyCsro06va\/Z1OknCa8pEajp4NfuamzdvolarjQF78OBBAgICUKlUpKWlsWzZMgIDAx1mEoIgCG3LKUNXU1LMwYsXLQau\/sZNyr7cSE1+Pi7e3viMTaXjkBjj8Rq9jvcy9vGPCZMtvnZ5eblJPfbYsWNERUWhUqmYO3cun3\/+Od26Nb0PmCAI9y6nDN01WRpqdfUWj5X\/\/2+Q3Fzp894StBdLuLRmLR69euLh38N4jqb4IiXVVfh37MT58+dN6rHFxcU88MADJCUl8cEHHxAfH0+HRkZACILgfJwudK\/cuEFm0QUsdZkZ6uq48VMOAW\/+Jy4KBZ7BQXRQRnBdk4VP2qPG83R6PVPeXcqFL75Gr9cb67Fz5swhMjISNzen+1gFQWgmp0uHg8VFuLu4orXQeVZ\/pQzJxQX3+\/2Mv1P06knNmQKT8\/SAtk8AP\/74I\/369RP1WEEQms3pQvdabS162fKC2HJdHS6\/GZoleXoi19WZnSt5erb5pAhBEO49TjdP1LWJp1JJocBQa7ovl1xbi2RhzQIXxNOtIAgt53Sh29XLCzfJ8tt29+uGbDBQX3rF+Dttyc949Ohhdu59YrKCIAh3welCd1jvQOoNlidDuCgUeEdFUrF9J4a6OmrPnuNGznE6xpluuePp5sbE\/hG2aK4gCPcYpwvdzgoFqaHhjZYZfKdMRK6vp\/B3Syj9++d0mzLRZLgY3JpckT4w0hbNFQThHuN0HWkAswfHsv3MKfQ688kRrt4d6D57ZqPXukgSyUHBdPVq\/qw0QRCEBk73pAswwO9+pkQo8bqL8bT3KRT8LulB6zdKEASn4JShC\/DOiGSSg4KbHbyukkRnhYIvJk3Fv423HRcE4d7ltKHrIkn8acyjvBAbh5ebGx3c3S2e5ypJeLq5oby\/O1unzyDcV6ybIAjC3XPKmm4DSZKYl5DI7Jg4vss\/yV+yNBRWXsPd1RW9wYC7iyvj+w9g1qBYQn197d1cQRDuAU4dug06uLszVRnFVGUUOoOB6ro6PN3c8HRzE1N8BUGwKhG6v+Hm4iJGJgiC0GactqYrCIJgDyJ0BUEQbEiEriAIgg2J0BUEQbAhEbqCIAg2JEJXEATBhkToCoIg2JAIXUEQBBuSZNnSvri\/HJSkK8AF2zVHEAThnhAoy7KfpQNNhq4gCIJgXaK8IAiCYEMidAVBEGxIhK4gCIINidAVBEGwIRG6giAINvR\/abtZaB0qKisAAAAASUVORK5CYII=\" \/><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing code_cell rendered\">\n<div class=\"input\">\n<div class=\"inner_cell\">\n<div class=\"input_area\">\n<div class=\" highlight hl-python\">\n<pre><span class=\"n\">color_classical<\/span> <span class=\"o\">=<\/span> <span class=\"n\">graph_coloring_classical<\/span><span class=\"p\">(<\/span><span class=\"n\">g<\/span><span class=\"p\">)<\/span>\n<span class=\"nb\">print<\/span><span class=\"p\">(<\/span><span class=\"n\">color_classical<\/span><span class=\"p\">)<\/span>\n<span class=\"n\">nx<\/span><span class=\"o\">.<\/span><span class=\"n\">draw_networkx<\/span><span class=\"p\">(<\/span><span class=\"n\">g<\/span><span class=\"p\">,<\/span> <span class=\"n\">node_color<\/span><span class=\"o\">=<\/span><span class=\"n\">color_classical<\/span><span class=\"p\">)<\/span>\n<span class=\"n\">plt<\/span><span class=\"o\">.<\/span><span class=\"n\">title<\/span><span class=\"p\">(<\/span><span class=\"s2\">\"Classical Graph Coloring\"<\/span><span class=\"p\">)<\/span>\n<span class=\"n\">plt<\/span><span class=\"o\">.<\/span><span class=\"n\">show<\/span><span class=\"p\">()<\/span>\n<\/pre>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"output_wrapper\">\n<div class=\"output\">\n<div class=\"output_area\">\n<div class=\"prompt\"><\/div>\n<div class=\"output_subarea output_stream output_stdout output_text\">\n<pre>[1, 0, 0, 0, 1, 2, 0, 1, 0, 2]\n<\/pre>\n<\/div>\n<\/div>\n<div class=\"output_area\">\n<div class=\"prompt\"><\/div>\n<div class=\"output_png output_subarea \"><img decoding=\"async\" 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JUSdFNSkpC3bp1ERkZKbf468fMBm9vb\/z4448VFi\/994\/z2PH9vlIL7kd0DXQwa+dkdBnR4Yv7TklJwd27d6WEWE9PTypTwtXVFYaGhl\/cBw+PulMlRXfbtm24efMmfHx85NrP+\/fv4enpCRcXF+zYsaPcmQ3ZmTkYYjUBwizZ4YRYeotXeIIcZEEXenCGG0zZ\/07CMDDWx4m43dDWqZjlxUSEV69eScWGHz9+DAcHBykhdnR05HOHeXjyqZKi26JFC6xbtw5dunSRe18ZGRnw8vJCRkZGuTMbAndfxPZZe2XGcBPpA54iBE3gDmOYQQjJlpJ6TL+gjn41Pcz+wxtfDZPPKjoAyMnJwYMHD6SEODk5uVDusEAgkJsNPDyqTJUT3fv376N\/\/\/6IjIxUmPclFosxZ84cnD17Fv7+\/l+U2UBE+NZxBqIjCp\/ZBgB36RJqoA5sWZ1i26nnYo8d99aXuf\/yEBcXJzVJd\/fuXVhYWEilrLm4uCg9x\/lziEsBxB8AygE0DAFNW7BPvsR4eL6E4kRXLaep9+7di7Fjxyp0uKupqYlNmzZh27ZtaNu2LU6ePInWrVuXqY2U+DTERSXILCMipCEZFqiBGxQIDhwsUAMN0BSaTFOq7uvHUcjOyIZ+NcWJh6WlJTw9PeHp6QlAsu\/ws2fPCjzhXbt2ISIiAk2bNpUSYnt7e4XnDhMRkHsblLkLyL0DMB1IzgvhABKD9PuBGY4B06qvULt4qgZq5+nm5OSgZs2aCA4Ohr29vVJs8Pf3x7fffovffvsN33zzTanvi3r2Ht+5L0B2euGTKISUjWvwhxFM4YI2YNDAQ9yEKSxQnzWWqqtroIs9TzfBspZqDe8zMjIQEhIiNUmXl5dXIMAfc4eNjY3lZgPlRYKSJwBcIkBFnfisCUAb0HEDq74FTIPfcIinbFQpT\/f06dNwcXFRmuACQO\/evXH+\/Hl4enri5cuXWLBgQam8OQ0NhqKOMtaAxJuthXrQzR\/+1qYGiMQz1Ie06GZnZ2HAgP4Q2JrDwsKi2Je+vuK84WrVqqFjx47o2LEjAInH+TF3+Pbt21i6dCnu378Pe3t7qZS1Ro0aQVNTs4TWS4ZET0BJIwHKRJFvNABALHnlBoESBwLmx8E0TMrdPw8PoIaiu3v3bowbN07ZZsDFxQW3b9+Gp6cnIiIisGPHjhI3LDc2N4IoN09mmTbTgS7pA\/ifeDPIFnItDW2sXLMCKekpiI+PR3x8PKKiohASElLwe0JCAuLj46GpqVmiMH98CQQCGBsbV1g4gDGGWrVqoVatWhg8eDAAQCQSITQ0FHfu3MGNGzewceNGvH\/\/Hm5ublJCbGNjU6a+SBwLShoDUEYZ7soFxNGgpHGA+REwxm84z1N+1Cq8EBUVhebNm+Pdu3cK9eCKIyMjA8OHD0dWVhZ8fX1LXHY7yWUOIh9FySx7SWFIRCxc0DY\/vHADprBAvc\/CC86tHbD5xqoSbSMiZGRkFAhxSa+EhATk5uZCIBCUWqTNzMzKHVtPTk5GUFCQVLaEoaFhodzh4v7mXOpCIPtvSLxYab4e+A637+VAK9+ZtrXRwtPr9p\/UMAAz+RlMv1e5noOn6lBlshdWrFiB2NhY\/Pbbb8o2RQqxWIzvv\/8e58+fh7+\/P+rUKTr74JLPNfw6eafMlDGOOITjAWLxFhrQgBVqoT6aSE2k6RvpYcFfM9CmX0u5PEt2dnaBl1yaV3p6OszMzEot0gKBoMQRAREhIiJCKlviyZMncHJykhLiBg0aQENDA8RlgOLaAJB9avPXA9\/Ba5ARJowoJoSg5QwNgV853jmeqkSViOlyHIe9e\/fi+PHjyjalEJqamti8eTO2bt1akNng4eFRqJ5YLMaThEfIzMqEpow\/jQbTgBNawAktCpV9RFtHG+59ii4vL\/r6+gUhgdIgEomQmJgoU5CfPHlS6FpSUhKMjIxKJdAdOnTAoEGDoK+vj+zsbNy\/fx937txBQEBAwe5yrVq1wrRxZujelivwZL+IvFcg0Qsw7QblaISHR41E98qVKzAyMkKLFvITnPIyffp01KlTB56enti+fbvUpur37t2Dt7c3dHV1MXnDdBxZfArC7DIuA9bXwbz931XIpFNFoa2tDWtra1hbW5eqPsdxSE5OlinSr1+\/xt27dwtd19HRKSTKQ4YMgZ6eHlJTU1Hb6hq0NIt\/Lxf9nIiFqxLgWF8HKxaYo1Mbg89qiIHcawAvujzlRG1Ed8+ePRg3bpzK7xfbp08fnDt3Dn379sXLly8xZcoU\/PTTTzhy5AjWrFmDMWPGQENDA9W0jbBr\/sFSC6+Ovg6mbR0H916q+6VTGjQ0NGBubg5zc3M4OTmVWJ+IkJaWJjU5+OkrNTUVhvqiYttYvVgAZwcd6GgDR05loN\/oaNy7UBv17D9dyCECcSlFTF3y8JQetYjppqamws7ODhEREZVm6enbt2\/Rvn17xMfHY+jQoVi\/fj3Mzc2l6lz\/+w42TtyBPFGezNxdQBLD1dXTwQ97p1V6wZUXXEI\/IO9pqev3HP4evbsY4rvxn016Gk6DhtHMCraORx1R+5jukSNH0LVr10ojuC9fvsS0adNgaGiIGjVqICoqSmZIoN0Ad7T2dMMd\/3s4us4Pz+68gKaOFkCAKFcEPSstLPpzFtx6uKhUSEHl0DAvuc4nMAYU9kV0wTQUe1oIj3qiFttCfQwtqDpCoRArVqyAu7s7OnfujAcPHuDatWtwdnZGmzZtEBkZWegeTS1NtOnXEptvrIJ\/tg983vwOn6jf8fOteXhZ\/SHce7vyglsCTL8\/wGRvRZmSKsbZ\/zKRk8MhL49wyDcN125no\/tX0jFdYa4QPr4fkJiYqAiTedSYSi+6jx8\/xvv379GtWzdlm1Isly5dQrNmzRASEoKQkBDMnTsX2tra0NTUxJYtW+Dt7Y22bdvizp07Rbahpa2F6hYmqG5hghauLRATE4O4uDgFPkXlg4hw+bYuMjNlL\/kViQg\/rU2EVeNXsGz0Cr\/tScXJvTZwqCe9MU96dj2c9g9G3bp10adPH\/j4+CAjoywLLXh4JFR60d27dy\/GjBmjst7ehw8fMHLkSIwbNw7r1q2Dn58f7OzsCtWbMWMG\/vjjD\/Tp0wcnTpwosV1NTU20bdsWV69elYfZlR4iwrlz59C+fXt4e8\/Amzh3EArn\/1oItHDnTG2kRtRH0vN6uOlfC107fuYVMwNY2C\/A0aNH8e7dOwwbNgwHDx6Era0tvLy88M8\/\/yA3t2yZJjxVl0oturm5uTh48CDGjh2rbFMKIRaL8fvvv6NJkyawtbVFWFgY+vbtW+w9HzMbZs+ejXXr1qG4SU4A6NixI65cuVKRZld6iAj+\/v7w8PDArFmzMG3aNDx58gSNWm0FNAQQF16QVgJ6gE5rQEdyGoeRkRFGjhyJgIAAREREoF27dli3bh1q1KiByZMn4\/Lly+A4rsKfi0eNIKIiX66urqTK+Pr6UocOHZRtRiHu3btHrVq1orZt21JoaGiZ73\/79i01a9aMJkyYQLm5uUXWu3PnDjVp0qQ8pqoNHMeRn58ftWjRgpo0aULHjh0jsVhcUJ6Xl0ffTRlAcU+cKC+mIYljGpTi1YTECSOI44Ql9v\/69Wtas2YNNWvWjGxtbWnOnDkUEhJCHMfJ87F5VBQAwVSErlZqT1fVJtDS09Mxe\/Zs9OjRA5MnT8bVq1fRuHHjkm\/8jJo1a+LatWuIiYlBr169kJqaKrNe8+bN8fr1ayQlJZXX9EoLx3Hw9fVF8+bNsXTpUixevBgPHjzAkCFDCvZ84DgO48ePx9PwNBjZXQTTaQlAF0Un7+hJyvUHgZntA2Mlb7xuZ2eH+fPn48GDBzh79iz09PQwePBgODk5YdmyZQgPD6+oR+ap7BSlxqTinu779+\/J1NSUMjIylG0KcRxHx48fJ1tbWxo3bhzFx8dXSLsikYi+++47cnZ2psjISJl1unXrRn5+fhXSX2UiLy+PDh8+TI0aNSI3Nzc6ffq0TK+S4zjy9vam9u3bS31WONEbEqeuInGsC4ljnEgc04jEMY4k\/tCOxBl7iBOnlNtGjuPo9u3bNGPGDLKysiJXV1f65Zdf6N27d+Vum0e1QTGebqUV3dWrV9PEiROVbQZFRERQjx49qFGjRnTt2jW59LF582aysbGhO3fuFCpbtWoVzZ49Wy79qiIikYgOHDhAjo6O5OHhQYGBgUUO4TmOo5kzZ5K7uzulpqYW2SbHZRMnTixVGOFLEYlEdP78eRo7diyZmprSV199RX\/88QclJibKrU8e5aF2ostxHDVo0IBu3bqlNBtycnJoxYoVZG5uTmvXri029loRnDp1igQCAZ04cULq+vXr16lFixZy7VsVyM3Npb1791L9+vWpXbt2dP78+WLjpRzH0YIFC6h58+aUnJysQEtLJjs7m3x9fWnw4MFkbGxMffv2pcOHD6vEqI2nYlA70b127Ro1bNhQaZMUly5dIkdHR\/L09KTXr18rrN+QkBCytbWldevWFTy7UCikatWqUUpK+YfDqohQKKQ\/\/\/yT6tSpQ1999RX9999\/pfq7L1u2jBo3blxhoR55kZqaSvv27aPu3buTiYkJjRgxgvz9\/eX+Jc4jX9ROdMeOHUvr169XeL+xsbE0cuRIql27ttLiqFFRUdS0aVOaNGlSwT\/m119\/Tf\/++69S7JEXOTk59Pvvv1Pt2rWpa9eudPXq1VLfu27dOnJ0dKTY2Fg5WljxxMbG0tatW6l169YkEAjI29ubrl69KpWFwVM5UCvRTUtLo+rVqyv0H0osFtOOHTvIwsKC5s6dS+np6QrrWxZpaWnUq1cv6tq1K6WkpNDSpUtp7ty5SrWposjOzqatW7dSzZo1qWfPnnTz5s0y3b9lyxaqW7dupZ+sevXqFf3888\/UuHFjqlWrFs2dO5fu37\/Pp6BVEtRKdHfv3k39+vVTWH\/3798nd3d3atu2LT169Ehh\/ZaESCSiadOmUaNGjejw4cPk7u6ubJPKRWZmJm3cuJFq1KhBffv2paCgoDK3sXPnTqpdu7ZCQz6K4NGjR\/Tjjz+SnZ0dNWzYkJYvX04vXrxQtlk8xaBWotu2bVs6deqU3PtJS0ujWbNmkaWlJe3atUslh3gcx9GmTZvIxsaG9PX1le6Bfwnp6em0bt06srKyooEDB9K9e\/e+qJ2\/\/vqLbG1t1VqMOI6jGzdu0HfffUeWlpbUqlUr2rRpE0VHRyvbNJ7PUBvRffbsGVlZWcl1koHjODpx4gTVrFmTxo4dq\/ITMUSSzAYtLS1asmSJsk0pNampqfTzzz+TpaUlffPNN+UaRRw9epRsbGzoyZMnFWihaiMSiejMmTM0evRoql69OnXu3Jl2796tcpkaVRW1Ed358+fLNXb58uVL6tmzJzk7O9OVK1fk1o88GD9+PFWrVo3Wr1+v0nG\/5ORkWr58OQkEAvLy8qKwsLBytefn50dWVlb08OHDCrKw8pGVlUXHjx+nAQMGkLGxMfXv35+OHTtGWVlZyjatyqIWoisSicja2lou3kxOTg6tXLmSzM3Nac2aNSQUyi9JXl6cP3+e3NzcCmU2qAqJiYn0008\/kbm5OY0ePZqeP39e7jYDAwPJwsKCgoODK8BC9SA5OZn27NlDXbp0oerVq9OoUaMoMDBQ5T4P6o5aiO7p06epdevWFd7uf\/\/9R05OTtSnT58il9pWBjIyMsjQ0JBiY2OpZ8+e1K1bN5XI3Y2Pj6eFCxeSmZkZjR8\/niIiIiqk3YsXL5JAIKAbN25USHvqSExMDG3evJnc3d3JwsKCpk6dStevX1fJ+Ql1Qy1Et3\/\/\/rRr164Ka+\/Dhw80atQoqlWrFv39998qPSQvLR4eHnTp0iUSiUQ0ZcoUaty4sdJm8mNjY2nu3LlkZmZGkydPrtAvtGvXrpGFhQVdvny5wtpUdyIiImjFihXUsGFDsrOzowULFqhUNo66UelFNzY2lqpXr05paWnlbkssFtPOnTvJwsKCfvjhh0o5418U8+fPp\/\/7v\/8jIsmE4McUrJLSr1IT0+hV6Bt6eiec3j5\/T8LsLw+vREdH0+zZs8nU1JSmTZtGUVFRX9yWLO7cuUMWFhZ09uzZCm23qsBxHD148IDmzZtHtWrVokaNGtGqVavo1atXyjZNraj0orthwwb69ttvy93OgwcPyMPDg1q3bq2WEy8BAQHUqVMnqWt+fn4kEAjo5GrVwzUAACAASURBVMmTUtfFYjEFn3tA87oup566w8jTeBT1qz6aPI1GUp9qI2jLd7vobXjpU5Hevn1L06dPJ1NTU5o5c6ZcFifcv3+fLC0t6fTp0xXedlVELBbTtWvXaMqUKSQQCMjDw4O2bNlS6VbyqSKVWnQ5jiNnZ+cyLQP9nLS0NJo9ezZZWFjQn3\/+qbYxrdTUVKpWrRrl5ORIXQ8ODiZbW1vasGEDcRxHkY+jyMvOmzyNRlIXNljmq7vOUOqlP5yW9F1D2Zk5RfRI9ObNG5oyZQqZmprSnDlzKCYmRi7P9vjxY7K2tqbjx4\/Lpf2qTm5uLgUEBNDIkSPJxMSEunbtSnv37lWJeYHKSHGiq\/KbmAcFBSE3Nxft2rUr871EBF9fXzg7OyM5ORlhYWGYMGFCwebW6oaxsTGcnJwQFBQkdd3V1RU3b97E\/v37MXbQBMxovRDxbxOQnZFTZFtikRi5OSKEnH+I6R4\/Iis9W6o8MjISkyZNQvPmzWFiYoLnz59jw4YNsLa2rvDnCg8PR7du3bBhwwYMHjy4wtvnAbS1tdGzZ08cOHAA0dHRGD9+PPz8\/FC7dm0MHjwYvr6+yMkp+vPCU3pUXn0+ng7BGCvTfZGRkejTpw+WLFmCgwcPYu\/evbCwsJCTlapDhw4dZJ6bVrt2bfge\/Bvv\/01FdkYOqPjj1wrIzRHh\/YtYLOrzM8RiMV68eIGxY8fCzc0NVlZWCA8Px+rVq+X23kZGRqJLly5YsWIFRowYIZc+eKQxMDDA0KFD4efnh9evX6NHjx7Yvn07bGxsMHbsWJw7dw55eXnKNrPSotKim5WVhePHj2P06NGlvic3NxerV69Gy5Yt0b59ezx48AAdO3aUo5WqRceOHYs8IfjY6tNgnPSfnCMxnlAwrlMA\/iM\/3KbzSKAYqToioQgvQl5hWJdRaN26Nezt7REREYEVK1bA3Nxcbs\/y9u1bdO7cGfPnz1epY5mqEqamppgwYQIuXryIsLAwNG3aFIsXL0bNmjUxY8YM3L59WxKn5Ck1rLg3zM3NjYKDgxVojjQHDhzAkSNH4O\/vX6r6V65cwZQpU1C3bl1s3boVderUkbOFqkdycjLs7OyQmJgIbe3\/HTmelpSO4TUnIzdHJFVfTHl4jeeoAXvowQAJiMFjBMEDXaHPpI8iN65tiD0PN8PExETuzxETE4OOHTvC29sb33\/\/vdz74ykbL168wOHDh+Hj44Pc3FwMHz4cXl5eaNSokbJNUwkYYyFE5CarTCU8XaJckPAaKMsXlOUDyv4XlBdV6oMn4+LiMGbMGIwaNQqrVq3CP\/\/8UyUFF5B4JnXr1kVISIjU9TN7\/gPTKByi0WRaqMcaQZ8ZgjEGC1YD+jBEGpIL1c2Jy0VmQnah6xVNfHw8unTpgjFjxvCCq6I0aNAAP\/30E54+fQpfX1\/k5uaie\/fuaNasGdasWYPXr18r20SVRamiS+IYcOkbQHGtQSkzQGkrQGlrQGlLII7vhdXz3qBv92ogEsu8n+M4\/PHHH2jcuDEsLCzw5MkTDBgwoMzxX3WjY8eOheK613xvQ5iVW+K9QspBFtJRDcaFCxlDyPlHFWWmTJKSktC1a1cMGDAAixYtkmtfPOWHMYbmzZtj\/fr1iIqKwpYtW\/D69Wu4ubmhXbt2+O233xAXF6dsM1UKpYkul3UMFN8NyNwHUDpAmQCyAOQAlAkNlotWzbWgmTkflNgXJE6Uuv\/hw4do164d9u3bhwsXLmDDhg2oVq2aMh5F5ZAluulJGSXexxGHMATBBnYwZIVFN08oQkZyZoXZ+Tmpqano0aMHOnfujBUrVsitHx75oKGhgY4dO2LHjh2Ijo7GggULcPPmTTg4OBRkRqSnpyvbTKWjpYxOuczdQPpmAMKSK1MWkBcJSuwPmPshM1sXS5cuxV9\/\/YVVq1Zh\/PjxapsCVhR5eXlISUlBUlISEhMTkZSUVPBKTEzE+\/fvceHCBXTt2rWgns0bR+jDsMg2iQhhCAKDBhzRXGYdpsFkhigqgoyMDPTu3RstW7bEhg0bqvxopbKjo6ODPn36oE+fPsjMzMTp06fh4+OD7777Dt27d4eXlxd69uwJXV1dZZuqcBQuupTzX77gliXnLw\/gEpH6uj9cOr9Bp05f4\/Hjx7C0tJSXmQpBLBYjOTlZSjBl\/fz572lpaTAxMYG5uTnMzMxgZmYm9XOzZs1w9uxZ9OnTBx4eHjA3N8emUbvw\/M5LmXYQEZ4gGLkQwgXtoMFkf4lp62jD2Nyowt+H7Oxs9O3bF05OTti6dSsvuGqGoaEhhg8fjuHDhyMxMRG+vr7YtGkTxo0bhwEDBsDLywudOnWCpqZmhfQnFotxN\/ABbp4KQvKHVDANBvMaZuj0TRs07eis9M+X4kU3fS1kCe7T8FxMXxiHkEdCWJhrYu0SAQb0+jRckAdN9gGnT8xFU7fpCrO3NHwunsUJqCzx\/Fw0P\/7s4OAgdf1jmYmJSYkf0GfPnkEsFsPd3R0A0HNsZ0SFvZe5IOIZ7iMT6WiBDtBkRbcrFnNw792ifG\/WZwiFQgwYMAA2NjbYuXNnlRu1VDXMzc0xadIkTJo0Ce\/evcPRo0cxb948REdHY+jQofDy8kLLli2\/SBgzUzNx6rczOLnJH7lCEbLT\/\/dZZwy4cPAqjEwNMWSOJ3pP6godPZ2KfLRSo9CUMRI9AiWNAkh6Bjwvj9C44xtMHmWCGROr48qtbPQbHY2Q87XhUO+zN0bbDRrmPhVm06eIxWKkpKSU2uP8+HNR4lmUmJZFPL+Uo0ePwsfHB6dOnQIAZGfmYIjVBAizpEM62ZSJGwiEBjTA8L8PuhNcYcNqF\/zOGNCqVwus\/OfHCrNRJBJhyJAh0NLSwpEjR6ClpZRoF48K8Pz584IUNI7j4OXlheHDh6Nhw4aluv\/Dm3jM6fR\/SP6QUigt8nN0DXRg28AG687\/BBOBjAnjCqC4lDGFii6XMgvIOQOAk7r++JkQbXq\/RWpEvYJvuO5D38O9hR6Wz\/88+V4XTOAPplUbRSFLPEszfP9UPEsSzE+FtXr16nITzy8lNjYWzs7OSEhIKPAeN0\/5A2f2XEKeSHY2SHHoGOjg538XolmnisnDzMvLg5eXF7Kzs+Hr6wsdHeV4HTyqBREhJCQEPj4+OHr0KCwtLeHl5YVhw4ahVq1aMu9Jik3GZJe5SEtMByfmZNb5HC1tLVjZW2B78FoYGOlX5CMAKF50Feta5N7D54JbFATC42eFJ9py8wgXT61H0COzIsW0OPE0MzNDgwYN4O7uXqhMFcXzS7G2toaFhQVCQ0PRrFkzAMCY5UNx659gJMWklGkVkYa2Bj6I3yFW+A7NUH7R5TgO48aNQ0pKCk6fPs0LLk8BjDG4ubnBzc0N69evx9WrV+Hj4wMXFxc0atQIXl5eGDx4MAQCQcE9iz3XICM5o9SCCwB5ojzERSVg3ZhtWHpyrjwepUgUK7qUJfOyYz0dWAo0sWF7MmZNMsV\/N7Jw9VY2OrUxKNyEWITUlLcAJOIpayivTuJZHj7uw\/BRdKtbmOCXy8sws+1iZCRnQpxXssera6CLxu2c0G3uZIwcNRLTp0\/HggULvngygojg7e2NqKgoBAQEQE9P74va4VF\/NDU18dVXX+Grr77Ctm3bcPbsWfj4+GD+\/Plo166dZAVcraaIevq+0OjtLUUgGm+QgVRYoxYasZaF2hcJRQgKvI\/4d4mwqCm\/5eyfo9jwQlxrgEuUWfboiRAzF8Xj8XMhXJvqwcJcE7q6DLs2Wn1msQGY8VIw\/f4VZpe6cvDgQfz999\/w9fWVup4Yk4yVQzciPPglxGIOYhnhBj0DXXAcB0\/vbpi4fhQ0NTXx7t07DB48GDVq1MC+fftgbFy2eBgRYebMmQgODsbZs2dhZFTxmRA86k96enpBClr0+VQIxDbAZzIWR+8BAIn4AA5imaILANq62hj8fR+MW+VVoTaqTkw3oS+Q96xUddt5vsWoIcaYPFp6nT\/BEBqmv4Hptqkwu9SVt2\/fokWLFoiLi5Ppmb4Lj8bfWwJwdt9lZGdlQ1dPF3m5eRDYmmHIHE90G9MJhibSub1CoRAzZ87E5cuX8ffff5d6ooOIMH\/+fFy6dAkXL15UyP4NPOpNdkY2BlmMg0hY9I5nEfQYQmQXKboAYFjdAH8n7qvQVDLV2XtB3wtA4ZABIPF0c3I4ZGVx+OX3ZMR8yMO3Qwt7Qskp6Rg7+XcEBAQgN7fkZa1VmVq1asHIyAhPnz6VWV7ToQamb5uAXREb8NjsOnze\/A7\/rEPwebMDA2b0LiS4AKCrq4sdO3Zg3rx56NChA06ePFkqW5YuXYozZ87g7NmzvODyVAgJ75OgpV3+CGlORg5yskqxUKuCUKjoMn1PFDWRdvBEGmxdImHd5BUuXsvC2aO20NX93Dxd6JiMhatrK6xatQo1atTAxIkTcfHiRYjFZZ+RrwrIWhL8ObGxsbCqYYXqFibQ1tEutu5Hxo0bh8DAQMyePRs\/\/vhjse\/\/mjVrcOzYMVy4cEGuW0HyVC2yM3IqZIWkppYmstPlv5HTRxQruhqGgH5\/AIVnq9f9ZIHEZ\/WQ9rI+AnxsUb+O7BltI8uJmD59Om7cuIF79+7B0dER8+fPh62tLb777jtcv34dHFf6WUx1pzSiGxMTAxsbmzK37ebmhuDgYAQFBaFnz55ISEgoVGfTpk3YvXs3Ll68WOlXEPKoFgZG+iCu\/Hv5ivPEMDCWPQKXBwpf\/sOM5gGatgDKml2gBxivANP83z9u7dq18cMPPyA4OBjXr1+HjY0NpkyZAjs7O8yZMwd3796t8hssf8xgKO59+FLRBQALCwucPXsWLi4uaNmyJe7du1dQtmPHDmzevBkXL15EjRo1vqh9Hp6iMLc1K1UGTknoG+lDV19xaYuKF12NamBmhwDN2pDl8cpGDzCaBw2DojMW6tevj0WLFiE0NBRnzpyBoaEhRowYgfr162PhwoV4+PBhlRTgOnXqQEtLCy9evCiyTnlEFwC0tLSwbt06rFu3Dt27d8f+\/fuxb98+rFq1ChcuXEDt2kUvZOHh+VL0DfXQbpAHNDQLyxhHHMQkhiTjnyAmMTgqPALW1tVGv2k9FLofg1LWXTJNAWB+EpS+Dsj2A8Ag2dbxUzSRKwLik\/RQ02krmG7pD6Zs1KgRli9fjmXLluHBgwc4cuQI+vXrB319fQwbNgxDhw6Fk5NTRT6SysIYKzjCx8HBQWad2NhY1K9fv9x9DRkyBM7OzujSpQvS0tJw69Yt1KtXr9zt8vDIIisrC2kmcRCJRdD8bOQciaeIxP8mkGMRhTpoiHoyFvf08e4md1s\/RWm7izANQ2iYLAOzvAVmvBDQcgY0LABWHdCoCeh5IltvN1y+jsL7ePsv6yN\/g+W1a9ciMjISe\/fuRUpKCjp37gwXFxesWbMGkZGRFftgKkhJcd3yerqfEh4eDo7j0KpVK3h7eyM6OrpC2uXh+YhYLMaePXvg4OCAl3HhqNfUDlra0qJbjzVCFzZY6lWPSQuujp42PDxdIahhpkjzlX9cD9MwADP4BhoCP2hY3oCGVRA0LC9Bo\/o6mFq0wbhx47Bu3bry98MYPDw88OuvvyIqKgqbN29GVFQU3N3d4e7ujo0bN+Ldu3cV8ESqx0fRLSq8UlGiGxAQAG9vbwQGBuLixYvo1asXWrZsiWvXrpW7bR4eIoK\/vz+aNWuGffv24cSJEzh27BjWn18KY4ExNLVKL2daOlqwrmOFuXunydHiIiCiIl+urq6kbGJiYsjU1JRiYmLk0r5IJKKzZ8\/SuHHjyMzMjNq3b0\/btm2j2NhYufSnDDiOIysrK3r16pXM8jp16tCLFy\/K1cf58+fJwsKCbt26JXU9ICCALC0tacuWLcRxXLn64Km6BAUFUadOncjJyYlOnTpV6LMU9zaBRtefRr0MvKgLG1zsq7fhCJracj6lJaXLzV4AwVSErird0y0Ja2trjBw5Ehs2bJBL+1paWujWrRt2796NmJgYzJs3D7du3YKjoyO6dOmCXbt2ISkpSS59K4qPcV1ZIQYiQkxMDKytrb+4\/WvXrsHLywu+vr7w8PCQKuvZsydu3bqF3bt3Y\/To0cjKkr3\/Bg+PLF69eoXhw4ejX79+GD58OEJDQ9G3b99CE18WNc3x+731+Hb5UJjZmEK\/mvSeHowx6BnqwqauFbx\/GYNfr62AkamSjvcqSo1JRTxdIqK3b9+SqakpxcfHK6zPzMxMOn78OA0ePJiMjY2pV69e9Ndff1FqaqrCbKhIfvvtN\/r2228LXU9OTqZq1ap9cbu3bt0iCwsLunDhQrH1MjMzacSIEdSsWTN6+fLlF\/fHUzWIj4+nmTNnkpmZGS1fvpwyMjJKfa9YLKbgcw9o24zdtPybX2jlsI30+\/f7KOzmM4WNtlCMp1spRJeIaPLkybRw4UKl9J2WlkaHDh0iT09PMjY2pgEDBtDRo0fL9EFQNo8fP6Y6deoUuv706VNq0KDBF7UZEhJClpaW5O\/vX6r6HMfRli1byNLSkgIDA7+oTx71Jisri1avXk3m5uY0derUShvmUwvRjYyMJDMzM0pKSlKqHUlJSbRnzx7q1q0bmZiY0LBhw8jPz49ycnKUaldJcBxHAoGAoqKipK5funSJOnToUOb2QkNDycrKik6ePFnme69evUo1atSglStXklgsLvP9POpHXl4e7dmzh2rWrEmDBg2i58+fK9ukclGc6Kp8TPcj9vb26Nu3L7Zs2aJUO0xNTTF27FicPXsWL168QMeOHfHrr7\/CxsYG3377LQIDAyESFX9ciDJgjKFDhw64evWq1PUvyVx49uwZunXrhk2bNmHAgAFltqV9+\/a4e\/cu\/P39MXDgQKSmppa5DR71gIgQGBgIFxcX7N69G8eOHcOJEyeKzClXC4pSY1IxT5eIKDw8nAQCgUrGVd+\/f0+bNm0iDw8PEggENGnSJLp48SLl5eUp27QCNm3aRBMnTpS6tmHDBpo1a1ap24iIiKCaNWvSvn37ym2PUCikqVOnkoODA4WFhZW7PZ7KRXBwMH399dfk6OhIfn5+apXdAnUIL3zEy8uLVq9erWwziiUyMpLWrl1LLVq0IGtra5o+fTpdv35d6UPp+\/fvk4ODg9S1OXPm0Nq1a0t1\/5s3b8jOzo5+\/\/33CrVr7969JBAI6Pjx4xXaLo9q8urVKxo+fDjZ2NjQjh07SCQSKdukCketRDcsLIwsLS0rzSTW8+fPafny5eTs7Ey1atWiH374ge7evauUb\/W8vDwyNTWl6OjogmsjRoyg\/fv3l3jv+\/fvqV69evTrr7\/Kxbbg4GCys7OjefPmqeU\/IQ9RQkICzZo1i8zMzGjZsmWUni6\/PFllU5zoVpqY7kecnZ3RoUMH7Ny5U9mmlAoHBwcsWbIEYWFhBWeCDR8+HA0aNMDixYsRGhqqsI14NDU10a5dO6m4bmliunFxcejcuTMmTJiAWbNmycU2V1dXBAcH4969e+jRowfi4+Pl0g+P4snOzsbatWvh6OgIoVCIsLAw\/PTTT6hWTUl5skqm0okuACxatAgbNmxAdrbiNh6uCBo3bowVK1YgPDwcR48eRW5uLvr06YPGjRtj+fLlCA8Pl7sNHze\/+UhJopuYmIguXbrgm2++wYIFC+Rqm0AgwJkzZwpOg63Io6J4FI9YLMb+\/fvh6OiIO3fu4MaNG9i+fXu5FuKoBUW5wKSi4YWPeHp60tatW5VtRrkRi8V048YNmjFjBllbW1Pz5s1pzZo1FBkZKZf+7t69S86NGlFydha9SUkmU1tbio2Lk1k3OTmZXF1dae7cuQoPh5w4cYIEAgHt3r1bof3ylB+O4ygwMJCaNm1Kbdq0oevXryvbJIWDYsILCj2YsiK5e\/cuBg0ahIiICOjoKG4DYnkiFotx7do1HDlyBL6+vqhXrx6GDRuGIUOGwNbWttztx2dl4tDDB9h0+SJ0jYygpaGBzOxs6OnpoVd9B0xo4QZnC8km8enp6ejevTvc3NywefNmhe43+pGnT59iwIAB6NSpEzZv3gxdXV2F28BTNu7du4d58+bh7du3WLNmDfr376+Uz46yUZnTgCuaHj16YNCgQZg4caKyTalwRCIRLl26hCNHjuDUqVNo0qQJhg0bhkGDBpX52JtcsRhL\/ruAU8+fggEQyjjPTJMxaGtqoq6pGTZ37obx3wyFg4MDdu7cqdR\/mrS0NIwZMwaxsbE4ceJEhXz58FQ8r1+\/xuLFi3Hx4kX83\/\/9H8aPHw9t7dKdt6eOqM5pwBXMkiVLsHr1apVcjFBetLW10b17d+zduxcxMTGYM2cOrl27BgcHB3Tr1g179uxBcnJyie0I8\/Iw4uQx\/BP+DLlisUzBBQAxEXLy8vAsIR7d\/9oDgUMD7NixQ+leirGxMXx9fdG3b1+0bNmy0OIOHuWSlJSEOXPmwNXVFfXr10d4eDi8vb2rtOCWRKUW3bZt28LOzg4+Pj7KNkWu6Orqom\/fvvDx8UF0dDQmTpwIf39\/2Nvbw9PTE4cOHUJ6enqh+4gI0wL+QVhcHHLy8krVF0cETls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\/><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">\n<p>\u3069\u3061\u3089\u30823\u8272\u3067\u5f69\u8272\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3057\u305f\u3002<\/p>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">\n<p>\u3044\u3088\u3044\u3088\u53e4\u5178\u30b3\u30f3\u30d4\u30e5\u30fc\u30bf\u3068\u91cf\u5b50\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u306e\u6700\u9069\u5316\u6027\u80fd\u306e\u6bd4\u8f03\u3092\u884c\u3044\u307e\u3059\u3002\u672c\u8a18\u4e8b\u3067\u306f\u9802\u70b9\u6570\u309220\u300140\u300160\u300180\u3001100\u3001\u8fba\u3092\u751f\u6210\u3059\u308b\u78ba\u7387\u306f\u9802\u70b9\u6570\u3092n\u3068\u3057\u305f\u3068\u304d4.5\/n\u3068\u3057\u30663\u8272\u3067\u5f69\u8272\u304c\u53ef\u80fd\u306a\u30b0\u30e9\u30d5\u3092\u9802\u70b9\u6570\u305d\u308c\u305e\u308c\u306b\u3064\u3044\u306620\u500b\u4f5c\u6210\u3057\u307e\u3059\u3002\u3053\u306e20\u500b\u306e\u30b0\u30e9\u30d5\u30923\u8272\u4ee5\u4e0b\u3067\u5f69\u8272\u3067\u304d\u305f\u78ba\u7387\u3092\u6c42\u3081\u307e\u3059\u3002<\/p>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing code_cell rendered\">\n<div class=\"input\">\n<div class=\"inner_cell\">\n<div class=\"input_area\">\n<div class=\" highlight hl-python\">\n<pre><span class=\"n\">success_probability_quantum<\/span> <span class=\"o\">=<\/span> <span class=\"p\">[]<\/span>\n<span class=\"n\">success_probability_classical<\/span> <span class=\"o\">=<\/span> <span class=\"p\">[]<\/span>\n\n<span class=\"c1\"># \u30b5\u30f3\u30d7\u30e9\u30fc\u306e\u8a2d\u5b9a<\/span>\n<span class=\"c1\"># SA\u306e\u5834\u5408<\/span>\n<span class=\"c1\"># sampler = SASampler()<\/span>\n\n<span class=\"c1\"># D-wave\u30de\u30b7\u30f3\u306e\u5834\u5408<\/span>\n<span class=\"n\">sampler_config<\/span> <span class=\"o\">=<\/span> <span class=\"p\">{<\/span><span class=\"s2\">\"solver\"<\/span><span class=\"p\">:<\/span> <span class=\"s2\">\"DW_2000Q_6\"<\/span><span class=\"p\">,<\/span> <span class=\"s2\">\"token\"<\/span><span class=\"p\">:<\/span> <span class=\"s2\">\"YOUR_TOKEN\"<\/span><span class=\"p\">}<\/span>\n<span class=\"n\">sampler<\/span> <span class=\"o\">=<\/span> <span class=\"n\">EmbeddingComposite<\/span><span class=\"p\">(<\/span><span class=\"n\">DWaveSampler<\/span><span class=\"p\">(<\/span><span class=\"o\">**<\/span><span class=\"n\">sampler_config<\/span><span class=\"p\">))<\/span>\n\n<span class=\"k\">for<\/span> <span class=\"n\">n<\/span> <span class=\"ow\">in<\/span> <span class=\"p\">[<\/span><span class=\"mi\">20<\/span><span class=\"p\">,<\/span> <span class=\"mi\">40<\/span><span class=\"p\">,<\/span> <span class=\"mi\">60<\/span><span class=\"p\">,<\/span> <span class=\"mi\">80<\/span><span class=\"p\">,<\/span> <span class=\"mi\">100<\/span><span class=\"p\">]:<\/span>\n    <span class=\"n\">success_count_quantum<\/span> <span class=\"o\">=<\/span> <span class=\"mi\">0<\/span>\n    <span class=\"n\">success_count_classical<\/span> <span class=\"o\">=<\/span> <span class=\"mi\">0<\/span>\n\n    <span class=\"k\">for<\/span> <span class=\"n\">i<\/span> <span class=\"ow\">in<\/span> <span class=\"nb\">range<\/span><span class=\"p\">(<\/span><span class=\"mi\">20<\/span><span class=\"p\">):<\/span>\n        <span class=\"n\">g<\/span> <span class=\"o\">=<\/span> <span class=\"n\">make_random_graph<\/span><span class=\"p\">(<\/span><span class=\"n\">node_num<\/span><span class=\"o\">=<\/span><span class=\"n\">n<\/span><span class=\"p\">,<\/span> <span class=\"n\">color_num<\/span><span class=\"o\">=<\/span><span class=\"mi\">3<\/span><span class=\"p\">,<\/span> <span class=\"n\">p<\/span><span class=\"o\">=<\/span><span class=\"mf\">4.5<\/span> <span class=\"o\">\/<\/span> <span class=\"n\">n<\/span><span class=\"p\">)<\/span>\n\n        <span class=\"n\">color_quantum<\/span> <span class=\"o\">=<\/span> <span class=\"n\">graph_coloring_quantum<\/span><span class=\"p\">(<\/span><span class=\"n\">g<\/span><span class=\"p\">,<\/span> <span class=\"n\">sampler<\/span><span class=\"o\">=<\/span><span class=\"n\">sampler<\/span><span class=\"p\">,<\/span> <span class=\"n\">num_reads<\/span><span class=\"o\">=<\/span><span class=\"mi\">30<\/span><span class=\"p\">)<\/span>\n        <span class=\"n\">color_classical<\/span> <span class=\"o\">=<\/span> <span class=\"n\">graph_coloring_classical<\/span><span class=\"p\">(<\/span><span class=\"n\">g<\/span><span class=\"p\">)<\/span>\n\n        <span class=\"k\">if<\/span> <span class=\"nb\">max<\/span><span class=\"p\">(<\/span><span class=\"n\">color_quantum<\/span><span class=\"p\">)<\/span> <span class=\"o\">&lt;<\/span> <span class=\"mi\">3<\/span><span class=\"p\">:<\/span>\n            <span class=\"n\">success_count_quantum<\/span> <span class=\"o\">+=<\/span> <span class=\"mi\">1<\/span>\n        <span class=\"k\">if<\/span> <span class=\"nb\">max<\/span><span class=\"p\">(<\/span><span class=\"n\">color_classical<\/span><span class=\"p\">)<\/span> <span class=\"o\">&lt;<\/span> <span class=\"mi\">3<\/span><span class=\"p\">:<\/span>\n            <span class=\"n\">success_count_classical<\/span> <span class=\"o\">+=<\/span> <span class=\"mi\">1<\/span>\n\n    <span class=\"n\">success_probability_quantum<\/span><span class=\"o\">.<\/span><span class=\"n\">append<\/span><span class=\"p\">(<\/span><span class=\"n\">success_count_quantum<\/span> <span class=\"o\">\/<\/span> <span class=\"mi\">20<\/span><span class=\"p\">)<\/span>\n    <span class=\"n\">success_probability_classical<\/span><span class=\"o\">.<\/span><span class=\"n\">append<\/span><span class=\"p\">(<\/span><span class=\"n\">success_count_classical<\/span> <span class=\"o\">\/<\/span> <span class=\"mi\">20<\/span><span class=\"p\">)<\/span>\n\n    <span class=\"nb\">print<\/span><span class=\"p\">(<\/span><span class=\"sa\">f<\/span><span class=\"s2\">\"\u9802\u70b9\u6570:<\/span><span class=\"si\">{<\/span><span class=\"n\">n<\/span><span class=\"si\">}<\/span><span class=\"s2\">\"<\/span><span class=\"p\">)<\/span>\n    <span class=\"nb\">print<\/span><span class=\"p\">(<\/span><span class=\"sa\">f<\/span><span class=\"s2\">\"Quantum Success Probability:<\/span><span class=\"si\">{<\/span><span class=\"n\">success_count_quantum<\/span><span class=\"o\">\/<\/span><span class=\"mi\">20<\/span><span class=\"si\">}<\/span><span class=\"s2\">\"<\/span><span class=\"p\">)<\/span>\n    <span class=\"nb\">print<\/span><span class=\"p\">(<\/span><span class=\"sa\">f<\/span><span class=\"s2\">\"Classical Success Probability:<\/span><span class=\"si\">{<\/span><span class=\"n\">success_count_classical<\/span><span class=\"o\">\/<\/span><span class=\"mi\">20<\/span><span class=\"si\">}<\/span><span class=\"s2\">\"<\/span><span class=\"p\">)<\/span>\n    <span class=\"nb\">print<\/span><span class=\"p\">(<\/span><span class=\"s2\">\"================================\"<\/span><span class=\"p\">)<\/span>\n<\/pre>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"output_wrapper\">\n<div class=\"output\">\n<div class=\"output_area\">\n<div class=\"prompt\"><\/div>\n<div class=\"output_subarea output_stream output_stdout output_text\">\n<pre>\u9802\u70b9\u6570:20\nQuantum Success Probability:0.45\nClassical Success Probability:0.35\n================================\n\u9802\u70b9\u6570:40\nQuantum Success Probability:0.4\nClassical Success Probability:0.25\n================================\n\u9802\u70b9\u6570:60\nQuantum Success Probability:0.2\nClassical Success Probability:0.15\n================================\n\u9802\u70b9\u6570:80\nQuantum Success Probability:0.1\nClassical Success Probability:0.05\n================================\n\u9802\u70b9\u6570:100\nQuantum Success Probability:0.05\nClassical Success Probability:0.0\n================================\n<\/pre>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing code_cell rendered\">\n<div class=\"input\">\n<div class=\"inner_cell\">\n<div class=\"input_area\">\n<div class=\" highlight hl-python\">\n<pre><span class=\"n\">graph_size<\/span> <span class=\"o\">=<\/span> <span class=\"p\">[<\/span><span class=\"mi\">20<\/span><span class=\"p\">,<\/span> <span class=\"mi\">40<\/span><span class=\"p\">,<\/span> <span class=\"mi\">60<\/span><span class=\"p\">,<\/span> <span class=\"mi\">80<\/span><span class=\"p\">,<\/span> <span class=\"mi\">100<\/span><span class=\"p\">]<\/span>\n<span class=\"n\">plt<\/span><span class=\"o\">.<\/span><span class=\"n\">plot<\/span><span class=\"p\">(<\/span><span class=\"n\">graph_size<\/span><span class=\"p\">,<\/span> <span class=\"n\">success_probability_quantum<\/span><span class=\"p\">,<\/span> <span class=\"n\">label<\/span><span class=\"o\">=<\/span><span class=\"s2\">\"Quantum\"<\/span><span class=\"p\">,<\/span> <span class=\"n\">marker<\/span><span class=\"o\">=<\/span><span class=\"s2\">\"o\"<\/span><span class=\"p\">)<\/span>\n<span class=\"n\">plt<\/span><span class=\"o\">.<\/span><span class=\"n\">plot<\/span><span class=\"p\">(<\/span><span class=\"n\">graph_size<\/span><span class=\"p\">,<\/span> <span class=\"n\">success_probability_classical<\/span><span class=\"p\">,<\/span> <span class=\"n\">label<\/span><span class=\"o\">=<\/span><span class=\"s2\">\"Classical\"<\/span><span class=\"p\">,<\/span> <span class=\"n\">marker<\/span><span class=\"o\">=<\/span><span class=\"s2\">\"x\"<\/span><span class=\"p\">)<\/span>\n<span class=\"n\">plt<\/span><span class=\"o\">.<\/span><span class=\"n\">xlabel<\/span><span class=\"p\">(<\/span><span class=\"s2\">\"Graph Size\"<\/span><span class=\"p\">)<\/span>\n<span class=\"n\">plt<\/span><span class=\"o\">.<\/span><span class=\"n\">xticks<\/span><span class=\"p\">(<\/span><span class=\"n\">graph_size<\/span><span class=\"p\">)<\/span>\n<span class=\"n\">plt<\/span><span class=\"o\">.<\/span><span class=\"n\">ylabel<\/span><span class=\"p\">(<\/span><span class=\"s2\">\"Success Probability\"<\/span><span class=\"p\">)<\/span>\n<span class=\"n\">plt<\/span><span class=\"o\">.<\/span><span class=\"n\">legend<\/span><span class=\"p\">()<\/span>\n<span class=\"n\">plt<\/span><span class=\"o\">.<\/span><span class=\"n\">show<\/span><span class=\"p\">()<\/span>\n<\/pre>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"output_wrapper\">\n<div class=\"output\">\n<div class=\"output_area\">\n<div class=\"prompt\"><\/div>\n<div class=\"output_png output_subarea \"><img decoding=\"async\" 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x5jnHvifzSgLGmEhtDZRPfl7uTBvThWpuroyZHkPSiTS7Q1KVkKenJ4cPH76gX2TKYozh8OHDxR5uqmsWqyJbuy+Z66b+RVg9X74c3wMvj3\/3JSh1oTIyMoiPjyc1VUeSl4SnpycNGzbE3f3cUvUFdRZrIlDF8vvGA\/zn01gGtarHuzdE6NKaSlUQdo0aUpXQRW3q8+Rlrfl900Ge+3mz3eEopUqBFp1TxTa2Vwh7Dp9m2p+7aFzbizG9QuwOSSlVApoI1AV54rLWxB9NYeJPmwiq5c2g1vXsDkkpdYH01pC6IK4uwpsjO9I2yI+7v1jN+vhjdoeklLpAmgjUBfP2cOPD0Z2p7ePBzR\/HEH\/0tN0hKaUugCYCVSIBvp7MGNuF1Iwsbp4Rw7GUDLtDUkoVkyYCVWKh9Xx5\/4YIdiad4vZPY0k\/r4y1Uqp800SgSkXP5nV54er2LNtxmMe+W6+zQ5WqQHTUkCo1wyMasvfIad78YxtNantz14BQu0NSShWBJgJVqu4dGEr8kdO8Om8rDWt7cVWnhnaHpJQqhCYCVapEhBeubs8\/x1J4aPY6Av286N60jt1hKaUKUPn7CJa+\/u91THcttvYrp\/Bwc+H9GzrTuLY342euZHviSbtDUkoVoPIngqDwcxe1zln0OijczqgqPT9vd2aM7YqHmwtjZ6zg0EktXa1UeVX5E0HOotazboCpkfDV6HMXvVZO06i2Nx+O7kLSiTTGfbySlPQsu0NSSuWh8icCsH7pB3WGf1ZD+ilI3AxZOvGpLHRsVJPXr+vE2vhk7p21huxsHVaqVHlTNRLBrsWwfw1EjAWTDb8+BO\/1hh0L7I6sShjStj6PX9KK3zYeYNKvWrpaqfKm8ieCnD6Ba2bA5a\/DDd9ANV9IOQqfXAVfjITDO+yOstK7pXcIo3s04YMlu5j51267w1FK5VL5h48mrDq3T6BpPxjxOexbAS6usPgVmNINetwBfR4Azxq2hltZiQhPXt6GhOQUnp6zkaCaXgxopaWrlSoPdKnKEwfgj\/\/Bmk\/BJwAGPAkdR4FL5W8s2eF0eibXvb+c7Ykn+fq2HrQN8rM7JKWqBF2qsiC+9eHKKXDrAqgVDHMmwAdRsHe53ZFVSt4ebnyUU7p6RgwJySl2h6RUlaeJIEdQBNzyOwz7EE4mwrTBMPtmSN5nd2SVTkANT6aN6UJKehY3T4\/heKqO4FLKTpoIchOB9tfAXSuh38Ow5Wd4uwssfAHSddGV0hRW35d3b4hgR9JJ7vh0FRlZWrpaKbtoIsiLhw9EPQYTYiBsCCycZCWEDd9ABetTKc96h9bl+WHtWLr9EP\/33QYtXa2UTQpNBCLyrYhcKiJVL2nUbGyNOBrzC3jXsm4VTb\/YmpimSsW1nRtxV\/\/mzFq5j3cW6jBepexQlF\/u7wDXA9tE5AURCXNyTOVPcC8YvwgufwMObYOpUfDDBKsvQZXYfYNaMLRjA16eG8cPaxLsDkepKqfQRGCMmW+MGQWEA7uB+SKyTETGioi7swMsN1xcIWIM3L0KetwJa7+AN8PhzzcgUwuqlYSI8NLw9nQNqc2DX69jxa4jdoekVJVSpNs9IlIHGAOMA1YDb2AlhnlOi6y88vSDwc\/BHcuhSU+Y9yS80x3iftX+gxKo5ubK1BsjaFjbi\/GfrGRHkpauVqqsFKWP4DtgCeANXG6MucIYM8sYcxdQ3dkBllt1Q2HUVzDqG3Bxgy9GwKfDIHGL3ZFVWDW9PZgxpiuuIoydHsNhLV2tVJkoSovgA2NMa2PMJGPMfgARqQaQ3yy1KiV0INy+DIa8AAmx8G5P+OUhOK23Ny5E4zrefDC6MwePpzJu5kpSM7R0tVLOVpRE8Gwe+\/4q7UAqNFd36H473LXa6keI+QDeCocVH0BWpt3RVTjhjWvx+nUdWbNPS1crVRbyTQQiUl9EIgAvEekkIuGORyTWbSJ1Pp86cNlr8J8lUK8t\/PIAvN8Hdi60O7IK5+J2gTx2cSt+3XCAF3\/T221KOVNB1UcHY3UQNwRey7X\/BPCYE2Oq+Oq3hdE\/wuYf4ffHYeZQaHkZXPQs1A6xO7oKY1yfEPYeOc37i3fSsLY3N3ZvYndISlVKhVYfFZGrjTHflFE8hSr16qPOlpEKy6fA4lchO8MaetrnfmtNBFWozKxsxn8Sy8K4RD4a3YWolgF2h6RUhXRB1UdF5AbHt8Eict\/5jyJeeIiIxInIdhF5JI\/nbxOR9SKyRkSWikjrIv1EFYm7p\/WL\/65YaHs1LJ0Mb0XAms8hW+vrFMbN1YW3RnaiVWAN7vx8FRsSjtkdklKVTkGdxT6Or9UB3zweBRIRV2AKcDHQGhiZxy\/6z40x7YwxHYGXOPcWVOVSIxCueg\/G\/QF+jeD72+HDAdYCOapAPtXcmDamC35e7tzycQz\/aOlqpUqV0xamEZEewNPGmMGO7UcBjDGT8jl+JHCTMebigs5b4W4N5SU7G9Z\/BfOfhhP7od21MPBp8AuyObDybcuB4wx\/9y8a1vLi69t64OtZdSa2K1VSBd0ayjcRiMibBZ3UGHN3IRcdDgwxxoxzbN8IdDPGTDjvuDuB+wAPoL8xZlse5xoPjAdo3LhxxJ49ewq6dMWRdtK6VbTsLauERe\/7oOcEcPeyO7Jya8m2JMZOj6FHszpMG9MFd9eqVwtRqQtxoSuUxRbyKBXGmCnGmGbAw8D\/5XPMVGNMZ2NMZ39\/\/9K6tP2qVYcBT8CEFdB8IEQ\/C293hY3fabmKfPQJ9ee5q9qyZNshnvheS1crVRryHT5qjPm4hOdOABrl2m7o2JefL4F3S3jNiqlWMFz3CexaAr89Al+PgSa9rNnKge3tjq7cua5LY\/YeOc2U6B00ruPNHZHN7Q5JqQqtoFFDrzu+\/igic85\/FOHcMUCoiISIiAcwAjjndSISmmvzUuBft4WqlJA+8J\/FcNlkSNoC7\/eFH++BU4fsjqzcuX9QGFd0aMBLv8UxZ+0\/doejVIVW0ISyTxxfX7mQExtjMkVkAjAXcAWmGWM2ishEYKUxZg4wQUQGAhnAUWD0hVyrUnFxhc43Q5thsOglWPE+bPgO+j0EXceDm4fdEZYLLi7Cy9e0Z\/+xFB74ai2Bfp50Ca5td1hKVUhFGjXk+Iu+JWCAOGNMurMDy0+lGDVUHElbYe5jsH0e1GkOgydBi4vsjqrcOHoqnWHvLuPo6XS+u6MXIXV9Cn+RUlXQhXYW57z4UmAH8CbwNrBdRAoc4qlKkX8LuGE2XP+1tf35NfDpcCtBKGr5eDB9TBdcRBgzfYWWrlbqAhRl7N2rQJQxJtIY0w+IAiY7Nyz1Ly0ugtv\/gsHPw76\/4d0e8NujkJJsd2S2C67rwwc3dWb\/sVTGfxKrpauVKqaiJIITxpjtubZ3YhWeU2XNzcOqVXTXKuh0Ayx\/1yp3vXIaZFftX34RTWox+dqOxO45yv1fr9XS1UoVQ0GjhoaJyDBgpYj8IiJjRGQ08CPWiCBll+r+cPkb1ggj\/5bw073wfj9r+GkVdmn7QB69uCU\/r9vPS3Pj7A5HqQqjoBbB5Y6HJ3AQ6AdEAkmATn0tDwLbw5if4ZqPIfUYfHwZzLoRju62OzLbjO\/blFHdGvPeoh189nclmYGulJMVNKFsbFkGoi6QCLS5EloMhmVvw9LXYOtc6HkX9L7Xmr1chYgIz1zRhoTkFJ78YSNBNb2IDNPS1UoVpCjrEXgCtwBtsFoHABhjbnZuaHmrcsNHi+tYAvzxDKybBb6BMPAZaHcNuFStmjwn0zK59r2\/2HP4FF\/f1pPWDWrYHZJStirR8FGsiWX1sVYsW4RVKkI7i8srvyAYNhVumWclgu\/Gw7SLIL7UykNVCNUdpat9Pd25eUYM+49p6Wql8lOURNDcGPMEcMpRf+hSoJtzw1Il1qirtfbBle9C8l74sD98dxsc3293ZGWmvp8n08d24WRaJmOnx3AiNcPukJQql4qSCHL+9ySLSFvAD9CbrhWBiwt0vN5aHa33fbDhG2t1tCWvWktoVgGtAmswZVQ42xJPMuHz1WRm6apwSp2vKIlgqojUAp7AKhq3CXjRqVGp0lXNFwY+BXeugGZR8MdEmNIVNs2pEuWu+7Xw539D27JoaxJP\/LBRS1crdZ5CE4Ex5kNjzFFjzCJjTFNjTIAx5v2yCE6VstohMOIzuOkH8PCBr26Ejy+HAxvsjszpru\/WmNsjm\/HFir28v3in3eEoVa4UpdZQHRF5S0RWiUisiLwuInXKIjjlJE0j4T9L4NJX4eAGeL8P\/HQfnDpsd2RO9eBFYVzWPpAXft3CT+u0dLVSOYpya+hLIBG4GhgOHAJmOTMoVQZc3aDLOKtcRdfxEDsD3uoEn4+AHQvOPXbXYlj6ui1hliYXF+GVazrQuUkt7vtqLbF7jtgdklLlQlESQaAx5n\/GmF2Ox7NAPWcHpsqId224+EW4fRkERcDWX63qpksddQV3LbZWTAsKtzXM0uLp7srUmzrTwM+TcR+vZPehU3aHpJTtipIIfheRESLi4nhci7XYjKpMAlrCDd\/CyFlQPQDmPw1vdrJKVlwzA0L62h1hqant48H0sV0BGDN9BUdO2ba8hlLlQkFF506IyHHgVuBzIN3x+BIYXzbhqTIlAmFD4J51EBIJR3ZC6nGrZEXqMbujK1UhjtLV\/xxLZfzMlVq6WlVp+SYCY4yvMaaG46uLMcbN8XAxxuh8\/cps33I4uB663wlu7vDX2\/BmOMR+XKnKXXcOrs2r13Rg5Z6jPDh7nZauVlVWkQrQiMgVIvKK43GZs4NSNsrpE7hmBgx5HkbNBk8\/63bRj3fD1H6w+0+7oyw1l3dowMNDWvLj2n945XctXa2qpqIMH30BuAdrItkm4B4RmeTswJRNElad2ycQ0heu+xTaXwfDp8HpozDjEitZJO+1M9JSc1u\/pozs2ph3Fu7gixWV42dSqjiKUn10HdDRGJPt2HYFVhtj2pdBfP+i1Udtln4alr3pGE5qoNc91sOjYi8an5mVzc0fr+TP7YeYNqYL\/Vr42x2SUqWqpNVHAWrm+t6v5CGpCsvDGyIfgbtWQsvLYNGL8FZnWPd1hS5X4ebqwpTrOxEaUJ07P1vF5v3H7Q5JqTJTlETwPLBaRGaIyMdALPCcc8NS5Z5fQxj+EYz9zeo\/+HYcTBts3VqqoHw93Zk+tgs+1Vy5eUYMB45VjcJ8ShWYCETEBcgGugPfAt8APYwxOrNYWZr0gFujYegUOLILPoiC7++AEwfsjuyCBPp5MW1MF46nZHDzjBhOpmXaHZJSTldgInD0CzxkjNlvjJnjeFTM\/+HKeVxcoNMNVrnrXvfAuq+sctdLJ0Nmmt3RFVubBn68PSqcuIMnuOvzVVq6WlV6Rbk1NF9EHhCRRiJSO+fh9MhUxeNZAwZNhDv\/hpB+1uzkKd1g808Vrv8gKiyAiUPbEB2XxFNztHS1qtzyXbw+l+scX+\/Mtc8ATUs\/HFUp1GkGIz+3itf99ijMGmUlhiEvQL3WdkdXZKO6NWHvkdO8v2gnTep4M75vM7tDUsopirIeQUgeD00CqnDN+sNtf8LFL8P+tfBeL\/j5AThdcap+Pjy4JZe2C+T5X7bwy\/qqs8ynqloKqjXUTUTWishJEflLRFqVZWCqknB1g27j4e7VVtnrldOsYnZ\/vw9Z5X8NYRcX4dVrOxDeuCb3zlpD7J6jdoekVKkrqEUwBXgAqAO8BlT8gvTKPt614ZKX4balENgBfn0I3uv977UPyiFPd1c+uKkz9f08uXXmSvYc1tLVqnIpKBG4GGPmGWPSjDFfAzrVUpVcvdbWUpkjPofMVPjkKvhiJBzeYXdkBapTvRrTx3Qh2xjGTo\/hqJauVpVIQYmgpogMy3nksa3UhRGBlpfCnStg4DNWobsp3WDek1bZ63KqqX91pt7YmfijKfznk1jSMitPJVZVteVba0hEphfwOmOMudk5IRVMaw1VQicOwh8TYc2n4BMAA56EjqOs+Qnl0A9rErjnyzVc0aEBr1\/XERcXsTskpQpVUK2hQovOlTeaCCqxhFXw2yOw728I7Ggtodm4u91R5WlK9HZenhvHhKjmPDA4zO5wlCpUaRSdU8r5gsLh5rlw9UdwKsmqXTT7ZkjeZ3dk\/3JHZDOu69yIt6O381VM+YtPqeJwaotARIYAbwCuwIfGmBfOe\/4+YByQCSQBNxtj9hR0Tm0RVBHpp+DPN6wHAr3\/C6K7hWcAAB7FSURBVD3vtqqflhMZWdncPCOGpdsOUdvHgyOn0mlQ04sHB4dxZacgu8NT6hy2tAgc6xZMAS4GWgMjReT8aaWrgc6OtQ1mAy85Kx5VwXj4QNRjMCHGWkd54SR4uwusn11uylW4u7pwSbv6ABw+lY4BEpJTePTb9Xy\/OsHe4JQqhqKsUHaNiPg6vv8\/EflWRMKLcO6uwHZjzE5jTM6i90NzH2CMiTbGnHZsLgcaFi98VenVbGytmDb2V2suwje3wLQh8M9quyMD4O0FOzg\/LaVkZPHyXF32UlUcRWkRPGGMOSEivYGBwEfAu0V4XRCQ++ZpvGNffm4Bfs3rCREZLyIrRWRlUlJSES6tKp0mPWH8Qrj8TTi8HaZGwQ8T4GSirWH9k5xSrP1KlUdFSQQ5g6UvBaYaY34GPEozCBG5AegMvJzX88aYqcaYzsaYzv7+Oq+tynJxhYjRcPcq6DkB1n4Jb4Zb\/Qg2lbtuUNMr3+fe+mMbqRk610CVf0VJBAki8j5WFdJfRKRaUV8HNMq13dCx7xwiMhB4HLjCGFPxitersufpBxc9C3csh+Be1kS0d7pD3K9l3n\/w4OAwvNxdz9lXzc2Fdg1r8Oq8rQx4dRG\/rN+vZaxVuVaUX+jXAnOBwcaYZKA28GARXhcDhIpIiIh4ACOAObkPEJFOwPtYScDeNr6qeOo2h+tnwahvwMUNvhgBnw6DxC1lFsKVnYKYNKwdQTW9ECCophcvXt2eORP68Pmt3fD1dOOOz1YxYupyNv1TfmdNq6qt0OGjItIMiDfGpIlIJNAemOlICoW99hKsYnWuwDRjzHMiMhFYaYyZIyLzgXZATn3fvcaYKwo6pw4fVXnKyoCYj2Dh85B20qp0GvmI1cFso8ysbL6M2cerv8dxLCWDEV0bc\/+gFtSpXs3WuFTVU6KZxSKyBuv+fTDwC\/AD0MYYc0kpx1kkmghUgU4dhujnIHa6dQsp6nGIGGuVw7bRsdMZvPHHNmb+tRsvD1fuGRDKTT2C8XDTOZ2qbJQ0EawyxoSLyENAijHmLRFZbYzp5IxgC6OJQBXJgQ1WuYrdSyCgNQyZBE0j7Y6K7YknmPjTZhZvTaKpvw9PXNaaqLAAu8NSVUBJJ5RliMhI4CbgJ8c+99IKTimnqN8WRv8I135izVKeORS+HAVHdtoaVvMAXz4e24VpYzqDgbHTYxg7fQU7kk7aGpeq2orSImgN3Ab8ZYz5QkRCgGuNMS+WRYDn0xaBKraMVFg+BRa\/CtkZ0ONO6HM\/VPO1Naz0zGxm\/rWbN+ZvIyUji9E9g7l7QCh+Xvp3lip9Ja4+KiJeQGNjjO3TJTURqAt2fD\/88Qys\/QKq14MBT0GHkbaXuz50Mo1Xf4\/jy5h91PL24IGLwriuSyNctby1KkUlujUkIpcDa4DfHNsdRWROwa9SqhyqEQhXvQfjFoBfI\/jhDviwP+xbYWtYdatXY9Kw9vw4oTfNA6rz2Hfrueytpfy147Ctcamqoyh\/Cj2NVTcoGcAYswZo6sSYlHKuhhFwyzy4aiqcOAAfDYJvboVj9haKaxvkx6zx3ZlyfTjHUzIY+cFy7vgsln1HThf+YqVKoEidxcaYY+fty3ZGMEqVGRcX6HAdTFgJfR6ATT\/A251h0UuQYV+dIBHh0vaB\/HF\/P+4f1ILoLUkMeG0Rr8yN41Rapm1xqcqtKIlgo4hcD7iKSKiIvAUsc3JcSpWNatVhwBMwYQWEDrLmILzdFTZ+Z2u5a093V+4aEMqCB\/pxSdv6vB29nf6vLuS71fFkZ2u5ClW6ipII7gLaAGnA58Ax4L\/ODEqpMlcrGK6dCaN\/As8a8PUYmH4J7F9ra1iBfl68PqIT39zeg3o1PLl31lqufm8Za\/YVOrFfqSLTNYuVOl92FqyaCQv+B6ePQPhN0P8JqG5v5dvsbMO3qxN48bctJJ1IY1h4EA8PaUm9Gp62xqUqhpLOLJ4HXJNTW0hEagFfGmMGl3qkRaCJQJWZlGSrz2DF++DuDf0ehq7jwa1Uq7AX28m0TKZEb+ejJbtwcxXujGrOLb1D8DyvCqpSuZU0EfyrnISWmFBVStJWmPsYbJ8HdZrD4Och9CIQe8f57zl8iud+3szvmw7SqLYXj1\/SmsFt6iE2x6XKp5KWmMgWkca5TtYE\/rU6n1KVl38LuGE2XP81IPD5tfDZcEiyd35lkzo+TL2pM5+N64a3uxu3fRrLqA\/\/ZssBLXetiqcoLYIhwFRgESBAH2C8MWau88P7N20RKFtlpkPMB7DwRcg4BUGdodfd0PLSs8fsWgwJq6B32Y2pyMzK5osVe3l13laOp2RwfbfG3DcojNo+9t7GUuVHaZSYqAt0d2wuN8YcKsX4ikUTgSoXTiZB9LMQOwMQ6HYbDH4O9vxpjTi6ZgaE9C3zsJJPp\/P6\/G18snwPPh6u3DuoBTd0b4K7q5a7rupK2kdwFbAgZ1KZiNQEIo0x35d6pEWgiUCVK\/vXwfe3w8EN4ONvrZ084jNbkkBu2w6eYOJPm1iy7RDNA6rzxGWt6ddC1\/uuykraR\/BU7pnFjtFDT5VWcEpVaIHt4bal0GoonEqCtOOwYioc3W1rWKH1fJl5c1c+vKkzmVnZjJ62gltmxLBTy12rPBQlEeR1jL3LPSlVnuxeAnuWQu97rWGmW3+3Zif\/MdFaNtMmIsLA1vWYe29fHrukJX\/vOsLg1xfz3M+bOJ6aYVtcqvwpSiJYKSKviUgzx+M1INbZgSlVIexafLZPYODTcP0s8PCGJj1gyavwVgSs+QKy7SvPVc3NlfF9mxH9QCTDOjXkw6W7iHp5IV+u2EuWlqtQFK2PwAd4Ahjo2DUPeNYYc8rJseVJ+whUubL0dQgKP7dPIGfUUJOe8OvD8M8qCIqAi1+Chnneoi1TGxKO8cyPG4nZfZQ2DWrw1OVt6BpS2+6wlJOVeNRQeaKJQFUo2dmwbhbMfwpOHoT2I2DgU1Cjga1hGWP4ad1+Jv2ymX+OpXJp+0AevbglDWt52xqXcp6SjhqKJo8JZMaY\/qUTXvFoIlAVUtoJWPIa\/PU2uLhDn\/ugxwRwt7dOUEp6Fu8v3sF7i3ZgDPynXzNu69cUbw\/tBqxsSpoIInJtegJXA5nGmIdKL8Si00SgKrQju2DeE7D5R6jZGC56FlpdYXu5ioTkFF74dQs\/rv2HQD9PHrm4JVd0aKDlKiqRUr81JCIrjDFdSxzZBdBEoCqFnYvgt0cgcRME94Ehk6B+O7ujImb3EZ75cSMbEo4T0aQWT13emvYNa9odlioFJW0R5O5FcgEigDeNMWGlF2LRaSJQlUZWJqyaAQueg9RkCB8N\/f8PfOraGlZ2tmF2bDwvzd3CoZPpXBPRkAeHhBHgq+WuK7KSJoJdWH0EAmQCu4CJxpilpR1oUWgiUJXO6SOw6EVY8QF4VIfIR6DrreDqbmtYJ1IzeHvBdqb9uQsPVxfuGhDK2F7BVHPTctcVkY4aUqoiSNwCcx+FHQugbgsYPAlCBxb+Oifbdcgqdz1\/80Ga1PHm8UtaMai1lruuaC6oxISIdBGR+rm2bxKRH0TkzfNuFymlSkNAS7jhWxg5C7Iz4bOr4bNr4NA2W8MKqevDh6M788ktXfFwdWH8J7Hc+NEK4g6csDUuVXrybRGIyCpgoD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