{"id":6652,"date":"2023-10-11T18:50:24","date_gmt":"2023-10-11T09:50:24","guid":{"rendered":"https:\/\/qard.is.tohoku.ac.jp\/T-Wave\/?p=6652"},"modified":"2023-10-11T18:50:24","modified_gmt":"2023-10-11T09:50:24","slug":"%e6%95%b0%e5%88%86%e5%89%b2%e5%95%8f%e9%a1%8c%e3%81%ab%e5%af%be%e3%81%99%e3%82%8b%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%e8%a7%a3","status":"publish","type":"post","link":"https:\/\/qard.is.tohoku.ac.jp\/T-Wave\/2023\/10\/11\/%e6%95%b0%e5%88%86%e5%89%b2%e5%95%8f%e9%a1%8c%e3%81%ab%e5%af%be%e3%81%99%e3%82%8b%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%e8%a7%a3\/","title":{"rendered":"\u6570\u5206\u5272\u554f\u984c\u306b\u5bfe\u3059\u308b\u91cf\u5b50\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u3092\u7528\u3044\u305f\u89e3\u6cd5"},"content":{"rendered":"<p><a href=\"https:\/\/colab.research.google.com\/github\/T-QARD\/t-wave\/blob\/main\/notebooks\/number_partitioning\/number_partitioning.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\">\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\/2023\/10\/11\/%e6%95%b0%e5%88%86%e5%89%b2%e5%95%8f%e9%a1%8c%e3%81%ab%e5%af%be%e3%81%99%e3%82%8b%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%e8%a7%a3\/#%E6%95%B0%E5%88%86%E5%89%B2%E5%95%8F%E9%A1%8C%E3%81%AB%E5%AF%BE%E3%81%99%E3%82%8B%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%E8%A7%A3%E6%B3%95\" >\u6570\u5206\u5272\u554f\u984c\u306b\u5bfe\u3059\u308b\u91cf\u5b50\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u3092\u7528\u3044\u305f\u89e3\u6cd5<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/qard.is.tohoku.ac.jp\/T-Wave\/2023\/10\/11\/%e6%95%b0%e5%88%86%e5%89%b2%e5%95%8f%e9%a1%8c%e3%81%ab%e5%af%be%e3%81%99%e3%82%8b%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%e8%a7%a3\/#%E6%A6%82%E8%A6%81\" >\u6982\u8981<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/qard.is.tohoku.ac.jp\/T-Wave\/2023\/10\/11\/%e6%95%b0%e5%88%86%e5%89%b2%e5%95%8f%e9%a1%8c%e3%81%ab%e5%af%be%e3%81%99%e3%82%8b%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%e8%a7%a3\/#%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-3'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/qard.is.tohoku.ac.jp\/T-Wave\/2023\/10\/11\/%e6%95%b0%e5%88%86%e5%89%b2%e5%95%8f%e9%a1%8c%e3%81%ab%e5%af%be%e3%81%99%e3%82%8b%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%e8%a7%a3\/#%E7%92%B0%E5%A2%83%E8%A8%AD%E5%AE%9A\" >\u74b0\u5883\u8a2d\u5b9a<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/qard.is.tohoku.ac.jp\/T-Wave\/2023\/10\/11\/%e6%95%b0%e5%88%86%e5%89%b2%e5%95%8f%e9%a1%8c%e3%81%ab%e5%af%be%e3%81%99%e3%82%8b%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%e8%a7%a3\/#%E5%95%8F%E9%A1%8C%E8%A8%AD%E5%AE%9A\" >\u554f\u984c\u8a2d\u5b9a<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/qard.is.tohoku.ac.jp\/T-Wave\/2023\/10\/11\/%e6%95%b0%e5%88%86%e5%89%b2%e5%95%8f%e9%a1%8c%e3%81%ab%e5%af%be%e3%81%99%e3%82%8b%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%e8%a7%a3\/#%E8%A7%A3%E6%B3%95\" >\u89e3\u6cd5<\/a><ul class='ez-toc-list-level-4' ><li class='ez-toc-heading-level-4'><a class=\"ez-toc-link ez-toc-heading-7\" href=\"https:\/\/qard.is.tohoku.ac.jp\/T-Wave\/2023\/10\/11\/%e6%95%b0%e5%88%86%e5%89%b2%e5%95%8f%e9%a1%8c%e3%81%ab%e5%af%be%e3%81%99%e3%82%8b%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%e8%a7%a3\/#%E3%83%93%E3%83%83%E3%83%88%E5%85%A8%E6%8E%A2%E7%B4%A2\" >\u30d3\u30c3\u30c8\u5168\u63a2\u7d22<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-4'><a class=\"ez-toc-link ez-toc-heading-8\" href=\"https:\/\/qard.is.tohoku.ac.jp\/T-Wave\/2023\/10\/11\/%e6%95%b0%e5%88%86%e5%89%b2%e5%95%8f%e9%a1%8c%e3%81%ab%e5%af%be%e3%81%99%e3%82%8b%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%e8%a7%a3\/#%E9%87%8F%E5%AD%90%E3%82%A2%E3%83%8B%E3%83%BC%E3%83%AA%E3%83%B3%E3%82%B0\" >\u91cf\u5b50\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-4'><a class=\"ez-toc-link ez-toc-heading-9\" href=\"https:\/\/qard.is.tohoku.ac.jp\/T-Wave\/2023\/10\/11\/%e6%95%b0%e5%88%86%e5%89%b2%e5%95%8f%e9%a1%8c%e3%81%ab%e5%af%be%e3%81%99%e3%82%8b%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%e8%a7%a3\/#%E3%82%B7%E3%83%9F%E3%83%A5%E3%83%AC%E3%83%BC%E3%83%86%E3%83%83%E3%83%89%E3%82%A2%E3%83%8B%E3%83%BC%E3%83%AA%E3%83%B3%E3%82%B0\" >\u30b7\u30df\u30e5\u30ec\u30fc\u30c6\u30c3\u30c9\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-10\" href=\"https:\/\/qard.is.tohoku.ac.jp\/T-Wave\/2023\/10\/11\/%e6%95%b0%e5%88%86%e5%89%b2%e5%95%8f%e9%a1%8c%e3%81%ab%e5%af%be%e3%81%99%e3%82%8b%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%e8%a7%a3\/#%E3%81%82%E3%81%A8%E3%81%8C%E3%81%8D\" >\u3042\u3068\u304c\u304d<\/a><\/li><\/ul><\/li><\/ul><\/nav><\/div>\n<h2><span class=\"ez-toc-section\" id=\"%E6%95%B0%E5%88%86%E5%89%B2%E5%95%8F%E9%A1%8C%E3%81%AB%E5%AF%BE%E3%81%99%E3%82%8B%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%E8%A7%A3%E6%B3%95\"><\/span>\u6570\u5206\u5272\u554f\u984c\u306b\u5bfe\u3059\u308b\u91cf\u5b50\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u3092\u7528\u3044\u305f\u89e3\u6cd5<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<h3><span class=\"ez-toc-section\" id=\"%E6%A6%82%E8%A6%81\"><\/span>\u6982\u8981<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>\u672c\u8a18\u4e8b\u3067\u306f\u91cf\u5b50\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u30de\u30b7\u30f3\u306b\u3088\u308b\u6570\u5206\u5272\u554f\u984c\u306e\u8a08\u7b97\u6642\u9593\u3092\u3001\u7dcf\u5f53\u305f\u308a\u306b\u3088\u308b\u8a08\u7b97\u6642\u9593\u3068\u6bd4\u8f03\u3059\u308b\u3053\u3068\u306b\u3088\u3063\u3066\u305d\u306e\u6709\u7528\u6027\u3092\u78ba\u8a8d\u3057\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<h3><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><\/h3>\n<ul>\n<li>\u30bf\u30a4\u30c8\u30eb\uff1aIsing formulations of many NP problems<\/li>\n<li>\u8457\u8005\uff1aAndrew Lucas<\/li>\n<li>\u66f8\u8a8c\u60c5\u5831\uff1a<a href=\"https:\/\/doi.org\/10.3389\/fphy.2014.00005\">https:\/\/doi.org\/10.3389\/fphy.2014.00005<\/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<h3><span class=\"ez-toc-section\" id=\"%E7%92%B0%E5%A2%83%E8%A8%AD%E5%AE%9A\"><\/span>\u74b0\u5883\u8a2d\u5b9a<span class=\"ez-toc-section-end\"><\/span><\/h3>\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><\/span><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><span class=\"o\">&gt;=<\/span><span class=\"mf\">3.5.1<\/span>  <span class=\"c1\"># 3.5.1\u672a\u6e80\u3067\u3042\u308b\u3068\u30b0\u30e9\u30d5\u306e\u8868\u793a\u304c\u6b63\u5e38\u306b\u884c\u308f\u308c\u306a\u3044\u53ef\u80fd\u6027\u3042\u308a<\/span>\n<span class=\"err\">!<\/span><span class=\"n\">pip<\/span> <span class=\"n\">install<\/span> <span class=\"n\">pandas<\/span>\n<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<\/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><\/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><\/span><span class=\"kn\">import<\/span> <span class=\"nn\">math<\/span>\n<span class=\"kn\">from<\/span> <span class=\"nn\">decimal<\/span> <span class=\"kn\">import<\/span> <span class=\"n\">Decimal<\/span><span class=\"p\">,<\/span> <span class=\"n\">ROUND_HALF_UP<\/span><span class=\"p\">,<\/span> <span class=\"n\">ROUND_HALF_EVEN<\/span>\n<span class=\"kn\">import<\/span> <span class=\"nn\">time<\/span>\n\n<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\">pandas<\/span> <span class=\"k\">as<\/span> <span class=\"nn\">pd<\/span>\n<span class=\"kn\">import<\/span> <span class=\"nn\">matplotlib.cm<\/span> <span class=\"k\">as<\/span> <span class=\"nn\">cm<\/span>\n<span class=\"kn\">import<\/span> <span class=\"nn\">matplotlib.pyplot<\/span> <span class=\"k\">as<\/span> <span class=\"nn\">plt<\/span>\n\n<span class=\"o\">%<\/span><span class=\"n\">matplotlib<\/span> <span class=\"n\">inline<\/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><\/span><span class=\"kn\">from<\/span> <span class=\"nn\">dwave.system.samplers<\/span> <span class=\"kn\">import<\/span> <span class=\"n\">DWaveSampler<\/span>\n<span class=\"kn\">from<\/span> <span class=\"nn\">dwave.system.composites<\/span> <span class=\"kn\">import<\/span> <span class=\"n\">EmbeddingComposite<\/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<h3><span class=\"ez-toc-section\" id=\"%E5%95%8F%E9%A1%8C%E8%A8%AD%E5%AE%9A\"><\/span>\u554f\u984c\u8a2d\u5b9a<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>\u6570\u5206\u5272\u554f\u984c\u3068\u306f\u3001\u4e0e\u3048\u3089\u308c\u305fN\u500b\u306e\u5b9f\u6570\u3092\u4e8c\u3064\u306e\u96c6\u5408\u306b\u5206\u3051\u305f\u3068\u304d\u3001\u7b49\u5206\u3067\u304d\u308b\u304b\u3069\u3046\u304b\u3092\u5224\u5b9a\u3059\u308b\u554f\u984c\u306e\u3053\u3068\u3067\u3059\u3002<\/p>\n<p>\u6570\u5206\u5272\u554f\u984c\u306fNP\u56f0\u96e3\u3068\u3055\u308c\u3066\u3044\u307e\u3059 [Lucas, 2014]\u3002NP\u56f0\u96e3\uff08NP-hard\uff09\u3068\u306fNP\u306b\u5c5e\u3059\u308b\u4efb\u610f\u306e\u554f\u984c\u3068\u6bd4\u3079\u3066\u3001\u5c11\u306a\u304f\u3068\u3082\u540c\u7a0b\u5ea6\u4ee5\u4e0a\u306b\u96e3\u3057\u3044\u554f\u984c\u306e\u3053\u3068\u3092\u6307\u3057\u307e\u3059\u3002\u8a00\u3044\u304b\u3048\u308b\u3068\u3001NP\u306b\u5c5e\u3059\u308b\u4efb\u610f\u306e\u554f\u984c\u304cA\u306b\u3088\u3063\u3066\u591a\u9805\u5f0f\u6642\u9593\u3067\u89e3\u3051\u308b\u3068\u304d\u3001A\u306fNP\u56f0\u96e3\u3067\u3042\u308b\u3068\u8a00\u3044\u307e\u3059\u3002\u305f\u3060\u3057\u3001NP\u3068\u306f\u975e\u6c7a\u5b9a\u7684\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u3067\u591a\u9805\u5f0f\u6642\u9593\u3067\u89e3\u3051\u308b\u554f\u984c\uff08Non-deterministic Polynomial Time-Solvable\uff09\u306e\u3053\u3068\u3067\u3042\u308a\u3001\u3053\u3053\u3067\u8a00\u3046\u975e\u6c7a\u5b9a\u7684\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u306f\u3001\u540c\u4e00\u306e\u5165\u529b\u306b\u5bfe\u3057\u3066\u7570\u306a\u308b\u51fa\u529b\u7d50\u679c\u3092\u8fd4\u3059\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u306e\u3053\u3068\u3067\u3059\u3002<\/p>\n<p>\u4ee5\u4e0b\u306e\u3088\u3046\u306b\u3057\u3066\u5e73\u5747\u5024Avg\u3001\u5206\u6563Var\u3068\u306a\u308b\u3088\u3046\u306aN\u500b\u306e\u30c7\u30fc\u30bfC\u3092\u751f\u6210\u3057\u3001\u305d\u308c\u3089\u3092\u6574\u6570\u306b\u4e38\u3081\u8fbc\u3080\u3053\u3068\u3067\u5b9f\u9a13\u7528\u30c7\u30fc\u30bfW\u3092\u4f5c\u6210\u3057\u307e\u3057\u305f\u3002\u6570\u5206\u5272\u554f\u984c\u3068\u3057\u3066\u3001\u3053\u306eN\u500b\u306e\u6570\u5024\u3092\u3069\u306e\u3088\u3046\u306b\u7d44\u307f\u5408\u308f\u305b\u308b\u3053\u3068\u306b\u3088\u3063\u30662\u3064\u306e\u30b0\u30eb\u30fc\u30d7\u306b\u5747\u7b49\u306b\u5206\u5272\u3067\u304d\u308b\u304b\u3092\u8003\u3048\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><\/span><span class=\"n\">N<\/span> <span class=\"o\">=<\/span> <span class=\"mi\">20<\/span>\n<span class=\"n\">Avg<\/span> <span class=\"o\">=<\/span> <span class=\"mi\">10<\/span>\n<span class=\"n\">Var<\/span> <span class=\"o\">=<\/span> <span class=\"mi\">10<\/span>\n\n<span class=\"n\">SD<\/span> <span class=\"o\">=<\/span> <span class=\"n\">np<\/span><span class=\"o\">.<\/span><span class=\"n\">sqrt<\/span><span class=\"p\">(<\/span><span class=\"n\">Var<\/span><span class=\"p\">)<\/span>\n<span class=\"n\">C<\/span> <span class=\"o\">=<\/span> <span class=\"n\">np<\/span><span class=\"o\">.<\/span><span class=\"n\">random<\/span><span class=\"o\">.<\/span><span class=\"n\">normal<\/span><span class=\"p\">(<\/span><span class=\"n\">loc<\/span><span class=\"o\">=<\/span><span class=\"n\">Avg<\/span><span class=\"p\">,<\/span> <span class=\"n\">scale<\/span><span class=\"o\">=<\/span><span class=\"n\">SD<\/span><span class=\"p\">,<\/span> <span class=\"n\">size<\/span><span class=\"o\">=<\/span><span class=\"n\">N<\/span><span class=\"p\">)<\/span>\n<span class=\"n\">W<\/span> <span class=\"o\">=<\/span> <span class=\"n\">np<\/span><span class=\"o\">.<\/span><span class=\"n\">round<\/span><span class=\"p\">(<\/span><span class=\"n\">C<\/span><span class=\"p\">)<\/span>  <span class=\"c1\"># \u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3092\u6574\u6570\u5024\u306b\u4e38\u3081\u8fbc\u3080<\/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><\/span><span class=\"k\">def<\/span> <span class=\"nf\">plot_numbers<\/span><span class=\"p\">(<\/span><span class=\"n\">numbers<\/span><span class=\"p\">):<\/span>\n    <span class=\"n\">x_list<\/span> <span class=\"o\">=<\/span> <span class=\"n\">np<\/span><span class=\"o\">.<\/span><span class=\"n\">arange<\/span><span class=\"p\">(<\/span><span class=\"nb\">len<\/span><span class=\"p\">(<\/span><span class=\"n\">numbers<\/span><span class=\"p\">))<\/span>\n    <span class=\"n\">plt<\/span><span class=\"o\">.<\/span><span class=\"n\">bar<\/span><span class=\"p\">(<\/span><span class=\"n\">x_list<\/span><span class=\"p\">,<\/span> <span class=\"n\">numbers<\/span><span class=\"p\">,<\/span> <span class=\"n\">color<\/span><span class=\"o\">=<\/span><span class=\"s2\">\"skyblue\"<\/span><span class=\"p\">)<\/span>\n    <span class=\"k\">for<\/span> <span class=\"n\">i<\/span><span class=\"p\">,<\/span> <span class=\"n\">n<\/span> <span class=\"ow\">in<\/span> <span class=\"nb\">enumerate<\/span><span class=\"p\">(<\/span><span class=\"n\">numbers<\/span><span class=\"p\">):<\/span>\n        <span class=\"n\">plt<\/span><span class=\"o\">.<\/span><span class=\"n\">text<\/span><span class=\"p\">(<\/span><span class=\"n\">i<\/span><span class=\"p\">,<\/span> <span class=\"n\">n<\/span> <span class=\"o\">\/<\/span> <span class=\"mi\">2<\/span><span class=\"p\">,<\/span> <span class=\"n\">n<\/span><span class=\"p\">,<\/span> <span class=\"n\">ha<\/span><span class=\"o\">=<\/span><span class=\"s2\">\"center\"<\/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>\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><\/span><span class=\"n\">plot_numbers<\/span><span class=\"p\">(<\/span><span class=\"n\">W<\/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\" alt=\"No description has been provided for this image\" 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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><\/span><span class=\"c1\"># \u751f\u6210\u3057\u305f\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306e\u5408\u8a08\u5024\u3001\u5e73\u5747\u5024\u3001\u5206\u6563\u3092\u8868\u793a<\/span>\n<span class=\"nb\">print<\/span><span class=\"p\">(<\/span><span class=\"s2\">\"\u5408\u8a08:<\/span><span class=\"se\">\\t<\/span><span class=\"s2\">\"<\/span><span class=\"p\">,<\/span> <span class=\"nb\">sum<\/span><span class=\"p\">(<\/span><span class=\"n\">W<\/span><span class=\"p\">))<\/span>\n<span class=\"nb\">print<\/span><span class=\"p\">(<\/span><span class=\"s2\">\"\u5e73\u5747:<\/span><span class=\"se\">\\t<\/span><span class=\"s2\">\"<\/span><span class=\"p\">,<\/span> <span class=\"nb\">sum<\/span><span class=\"p\">(<\/span><span class=\"n\">W<\/span><span class=\"p\">)<\/span> <span class=\"o\">\/<\/span> <span class=\"n\">N<\/span><span class=\"p\">)<\/span>\n<span class=\"nb\">print<\/span><span class=\"p\">(<\/span><span class=\"s2\">\"\u5206\u6563:<\/span><span class=\"se\">\\t<\/span><span class=\"s2\">\"<\/span><span class=\"p\">,<\/span> <span class=\"n\">np<\/span><span class=\"o\">.<\/span><span class=\"n\">var<\/span><span class=\"p\">(<\/span><span class=\"n\">W<\/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>\u5408\u8a08:\t 195.0\n\u5e73\u5747:\t 9.75\n\u5206\u6563:\t 9.8875\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<h3><span class=\"ez-toc-section\" id=\"%E8%A7%A3%E6%B3%95\"><\/span>\u89e3\u6cd5<span class=\"ez-toc-section-end\"><\/span><\/h3>\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<h4><span class=\"ez-toc-section\" id=\"%E3%83%93%E3%83%83%E3%83%88%E5%85%A8%E6%8E%A2%E7%B4%A2\"><\/span>\u30d3\u30c3\u30c8\u5168\u63a2\u7d22<span class=\"ez-toc-section-end\"><\/span><\/h4>\n<p>\u3053\u3053\u3067\u306f\u4e0e\u3048\u3089\u308c\u305f\u6570\u5024\u306b\u3064\u3044\u3066\u3001\u5168\u3066\u306e\u5206\u3051\u65b9\u3092\u8003\u3048\u308b\u3053\u3068\u3067\u6700\u9069\u89e3\u3092\u898b\u3064\u3051\u307e\u3059\u3002\u4ee5\u4e0b\u3067\u306f\u305d\u306e\u5177\u4f53\u7684\u306a\u5185\u5bb9\u306b\u3064\u3044\u3066\u8ff0\u3079\u307e\u3059\u3002<\/p>\n<p>\u4e0e\u3048\u3089\u308c\u305f\u6570\u5024\u30922\u3064\u306e\u30b0\u30eb\u30fc\u30d7\u306b\u5206\u3051\u308b\u3053\u3068\u3092\u8003\u3048\u3001\u540d\u524d\u3092\u305d\u308c\u305e\u308c$A,B$\u3068\u3057\u307e\u3059\u3002$A$\u3068$B$\u3092\u533a\u5225\u3059\u308b\u306a\u3089\u3070\u3001\u6570\u5024\u306e\u632f\u308a\u5206\u3051\u65b9\u306f$2^N$\u901a\u308a\u3042\u308a\u307e\u3059\u3002<\/p>\n<p>\u6b21\u306b\u30b0\u30eb\u30fc\u30d7\u5206\u3051\u306e\u8868\u8a18\u306e\u4ed5\u65b9\u306b\u3064\u3044\u3066\u8ff0\u3079\u307e\u3059\u3002\u3053\u3053\u3067\u306f\u30b0\u30eb\u30fc\u30d7$A$\u306b\u6240\u5c5e\u3059\u308b\u3053\u3068\u3092$0$\u3001\u30b0\u30eb\u30fc\u30d7$B$\u306b\u6240\u5c5e\u3059\u308b\u3053\u3068\u3092$1$\u3067\u8868\u73fe\u3057\u307e\u3059\u3002\u307e\u305a\u521d\u3081\u306b$0$\u304b\u3089$2^N$\u307e\u3067\u306e\u6570\u5024\u3092\u4e8c\u9032\u6570\u3067\u751f\u6210\u3057\u307e\u3059\u3002\u751f\u6210\u3057\u305f\u4e8c\u9032\u6570\u306b\u5bfe\u3057$2^k$\u306e\u4f4d\u306e\u5024\uff08$0$\u307e\u305f\u306f$1$\uff09\u3092\u898b\u3066\u3001\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306e$k$\u756a\u76ee\u306e\u6570\u5024\u3092\u3069\u3061\u3089\u306e\u30b0\u30eb\u30fc\u30d7\u306b\u5272\u308a\u632f\u308b\u304b\u3092\u6c7a\u5b9a\u3057\u307e\u3059\u3002\u3053\u306e\u3068\u304d\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8$W$\u306e\u5148\u982d\u306f0\u756a\u76ee\u3067\u3042\u308b\u3068\u3057\u3001$k$\u306f$0&lt;k&lt;N-1$\u3092\u6e80\u305f\u3059\u3053\u3068\u306b\u6ce8\u610f\u3057\u3066\u304f\u3060\u3055\u3044\u3002\u3053\u306e\u64cd\u4f5c\u3092$2^0$\u306e\u4f4d\u304b\u3089$2^{N-1}$\u306e\u4f4d\u307e\u3067\u884c\u3044\u307e\u3059\u3002\u3055\u3089\u306b\u3001\u3053\u306e\u64cd\u4f5c\u3092\u751f\u6210\u3057\u305f\u4e8c\u9032\u6570$0$\u304b\u3089$2^{N-1}$\u307e\u3067\u884c\u3044\u307e\u3059\u3002<\/p>\n<p>\u305f\u3060\u3057\u3001\u672c\u6765\u306a\u3089\u30702\u3064\u306e\u30b0\u30eb\u30fc\u30d7\u3092\u533a\u5225\u3059\u308b\u5fc5\u8981\u306f\u3042\u308a\u307e\u305b\u3093\u304c\u3001\u3053\u306e\u8a08\u7b97\u65b9\u6cd5\u3067\u306f\u533a\u5225\u3057\u3066\u3057\u307e\u3063\u3066\u3044\u307e\u3059\u3002\u672c\u8a18\u4e8b\u3067\u306f\u91cf\u5b50\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u3068\u30d3\u30c3\u30c8\u5168\u63a2\u7d22\u306e\u8a08\u7b97\u6642\u9593\u306e\u5dee\u3092\u6bd4\u8f03\u3059\u308b\u3053\u3068\u3092\u76ee\u7684\u3068\u3057\u3066\u304a\u308a\u3001\u5f8c\u8ff0\u3059\u308b\u901a\u308a\u305d\u306e\u5dee\u306f\u660e\u78ba\u3067\u3059\u3002\u305d\u306e\u305f\u3081\u3001\u4eca\u56de\u306f\u7dcf\u5f53\u305f\u308a\u8a08\u7b97\u306e\u52b9\u7387\u3092\u8ffd\u6c42\u3059\u308b\u3053\u3068\u306f\u3057\u307e\u305b\u3093\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>\u4ee5\u4e0b\u3067\u306f\uff0c\u524d\u8ff0\u3057\u305f\u30d3\u30c3\u30c8\u5168\u63a2\u7d22\u306b\u3088\u3063\u3066\u4e0e\u3048\u3089\u308c\u305f\u6570\u5206\u5272\u554f\u984c\u306b\u5bfe\u3059\u308b\u6700\u9069\u89e3\u3092\u53d6\u308a\u51fa\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><\/span><span class=\"n\">t1<\/span> <span class=\"o\">=<\/span> <span class=\"n\">time<\/span><span class=\"o\">.<\/span><span class=\"n\">perf_counter<\/span><span class=\"p\">()<\/span>\n\n<span class=\"c1\"># \u5168\u901a\u308a\u306e\u30b0\u30eb\u30fc\u30d7\u5206\u3051\u306e\u7d50\u679c<\/span>\n<span class=\"n\">Group_A_BF<\/span> <span class=\"o\">=<\/span> <span class=\"n\">np<\/span><span class=\"o\">.<\/span><span class=\"n\">zeros<\/span><span class=\"p\">(((<\/span><span class=\"mi\">2<\/span><span class=\"o\">**<\/span><span class=\"n\">N<\/span><span class=\"p\">),<\/span> <span class=\"n\">N<\/span><span class=\"p\">))<\/span>\n<span class=\"n\">Group_B_BF<\/span> <span class=\"o\">=<\/span> <span class=\"n\">np<\/span><span class=\"o\">.<\/span><span class=\"n\">zeros<\/span><span class=\"p\">(((<\/span><span class=\"mi\">2<\/span><span class=\"o\">**<\/span><span class=\"n\">N<\/span><span class=\"p\">),<\/span> <span class=\"n\">N<\/span><span class=\"p\">))<\/span>\n\n<span class=\"c1\"># bit\u306b\u3088\u308b\u7d44\u307f\u5408\u308f\u305b<\/span>\n<span class=\"n\">Combo<\/span> <span class=\"o\">=<\/span> <span class=\"n\">np<\/span><span class=\"o\">.<\/span><span class=\"n\">zeros<\/span><span class=\"p\">(((<\/span><span class=\"mi\">2<\/span><span class=\"o\">**<\/span><span class=\"n\">N<\/span><span class=\"p\">),<\/span> <span class=\"n\">N<\/span><span class=\"p\">))<\/span>\n\n<span class=\"c1\"># 2\u3064\u306e\u30b0\u30eb\u30fc\u30d7\u306e\u5dee\u306e\u6700\u5c0f\u5024<\/span>\n<span class=\"n\">Diff_BF<\/span> <span class=\"o\">=<\/span> <span class=\"nb\">sum<\/span><span class=\"p\">(<\/span><span class=\"n\">W<\/span><span class=\"p\">)<\/span>\n\n<span class=\"c1\"># \u6700\u9069\u89e3\u306e\u30b0\u30eb\u30fc\u30d7\u5206\u3051\u306e\u66ab\u5b9a\u5024<\/span>\n<span class=\"n\">note<\/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\">2<\/span><span class=\"o\">**<\/span><span class=\"n\">N<\/span><span class=\"p\">):<\/span>\n    <span class=\"c1\"># bit\u3067\u7d44\u307f\u5408\u308f\u305b\u3092\u8868\u73fe\u3059\u308b\u305f\u3081\u306bi\u30922\u9032\u6570\u306b\u5909\u63db\u3057\u3001\u6b8b\u308a\u30920\u3067\u57cb\u3081\u308b<\/span>\n    <span class=\"n\">Bit<\/span> <span class=\"o\">=<\/span> <span class=\"nb\">format<\/span><span class=\"p\">(<\/span><span class=\"n\">i<\/span><span class=\"p\">,<\/span> <span class=\"s2\">\"b\"<\/span><span class=\"p\">)<\/span><span class=\"o\">.<\/span><span class=\"n\">zfill<\/span><span class=\"p\">(<\/span><span class=\"n\">N<\/span><span class=\"p\">)<\/span>\n\n    <span class=\"k\">for<\/span> <span class=\"n\">j<\/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=\"c1\"># Bit\u306e0,1\u306b\u5fdc\u3058\u3066\u5168\u901a\u308a\u306e\u7d44\u5408\u305b\u3092\u4fdd\u5b58\u3059\u308b<\/span>\n        <span class=\"k\">if<\/span> <span class=\"n\">Bit<\/span><span class=\"p\">[<\/span><span class=\"n\">j<\/span><span class=\"p\">]<\/span> <span class=\"o\">==<\/span> <span class=\"s2\">\"1\"<\/span><span class=\"p\">:<\/span>\n            <span class=\"n\">Group_A_BF<\/span><span class=\"p\">[<\/span><span class=\"n\">i<\/span><span class=\"p\">][<\/span><span class=\"n\">j<\/span><span class=\"p\">]<\/span> <span class=\"o\">=<\/span> <span class=\"n\">W<\/span><span class=\"p\">[<\/span><span class=\"n\">j<\/span><span class=\"p\">]<\/span>\n        <span class=\"k\">else<\/span><span class=\"p\">:<\/span>\n            <span class=\"n\">Group_B_BF<\/span><span class=\"p\">[<\/span><span class=\"n\">i<\/span><span class=\"p\">][<\/span><span class=\"n\">j<\/span><span class=\"p\">]<\/span> <span class=\"o\">=<\/span> <span class=\"n\">W<\/span><span class=\"p\">[<\/span><span class=\"n\">j<\/span><span class=\"p\">]<\/span>\n\n    <span class=\"c1\"># \u4e0a\u3067\u6c42\u3081\u305f\u5168\u901a\u308a\u306e\u7d44\u5408\u305b\u306e\u3046\u3061\u3001\u5dee\u304c\u6700\u5c0f\u3068\u306a\u308b\u3082\u306e\u3092\u62bd\u51fa\u3059\u308b<\/span>\n    <span class=\"n\">Diff_tmp<\/span> <span class=\"o\">=<\/span> <span class=\"nb\">abs<\/span><span class=\"p\">(<\/span><span class=\"nb\">sum<\/span><span class=\"p\">(<\/span><span class=\"n\">Group_A_BF<\/span><span class=\"p\">[<\/span><span class=\"n\">i<\/span><span class=\"p\">])<\/span> <span class=\"o\">-<\/span> <span class=\"nb\">sum<\/span><span class=\"p\">(<\/span><span class=\"n\">Group_B_BF<\/span><span class=\"p\">[<\/span><span class=\"n\">i<\/span><span class=\"p\">]))<\/span>\n\n    <span class=\"k\">if<\/span> <span class=\"n\">Diff_tmp<\/span> <span class=\"o\">&lt;=<\/span> <span class=\"n\">Diff_BF<\/span><span class=\"p\">:<\/span>\n        <span class=\"n\">Diff_BF<\/span> <span class=\"o\">=<\/span> <span class=\"n\">Diff_tmp<\/span>\n        <span class=\"n\">note<\/span> <span class=\"o\">=<\/span> <span class=\"n\">i<\/span>\n\n<span class=\"n\">t2<\/span> <span class=\"o\">=<\/span> <span class=\"n\">time<\/span><span class=\"o\">.<\/span><span class=\"n\">perf_counter<\/span><span class=\"p\">()<\/span>\n\n<span class=\"c1\"># \u8a08\u7b97\u6642\u9593\u3092\u8a18\u9332\u3059\u308b<\/span>\n<span class=\"n\">Time_BF<\/span> <span class=\"o\">=<\/span> <span class=\"n\">t2<\/span> <span class=\"o\">-<\/span> <span class=\"n\">t1<\/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>\u3082\u3057\u3082\u3053\u3053\u3067\u30af\u30e9\u30c3\u30b7\u30e5\u3057\u3066\u3057\u307e\u3046\u5834\u5408\u306f\u3001\u554f\u984c\u30b5\u30a4\u30ba\u3092\u5c0f\u3055\u304f\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<p>\u6700\u5f8c\u306b\u5148\u307b\u3069\u6c42\u3081\u305f\u6700\u9069\u89e3\u306e\u5185\u306e\uff11\u3064\u3092\u8868\u793a\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><\/span><span class=\"k\">def<\/span> <span class=\"nf\">plot_grouping<\/span><span class=\"p\">(<\/span><span class=\"n\">A<\/span><span class=\"p\">,<\/span> <span class=\"n\">B<\/span><span class=\"p\">,<\/span> <span class=\"n\">bar_width<\/span><span class=\"o\">=<\/span><span class=\"mf\">0.4<\/span><span class=\"p\">,<\/span> <span class=\"n\">alpha<\/span><span class=\"o\">=<\/span><span class=\"mi\">1<\/span><span class=\"p\">):<\/span>\n    <span class=\"n\">df<\/span> <span class=\"o\">=<\/span> <span class=\"n\">pd<\/span><span class=\"o\">.<\/span><span class=\"n\">DataFrame<\/span><span class=\"p\">([<\/span><span class=\"n\">A<\/span><span class=\"p\">,<\/span> <span class=\"n\">B<\/span><span class=\"p\">],<\/span> <span class=\"n\">index<\/span><span class=\"o\">=<\/span><span class=\"p\">[<\/span><span class=\"s2\">\"A\"<\/span><span class=\"p\">,<\/span> <span class=\"s2\">\"B\"<\/span><span class=\"p\">])<\/span><span class=\"o\">.<\/span><span class=\"n\">T<\/span>\n    <span class=\"n\">df_nan<\/span> <span class=\"o\">=<\/span> <span class=\"n\">df<\/span><span class=\"o\">.<\/span><span class=\"n\">replace<\/span><span class=\"p\">([<\/span><span class=\"mi\">0<\/span><span class=\"p\">],<\/span> <span class=\"n\">np<\/span><span class=\"o\">.<\/span><span class=\"n\">nan<\/span><span class=\"p\">)<\/span>\n\n    <span class=\"n\">fig<\/span><span class=\"p\">,<\/span> <span class=\"n\">ax<\/span> <span class=\"o\">=<\/span> <span class=\"n\">plt<\/span><span class=\"o\">.<\/span><span class=\"n\">subplots<\/span><span class=\"p\">()<\/span>\n\n    <span class=\"n\">Sum<\/span> <span class=\"o\">=<\/span> <span class=\"n\">np<\/span><span class=\"o\">.<\/span><span class=\"n\">array<\/span><span class=\"p\">([<\/span><span class=\"nb\">sum<\/span><span class=\"p\">(<\/span><span class=\"n\">A<\/span><span class=\"p\">),<\/span> <span class=\"nb\">sum<\/span><span class=\"p\">(<\/span><span class=\"n\">B<\/span><span class=\"p\">)])<\/span>\n\n    <span class=\"n\">data_points<\/span> <span class=\"o\">=<\/span> <span class=\"n\">np<\/span><span class=\"o\">.<\/span><span class=\"n\">arange<\/span><span class=\"p\">(<\/span><span class=\"nb\">len<\/span><span class=\"p\">(<\/span><span class=\"n\">df<\/span><span class=\"o\">.<\/span><span class=\"n\">columns<\/span><span class=\"p\">))<\/span>\n    <span class=\"n\">bottom_data<\/span> <span class=\"o\">=<\/span> <span class=\"n\">pd<\/span><span class=\"o\">.<\/span><span class=\"n\">Series<\/span><span class=\"p\">(<\/span><span class=\"n\">np<\/span><span class=\"o\">.<\/span><span class=\"n\">zeros<\/span><span class=\"p\">(<\/span><span class=\"nb\">len<\/span><span class=\"p\">(<\/span><span class=\"n\">df<\/span><span class=\"o\">.<\/span><span class=\"n\">columns<\/span><span class=\"p\">)),<\/span> <span class=\"n\">index<\/span><span class=\"o\">=<\/span><span class=\"n\">df<\/span><span class=\"o\">.<\/span><span class=\"n\">columns<\/span><span class=\"o\">.<\/span><span class=\"n\">tolist<\/span><span class=\"p\">())<\/span>\n\n    <span class=\"n\">index<\/span> <span class=\"o\">=<\/span> <span class=\"n\">np<\/span><span class=\"o\">.<\/span><span class=\"n\">array<\/span><span class=\"p\">([<\/span><span class=\"s2\">\"A\"<\/span><span class=\"p\">,<\/span> <span class=\"s2\">\"B\"<\/span><span class=\"p\">])<\/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=\"nb\">len<\/span><span class=\"p\">(<\/span><span class=\"n\">df<\/span><span class=\"o\">.<\/span><span class=\"n\">index<\/span><span class=\"p\">)):<\/span>\n        <span class=\"n\">p1<\/span> <span class=\"o\">=<\/span> <span class=\"n\">ax<\/span><span class=\"o\">.<\/span><span class=\"n\">bar<\/span><span class=\"p\">(<\/span>\n            <span class=\"n\">index<\/span><span class=\"p\">,<\/span>\n            <span class=\"n\">df<\/span><span class=\"o\">.<\/span><span class=\"n\">iloc<\/span><span class=\"p\">[<\/span><span class=\"n\">i<\/span><span class=\"p\">],<\/span>\n            <span class=\"n\">bar_width<\/span><span class=\"p\">,<\/span>\n            <span class=\"n\">bottom<\/span><span class=\"o\">=<\/span><span class=\"n\">bottom_data<\/span><span class=\"p\">,<\/span>\n            <span class=\"n\">alpha<\/span><span class=\"o\">=<\/span><span class=\"n\">alpha<\/span><span class=\"p\">,<\/span>\n            <span class=\"n\">color<\/span><span class=\"o\">=<\/span><span class=\"s2\">\"skyblue\"<\/span><span class=\"p\">,<\/span>\n            <span class=\"n\">edgecolor<\/span><span class=\"o\">=<\/span><span class=\"s2\">\"white\"<\/span><span class=\"p\">,<\/span>\n            <span class=\"n\">linewidth<\/span><span class=\"o\">=<\/span><span class=\"mf\">0.5<\/span><span class=\"p\">,<\/span>\n        <span class=\"p\">)<\/span>\n        <span class=\"n\">ax<\/span><span class=\"o\">.<\/span><span class=\"n\">bar_label<\/span><span class=\"p\">(<\/span><span class=\"n\">p1<\/span><span class=\"p\">,<\/span> <span class=\"n\">label_type<\/span><span class=\"o\">=<\/span><span class=\"s2\">\"center\"<\/span><span class=\"p\">)<\/span>\n\n        <span class=\"n\">bottom_data<\/span> <span class=\"o\">+=<\/span> <span class=\"n\">df<\/span><span class=\"o\">.<\/span><span class=\"n\">iloc<\/span><span class=\"p\">[<\/span><span class=\"n\">i<\/span><span class=\"p\">]<\/span>\n        <span class=\"n\">ax<\/span><span class=\"o\">.<\/span><span class=\"n\">set_xticks<\/span><span class=\"p\">(<\/span><span class=\"n\">data_points<\/span><span class=\"p\">)<\/span>\n        <span class=\"n\">ax<\/span><span class=\"o\">.<\/span><span class=\"n\">set_xticklabels<\/span><span class=\"p\">(<\/span><span class=\"n\">df<\/span><span class=\"o\">.<\/span><span class=\"n\">columns<\/span><span class=\"p\">)<\/span>\n\n    <span class=\"k\">return<\/span> <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>\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><\/span><span class=\"n\">plot_grouping<\/span><span class=\"p\">(<\/span><span class=\"n\">Group_A_BF<\/span><span class=\"p\">[<\/span><span class=\"n\">note<\/span><span class=\"p\">],<\/span> <span class=\"n\">Group_B_BF<\/span><span class=\"p\">[<\/span><span class=\"n\">note<\/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\" alt=\"No description has been provided for this image\" 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oygfAADAUZQPAADgKMoHAABwFOUDAAA4ivIBAAAcRfkAAACOonwAAABHUT4AAICjKB8AAMBRlA8AAOAoygcAAHAU5QMAADiKT7Wthw7v3KLNy+Yrc\/8eFZ7I0ag5SxXf+9pqzzn21Rfa8MyD+mrXFlVVVOqC1u016vElCo5qbig1AMAWlI96qKykWFHt45Uw9Ca9fPfNZx0\/mXFYC28ZpG5DRyppwr3y9Q9QzlcH5ePr63xYAIB1KB\/1UGxikmITk370+Mb5jyo2MUkDJs\/w7AuNjnEiGgAAzPmwTVVVlQ58\/DeFtWyjxX8aroev6aD5\/9NP\/\/zwXdPRAACWoHxY5vSp4yorPq1NS55R+57XaMxzryq+97VafvfN+mrnJ6bjAQAswGUXy7jdbknSRVf11xWjJkiSmsV21JE9n2nba0vVumuiyXgAAAtQPizTOLipvHx8dEHr9tX2h8e01ze7PzWUCoCTfFwujYkLNh0DBvm4XGbPb\/TscJxPg4ZqftGlOv71v6rtP3HkXwqOijaUCoCTKtxuLT6QZzoGDBrXIdjo+Skf9VBpcZFOZhz2bOdmHlHWwc\/VODBEwVHN1et\/JmrltHGK6dJDrRMS9cWWD3Rg83sa98Jac6EBANagfNRDmfv2aNH4ZM\/2O3OnS5K6DB6h4TPnKf7qgUq+73F9tORpvf34fQpv2UYjH1+iVpdebigxAMAmlI96qHVColJ3Hf+vz0lIHqmE5JEOJQIA4N9YagsAABxF+QAAAI6ifAAAAEdRPgAAgKMoHwAAwFGUDwAA4CjKBwAAcBTlAwAAOIryAQAAHEX5AAAAjqJ8AAAAR1E+AACAoygfAADAUZQPAADgKB\/TAQAAqG2Hd27R5mXzlbl\/jwpP5GjUnKWK732t5\/j7C2dr78Y1ysvOkneDBrqwQ2f1nXifWnTsajC1PRj5AADUO2UlxYpqH6+h02ad83hYyzYaMvUxTX51kyYsXqeQZtFaPHG4inJPOJzUTox8AADqndjEJMUmJv3o8UsGDKu2PXDKQ9qxdrmyv9intt171XU86zHyAQCwWkV5mba\/sUx+TQIV1T7edBwrMPIBALDS\/s0b9UrKOJWXnFFAWITGLHhN\/iGhpmNZgZEPAICV2nRL1KSVH2rCknfVvufVWjl1rIpOHTcdywqUDwCAlRo28ldYi9Zq0SlBw2Y8LS9vb+1Yu9x0LCtQPgAAkOR2u1VRVmY6hhWY8wEAqHdKi4t0MuOwZzs384iyDn6uxoEhahwcog9ffFIdruyvgLAIFeed0tZX01Rw7Kg69hliMLU9KB8AgHonc98eLRqf7Nl+Z+50SVKXwSOUfN8TOv71Ie1aN1qn806pcVCImsdfqvFpbyuiTZyhxHahfAAA6p3WCYlK3fXjk0dHzXnJuTA4S43LR2ZmpqZOnar169eruLhYbdu21ZIlS5SQkCDpu2tmM2bM0KJFi5SXl6fExEQtWLBA7dq1q\/Xw58PH5dKYuGDTMWCQj8tlOgIAWK1G5SM3N1eJiYnq3bu31q9fr\/DwcH355ZcKCQnxPGf27Nl65plntHTpUsXExGj69Onq16+f9u3bJz8\/v1r\/Bmqqwu3W4gN5pmPAoHEdgk1HAACr1ah8zJo1S9HR0VqyZIlnX0xMjOe\/3W63nnrqKf35z3\/W0KFDJUnLli1TRESE1q5dqxtuuKGWYgMAgN+qGi21feutt5SQkKDhw4frggsu0KWXXqpFixZ5jh8+fFjZ2dlKSvr3\/fSDgoLUvXt3bd269ZyvWVpaqoKCgmoPAABQf9WofHz11Vee+RvvvfeebrvtNt1xxx1aunSpJCk7O1uSFBERUe3rIiIiPMf+U2pqqoKCgjyP6Ojo8\/k+AADAb0SNykdVVZW6dOmiRx99VJdeeqnGjx+vcePGaeHChecdICUlRfn5+Z5HRkbGeb8WAAD49atR+YiKitJFF11UbV+HDh105MgRSVJkZKQkKScnp9pzcnJyPMf+k6+vrwIDA6s9AABA\/VWj8pGYmKiDBw9W2\/fFF1+oZcuWkr6bfBoZGan09HTP8YKCAm3btk09evSohbgAAOC3rkarXe666y717NlTjz76qK6\/\/npt375dL7zwgl544QVJksvl0uTJk\/Xwww+rXbt2nqW2zZo1U3Jycl3kBwAAvzE1Kh\/dunXTmjVrlJKSogcffFAxMTF66qmnNHLkSM9z7r33Xp0+fVrjx49XXl6errjiCm3YsOFXcY8PAABgnsvtdrtNh\/ihgoICBQUFKT8\/v07mf5wsqdCi\/Xm1\/rr47RjXIVihfnyyAOzF+yDq4n2wJr+\/azTnAwAA4Jfizz9LlJ4u0sbnUrXvw3dVlHtCzWI7atA9jyg6\/lLT0QAAlmHkwxKvPzhZh7Zt0vUPzdedqzap3eVXKe22Yco\/dtR0NACAZSgfFigvOaN\/frBOA+58QDFdeyqsRWslTbhXoc1jtG31kp9+AQAAahHlwwJVlZWqqqyUT8PqK44a+Pnp693bDKUCANiK8mEBX\/8matGpmz54cY4KjmerqrJSf39ntY7s3aHCEzk\/\/QIAANQiyoclrn9ovuR2K7VfR02\/\/EJteWWROve7Ti4X\/wQAAM5itYslQqNjNP7Ft1R25rRKigoVGB6pFVPHqmnzlqajAQAsQ\/mwTMNG\/mrYyF9nCvL05dYPNeDOGaYjAXCYj8ulMXHBpmPAIB+Xy+z5jZ4djvliywdyu90Kb9VWJzMOa\/1Tf1F4q3bqOuRG09EAOKzC7dbiA3mmY8CgcR2CjZ6f8mGJkqICvTfvEeXnZKlxULDirx6kfhPvl3eDBqajAQAsQ\/mwRKe+yerUN9l0DAAAWO0CAACcRfkAAACOonwAAABHUT4AAICjKB8AAMBRlA8AAOAoygcAAHAU5QMAADiK8gEAABxF+QAAAI6ifAAAAEdZ99kufJQ0TH+UNIC6d3jnFm1eNl+Z+\/eo8ESORs1Zqvje13qO\/yN9nba9vlSZ+\/foTH6uJq38QM1iOxpMbBfrygcfJQ3THyUNoO6VlRQrqn28EobepJfvvvns42eK1eqS7urUZ4jeeGiK8wEtZ135AADUf7GJSYpNTPrR410GXS9Jys064lQk\/ABzPgAAgKMoHwAAwFGUDwAA4CjKBwAAcBTlAwAAOIrVLgCAeqe0uEgnMw57tnMzjyjr4OdqHBii4KjmKs7PVV72tyo4ni1JOvH1IUlSQOgFCgiLMJLZJpQPAEC9k7lvjxaNT\/ZsvzN3uiSpy+ARGj5znvZv2qDX\/nKH5\/jKlPGSpGvG36OkCfc6mtVGlA8AQL3TOiFRqbuO\/+jxrkNuVNchNzqYCD9E+bBE6ekibXwuVfs+fFdFuSfULLajBt3ziKLjLzUdDQBgGSacWuL1Byfr0LZNuv6h+bpz1Sa1u\/wqpd02TPnHjpqOBgCwDOXDAuUlZ\/TPD9ZpwJ0PKKZrT4W1aK2kCfcqtHmMtq1eYjoeAMAylA8LVFVWqqqyUj4N\/artb+Dnp693bzOUCgBgK8qHBXz9m6hFp2764MU5KjierarKSv39ndU6sneHCk\/kmI4HALAM5cMS1z80X3K7ldqvo6ZffqG2vLJInftdJ5eLfwIAAGex2sUSodExGv\/iWyo7c1olRYUKDI\/Uiqlj1bR5S9PRAACW4c9eyzRs5K\/A8EidKcjTl1s\/1EVXDjAdCQBgGUY+LPHFlg\/kdrsV3qqtTmYc1vqn\/qLwVu24yQ4AwHGUD0uUFBXovXmPKD8nS42DghV\/9SD1m3i\/vBs0MB0NAGAZyoclOvVNVqe+yaZjAADAnA8AAOAsygcAAHAU5QMAADiK8gEAABxF+QAAAI5itQsAWMbH5dKYuGDTMWCQj8tl9vxGzw4AcFyF263FB\/JMx4BB4zoEGz0\/l10AAICjKB8AAMBRlA8AAOAoygcAAHAU5QMAADjKutUuLDGD6SVmAGA768oHS8xgeokZANiOyy4AAMBRlA8AAOAo6y67AADsVHq6SBufS9W+D99VUe4JNYvtqEH3PKLo+EtNR7MOIx8AACu8\/uBkHdq2Sdc\/NF93rtqkdpdfpbTbhin\/2FHT0axD+QAA1HvlJWf0zw\/WacCdDyima0+FtWitpAn3KrR5jLatXmI6nnV+Ufl47LHH5HK5NHnyZM++kpISTZw4UaGhoWrSpImGDRumnJycX5oTAIDzVlVZqarKSvk09Ku2v4Gfn77evc1QKnudd\/n47LPP9Pzzz6tTp07V9t911116++23tXr1am3atElZWVm67rrrfnFQAADOl69\/E7Xo1E0fvDhHBcezVVVZqb+\/s1pH9u5Q4Qn+QHbaeZWPoqIijRw5UosWLVJISIhnf35+vtLS0jR37lxdffXV6tq1q5YsWaItW7bo008\/rbXQAADU1PUPzZfcbqX266jpl1+oLa8sUud+18nlYgaC087rJz5x4kQNHDhQSUlJ1fbv3LlT5eXl1fbHxcWpRYsW2rp16zlfq7S0VAUFBdUeAADUttDoGI1\/8S3N\/ORrTX13tyb+daMqK8rVtHlL09GsU+Oltq+88op27dqlzz777Kxj2dnZatiwoYKDg6vtj4iIUHZ29jlfLzU1VTNnzqxpDNQQS8wA4DsNG\/mrYSN\/nSnI05dbP9SAO2eYjmSdGo18ZGRk6M4779Ty5cvl5+f301\/wM6SkpCg\/P9\/zyMjIqJXXRXUsMQNguy+2fKCDn6TrVOY3+vLTj7RofLLCW7VT1yE3mo5mnRqNfOzcuVPHjh1Tly5dPPsqKyu1efNmzZs3T++9957KysqUl5dXbfQjJydHkZGR53xNX19f+fr6nl96\/CzfLzH7w9xliunaU5KUNOFe7d\/8nratXqK+E+8znBAA6l5JUYHem\/eI8nOy1DgoWPFXD1K\/iffLu0ED09GsU6Pycc011+jzzz+vtm\/06NGKi4vT1KlTFR0drQYNGig9PV3Dhg2TJB08eFBHjhxRjx49ai81aoQlZgAgdeqbrE59k03HgGpYPgICAnTxxRdX2+fv76\/Q0FDP\/ltuuUVTpkxR06ZNFRgYqEmTJqlHjx66\/PLLay81auSHS8wuaN1eTZqGa8+GN3Rk7w6FRseYjgcAsEytf7bLk08+KS8vLw0bNkylpaXq16+fnnvuudo+DWro+ofm6\/WZdyq1X0d5eXurWVwnde53nTL37zEdDQBgmV9cPj766KNq235+fpo\/f77mz5\/\/S18atej7JWZlZ06rpKhQgeGRWjF1LEvMAACO484qlmnYyF+B4ZGeJWYXXTnAdCQAgGVq\/bILfp2+2PKB3G63wlu11cmMw1r\/1F9YYgYAMILyYQmWmAEAfi0oH5ZgiRkA4NeCOR8AAMBRlA8AAOAoygcAAHAU5QMAADiK8gEAABzFahcAsIyPy6UxccGmY8AgH5fL7PmNnh0A4LgKt1uLD+SZjgGDxnUINnp+LrsAAABHUT4AAICjKB8AAMBRlA8AAOAoygcAAHCUdatdWGIG00vMAMB21pUPlpjB9BIzALAdl10AAICjKB8AAMBRlA8AAOAoygcAAHAU5QMAADiK8gEAABxF+QAAAI6ifAAAAEdRPgAAgKOsu8MpAKD+O7xzizYvm6\/M\/XtUeCJHo+YsVXzvaz3H3184W3s3rlFedpa8GzTQhR06q+\/E+9SiY1eDqe3ByAcAoN4pKylWVPt4DZ0265zHw1q20ZCpj2nyq5s0YfE6hTSL1uKJw1WUe8LhpHZi5AMAUO\/EJiYpNjHpR49fMmBYte2BUx7SjrXLlf3FPrXt3quu41mPkQ8AgNUqysu0\/Y1l8msSqKj28abjWIGRDwCAlfZv3qhXUsapvOSMAsIiNGbBa\/IPCTUdywqMfAAArNSmW6ImrfxQE5a8q\/Y9r9bKqWNVdOq46VhWoHwAAKzUsJG\/wlq0VotOCRo242l5eXtrx9rlpmNZgfIBAIAkt9utirIy0zGswJyPeoj17QBsV1pcpJMZhz3buZlHlHXwczUODFHj4BB9+OKT6nBlfwWERag475S2vpqmgmNH1bHPEIOp7UH5qIe+X9+eMPQmvXz3zWcd\/359e9MLW6q8tEQfL1+oxROH6+43t6tJSJjzgQGglmXu26NF45M92+\/MnS5J6jJ4hJLve0LHvz6kXetG63TeKTUOClHz+Es1Pu1tRbSJM5TYLpSPeoj17QBs1zohUam7fnzy6Kg5LzkXBmdhzoflWN8OAHAaIx+WYn07AMAURj4sxfp2AIAplA9Lsb4dAGAK5QOSWN8OAHAOcz7qIda3AwB+zSgf9RDr2wEAv2aUj3qI9e0AgF8z5nwAAABHUT4AAICjKB8AAMBRlA8AAOAoygcAAHAU5QMAADiK8gEAsMbWVWmaNbCLpl\/eXPP\/p58y\/rHLdCQrUT4AAFbY+94avTP3AV0z\/m7dviJdUe3itXji9XyopgGUDwCAFf5v+UJ1+90oJQy9SRGtY5V8\/xNq6NdIO95cYTqadSgfAIB6r6K8TFn796ht9ys9+7y8vNSmey8d2bvDYDI7UT4AAPVecd4pVVVWqknT8Gr7A5peoMKTxwylshflAwAAOIoPlgMAyzTwcmlsXLDpGI4qa91Ys7291aNRsa79wff+98o8NW55oXU\/jwZeLqPnp3wAgGXKq9x68UCe6RiOi+rQWQvXrFdW++\/mfVRVVWnD39LVY8Qt1v08xnUINnp+ygcAwAr\/38gJWj1jki686BJFx3fRJyueV9mZYnUdcqPpaNahfAAArNCp3+9UlHtS7y+YpcKTxxQVe7FGz1ulgNALTEezDuUDAGCNnjeMVc8bxpqOYT1WuwAAAEdRPgAAgKNqdNklNTVVb7zxhg4cOKBGjRqpZ8+emjVrlmJjYz3PKSkp0f\/+7\/\/qlVdeUWlpqfr166fnnntOERERtR7+fPi4XBpj2ZIqVOfjMrvEDABsV6PysWnTJk2cOFHdunVTRUWF7rvvPvXt21f79u2Tv7+\/JOmuu+7SO++8o9WrVysoKEi33367rrvuOn3yySd18g3UVIXbrcWWLalCdaaXmAGA7WpUPjZs2FBt+6WXXtIFF1ygnTt3qlevXsrPz1daWppWrFihq6++WpK0ZMkSdejQQZ9++qkuv\/zy2ksOAAB+k37RnI\/8\/HxJUtOmTSVJO3fuVHl5uZKSkjzPiYuLU4sWLbR169ZzvkZpaakKCgqqPQAAQP113kttq6qqNHnyZCUmJuriiy+WJGVnZ6thw4YKDg6u9tyIiAhlZ2ef83VSU1M1c+bM842Bn+H9hbOV\/sLj1faFt2qrKW+cuxACAFCXzrt8TJw4Uf\/4xz\/08ccf\/6IAKSkpmjJlime7oKBA0dHRv+g1cbaINnG6ZcFrnm0vb27xAgAw47x+A91+++1at26dNm\/erObNm3v2R0ZGqqysTHl5edVGP3JychQZGXnO1\/L19ZWvr+\/5xEANeHl7KyDs17HiCABgtxrN+XC73br99tu1Zs0affDBB4qJial2vGvXrmrQoIHS09M9+w4ePKgjR46oR48etZMY5+XEkcN6tO\/Fmj04Qa\/cP0F5R781HQkAYKkajXxMnDhRK1as0JtvvqmAgADPPI6goCA1atRIQUFBuuWWWzRlyhQ1bdpUgYGBmjRpknr06MFKF4OiO3bR8JnPKKxlWxWeyFH6C0\/o+VsGa\/Lq\/5OvfxPT8QCg1h3euUWbl81X5v49KjyRo1Fzliq+97We4\/9IX6dtry9V5v49OpOfq0krP1Cz2I4GE9ulRiMfCxYsUH5+vq666ipFRUV5HqtWrfI858knn9SgQYM0bNgw9erVS5GRkXrjjTdqPTh+vtjEJHXsM1RR7ePVvufVuvnZlTpTlK+9f1trOhoA1ImykmJFtY\/X0Gmzzn38TLFaXdJdA+6Y7nAySDUc+XC73T\/5HD8\/P82fP1\/z588\/71CoW40CghTWoo1OZhw2HQUA6kRsYpJiE5N+9HiXQddLknKzjjgVCT\/AZ7tYqLS4SKe+\/ZoJqAAAI1hvaYF3n5yhuF59FRIVrYLj2Xp\/4Wx5eXmrc\/\/rTEcDAFiI8mGB\/JwsvZJyq4rzc+UfEqpWl3TXbUvXq0lImOloAAALUT4scONji0xHAADAgzkfAADAUYx8AADqndLiomor+nIzjyjr4OdqHBii4KjmKs7PVV72tyo4\/t39qk58fUiSFBB6AZPxHUD5AADUO5n79mjR+GTP9jtzv7ufR5fBIzR85jzt37RBr\/3lDs\/xlSnjJUnXjL9HSRPudTSrjSgfAIB6p3VColJ3Hf\/R412H3KiuQ250MBF+yLry4eNyaUxcsOkYMMjH5TIdAQCsZl35qHC7tfhAnukYMGhch2DTEQDAaqx2AQAAjqJ8AAAAR1E+AACAoygfAADAUZQPAADgKMoHAABwFOUDAAA4ivIBAAAcRfkAAACOonwAAABHUT4AAICjKB8AAMBRlA8AAOAo6z7VFgBs5+NyaUxcsOkYMMjH5TJ7fqNnBwA4rsLt1uIDeaZjwKBxHYKNnp\/yUQ8d3rlFm5fNV+b+PSo8kaNRc5Yqvve1kqTK8nJtfC5VBz95X6e+\/UZ+TQLUtvuV6n\/HdAWGRxpODgCwAXM+6qGykmJFtY\/X0GmzzjpWXnJGWQf26uqxUzRpRbpGPfGSjn9zSMsmjzKQFABgI0Y+6qHYxCTFJiad85hfQKBuWfBatX1Dpj6m5\/7QV3lHv1VwVHMnIgIALMbIB1RaVCCXyyW\/gCDTUQAAFqB8WK68tETrn35QnfpfJ78mAabjAAAsQPmwWGV5uVZOHSvJreSUx03HAQBYgjkflqosL9eKaWOVe\/RbjX3+DUY9AACOoXxY6PvicfLIVxr7whr5Bzc1HQkAYBHKRz1UWlykkxmHPdu5mUeUdfBzNQ4MUUBYhJbfO0ZZB\/bqj08vl7uyUoUnciRJjYJC5NOgoanYAABLUD7qocx9e7RofLJn+5250yVJXQaPUNKt92r\/pg2SpGdu6F3t68a9sFatExIdywkAsBPlox5qnZCo1F3Hf\/T4fzsGAEBdY7ULAABwFOUDAAA4ivIBAAAcRfkAAACOYsIpAKDeObxzizYvm6\/M\/XtUeCJHo+YsVXzvayV9d6+jjc+l6uAn7+vUt9\/Ir0mA2na\/Uv3vmK7A8EjDye3AyAcAoN4pKylWVPt4DZ0266xj5SVnlHVgr64eO0WTVqRr1BMv6fg3h7Rs8igDSe3EyAcAoN6JTUxSbGLSOY\/5BQTqlgWvVds3ZOpjeu4PfZV39FsFRzV3IqLVGPkAAFivtKhALpdLfgFBpqNYgfIBALBaeWmJ1j\/9oDr1v44P2XQI5QMAYK3K8nKtnDpWklvJKY+bjmMN5nwAAKz0\/Sd85x79VmOff4NRDwdRPgAA1vm+eJw88pXGvrBG\/sFNTUeyCuUDAFDvlBYX6WTGYc92buYRZR38XI0DQxQQFqHl945R1oG9+uPTy+WurFThiRxJUqOgEPk0aGgqtjUoHwCAeidz3x4tGp\/s2X5n7nRJUpfBI5R0673av2mDJOmZG3pX+7pxL6xV64REx3LaivIBAKh3WickKnXX8R89\/t+Ooe6x2gUAADiK8gEAABxl3WUXH5dLY+KCTceAQT4ul+kIAGA168pHhdutxQfyTMeAQeM6BJuOAABW47KLhT5a8rRSuoTr7cfvNx0FAGAhyodlMv75d21\/fZki28WbjgIAsBTlwyKlxUVadf8EXTd9rhoF8smNAAAzKB8WefOxqYq7oo\/adr\/SdBQAgMWsm3Bqqz3vrVHWgc818a8bTUcBAFiO8mGBvOxMrXv8fo15brUa+PqZjgMAsBzlwwKZ+\/eo6NRxzRt5jWdfVWWlvt61VZ++mqaHPs2Ul7e3wYQAAJtQPizQ9rJeuvPVzdX2vfaXOxTeqp2uvHkSxQMA4CjKhwV8\/Zsosm2HavsaNmqsxkEhZ+0HgPospUt4tW3\/kDD9OX2\/oTT2qrPVLvPnz1erVq3k5+en7t27a\/v27XV1KgAAflJK14j\/\/79cCmvZTpJ0OveEXp85xVwoS9VJ+Vi1apWmTJmiGTNmaNeuXercubP69eunY8eO1cXpcB7GL3pTg+95xHQMAHCOu0qSlLrrmP53zRalbPxuxGPHm381mcpKdVI+5s6dq3Hjxmn06NG66KKLtHDhQjVu3FiLFy+ui9MBAPBffb37u9F3L+9\/zzYIDAszFcd6tT7no6ysTDt37lRKSopnn5eXl5KSkrR169aznl9aWqrS0lLPdn5+viSpoKCgtqNJkgpLKlRSVFgnr43fhsICLzUoY7oT7GXj++Cml56VJDVs7H\/O7922n0ddvA9+\/3vb7Xb\/9JPdtSwzM9Mtyb1ly5Zq+++55x73ZZdddtbzZ8yY4ZbEgwcPHjx48KgHj4yMjJ\/sCsb\/\/EtJSdGUKf+e7FNVVaVTp04pNDRULpfLYLL6p6CgQNHR0crIyFBgYKDpOADgmG3btqlv377y8fFRRUWF530wKChI0r9H3XH+3G63CgsL1axZs598bq2Xj7CwMHl7eysnJ6fa\/pycHEVGRp71fF9fX\/n6+lbbFxwcXNux8AOBgYGUDwBW6dOnjySpoqJC0nfvg2VlZZ7jvCfWju\/L3E+p9QmnDRs2VNeuXZWenu7ZV1VVpfT0dPXo0aO2TwcAwM\/i5fXvX3mXXXaZwsO\/u+fHzTffbCiRverkssuUKVP0xz\/+UQkJCbrsssv01FNP6fTp0xo9enRdnA4AgJ9UWVnpuZx\/8OBBSVJ4eLiWLFliMpaV6qR8jBgxQsePH9cDDzyg7OxsXXLJJdqwYYMiIiJ++otRZ3x9fTVjxoyzLnMBgC1KSkqUmpqqlJQU3gsNcrndP2dNDAAAQO2os9urAwAAnAvlAwAAOIryAQAAHEX5AAAAjqJ8WGTr1q3y9vbWwIEDTUcBAEfdfPPNcrlcnkdoaKj69++vvXv3mo5mJcqHRdLS0jRp0iRt3rxZWVlZpuMAgKP69++vo0eP6ujRo0pPT5ePj48GDRpkOpaVKB+WKCoq0qpVq3Tbbbdp4MCBeumll0xHAgBH+fr6KjIyUpGRkbrkkks0bdo0ZWRk6Pjx46ajWYfyYYlXX31VcXFxio2N1ahRo7R48eKf97HHAFAPFRUV6eWXX1bbtm0VGhpqOo51jH+qLZyRlpamUaNGSfpu6DE\/P1+bNm3SVVddZTYYADhk3bp1atKkiSTp9OnTioqK0rp166p95gucwU\/cAgcPHtT27dt14403SpJ8fHw0YsQIpaWlGU4GAM7p3bu3du\/erd27d2v79u3q16+fBgwYoG+++cZ0NOsw8mGBtLQ0VVRUqFmzZp59brdbvr6+mjdv3s\/+CGQA+C3z9\/dX27ZtPdsvvviigoKCtGjRIj388MMGk9mHkY96rqKiQsuWLdOcOXM8jX\/37t3as2ePmjVrppUrV5qOCABGuFwueXl56cyZM6ajWIeRj3pu3bp1ys3N1S233HLWCMewYcOUlpamCRMmGEoHAM4pLS1Vdna2JCk3N1fz5s1TUVGRBg8ebDiZfRj5qOfS0tKUlJR0zksrw4YN044dO7jJDgArbNiwQVFRUYqKilL37t312WefafXq1Uy8N8DlZr0lAABwECMfAADAUZQPAADgKMoHAABwFOUDAAA4ivIBAAAcRfkAAACOonwAAABHUT4AAICjKB8AAMBRlA8AAOAoygcAAHAU5QMAADjq\/wGZzWbQBdGNhwAAAABJRU5ErkJggg==\" \/><\/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><\/span><span class=\"nb\">print<\/span><span class=\"p\">(<\/span><span class=\"s2\">\"\u5408\u8a08\u5024\u306e\u5dee<\/span><span class=\"se\">\\t<\/span><span class=\"s2\">\"<\/span><span class=\"p\">,<\/span> <span class=\"n\">Diff_BF<\/span><span class=\"p\">)<\/span>\n<span class=\"nb\">print<\/span><span class=\"p\">(<\/span><span class=\"s2\">\"\u8a08\u7b97\u6642\u9593[s]<\/span><span class=\"se\">\\t<\/span><span class=\"s2\">\"<\/span><span class=\"p\">,<\/span> <span class=\"n\">Time_BF<\/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>\u5408\u8a08\u5024\u306e\u5dee\t 1.0\n\u8a08\u7b97\u6642\u9593[s]\t 37.245861749\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<h4><span class=\"ez-toc-section\" id=\"%E9%87%8F%E5%AD%90%E3%82%A2%E3%83%8B%E3%83%BC%E3%83%AA%E3%83%B3%E3%82%B0\"><\/span>\u91cf\u5b50\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0<span class=\"ez-toc-section-end\"><\/span><\/h4>\n<p>\u672c\u8a18\u4e8b\u3067\u306f\u3001D-Wave Systems\u306e\u91cf\u5b50\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u30de\u30b7\u30f3\u3092\u7528\u3044\u3066\u6570\u5206\u5272\u554f\u984c\u306b\u53d6\u308a\u7d44\u307f\u307e\u3059\u3002<\/p>\n<p>$0$\u3068$1$\u306e\u307f\u3092\u53d6\u308b\u4e8c\u5024\u5909\u6570$q_i$\u3092\u7528\u3044\u3066\u3001$i$\u756a\u76ee\u306e\u6570\u5024$w_i$\u304c$A$\u306b\u5c5e\u3059\u308b\u5834\u5408\u306f$q_i=1$\u3001$B$\u306b\u5c5e\u3059\u308b\u5834\u5408\u306f$q_i=0$\u3068\u5b9a\u7fa9\u3057\u307e\u3059\u3002\u4eca\u56de\u306e\u6570\u5206\u5272\u554f\u984c\u306f\u5404\u30b0\u30eb\u30fc\u30d7\u306e\u7dcf\u548c\u306e\u5dee\u304c$0$\u306b\u306a\u308b\u3053\u3068\u304c\u76ee\u6a19\u3067\u3042\u308b\u305f\u3081\u3001\u5236\u7d04\u6761\u4ef6\u3068\u3057\u3066\u4ee5\u4e0b\u306e\u3088\u3046\u306b\u5b9a\u5f0f\u5316\u3057\u307e\u3059\u3002<\/p>\n<p>$$ \\sum_{i=1}^N w_i q_i- \\sum_{i=1}^N w_i \\left(1 &#8211; q_i \\right) = 0 $$<\/p>\n<p>\u5de6\u8fba\u7b2c\u4e00\u9805\u306f\u30b0\u30eb\u30fc\u30d7$A$\u306e\u7dcf\u548c\u3001\u5de6\u8fba\u7b2c\u4e8c\u9805\u306f\u30b0\u30eb\u30fc\u30d7$B$\u306e\u7dcf\u548c\u3092\u8868\u3057\u3066\u3044\u307e\u3059\u3002\u3088\u3063\u3066\u6570\u5206\u5272\u554f\u984c\u306b\u5bfe\u3059\u308bQUBO(Quadratic Unconstrained Binary Optimization)\u306f\u4ee5\u4e0b\u306e\u3088\u3046\u306b\u306a\u308a\u307e\u3059\u3002<\/p>\n<p>$$<br \/>\nH \\left(q \\right) = \\left( \\sum_{i=1}^N w_i q_i- \\sum_{i=1}^N w_i \\left(1 &#8211; q_i \\right) \\right)^2 = \\left( 2 \\sum_{i=1}^N w_i q_i &#8211; \\sum_{i=1}^N w_i \\right)^2<br \/>\n\\\\= 4 \\sum_{i=1}^N w_i \\left(w_i &#8211; \\sum_{j=1}^N w_j \\right)q_i + 8 \\sum_{i=1}^N \\sum_{j=1}^N w_i w_j q_i q_j + \\left( \\sum_{i=1}^N w_i \\right)^2<br \/>\n$$<\/p>\n<p>\u306a\u304a\u3001\u4e0a\u5f0f\u53f3\u8fba\u7b2c\u4e09\u9805\u306f\u5b9a\u6570\u3067$q$\u306b\u4f9d\u5b58\u3057\u306a\u3044\u5b9a\u6570\u3067\u3042\u308b\u305f\u3081\u3001$H(q)$\u306e\u6700\u5c0f\u5024\u3092\u8003\u3048\u308b\u3046\u3048\u3067\u7121\u8996\u3059\u308b\u3053\u3068\u304c\u3067\u304d\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<p>\u4ee5\u4e0b\u3067\u306f\u5b9f\u969b\u306bQUBO\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><\/span><span class=\"n\">Q<\/span> <span class=\"o\">=<\/span> <span class=\"p\">{}<\/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\">Q<\/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=\"mi\">4<\/span> <span class=\"o\">*<\/span> <span class=\"n\">W<\/span><span class=\"p\">[<\/span><span class=\"n\">i<\/span><span class=\"p\">]<\/span> <span class=\"o\">*<\/span> <span class=\"p\">(<\/span><span class=\"n\">W<\/span><span class=\"p\">[<\/span><span class=\"n\">i<\/span><span class=\"p\">]<\/span> <span class=\"o\">-<\/span> <span class=\"nb\">sum<\/span><span class=\"p\">(<\/span><span class=\"n\">W<\/span><span class=\"p\">))<\/span>\n    <span class=\"k\">for<\/span> <span class=\"n\">j<\/span> <span class=\"ow\">in<\/span> <span class=\"nb\">range<\/span><span class=\"p\">(<\/span><span class=\"n\">i<\/span> <span class=\"o\">+<\/span> <span class=\"mi\">1<\/span><span class=\"p\">,<\/span> <span class=\"n\">N<\/span><span class=\"p\">):<\/span>\n        <span class=\"n\">Q<\/span><span class=\"p\">[<\/span><span class=\"n\">i<\/span><span class=\"p\">,<\/span> <span class=\"n\">j<\/span><span class=\"p\">]<\/span> <span class=\"o\">=<\/span> <span class=\"mi\">8<\/span> <span class=\"o\">*<\/span> <span class=\"n\">W<\/span><span class=\"p\">[<\/span><span class=\"n\">i<\/span><span class=\"p\">]<\/span> <span class=\"o\">*<\/span> <span class=\"n\">W<\/span><span class=\"p\">[<\/span><span class=\"n\">j<\/span><span class=\"p\">]<\/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>\u3053\u3053\u3067\u3001\u4f5c\u6210\u3057\u305fQUBO\u3092\u53ef\u8996\u5316\u3057\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><\/span><span class=\"k\">def<\/span> <span class=\"nf\">show_qubo<\/span><span class=\"p\">(<\/span><span class=\"n\">qubo<\/span><span class=\"p\">,<\/span> <span class=\"n\">cmap<\/span><span class=\"o\">=<\/span><span class=\"n\">cm<\/span><span class=\"o\">.<\/span><span class=\"n\">GnBu<\/span><span class=\"p\">,<\/span> <span class=\"n\">save_path<\/span><span class=\"o\">=<\/span><span class=\"kc\">None<\/span><span class=\"p\">):<\/span>\n    <span class=\"n\">n_qubo<\/span> <span class=\"o\">=<\/span> <span class=\"p\">(<\/span>\n        <span class=\"nb\">max<\/span><span class=\"p\">(<\/span><span class=\"nb\">sorted<\/span><span class=\"p\">(<\/span><span class=\"n\">qubo<\/span><span class=\"o\">.<\/span><span class=\"n\">keys<\/span><span class=\"p\">())[<\/span><span class=\"o\">-<\/span><span class=\"mi\">1<\/span><span class=\"p\">][<\/span><span class=\"mi\">0<\/span><span class=\"p\">],<\/span> <span class=\"nb\">sorted<\/span><span class=\"p\">(<\/span><span class=\"n\">qubo<\/span><span class=\"o\">.<\/span><span class=\"n\">keys<\/span><span class=\"p\">(),<\/span> <span class=\"n\">key<\/span><span class=\"o\">=<\/span><span class=\"k\">lambda<\/span> <span class=\"n\">x<\/span><span class=\"p\">:<\/span> <span class=\"n\">x<\/span><span class=\"p\">[<\/span><span class=\"mi\">1<\/span><span class=\"p\">])[<\/span><span class=\"o\">-<\/span><span class=\"mi\">1<\/span><span class=\"p\">][<\/span><span class=\"mi\">1<\/span><span class=\"p\">])<\/span>\n        <span class=\"o\">+<\/span> <span class=\"mi\">1<\/span>\n    <span class=\"p\">)<\/span>\n\n    <span class=\"n\">np_qubo<\/span> <span class=\"o\">=<\/span> <span class=\"n\">np<\/span><span class=\"o\">.<\/span><span class=\"n\">zeros<\/span><span class=\"p\">((<\/span><span class=\"n\">n_qubo<\/span><span class=\"p\">,<\/span> <span class=\"n\">n_qubo<\/span><span class=\"p\">))<\/span>\n    <span class=\"k\">for<\/span> <span class=\"p\">(<\/span><span class=\"n\">pos_x<\/span><span class=\"p\">,<\/span> <span class=\"n\">pos_y<\/span><span class=\"p\">),<\/span> <span class=\"n\">coeff<\/span> <span class=\"ow\">in<\/span> <span class=\"n\">qubo<\/span><span class=\"o\">.<\/span><span class=\"n\">items<\/span><span class=\"p\">():<\/span>\n        <span class=\"n\">np_qubo<\/span><span class=\"p\">[<\/span><span class=\"n\">pos_x<\/span><span class=\"p\">][<\/span><span class=\"n\">pos_y<\/span><span class=\"p\">]<\/span> <span class=\"o\">=<\/span> <span class=\"n\">coeff<\/span>\n\n    <span class=\"n\">plt<\/span><span class=\"o\">.<\/span><span class=\"n\">imshow<\/span><span class=\"p\">(<\/span><span class=\"n\">np_qubo<\/span><span class=\"p\">,<\/span> <span class=\"n\">cmap<\/span><span class=\"o\">=<\/span><span class=\"n\">cmap<\/span><span class=\"p\">)<\/span>\n    <span class=\"n\">plt<\/span><span class=\"o\">.<\/span><span class=\"n\">colorbar<\/span><span class=\"p\">()<\/span>\n\n    <span class=\"k\">if<\/span> <span class=\"n\">save_path<\/span> <span class=\"ow\">is<\/span> <span class=\"ow\">not<\/span> <span class=\"kc\">None<\/span><span class=\"p\">:<\/span>\n        <span class=\"n\">plt<\/span><span class=\"o\">.<\/span><span class=\"n\">savefig<\/span><span class=\"p\">(<\/span><span class=\"n\">save_path<\/span><span class=\"p\">)<\/span>\n\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>\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><\/span><span class=\"n\">show_qubo<\/span><span class=\"p\">(<\/span><span class=\"n\">Q<\/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\" alt=\"No description has been provided for this image\" 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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>\u3053\u308c\u3092\u91cf\u5b50\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u30de\u30b7\u30f3\u306b\u5165\u529b\u3057\u3001\u5f97\u3089\u308c\u305f\u30a8\u30cd\u30eb\u30ae\u30fc\u304b\u3089\u6700\u9069\u89e3\u3092\u898b\u3064\u3051\u307e\u3059\u3002<\/p>\n<p>\u307e\u305a\u521d\u3081\u306b\u3001\u5148\u7a0b\u4f5c\u6210\u3057\u305fQUBO\u3092D-Wave\u306b\u5165\u529b\u3057\u307e\u3059\u3002\u6700\u521d\u306b\u4f5c\u6210\u3057\u305f<a href=\"https:\/\/cloud.dwavesys.com\/leap\/\">D-Wave Leap<\/a>\u306e\u30a2\u30ab\u30a6\u30f3\u30c8\u306e\u63a5\u7d9a\u60c5\u5831\u3092\u7528\u3044\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><\/span><span class=\"c1\"># \u63a5\u7d9a\u60c5\u5831<\/span>\n<span class=\"n\">endpoint<\/span> <span class=\"o\">=<\/span> <span class=\"s2\">\"https:\/\/cloud.dwavesys.com\/sapi\"<\/span>\n<span class=\"n\">token<\/span> <span class=\"o\">=<\/span> <span class=\"s2\">\"YOUR_TOKEN\"<\/span>\n<span class=\"n\">solver<\/span> <span class=\"o\">=<\/span> <span class=\"s2\">\"Advantage_system6.2\"<\/span>\n\n<span class=\"n\">dw<\/span> <span class=\"o\">=<\/span> <span class=\"n\">DWaveSampler<\/span><span class=\"p\">(<\/span><span class=\"n\">endpoint<\/span><span class=\"o\">=<\/span><span class=\"n\">endpoint<\/span><span class=\"p\">,<\/span> <span class=\"n\">token<\/span><span class=\"o\">=<\/span><span class=\"n\">token<\/span><span class=\"p\">,<\/span> <span class=\"n\">solver<\/span><span class=\"o\">=<\/span><span class=\"n\">solver<\/span><span class=\"p\">)<\/span>\n\n<span class=\"c1\"># D-Wave\u30de\u30b7\u30f3\u306e\u30cf\u30fc\u30c9\u30a6\u30a7\u30a2\u30b0\u30e9\u30d5\u306b\u57cb\u3081\u8fbc\u307f\u3092\u884c\u3046<\/span>\n<span class=\"n\">sampler<\/span> <span class=\"o\">=<\/span> <span class=\"n\">EmbeddingComposite<\/span><span class=\"p\">(<\/span><span class=\"n\">dw<\/span><span class=\"p\">)<\/span>\n\n<span class=\"c1\"># \u4e00\u5ea6\u306b\u53d6\u5f97\u3059\u308b\u30b5\u30f3\u30d7\u30eb\u6570<\/span>\n<span class=\"n\">num_reads<\/span> <span class=\"o\">=<\/span> <span class=\"mi\">300<\/span>\n\n<span class=\"c1\"># D-Wave\u30de\u30b7\u30f3\u306e\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u6642\u9593<\/span>\n<span class=\"n\">annealing_time<\/span> <span class=\"o\">=<\/span> <span class=\"mi\">20<\/span>\n\n<span class=\"c1\"># D-Wave\u30de\u30b7\u30f3\u306b\u3088\u308b\u30b5\u30f3\u30d7\u30ea\u30f3\u30b0\u3092\u5b9f\u884c\u3059\u308b<\/span>\n<span class=\"n\">response_DW<\/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\">Q<\/span><span class=\"p\">,<\/span> <span class=\"n\">num_reads<\/span><span class=\"o\">=<\/span><span class=\"n\">num_reads<\/span><span class=\"p\">,<\/span> <span class=\"n\">annealing_time<\/span><span class=\"o\">=<\/span><span class=\"n\">annealing_time<\/span><span class=\"p\">)<\/span><\/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=\"output_subarea output_text output_error\">\n<pre><\/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\u3001\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u30de\u30b7\u30f3\u304b\u3089\u8fd4\u3055\u308c\u305f\u8a08\u7b97\u7d50\u679c\u3092\u8868\u793a\u3057\u307e\u3059\u3002\n<\/p><\/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><\/span><span class=\"n\">response_DW<\/span><span class=\"o\">.<\/span><span class=\"n\">to_pandas_dataframe<\/span><span class=\"p\">()<\/span><span class=\"o\">.<\/span><span class=\"n\">head<\/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 output_prompt\">Out[\u00a0]:<\/div>\n<div class=\"output_html rendered_html output_subarea output_execute_result\">\n<div id=\"df-8052fab1-031c-4f58-a89b-247db19a6577\">\n<div class=\"colab-df-container\">\n<div>\n<style scoped=\"\">\n    .dataframe tbody tr th:only-of-type {<br \/>        vertical-align: middle;<br \/>    }<\/p>\n<p>    .dataframe tbody tr th {<br \/>        vertical-align: top;<br \/>    }<\/p>\n<p>    .dataframe thead th {<br \/>        text-align: right;<br \/>    }<br \/><\/style>\n<table border=\"1\" class=\"dataframe\">\n<thead>\n<tr style=\"text-align: right;\">\n<th><\/th>\n<th>0<\/th>\n<th>1<\/th>\n<th>2<\/th>\n<th>3<\/th>\n<th>4<\/th>\n<th>5<\/th>\n<th>6<\/th>\n<th>7<\/th>\n<th>8<\/th>\n<th>9<\/th>\n<th>&#8230;<\/th>\n<th>13<\/th>\n<th>14<\/th>\n<th>15<\/th>\n<th>16<\/th>\n<th>17<\/th>\n<th>18<\/th>\n<th>19<\/th>\n<th>chain_break_fraction<\/th>\n<th>energy<\/th>\n<th>num_occurrences<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<th>0<\/th>\n<td>1<\/td>\n<td>1<\/td>\n<td>0<\/td>\n<td>0<\/td>\n<td>0<\/td>\n<td>1<\/td>\n<td>0<\/td>\n<td>1<\/td>\n<td>0<\/td>\n<td>0<\/td>\n<td>&#8230;<\/td>\n<td>1<\/td>\n<td>0<\/td>\n<td>0<\/td>\n<td>1<\/td>\n<td>1<\/td>\n<td>1<\/td>\n<td>1<\/td>\n<td>0.20<\/td>\n<td>-40656.0<\/td>\n<td>7<\/td>\n<\/tr>\n<tr>\n<th>1<\/th>\n<td>0<\/td>\n<td>0<\/td>\n<td>1<\/td>\n<td>1<\/td>\n<td>1<\/td>\n<td>1<\/td>\n<td>1<\/td>\n<td>0<\/td>\n<td>1<\/td>\n<td>1<\/td>\n<td>&#8230;<\/td>\n<td>0<\/td>\n<td>1<\/td>\n<td>1<\/td>\n<td>0<\/td>\n<td>0<\/td>\n<td>0<\/td>\n<td>0<\/td>\n<td>0.20<\/td>\n<td>-41944.0<\/td>\n<td>3<\/td>\n<\/tr>\n<tr>\n<th>2<\/th>\n<td>0<\/td>\n<td>0<\/td>\n<td>1<\/td>\n<td>1<\/td>\n<td>1<\/td>\n<td>1<\/td>\n<td>1<\/td>\n<td>0<\/td>\n<td>1<\/td>\n<td>1<\/td>\n<td>&#8230;<\/td>\n<td>0<\/td>\n<td>1<\/td>\n<td>1<\/td>\n<td>0<\/td>\n<td>0<\/td>\n<td>0<\/td>\n<td>0<\/td>\n<td>0.15<\/td>\n<td>-41944.0<\/td>\n<td>1<\/td>\n<\/tr>\n<tr>\n<th>3<\/th>\n<td>1<\/td>\n<td>1<\/td>\n<td>0<\/td>\n<td>1<\/td>\n<td>0<\/td>\n<td>1<\/td>\n<td>0<\/td>\n<td>1<\/td>\n<td>0<\/td>\n<td>0<\/td>\n<td>&#8230;<\/td>\n<td>1<\/td>\n<td>0<\/td>\n<td>0<\/td>\n<td>1<\/td>\n<td>1<\/td>\n<td>1<\/td>\n<td>1<\/td>\n<td>0.25<\/td>\n<td>-39000.0<\/td>\n<td>6<\/td>\n<\/tr>\n<tr>\n<th>4<\/th>\n<td>0<\/td>\n<td>0<\/td>\n<td>0<\/td>\n<td>1<\/td>\n<td>1<\/td>\n<td>1<\/td>\n<td>1<\/td>\n<td>0<\/td>\n<td>1<\/td>\n<td>1<\/td>\n<td>&#8230;<\/td>\n<td>0<\/td>\n<td>1<\/td>\n<td>1<\/td>\n<td>0<\/td>\n<td>0<\/td>\n<td>0<\/td>\n<td>0<\/td>\n<td>0.20<\/td>\n<td>-42024.0<\/td>\n<td>3<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>5 rows \u00d7 23 columns<\/p>\n<\/div>\n<p><button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-8052fab1-031c-4f58-a89b-247db19a6577')\" style=\"display: none;\" title=\"Convert this dataframe to an interactive table.\"><br \/>\n<svg height=\"24px\" viewbox=\"0 0 24 24\" width=\"24px\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><\/svg>\n<path d=\"M0 0h24v24H0V0z\" fill=\"none\"><\/path> <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"><\/path><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"><\/path> <\/button><\/p>\n<div id=\"df-6fb185e4-339f-4dfd-8dc4-06daa5a7891d\"><button class=\"colab-df-quickchart\" onclick=\"quickchart('df-6fb185e4-339f-4dfd-8dc4-06daa5a7891d')\" style=\"display: none;\" title=\"Suggest charts.\"><\/button><button class=\"colab-df-quickchart\" onclick=\"quickchart('df-6fb185e4-339f-4dfd-8dc4-06daa5a7891d')\" style=\"display: none;\" title=\"Suggest charts.\"><br \/>\n<svg height=\"24px\" viewbox=\"0 0 24 24\" width=\"24px\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><\/svg><br \/>\n<g>\n<path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"><\/path> <\/g><\/button><\/div>\n<style>\n  .colab-df-quickchart {<br \/>    background-color: #E8F0FE;<br \/>    border: none;<br \/>    border-radius: 50%;<br \/>    cursor: pointer;<br \/>    display: none;<br \/>    fill: #1967D2;<br \/>    height: 32px;<br \/>    padding: 0 0 0 0;<br \/>    width: 32px;<br \/>  }<\/p>\n<p>  .colab-df-quickchart:hover {<br \/>    background-color: #E2EBFA;<br \/>    box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);<br \/>    fill: #174EA6;<br \/>  }<\/p>\n<p>  [theme=dark] .colab-df-quickchart {<br \/>    background-color: #3B4455;<br \/>    fill: #D2E3FC;<br \/>  }<\/p>\n<p>  [theme=dark] .colab-df-quickchart:hover {<br \/>    background-color: #434B5C;<br \/>    box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);<br \/>    filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));<br \/>    fill: #FFFFFF;<br \/>  }<br \/><\/style>\n<p><script>\n      async function quickchart(key) {\n        const containerElement = document.querySelector('#' + key);\n        const charts = await google.colab.kernel.invokeFunction(\n            'suggestCharts', [key], {});\n      }\n    <\/script><br \/>\n<script><\/p>\n<p>function displayQuickchartButton(domScope) {\n  let quickchartButtonEl =\n    domScope.querySelector('#df-6fb185e4-339f-4dfd-8dc4-06daa5a7891d button.colab-df-quickchart');\n  quickchartButtonEl.style.display =\n    google.colab.kernel.accessAllowed ? 'block' : 'none';\n}<\/p>\n<p>        displayQuickchartButton(document);\n      <\/script><\/p>\n<style>\n    .colab-df-container {<br \/>      display:flex;<br \/>      flex-wrap:wrap;<br \/>      gap: 12px;<br \/>    }<\/p>\n<p>    .colab-df-convert {<br \/>      background-color: #E8F0FE;<br \/>      border: none;<br \/>      border-radius: 50%;<br \/>      cursor: pointer;<br \/>      display: none;<br \/>      fill: #1967D2;<br \/>      height: 32px;<br \/>      padding: 0 0 0 0;<br \/>      width: 32px;<br \/>    }<\/p>\n<p>    .colab-df-convert:hover {<br \/>      background-color: #E2EBFA;<br \/>      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);<br \/>      fill: #174EA6;<br \/>    }<\/p>\n<p>    [theme=dark] .colab-df-convert {<br \/>      background-color: #3B4455;<br \/>      fill: #D2E3FC;<br \/>    }<\/p>\n<p>    [theme=dark] .colab-df-convert:hover {<br \/>      background-color: #434B5C;<br \/>      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);<br \/>      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));<br \/>      fill: #FFFFFF;<br \/>    }<br \/>  <\/style>\n<p><script>\n        const buttonEl =\n          document.querySelector('#df-8052fab1-031c-4f58-a89b-247db19a6577 button.colab-df-convert');\n        buttonEl.style.display =\n          google.colab.kernel.accessAllowed ? 'block' : 'none';<\/p>\n<p>        async function convertToInteractive(key) {\n          const element = document.querySelector('#df-8052fab1-031c-4f58-a89b-247db19a6577');\n          const dataTable =\n            await google.colab.kernel.invokeFunction('convertToInteractive',\n                                                     [key], {});\n          if (!dataTable) return;<\/p>\n<p>          const docLinkHtml = 'Like what you see? Visit the ' +\n            '<a target=\"_blank\" href=https:\/\/colab.research.google.com\/notebooks\/data_table.ipynb>data table notebook<\/a>'\n            + ' to learn more about interactive tables.';\n          element.innerHTML = '';\n          dataTable['output_type'] = 'display_data';\n          await google.colab.output.renderOutput(dataTable, element);\n          const docLink = document.createElement('div');\n          docLink.innerHTML = docLinkHtml;\n          element.appendChild(docLink);\n        }\n      <\/script><\/p>\n<\/div>\n<\/div>\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>\u3055\u3089\u306b\u3001\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u306b\u304b\u304b\u3063\u305f\u6642\u9593\u3084\u901a\u4fe1\u6642\u9593\u3092\u8868\u793a\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><\/span><span class=\"n\">response_DW<\/span><span class=\"o\">.<\/span><span class=\"n\">info<\/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 output_prompt\">Out[\u00a0]:<\/div>\n<div class=\"output_text output_subarea output_execute_result\">\n<pre>{'timing': {'qpu_sampling_time': 25896.0,\n  'qpu_anneal_time_per_sample': 20.0,\n  'qpu_readout_time_per_sample': 45.78,\n  'qpu_access_time': 41822.77,\n  'qpu_access_overhead_time': 815.23,\n  'qpu_programming_time': 15926.77,\n  'qpu_delay_time_per_sample': 20.54,\n  'post_processing_overhead_time': 1820.0,\n  'total_post_processing_time': 1820.0},\n 'problem_id': 'c66de046-b25c-48af-ab8c-40ca0194e266'}<\/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>\u7d9a\u3044\u3066\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u30de\u30b7\u30f3\u304b\u3089\u8fd4\u3055\u308c\u305f\u60c5\u5831\u304b\u3089\u3001\u5404\u7d50\u679c\u306e\u30a8\u30cd\u30eb\u30ae\u30fc\u3092\u6bd4\u8f03\u3057\u6700\u9069\u89e3\u3092\u53d6\u308a\u51fa\u3057\u307e\u3059\u3002<\/p>\n<p>\u5177\u4f53\u7684\u306b\u306f\u3001\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u30de\u30b7\u30f3\u304c\u8fd4\u3057\u305f\u3059\u3079\u3066\u306e\u89e3\u306b\u3064\u3044\u3066\u3001\u305d\u306e\u30b0\u30eb\u30fc\u30d7\u5206\u3051\u306e\u969b\u306e\u5dee\u3092\u8a08\u7b97\u3059\u308b\u3053\u3068\u3067\u6700\u9069\u89e3\u3092\u53d6\u308a\u51fa\u3057\u307e\u3059\u3002\u4eca\u56de\u306f5.1.\u3067\u7528\u3044\u305f\u30d3\u30c3\u30c8\u5168\u63a2\u7d22\u306b\u3088\u3063\u3066\u6700\u9069\u89e3\u304c\u5206\u304b\u3063\u3066\u3044\u308b\u305f\u3081\u3001\u305d\u308c\u3092\u53c2\u8003\u306b\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u30de\u30b7\u30f3\u306b\u3088\u308b\u6700\u9069\u89e3\u3092\u62bd\u51fa\u3057\u307e\u3059\u3002\u306a\u304a\u3001\u3053\u306e\u65b9\u6cd5\u3067\u306f\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u30de\u30b7\u30f3\u304c\u6700\u9069\u89e3\u3067\u306f\u306a\u304f\u8fd1\u4f3c\u89e3\u306e\u307f\u3092\u5c0e\u51fa\u3057\u305f\u969b\u306b\u554f\u984c\u304c\u767a\u751f\u3057\u307e\u3059\u3002<\/p>\n<p>\u305d\u3053\u3067\u6700\u9069\u5316\u3082\u542b\u3081\u3066\u53d6\u308a\u51fa\u3059\u305f\u3081\u306b\u3001\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u30de\u30b7\u30f3\u304c\u8fd4\u3057\u305f\u5168\u3066\u306e\u7d50\u679c\u306e\u30a8\u30cd\u30eb\u30ae\u30fc\u3092\u6bd4\u8f03\u3057\u3001\u6700\u3082\u30a8\u30cd\u30eb\u30ae\u30fc\u304c\u4f4e\u304b\u3063\u305f\u3082\u306e\u3092\u8fd1\u4f3c\u89e3\u3068\u3057\u3066\u51fa\u529b\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><\/span><span class=\"c1\"># \u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u30de\u30b7\u30f3\u304b\u3089\u8fd4\u3055\u308c\u305f\u7d50\u679c\u306e\u30a8\u30cd\u30eb\u30ae\u30fc\u3092\u8a08\u7b97\u3059\u308b\u95a2\u6570<\/span>\n<span class=\"k\">def<\/span> <span class=\"nf\">calculate_energy<\/span><span class=\"p\">(<\/span><span class=\"n\">solution<\/span><span class=\"p\">):<\/span>\n    <span class=\"n\">Ene<\/span> <span class=\"o\">=<\/span> <span class=\"nb\">sum<\/span><span class=\"p\">(<\/span><span class=\"n\">W<\/span><span class=\"p\">)<\/span> <span class=\"o\">**<\/span> <span class=\"mi\">2<\/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\">Ene<\/span> <span class=\"o\">+=<\/span> <span class=\"n\">Q<\/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=\"n\">solution<\/span><span class=\"p\">[<\/span><span class=\"n\">i<\/span><span class=\"p\">]<\/span>\n        <span class=\"k\">for<\/span> <span class=\"n\">j<\/span> <span class=\"ow\">in<\/span> <span class=\"nb\">range<\/span><span class=\"p\">(<\/span><span class=\"n\">i<\/span> <span class=\"o\">+<\/span> <span class=\"mi\">1<\/span><span class=\"p\">,<\/span> <span class=\"n\">N<\/span><span class=\"p\">):<\/span>\n            <span class=\"n\">Ene<\/span> <span class=\"o\">+=<\/span> <span class=\"n\">Q<\/span><span class=\"p\">[<\/span><span class=\"n\">i<\/span><span class=\"p\">,<\/span> <span class=\"n\">j<\/span><span class=\"p\">]<\/span> <span class=\"o\">*<\/span> <span class=\"n\">solution<\/span><span class=\"p\">[<\/span><span class=\"n\">i<\/span><span class=\"p\">]<\/span> <span class=\"o\">*<\/span> <span class=\"n\">solution<\/span><span class=\"p\">[<\/span><span class=\"n\">j<\/span><span class=\"p\">]<\/span>\n    <span class=\"k\">return<\/span> <span class=\"n\">Ene<\/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><\/span><span class=\"c1\"># \u6700\u9069\u89e3\u3068\u8fd1\u4f3c\u89e3\u306e\u500b\u6570\u3092\u30ab\u30a6\u30f3\u30c8\u3059\u308b\u95a2\u6570<\/span>\n<span class=\"k\">def<\/span> <span class=\"nf\">count_solutions<\/span><span class=\"p\">(<\/span><span class=\"n\">response<\/span><span class=\"p\">):<\/span>\n    <span class=\"c1\"># \u6700\u9069\u89e3\u3068\u8fd1\u4f3c\u89e3\u306e\u500b\u6570<\/span>\n    <span class=\"n\">num_optimal_sol<\/span> <span class=\"o\">=<\/span> <span class=\"mi\">0<\/span>\n    <span class=\"n\">num_approx_sol<\/span> <span class=\"o\">=<\/span> <span class=\"mi\">0<\/span>\n\n    <span class=\"c1\"># \u6700\u9069\u89e3\u3068\u8fd1\u4f3c\u89e3<\/span>\n    <span class=\"n\">optimal_sol<\/span> <span class=\"o\">=<\/span> <span class=\"p\">[]<\/span>\n    <span class=\"n\">approx_sol<\/span> <span class=\"o\">=<\/span> <span class=\"p\">[]<\/span>\n\n    <span class=\"c1\"># \u30a8\u30cd\u30eb\u30ae\u30fc<\/span>\n    <span class=\"n\">Energies<\/span> <span class=\"o\">=<\/span> <span class=\"p\">[]<\/span>\n\n    <span class=\"k\">for<\/span> <span class=\"n\">state<\/span> <span class=\"ow\">in<\/span> <span class=\"n\">response<\/span><span class=\"o\">.<\/span><span class=\"n\">record<\/span><span class=\"p\">:<\/span>\n        <span class=\"n\">energy<\/span> <span class=\"o\">=<\/span> <span class=\"n\">calculate_energy<\/span><span class=\"p\">(<\/span><span class=\"n\">state<\/span><span class=\"o\">.<\/span><span class=\"n\">sample<\/span><span class=\"p\">)<\/span>\n\n        <span class=\"c1\"># \u51fa\u73fe\u56de\u6570\u5206\u3060\u3051\u30a8\u30cd\u30eb\u30ae\u30fc\u3092\u52a0\u3048\u308b\u3053\u3068\u3067\u3001\u5f8c\u3067\u5168\u4f53\u306e\u30a8\u30cd\u30eb\u30ae\u30fc\u5206\u5e03\u3092\u628a\u63e1\u3059\u308b<\/span>\n        <span class=\"n\">Energies<\/span> <span class=\"o\">+=<\/span> <span class=\"p\">[<\/span><span class=\"n\">energy<\/span><span class=\"p\">]<\/span> <span class=\"o\">*<\/span> <span class=\"n\">state<\/span><span class=\"o\">.<\/span><span class=\"n\">num_occurrences<\/span>\n\n    <span class=\"c1\"># \u30d3\u30c3\u30c8\u5168\u63a2\u7d22\u306e\u7d50\u679c\u3092\u5143\u306b\u3001\u6700\u9069\u89e3\u3092\u898b\u3064\u3051\u308b<\/span>\n    <span class=\"k\">for<\/span> <span class=\"n\">state<\/span> <span class=\"ow\">in<\/span> <span class=\"n\">response<\/span><span class=\"o\">.<\/span><span class=\"n\">record<\/span><span class=\"p\">:<\/span>\n        <span class=\"n\">energy<\/span> <span class=\"o\">=<\/span> <span class=\"n\">calculate_energy<\/span><span class=\"p\">(<\/span><span class=\"n\">state<\/span><span class=\"o\">.<\/span><span class=\"n\">sample<\/span><span class=\"p\">)<\/span>\n\n        <span class=\"k\">if<\/span> <span class=\"n\">energy<\/span> <span class=\"o\">==<\/span> <span class=\"n\">Diff_BF<\/span><span class=\"p\">:<\/span>\n            <span class=\"n\">num_optimal_sol<\/span> <span class=\"o\">+=<\/span> <span class=\"n\">state<\/span><span class=\"o\">.<\/span><span class=\"n\">num_occurrences<\/span>\n            <span class=\"n\">optimal_sol<\/span><span class=\"o\">.<\/span><span class=\"n\">append<\/span><span class=\"p\">(<\/span><span class=\"n\">state<\/span><span class=\"o\">.<\/span><span class=\"n\">sample<\/span><span class=\"p\">)<\/span>\n\n        <span class=\"k\">if<\/span> <span class=\"n\">energy<\/span> <span class=\"o\">==<\/span> <span class=\"nb\">min<\/span><span class=\"p\">(<\/span><span class=\"n\">Energies<\/span><span class=\"p\">):<\/span>\n            <span class=\"n\">num_approx_sol<\/span> <span class=\"o\">+=<\/span> <span class=\"n\">state<\/span><span class=\"o\">.<\/span><span class=\"n\">num_occurrences<\/span>\n            <span class=\"n\">approx_sol<\/span><span class=\"o\">.<\/span><span class=\"n\">append<\/span><span class=\"p\">(<\/span><span class=\"n\">state<\/span><span class=\"o\">.<\/span><span class=\"n\">sample<\/span><span class=\"p\">)<\/span>\n\n    <span class=\"k\">return<\/span> <span class=\"n\">num_optimal_sol<\/span><span class=\"p\">,<\/span> <span class=\"n\">num_approx_sol<\/span><span class=\"p\">,<\/span> <span class=\"n\">optimal_sol<\/span><span class=\"p\">,<\/span> <span class=\"n\">approx_sol<\/span><span class=\"p\">,<\/span> <span class=\"n\">Energies<\/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><\/span><span class=\"n\">num_optimal_sol<\/span><span class=\"p\">,<\/span> <span class=\"n\">num_approx_sol<\/span><span class=\"p\">,<\/span> <span class=\"n\">optimal_sol<\/span><span class=\"p\">,<\/span> <span class=\"n\">approx_sol<\/span><span class=\"p\">,<\/span> <span class=\"n\">Energies<\/span> <span class=\"o\">=<\/span> <span class=\"n\">count_solutions<\/span><span class=\"p\">(<\/span>\n    <span class=\"n\">response_DW<\/span>\n<span class=\"p\">)<\/span>\n\n<span class=\"nb\">print<\/span><span class=\"p\">(<\/span><span class=\"s2\">\"\u6700\u9069\u89e3\uff08\u500b\uff09<\/span><span class=\"se\">\\t<\/span><span class=\"s2\">\"<\/span><span class=\"p\">,<\/span> <span class=\"n\">num_optimal_sol<\/span><span class=\"p\">)<\/span>\n<span class=\"nb\">print<\/span><span class=\"p\">(<\/span><span class=\"s2\">\"\u8fd1\u4f3c\u89e3\uff08\u500b\uff09<\/span><span class=\"se\">\\t<\/span><span class=\"s2\">\"<\/span><span class=\"p\">,<\/span> <span class=\"n\">num_approx_sol<\/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>\u6700\u9069\u89e3\uff08\u500b\uff09\t 30\n\u8fd1\u4f3c\u89e3\uff08\u500b\uff09\t 30\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>\u5f8c\u8ff0\u3057\u307e\u3059\u304c\u3001TTS\u3068\u547c\u3070\u308c\u308b\u6307\u6a19\u3092\u8a08\u7b97\u3059\u308b\u969b\u306b\u3053\u3053\u3067\u6700\u9069\u89e3\u3092\u5c11\u306a\u304f\u3068\u3082\uff11\u3064\u4ee5\u4e0a\u51fa\u3059\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002\u3082\u3057\u6700\u9069\u89e3\u304c\u5f97\u3089\u308c\u306a\u304b\u3063\u305f\u5834\u5408\u306f\u3001\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u30de\u30b7\u30f3\u3092\u518d\u5ea6\u52d5\u304b\u3057\u3066\u307f\u307e\u3057\u3087\u3046\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>\u5f97\u3089\u308c\u305f\u6700\u9069\u89e3\u306f$0,1$\u306e\u7d44\u5408\u305b\u304c\u8868\u73fe\u3055\u308c\u3066\u3044\u308b\u3060\u3051\u3067\u3001\u3069\u306e\u6570\u5024\u306b\u5bfe\u5fdc\u3057\u3066\u3044\u308b\u304b\u307e\u3067\u306e\u60c5\u5831\u3092\u4fdd\u6301\u3057\u3066\u3044\u306a\u3044\u306e\u3067\u3001\u4ee5\u4e0b\u3067\u306f\u30b0\u30eb\u30fc\u30d7\u5206\u3051\u306e\u4ed5\u65b9\u3068\u305d\u306e\u6570\u5024\u3092\u5bfe\u5fdc\u3055\u305b\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><\/span><span class=\"n\">Group_A_DW<\/span> <span class=\"o\">=<\/span> <span class=\"p\">[]<\/span>\n<span class=\"n\">Group_B_DW<\/span> <span class=\"o\">=<\/span> <span class=\"p\">[]<\/span>\n\n<span class=\"k\">for<\/span> <span class=\"n\">solution<\/span> <span class=\"ow\">in<\/span> <span class=\"n\">approx_sol<\/span><span class=\"p\">:<\/span>\n    <span class=\"n\">Group_A<\/span> <span class=\"o\">=<\/span> <span class=\"n\">np<\/span><span class=\"o\">.<\/span><span class=\"n\">zeros<\/span><span class=\"p\">(<\/span><span class=\"n\">N<\/span><span class=\"p\">)<\/span>\n    <span class=\"n\">Group_B<\/span> <span class=\"o\">=<\/span> <span class=\"n\">np<\/span><span class=\"o\">.<\/span><span class=\"n\">zeros<\/span><span class=\"p\">(<\/span><span class=\"n\">N<\/span><span class=\"p\">)<\/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=\"n\">N<\/span><span class=\"p\">):<\/span>\n        <span class=\"k\">if<\/span> <span class=\"n\">solution<\/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            <span class=\"n\">Group_A<\/span><span class=\"p\">[<\/span><span class=\"n\">i<\/span><span class=\"p\">]<\/span> <span class=\"o\">=<\/span> <span class=\"n\">W<\/span><span class=\"p\">[<\/span><span class=\"n\">i<\/span><span class=\"p\">]<\/span>\n        <span class=\"k\">else<\/span><span class=\"p\">:<\/span>\n            <span class=\"n\">Group_B<\/span><span class=\"p\">[<\/span><span class=\"n\">i<\/span><span class=\"p\">]<\/span> <span class=\"o\">=<\/span> <span class=\"n\">W<\/span><span class=\"p\">[<\/span><span class=\"n\">i<\/span><span class=\"p\">]<\/span>\n\n    <span class=\"n\">Group_A_DW<\/span><span class=\"o\">.<\/span><span class=\"n\">append<\/span><span class=\"p\">(<\/span><span class=\"n\">Group_A<\/span><span class=\"p\">)<\/span>\n    <span class=\"n\">Group_B_DW<\/span><span class=\"o\">.<\/span><span class=\"n\">append<\/span><span class=\"p\">(<\/span><span class=\"n\">Group_B<\/span><span class=\"p\">)<\/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><\/span><span class=\"c1\"># \u5f97\u3089\u308c\u305f\u8fd1\u4f3c\u89e3\u306e\u7d44\u5408\u305b\u30921\u3064\u8868\u793a\u3059\u308b<\/span>\n<span class=\"n\">S<\/span> <span class=\"o\">=<\/span> <span class=\"mi\">0<\/span>  <span class=\"c1\"># \u89e3\u306e\u30a4\u30f3\u30c7\u30c3\u30af\u30b9 (0 &lt;= S &lt;= num_optimal_sol - 1)<\/span>\n<span class=\"n\">plot_grouping<\/span><span class=\"p\">(<\/span><span class=\"n\">Group_A_DW<\/span><span class=\"p\">[<\/span><span class=\"n\">S<\/span><span class=\"p\">],<\/span> <span class=\"n\">Group_B_DW<\/span><span class=\"p\">[<\/span><span class=\"n\">S<\/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\" alt=\"No description has been provided for this image\" 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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><\/span><span class=\"nb\">print<\/span><span class=\"p\">(<\/span><span class=\"s2\">\"2\u3064\u306e\u30b0\u30eb\u30fc\u30d7\u306e\u5408\u8a08\u5024\u306e\u5dee<\/span><span class=\"se\">\\t<\/span><span class=\"s2\">\"<\/span><span class=\"p\">,<\/span> <span class=\"nb\">abs<\/span><span class=\"p\">(<\/span><span class=\"nb\">sum<\/span><span class=\"p\">(<\/span><span class=\"n\">Group_A_DW<\/span><span class=\"p\">[<\/span><span class=\"n\">S<\/span><span class=\"p\">])<\/span> <span class=\"o\">-<\/span> <span class=\"nb\">sum<\/span><span class=\"p\">(<\/span><span class=\"n\">Group_B_DW<\/span><span class=\"p\">[<\/span><span class=\"n\">S<\/span><span class=\"p\">])))<\/span>\n<span class=\"nb\">print<\/span><span class=\"p\">(<\/span><span class=\"s2\">\"\u8a08\u7b97\u6642\u9593\uff08\u7406\u8ad6\u5024\uff09[s]<\/span><span class=\"se\">\\t<\/span><span class=\"s2\">\"<\/span><span class=\"p\">,<\/span> <span class=\"n\">annealing_time<\/span> <span class=\"o\">*<\/span> <span class=\"n\">num_reads<\/span> <span class=\"o\">\/<\/span> <span class=\"mi\">10<\/span><span class=\"o\">**<\/span><span class=\"mi\">6<\/span><span class=\"p\">)<\/span>\n<span class=\"nb\">print<\/span><span class=\"p\">(<\/span><span class=\"s2\">\"\u8a08\u7b97\u6642\u9593\uff08\u5b9f\u6e2c\u5024\uff09[s]<\/span><span class=\"se\">\\t<\/span><span class=\"s2\">\"<\/span><span class=\"p\">,<\/span> <span class=\"n\">response_DW<\/span><span class=\"o\">.<\/span><span class=\"n\">info<\/span><span class=\"p\">[<\/span><span class=\"s2\">\"timing\"<\/span><span class=\"p\">][<\/span><span class=\"s2\">\"qpu_sampling_time\"<\/span><span class=\"p\">]<\/span> <span class=\"o\">\/<\/span> <span class=\"mi\">10<\/span><span class=\"o\">**<\/span><span class=\"mi\">6<\/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>2\u3064\u306e\u30b0\u30eb\u30fc\u30d7\u306e\u5408\u8a08\u5024\u306e\u5dee\t 1.0\n\u8a08\u7b97\u6642\u9593\uff08\u7406\u8ad6\u5024\uff09[s]\t 0.006\n\u8a08\u7b97\u6642\u9593\uff08\u5b9f\u6e2c\u5024\uff09[s]\t 0.025896\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>\u30d3\u30c3\u30c8\u5168\u63a2\u7d22\u6642\u306b\u6bd4\u3079\u3066\u3001\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u30de\u30b7\u30f3\u306b\u3088\u308b\u624b\u6cd5\u306f\u77ed\u6642\u9593\u3067\u6700\u9069\u89e3\u3092\u5c0e\u51fa\u53ef\u80fd\u306a\u3053\u3068\u304c\u5206\u304b\u308a\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<p>\u7d9a\u3044\u3066\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u30de\u30b7\u30f3\u3067\u5f97\u3089\u308c\u305f\u89e3\u306e\u5206\u5e03\u306e\u69d8\u5b50\u3092\u89b3\u5bdf\u3057\u3066\u307f\u307e\u3059\u3002\u30a8\u30cd\u30eb\u30ae\u30fc\u304c\u5c0f\u3055\u3044\u307b\u3069\u30012\u3064\u306e\u30b0\u30eb\u30fc\u30d7\u306e\u5024\u306e\u5dee\u304c\u5c0f\u3055\u3044\u3053\u3068\u3092\u8868\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><\/span><span class=\"c1\"># \u89e3\u306e\u30a8\u30cd\u30eb\u30ae\u30fc\u5206\u5e03\u3092\u53ef\u8996\u5316\u3059\u308b\u95a2\u6570<\/span>\n<span class=\"k\">def<\/span> <span class=\"nf\">plot_energies<\/span><span class=\"p\">(<\/span><span class=\"n\">energies<\/span><span class=\"p\">):<\/span>\n    <span class=\"n\">plt<\/span><span class=\"o\">.<\/span><span class=\"n\">hist<\/span><span class=\"p\">(<\/span><span class=\"n\">energies<\/span><span class=\"p\">,<\/span> <span class=\"n\">color<\/span><span class=\"o\">=<\/span><span class=\"s2\">\"skyblue\"<\/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\">\"Energy\"<\/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\">\"Frequency\"<\/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>\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><\/span><span class=\"n\">plot_energies<\/span><span class=\"p\">(<\/span><span class=\"n\">Energies<\/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\" alt=\"No description has been provided for this image\" 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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>\u6700\u5f8c\u306b\u3001\u91cf\u5b50\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u30de\u30b7\u30f3\u306e\u30d9\u30f3\u30c1\u30de\u30fc\u30af\u3068\u3057\u3066\u3001\u78ba\u7387$p_d$\u3067\u6700\u9069\u89e3\u304c\u5f97\u3089\u308c\u308b\u307e\u3067\u306e\u8a08\u7b97\u6642\u9593TTS(Time to solution)\u3092\u6c42\u3081\u307e\u3059\u3002<\/p>\n<p>\uff11\u56de\u306e\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u306e\u6642\u9593\u3092$\\tau[s]$\u3067\u6700\u9069\u89e3\u304c\u5f97\u3089\u308c\u308b\u78ba\u7387\u3092$P_s \\left(\\tau \\right)$\u3068\u3059\u308b\u3068\u3001$R$\u56de\u306e\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u306b\u304a\u3044\u3066\u6700\u9069\u89e3\u304c\uff11\u56de\u3082\u5f97\u3089\u308c\u306a\u3044\u78ba\u7387\u306f$\\left(1-P_s \\left(\\tau \\right) \\right)^R$\u3067\u8868\u3055\u308c\u307e\u3059\u3002\u3053\u3053\u3067\u3001$R$\u56de\u306e\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u306e\u3046\u3061\u3001\uff11\u56de\u306f\u6700\u9069\u89e3\u304c\u5f97\u3089\u308c\u308b\u78ba\u7387\u3092\u4e00\u822c\u306b$p_d$\u3068\u3059\u308b\u3068\u3001$p_d$\u306f\u6b21\u5f0f\u3067\u8868\u3055\u308c\u307e\u3059\u3002<\/p>\n<p>$$ p_d = 1 &#8211; \\left(1 &#8211; P_s \\left(\\tau \\right) \\right)^R $$<\/p>\n<p>\u3088\u3063\u3066\u3001\u78ba\u7387$p_d$\u3067\u6700\u9069\u89e3\u3092\u5f97\u3089\u308c\u308b\u8a66\u884c\u56de\u6570$R$\u306f\u3001\u4ee5\u4e0b\u306e\u3088\u3046\u306b\u6c42\u3081\u3089\u308c\u307e\u3059\u3002<\/p>\n<p>$$ R = \\frac{\\ln(1 &#8211; p_d)}{\\ln(1-P_s(\\tau))} $$<\/p>\n<p>\u4ee5\u4e0a\u306b\u3088\u308a\u3001$p_d$\u306e\u78ba\u7387\u3067\u6700\u9069\u89e3\u304c\u6c42\u307e\u308b\u8a08\u7b97\u6642\u9593$TTS(\\tau,p_d)$\u306f\u3001\u4ee5\u4e0b\u306e\u5f0f\u3067\u4e0e\u3048\u3089\u308c\u307e\u3059\u3002<\/p>\n<p>$$TTS(\\tau,p_d) = \\tau R = \\tau \\frac{\\ln(1-p_d)}{\\ln(1-P_s(\\tau))}$$<\/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>\u3000TTS\u3092\u5c0e\u51fa\u3059\u308b\u306b\u3042\u305f\u3063\u3066\u3001\u4e0a\u8a18\u3067\u5f97\u3089\u308c\u305f\u6700\u9069\u89e3\u306e\u500b\u6570\u304c0\u306e\u5834\u5408\u306f\u8a08\u7b97\u304c\u3067\u304d\u307e\u305b\u3093\u3002\u3053\u308c\u306f$P_s \\left(\\tau \\right)$\u3092\u5c0e\u51fa\u3067\u304d\u306a\u3044\u3053\u3068\u306b\u539f\u56e0\u304c\u3042\u308a\u307e\u3059\u3002\u518d\u3073\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u30de\u30b7\u30f3\u3092\u52d5\u304b\u3057\u3066\u3001\u8a08\u7b97\u3057\u76f4\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><\/span><span class=\"c1\"># TTS\u3092\u8a08\u7b97\u3059\u308b\u95a2\u6570\uff08Tau[s]\uff09<\/span>\n<span class=\"k\">def<\/span> <span class=\"nf\">calculate_TTS<\/span><span class=\"p\">(<\/span><span class=\"n\">p_d<\/span><span class=\"p\">,<\/span> <span class=\"n\">Tau<\/span><span class=\"p\">,<\/span> <span class=\"n\">p_s<\/span><span class=\"p\">):<\/span>\n    <span class=\"k\">if<\/span> <span class=\"n\">p_s<\/span> <span class=\"o\">==<\/span> <span class=\"mi\">0<\/span><span class=\"p\">:<\/span>\n        <span class=\"k\">raise<\/span> <span class=\"ne\">ValueError<\/span><span class=\"p\">(<\/span><span class=\"s2\">\"p_s!=0 is required\"<\/span><span class=\"p\">)<\/span>\n    <span class=\"k\">return<\/span> <span class=\"n\">Tau<\/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=\"mi\">1<\/span> <span class=\"o\">-<\/span> <span class=\"n\">p_d<\/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=\"mi\">1<\/span> <span class=\"o\">-<\/span> <span class=\"n\">p_s<\/span><span class=\"p\">)<\/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><\/span><span class=\"n\">p_d<\/span> <span class=\"o\">=<\/span> <span class=\"mf\">0.99<\/span>  <span class=\"c1\"># 0.99\u306e\u5834\u5408\u300199%\u306e\u78ba\u7387\u3067\u6700\u9069\u89e3\u304c\u5f97\u3089\u308c\u308b\u307e\u3067\u306e\u8a08\u7b97\u6642\u9593<\/span>\n<span class=\"n\">Tau<\/span> <span class=\"o\">=<\/span> <span class=\"n\">annealing_time<\/span> <span class=\"o\">*<\/span> <span class=\"mi\">10<\/span> <span class=\"o\">**<\/span> <span class=\"p\">(<\/span><span class=\"o\">-<\/span><span class=\"mi\">6<\/span><span class=\"p\">)<\/span>\n<span class=\"n\">p_s<\/span> <span class=\"o\">=<\/span> <span class=\"n\">num_optimal_sol<\/span> <span class=\"o\">\/<\/span> <span class=\"n\">num_reads<\/span>\n\n<span class=\"nb\">print<\/span><span class=\"p\">(<\/span><span class=\"s2\">\"TTS[\u00b5s]\"<\/span><span class=\"p\">,<\/span> <span class=\"n\">calculate_TTS<\/span><span class=\"p\">(<\/span><span class=\"n\">p_d<\/span><span class=\"p\">,<\/span> <span class=\"n\">Tau<\/span><span class=\"p\">,<\/span> <span class=\"n\">p_s<\/span><span class=\"p\">)<\/span> <span class=\"o\">*<\/span> <span class=\"mi\">10<\/span><span class=\"o\">**<\/span><span class=\"mi\">6<\/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>TTS[\u00b5s] 874.1738130713132\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>TTS\u306e\u8a08\u7b97\u306b\u3088\u3063\u3066\u300199%\u306e\u78ba\u7387\u3067\u6700\u9069\u89e3\u304c\u5f97\u3089\u308c\u308b\u8a08\u7b97\u6642\u9593\u304c\u5206\u304b\u308a\u307e\u3057\u305f\u3002\u4eca\u56de\u306e\u8a08\u7b97\u6642\u9593\uff08\u7406\u8ad6\u5024\uff09\u306f6000[\u00b5s]\u3067\u3042\u3063\u305f\u306e\u3067\u3001\u6700\u9069\u89e3\u304c\u5f97\u3089\u308c\u308b\u78ba\u7387\u306f99%\u3088\u308a\u306f\u4f4e\u304b\u3063\u305f\u3053\u3068\u304c\u8003\u3048\u3089\u308c\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<h4><span class=\"ez-toc-section\" id=\"%E3%82%B7%E3%83%9F%E3%83%A5%E3%83%AC%E3%83%BC%E3%83%86%E3%83%83%E3%83%89%E3%82%A2%E3%83%8B%E3%83%BC%E3%83%AA%E3%83%B3%E3%82%B0\"><\/span>\u30b7\u30df\u30e5\u30ec\u30fc\u30c6\u30c3\u30c9\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0<span class=\"ez-toc-section-end\"><\/span><\/h4>\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>\u3000\u91cf\u5b50\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u306e\u6642\u3068\u540c\u69d8\u306bQUBO\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><\/span><span class=\"c1\"># SA\u3092\u30b5\u30f3\u30d7\u30e9\u30fc\u3068\u3057\u3066\u9078\u629e<\/span>\n<span class=\"n\">sampler<\/span> <span class=\"o\">=<\/span> <span class=\"n\">SASampler<\/span><span class=\"p\">()<\/span>\n\n<span class=\"c1\"># \u4e00\u5ea6\u306b\u53d6\u5f97\u3059\u308b\u30b5\u30f3\u30d7\u30eb\u6570<\/span>\n<span class=\"n\">num_reads<\/span> <span class=\"o\">=<\/span> <span class=\"mi\">300<\/span>\n\n<span class=\"c1\"># \u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u4e2d\u306e\u30d1\u30e9\u30e1\u30fc\u30bf(\u6e29\u5ea6, \u6a2a\u78c1\u5834)\u3092\u4e0b\u3052\u3066\u3044\u304f\u3068\u304d\u306e\u5206\u5272\u6570<\/span>\n<span class=\"c1\"># \u3053\u306e\u5024\u3092\u5897\u3084\u3059\u307b\u3069\u3086\u3063\u304f\u308a\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u3092\u3059\u308b\u3053\u3068\u306b\u76f8\u5f53\u3057\u3001\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u6642\u9593\u304c\u4f38\u3073\u308b<\/span>\n<span class=\"n\">num_sweeps<\/span> <span class=\"o\">=<\/span> <span class=\"mi\">50<\/span>\n\n<span class=\"c1\"># SA\u306b\u3088\u308b\u30b5\u30f3\u30d7\u30ea\u30f3\u30b0\u3092\u5b9f\u884c\u3059\u308b<\/span>\n<span class=\"n\">response_SA<\/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\">Q<\/span><span class=\"p\">,<\/span> <span class=\"n\">num_reads<\/span><span class=\"o\">=<\/span><span class=\"n\">num_reads<\/span><span class=\"p\">,<\/span> <span class=\"n\">num_sweeps<\/span><span class=\"o\">=<\/span><span class=\"n\">num_sweeps<\/span><span class=\"p\">)<\/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><\/span><span class=\"n\">response_SA<\/span><span class=\"o\">.<\/span><span class=\"n\">to_pandas_dataframe<\/span><span class=\"p\">()<\/span><span class=\"o\">.<\/span><span class=\"n\">head<\/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 output_prompt\">Out[\u00a0]:<\/div>\n<div class=\"output_html rendered_html output_subarea output_execute_result\">\n<div class=\"colab-df-container\" id=\"df-45e8c260-494e-498b-918f-34f5227e28f2\">\n<div>\n<style scoped=\"\">\n    .dataframe tbody tr th:only-of-type {<br \/>        vertical-align: middle;<br \/>    }<\/p>\n<p>    .dataframe tbody tr th {<br \/>        vertical-align: top;<br \/>    }<\/p>\n<p>    .dataframe thead th {<br \/>        text-align: right;<br \/>    }<br \/><\/style>\n<table border=\"1\" class=\"dataframe\">\n<thead>\n<tr style=\"text-align: right;\">\n<th><\/th>\n<th>0<\/th>\n<th>1<\/th>\n<th>2<\/th>\n<th>3<\/th>\n<th>4<\/th>\n<th>5<\/th>\n<th>6<\/th>\n<th>7<\/th>\n<th>8<\/th>\n<th>9<\/th>\n<th>&#8230;<\/th>\n<th>12<\/th>\n<th>13<\/th>\n<th>14<\/th>\n<th>15<\/th>\n<th>16<\/th>\n<th>17<\/th>\n<th>18<\/th>\n<th>19<\/th>\n<th>energy<\/th>\n<th>num_occurrences<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<th>0<\/th>\n<td>0<\/td>\n<td>0<\/td>\n<td>0<\/td>\n<td>0<\/td>\n<td>1<\/td>\n<td>0<\/td>\n<td>1<\/td>\n<td>0<\/td>\n<td>1<\/td>\n<td>1<\/td>\n<td>&#8230;<\/td>\n<td>0<\/td>\n<td>1<\/td>\n<td>1<\/td>\n<td>1<\/td>\n<td>0<\/td>\n<td>1<\/td>\n<td>0<\/td>\n<td>1<\/td>\n<td>-38016.0<\/td>\n<td>1<\/td>\n<\/tr>\n<tr>\n<th>1<\/th>\n<td>1<\/td>\n<td>1<\/td>\n<td>0<\/td>\n<td>1<\/td>\n<td>1<\/td>\n<td>1<\/td>\n<td>0<\/td>\n<td>0<\/td>\n<td>0<\/td>\n<td>0<\/td>\n<td>&#8230;<\/td>\n<td>1<\/td>\n<td>0<\/td>\n<td>1<\/td>\n<td>0<\/td>\n<td>0<\/td>\n<td>1<\/td>\n<td>0<\/td>\n<td>1<\/td>\n<td>-38024.0<\/td>\n<td>1<\/td>\n<\/tr>\n<tr>\n<th>2<\/th>\n<td>1<\/td>\n<td>1<\/td>\n<td>0<\/td>\n<td>1<\/td>\n<td>0<\/td>\n<td>1<\/td>\n<td>1<\/td>\n<td>1<\/td>\n<td>1<\/td>\n<td>1<\/td>\n<td>&#8230;<\/td>\n<td>0<\/td>\n<td>0<\/td>\n<td>0<\/td>\n<td>1<\/td>\n<td>0<\/td>\n<td>0<\/td>\n<td>0<\/td>\n<td>1<\/td>\n<td>-38024.0<\/td>\n<td>1<\/td>\n<\/tr>\n<tr>\n<th>3<\/th>\n<td>1<\/td>\n<td>1<\/td>\n<td>0<\/td>\n<td>0<\/td>\n<td>0<\/td>\n<td>1<\/td>\n<td>1<\/td>\n<td>1<\/td>\n<td>1<\/td>\n<td>1<\/td>\n<td>&#8230;<\/td>\n<td>1<\/td>\n<td>0<\/td>\n<td>0<\/td>\n<td>0<\/td>\n<td>1<\/td>\n<td>1<\/td>\n<td>0<\/td>\n<td>0<\/td>\n<td>-38024.0<\/td>\n<td>1<\/td>\n<\/tr>\n<tr>\n<th>4<\/th>\n<td>0<\/td>\n<td>1<\/td>\n<td>0<\/td>\n<td>0<\/td>\n<td>1<\/td>\n<td>0<\/td>\n<td>0<\/td>\n<td>1<\/td>\n<td>0<\/td>\n<td>0<\/td>\n<td>&#8230;<\/td>\n<td>1<\/td>\n<td>1<\/td>\n<td>0<\/td>\n<td>0<\/td>\n<td>0<\/td>\n<td>1<\/td>\n<td>1<\/td>\n<td>0<\/td>\n<td>-38024.0<\/td>\n<td>1<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>5 rows \u00d7 22 columns<\/p>\n<\/div>\n<div class=\"colab-df-buttons\">\n<div class=\"colab-df-container\"><button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-45e8c260-494e-498b-918f-34f5227e28f2')\" style=\"display: none;\" title=\"Convert this dataframe to an interactive table.\"><br \/>\n<svg height=\"24px\" viewbox=\"0 -960 960 960\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><\/svg>\n<path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"><\/path> <\/button> <\/p>\n<style>\n    .colab-df-container {<br \/>      display:flex;<br \/>      gap: 12px;<br \/>    }<\/p>\n<p>    .colab-df-convert {<br \/>      background-color: #E8F0FE;<br \/>      border: none;<br \/>      border-radius: 50%;<br \/>      cursor: pointer;<br \/>      display: none;<br \/>      fill: #1967D2;<br \/>      height: 32px;<br \/>      padding: 0 0 0 0;<br \/>      width: 32px;<br \/>    }<\/p>\n<p>    .colab-df-convert:hover {<br \/>      background-color: #E2EBFA;<br \/>      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);<br \/>      fill: #174EA6;<br \/>    }<\/p>\n<p>    .colab-df-buttons div {<br \/>      margin-bottom: 4px;<br \/>    }<\/p>\n<p>    [theme=dark] .colab-df-convert {<br \/>      background-color: #3B4455;<br \/>      fill: #D2E3FC;<br \/>    }<\/p>\n<p>    [theme=dark] .colab-df-convert:hover {<br \/>      background-color: #434B5C;<br \/>      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);<br \/>      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));<br \/>      fill: #FFFFFF;<br \/>    }<br \/>  <\/style>\n<p><script>\n      const buttonEl =\n        document.querySelector('#df-45e8c260-494e-498b-918f-34f5227e28f2 button.colab-df-convert');\n      buttonEl.style.display =\n        google.colab.kernel.accessAllowed ? 'block' : 'none';<\/p>\n<p>      async function convertToInteractive(key) {\n        const element = document.querySelector('#df-45e8c260-494e-498b-918f-34f5227e28f2');\n        const dataTable =\n          await google.colab.kernel.invokeFunction('convertToInteractive',\n                                                    [key], {});\n        if (!dataTable) return;<\/p>\n<p>        const docLinkHtml = 'Like what you see? Visit the ' +\n          '<a target=\"_blank\" href=https:\/\/colab.research.google.com\/notebooks\/data_table.ipynb>data table notebook<\/a>'\n          + ' to learn more about interactive tables.';\n        element.innerHTML = '';\n        dataTable['output_type'] = 'display_data';\n        await google.colab.output.renderOutput(dataTable, element);\n        const docLink = document.createElement('div');\n        docLink.innerHTML = docLinkHtml;\n        element.appendChild(docLink);\n      }\n    <\/script><\/p>\n<\/div>\n<div id=\"df-26735756-ad23-4c81-825e-8c480fcd2166\"><button class=\"colab-df-quickchart\" onclick=\"quickchart('df-26735756-ad23-4c81-825e-8c480fcd2166')\" style=\"display: none;\" title=\"Suggest charts.\"><\/button><button class=\"colab-df-quickchart\" onclick=\"quickchart('df-26735756-ad23-4c81-825e-8c480fcd2166')\" style=\"display: none;\" title=\"Suggest charts.\"><br \/>\n<svg height=\"24px\" viewbox=\"0 0 24 24\" width=\"24px\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><\/svg><br \/>\n<g>\n<path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"><\/path> <\/g><\/button>\u00a0 <\/p>\n<style>\n  .colab-df-quickchart {<br \/>      --bg-color: #E8F0FE;<br \/>      --fill-color: #1967D2;<br \/>      --hover-bg-color: #E2EBFA;<br \/>      --hover-fill-color: #174EA6;<br \/>      --disabled-fill-color: #AAA;<br \/>      --disabled-bg-color: #DDD;<br \/>  }<\/p>\n<p>  [theme=dark] .colab-df-quickchart {<br \/>      --bg-color: #3B4455;<br \/>      --fill-color: #D2E3FC;<br \/>      --hover-bg-color: #434B5C;<br \/>      --hover-fill-color: #FFFFFF;<br \/>      --disabled-bg-color: #3B4455;<br \/>      --disabled-fill-color: #666;<br \/>  }<\/p>\n<p>  .colab-df-quickchart {<br \/>    background-color: var(--bg-color);<br \/>    border: none;<br \/>    border-radius: 50%;<br \/>    cursor: pointer;<br \/>    display: none;<br \/>    fill: var(--fill-color);<br \/>    height: 32px;<br \/>    padding: 0;<br \/>    width: 32px;<br \/>  }<\/p>\n<p>  .colab-df-quickchart:hover {<br \/>    background-color: var(--hover-bg-color);<br \/>    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);<br \/>    fill: var(--button-hover-fill-color);<br \/>  }<\/p>\n<p>  .colab-df-quickchart-complete:disabled,<br \/>  .colab-df-quickchart-complete:disabled:hover {<br \/>    background-color: var(--disabled-bg-color);<br \/>    fill: var(--disabled-fill-color);<br \/>    box-shadow: none;<br \/>  }<\/p>\n<p>  .colab-df-spinner {<br \/>    border: 2px solid var(--fill-color);<br \/>    border-color: transparent;<br \/>    border-bottom-color: var(--fill-color);<br \/>    animation:<br \/>      spin 1s steps(1) infinite;<br \/>  }<\/p>\n<p>  @keyframes spin {<br \/>    0% {<br \/>      border-color: transparent;<br \/>      border-bottom-color: var(--fill-color);<br \/>      border-left-color: var(--fill-color);<br \/>    }<br \/>    20% {<br \/>      border-color: transparent;<br \/>      border-left-color: var(--fill-color);<br \/>      border-top-color: var(--fill-color);<br \/>    }<br \/>    30% {<br \/>      border-color: transparent;<br \/>      border-left-color: var(--fill-color);<br \/>      border-top-color: var(--fill-color);<br \/>      border-right-color: var(--fill-color);<br \/>    }<br \/>    40% {<br \/>      border-color: transparent;<br \/>      border-right-color: var(--fill-color);<br \/>      border-top-color: var(--fill-color);<br \/>    }<br \/>    60% {<br \/>      border-color: transparent;<br \/>      border-right-color: var(--fill-color);<br \/>    }<br \/>    80% {<br \/>      border-color: transparent;<br \/>      border-right-color: var(--fill-color);<br \/>      border-bottom-color: var(--fill-color);<br \/>    }<br \/>    90% {<br \/>      border-color: transparent;<br \/>      border-bottom-color: var(--fill-color);<br \/>    }<br \/>  }<br \/><\/style>\n<p><script>\n    async function quickchart(key) {\n      const quickchartButtonEl =\n        document.querySelector('#' + key + ' button');\n      quickchartButtonEl.disabled = true;  \/\/ To prevent multiple clicks.\n      quickchartButtonEl.classList.add('colab-df-spinner');\n      try {\n        const charts = await google.colab.kernel.invokeFunction(\n            'suggestCharts', [key], {});\n      } catch (error) {\n        console.error('Error during call to suggestCharts:', error);\n      }\n      quickchartButtonEl.classList.remove('colab-df-spinner');\n      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n    }\n    (() => {\n      let quickchartButtonEl =\n        document.querySelector('#df-26735756-ad23-4c81-825e-8c480fcd2166 button');\n      quickchartButtonEl.style.display =\n        google.colab.kernel.accessAllowed ? 'block' : 'none';\n    })();\n  <\/script><\/p>\n<\/div>\n<\/div>\n<\/div>\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><\/span><span class=\"n\">num_optimal_sol<\/span><span class=\"p\">,<\/span> <span class=\"n\">num_approx_sol<\/span><span class=\"p\">,<\/span> <span class=\"n\">optimal_sol<\/span><span class=\"p\">,<\/span> <span class=\"n\">approx_sol<\/span><span class=\"p\">,<\/span> <span class=\"n\">Energies<\/span> <span class=\"o\">=<\/span> <span class=\"n\">count_solutions<\/span><span class=\"p\">(<\/span>\n    <span class=\"n\">response_SA<\/span>\n<span class=\"p\">)<\/span>\n\n<span class=\"nb\">print<\/span><span class=\"p\">(<\/span><span class=\"s2\">\"\u6700\u9069\u89e3\uff08\u500b\uff09<\/span><span class=\"se\">\\t<\/span><span class=\"s2\">\"<\/span><span class=\"p\">,<\/span> <span class=\"n\">num_optimal_sol<\/span><span class=\"p\">)<\/span>\n<span class=\"nb\">print<\/span><span class=\"p\">(<\/span><span class=\"s2\">\"\u6700\u9069\u89e3\uff08\u500b\uff09<\/span><span class=\"se\">\\t<\/span><span class=\"s2\">\"<\/span><span class=\"p\">,<\/span> <span class=\"n\">num_approx_sol<\/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>\u6700\u9069\u89e3\uff08\u500b\uff09\t 150\n\u6700\u9069\u89e3\uff08\u500b\uff09\t 150\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><\/span><span class=\"n\">Group_A_SA<\/span> <span class=\"o\">=<\/span> <span class=\"p\">[]<\/span>\n<span class=\"n\">Group_B_SA<\/span> <span class=\"o\">=<\/span> <span class=\"p\">[]<\/span>\n\n<span class=\"k\">for<\/span> <span class=\"n\">solution<\/span> <span class=\"ow\">in<\/span> <span class=\"n\">approx_sol<\/span><span class=\"p\">:<\/span>\n    <span class=\"n\">Group_A<\/span> <span class=\"o\">=<\/span> <span class=\"n\">np<\/span><span class=\"o\">.<\/span><span class=\"n\">zeros<\/span><span class=\"p\">(<\/span><span class=\"n\">N<\/span><span class=\"p\">)<\/span>\n    <span class=\"n\">Group_B<\/span> <span class=\"o\">=<\/span> <span class=\"n\">np<\/span><span class=\"o\">.<\/span><span class=\"n\">zeros<\/span><span class=\"p\">(<\/span><span class=\"n\">N<\/span><span class=\"p\">)<\/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=\"n\">N<\/span><span class=\"p\">):<\/span>\n        <span class=\"k\">if<\/span> <span class=\"n\">solution<\/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            <span class=\"n\">Group_A<\/span><span class=\"p\">[<\/span><span class=\"n\">i<\/span><span class=\"p\">]<\/span> <span class=\"o\">=<\/span> <span class=\"n\">W<\/span><span class=\"p\">[<\/span><span class=\"n\">i<\/span><span class=\"p\">]<\/span>\n        <span class=\"k\">else<\/span><span class=\"p\">:<\/span>\n            <span class=\"n\">Group_B<\/span><span class=\"p\">[<\/span><span class=\"n\">i<\/span><span class=\"p\">]<\/span> <span class=\"o\">=<\/span> <span class=\"n\">W<\/span><span class=\"p\">[<\/span><span class=\"n\">i<\/span><span class=\"p\">]<\/span>\n\n    <span class=\"n\">Group_A_SA<\/span><span class=\"o\">.<\/span><span class=\"n\">append<\/span><span class=\"p\">(<\/span><span class=\"n\">Group_A<\/span><span class=\"p\">)<\/span>\n    <span class=\"n\">Group_B_SA<\/span><span class=\"o\">.<\/span><span class=\"n\">append<\/span><span class=\"p\">(<\/span><span class=\"n\">Group_B<\/span><span class=\"p\">)<\/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><\/span><span class=\"c1\"># \u5f97\u3089\u308c\u305f\u8fd1\u4f3c\u89e3\u306e\u7d44\u5408\u305b\u30921\u3064\u8868\u793a\u3059\u308b<\/span>\n<span class=\"n\">S<\/span> <span class=\"o\">=<\/span> <span class=\"mi\">0<\/span>  <span class=\"c1\"># \u89e3\u306e\u30a4\u30f3\u30c7\u30c3\u30af\u30b9 (0 &lt;= S &lt;= num_optimal_sol - 1)<\/span>\n<span class=\"n\">plot_grouping<\/span><span class=\"p\">(<\/span><span class=\"n\">Group_A_SA<\/span><span class=\"p\">[<\/span><span class=\"n\">S<\/span><span class=\"p\">],<\/span> <span class=\"n\">Group_B_SA<\/span><span class=\"p\">[<\/span><span class=\"n\">S<\/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\" alt=\"No description has been provided for this image\" 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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><\/span><span class=\"nb\">print<\/span><span class=\"p\">(<\/span><span class=\"s2\">\"2\u3064\u306e\u30b0\u30eb\u30fc\u30d7\u306e\u5408\u8a08\u5024\u306e\u5dee<\/span><span class=\"se\">\\t<\/span><span class=\"s2\">\"<\/span><span class=\"p\">,<\/span> <span class=\"nb\">abs<\/span><span class=\"p\">(<\/span><span class=\"nb\">sum<\/span><span class=\"p\">(<\/span><span class=\"n\">Group_A_SA<\/span><span class=\"p\">[<\/span><span class=\"n\">S<\/span><span class=\"p\">])<\/span> <span class=\"o\">-<\/span> <span class=\"nb\">sum<\/span><span class=\"p\">(<\/span><span class=\"n\">Group_B_SA<\/span><span class=\"p\">[<\/span><span class=\"n\">S<\/span><span class=\"p\">])))<\/span>\n<span class=\"nb\">print<\/span><span class=\"p\">(<\/span><span class=\"s2\">\"\u8a08\u7b97\u6642\u9593[\u00b5s]<\/span><span class=\"se\">\\t<\/span><span class=\"s2\">\"<\/span><span class=\"p\">,<\/span> <span class=\"n\">response_SA<\/span><span class=\"o\">.<\/span><span class=\"n\">info<\/span><span class=\"p\">[<\/span><span class=\"s2\">\"execution_time\"<\/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>2\u3064\u306e\u30b0\u30eb\u30fc\u30d7\u306e\u5408\u8a08\u5024\u306e\u5dee\t 1.0\n\u8a08\u7b97\u6642\u9593[\u00b5s]\t 60.54146000015711\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><\/span><span class=\"n\">plot_energies<\/span><span class=\"p\">(<\/span><span class=\"n\">Energies<\/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\" alt=\"No description has been provided for this image\" 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