{"id":2819,"date":"2022-03-03T14:36:07","date_gmt":"2022-03-03T05:36:07","guid":{"rendered":"https:\/\/qard.is.tohoku.ac.jp\/T-Wave\/?p=2819"},"modified":"2022-03-03T14:36:07","modified_gmt":"2022-03-03T05:36:07","slug":"%e3%83%9c%e3%83%ab%e3%83%84%e3%83%9e%e3%83%b3%e6%a9%9f%e6%a2%b0%e5%ad%a6%e7%bf%92%e3%81%abd-wave%e3%83%9e%e3%82%b7%e3%83%b3%e3%82%92%e7%94%a8%e3%81%84%e3%82%8b%e5%ae%9f%e8%b7%b5%e7%b7%a8part2","status":"publish","type":"post","link":"https:\/\/qard.is.tohoku.ac.jp\/T-Wave\/2022\/03\/03\/%e3%83%9c%e3%83%ab%e3%83%84%e3%83%9e%e3%83%b3%e6%a9%9f%e6%a2%b0%e5%ad%a6%e7%bf%92%e3%81%abd-wave%e3%83%9e%e3%82%b7%e3%83%b3%e3%82%92%e7%94%a8%e3%81%84%e3%82%8b%e5%ae%9f%e8%b7%b5%e7%b7%a8part2\/","title":{"rendered":"\u30dc\u30eb\u30c4\u30de\u30f3\u6a5f\u68b0\u5b66\u7fd2\u306bD-Wave\u30de\u30b7\u30f3\u3092\u7528\u3044\u308b(\u5b9f\u8df5\u7de8part2)"},"content":{"rendered":"<p><a href=\"https:\/\/colab.research.google.com\/github\/T-QARD\/t-wave\/blob\/main\/notebooks\/BM_dwave\/SKmodel_dwave.ipynb\" target=\"_blank\" rel=\"noopener noreferrer\"><img decoding=\"async\" src=\"https:\/\/colab.research.google.com\/assets\/colab-badge.svg\" alt=\"Open in Colab\" \/><\/a><\/p>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\"><\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">\n<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_82_2 counter-hierarchy ez-toc-counter ez-toc-white ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\">\n<p class=\"ez-toc-title ez-toc-toggle\" style=\"cursor:pointer\">Table of Contents<\/p>\n<span class=\"ez-toc-title-toggle\"><a href=\"#\" class=\"ez-toc-pull-right ez-toc-btn ez-toc-btn-xs ez-toc-btn-default ez-toc-toggle\" aria-label=\"Toggle Table of Content\"><span class=\"ez-toc-js-icon-con\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #999;color:#999\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewBox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #999;color:#999\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewBox=\"0 0 24 24\" version=\"1.2\" baseProfile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/span><\/a><\/span><\/div>\n<nav><ul class='ez-toc-list ez-toc-list-level-1 ' ><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/qard.is.tohoku.ac.jp\/T-Wave\/2022\/03\/03\/%e3%83%9c%e3%83%ab%e3%83%84%e3%83%9e%e3%83%b3%e6%a9%9f%e6%a2%b0%e5%ad%a6%e7%bf%92%e3%81%abd-wave%e3%83%9e%e3%82%b7%e3%83%b3%e3%82%92%e7%94%a8%e3%81%84%e3%82%8b%e5%ae%9f%e8%b7%b5%e7%b7%a8part2\/#%E6%A6%82%E8%A6%81\" >\u6982\u8981<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/qard.is.tohoku.ac.jp\/T-Wave\/2022\/03\/03\/%e3%83%9c%e3%83%ab%e3%83%84%e3%83%9e%e3%83%b3%e6%a9%9f%e6%a2%b0%e5%ad%a6%e7%bf%92%e3%81%abd-wave%e3%83%9e%e3%82%b7%e3%83%b3%e3%82%92%e7%94%a8%e3%81%84%e3%82%8b%e5%ae%9f%e8%b7%b5%e7%b7%a8part2\/#%E6%96%87%E7%8C%AE%E6%83%85%E5%A0%B1\" >\u6587\u732e\u60c5\u5831<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/qard.is.tohoku.ac.jp\/T-Wave\/2022\/03\/03\/%e3%83%9c%e3%83%ab%e3%83%84%e3%83%9e%e3%83%b3%e6%a9%9f%e6%a2%b0%e5%ad%a6%e7%bf%92%e3%81%abd-wave%e3%83%9e%e3%82%b7%e3%83%b3%e3%82%92%e7%94%a8%e3%81%84%e3%82%8b%e5%ae%9f%e8%b7%b5%e7%b7%a8part2\/#%E5%95%8F%E9%A1%8C\" >\u554f\u984c<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/qard.is.tohoku.ac.jp\/T-Wave\/2022\/03\/03\/%e3%83%9c%e3%83%ab%e3%83%84%e3%83%9e%e3%83%b3%e6%a9%9f%e6%a2%b0%e5%ad%a6%e7%bf%92%e3%81%abd-wave%e3%83%9e%e3%82%b7%e3%83%b3%e3%82%92%e7%94%a8%e3%81%84%e3%82%8b%e5%ae%9f%e8%b7%b5%e7%b7%a8part2\/#SK%E6%A8%A1%E5%9E%8B%E3%81%AE%E5%AD%A6%E7%BF%92\" >SK\u6a21\u578b\u306e\u5b66\u7fd2<\/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\/2022\/03\/03\/%e3%83%9c%e3%83%ab%e3%83%84%e3%83%9e%e3%83%b3%e6%a9%9f%e6%a2%b0%e5%ad%a6%e7%bf%92%e3%81%abd-wave%e3%83%9e%e3%82%b7%e3%83%b3%e3%82%92%e7%94%a8%e3%81%84%e3%82%8b%e5%ae%9f%e8%b7%b5%e7%b7%a8part2\/#%E5%AD%A6%E7%BF%92%E6%96%B9%E6%B3%95\" >\u5b66\u7fd2\u65b9\u6cd5<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/qard.is.tohoku.ac.jp\/T-Wave\/2022\/03\/03\/%e3%83%9c%e3%83%ab%e3%83%84%e3%83%9e%e3%83%b3%e6%a9%9f%e6%a2%b0%e5%ad%a6%e7%bf%92%e3%81%abd-wave%e3%83%9e%e3%82%b7%e3%83%b3%e3%82%92%e7%94%a8%e3%81%84%e3%82%8b%e5%ae%9f%e8%b7%b5%e7%b7%a8part2\/#%E5%AE%9F%E9%A8%93\" >\u5b9f\u9a13<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-7\" href=\"https:\/\/qard.is.tohoku.ac.jp\/T-Wave\/2022\/03\/03\/%e3%83%9c%e3%83%ab%e3%83%84%e3%83%9e%e3%83%b3%e6%a9%9f%e6%a2%b0%e5%ad%a6%e7%bf%92%e3%81%abd-wave%e3%83%9e%e3%82%b7%e3%83%b3%e3%82%92%e7%94%a8%e3%81%84%e3%82%8b%e5%ae%9f%e8%b7%b5%e7%b7%a8part2\/#%E5%85%A8%E4%BD%93%E5%83%8F\" >\u5168\u4f53\u50cf<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-8\" href=\"https:\/\/qard.is.tohoku.ac.jp\/T-Wave\/2022\/03\/03\/%e3%83%9c%e3%83%ab%e3%83%84%e3%83%9e%e3%83%b3%e6%a9%9f%e6%a2%b0%e5%ad%a6%e7%bf%92%e3%81%abd-wave%e3%83%9e%e3%82%b7%e3%83%b3%e3%82%92%e7%94%a8%e3%81%84%e3%82%8b%e5%ae%9f%e8%b7%b5%e7%b7%a8part2\/#%E3%83%A9%E3%82%A4%E3%83%96%E3%83%A9%E3%83%AA%E3%81%AE%E3%82%A4%E3%83%B3%E3%82%B9%E3%83%88%E3%83%BC%E3%83%AB\" >\u30e9\u30a4\u30d6\u30e9\u30ea\u306e\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-9\" href=\"https:\/\/qard.is.tohoku.ac.jp\/T-Wave\/2022\/03\/03\/%e3%83%9c%e3%83%ab%e3%83%84%e3%83%9e%e3%83%b3%e6%a9%9f%e6%a2%b0%e5%ad%a6%e7%bf%92%e3%81%abd-wave%e3%83%9e%e3%82%b7%e3%83%b3%e3%82%92%e7%94%a8%e3%81%84%e3%82%8b%e5%ae%9f%e8%b7%b5%e7%b7%a8part2\/#%E3%82%AC%E3%82%A6%E3%82%B9%E5%88%86%E5%B8%83%E3%81%8B%E3%82%89%E7%9B%B8%E4%BA%92%E4%BD%9C%E7%94%A8%E3%81%AE%E4%BD%9C%E6%88%90\" >\u30ac\u30a6\u30b9\u5206\u5e03\u304b\u3089\u76f8\u4e92\u4f5c\u7528\u306e\u4f5c\u6210<\/a><\/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\/2022\/03\/03\/%e3%83%9c%e3%83%ab%e3%83%84%e3%83%9e%e3%83%b3%e6%a9%9f%e6%a2%b0%e5%ad%a6%e7%bf%92%e3%81%abd-wave%e3%83%9e%e3%82%b7%e3%83%b3%e3%82%92%e7%94%a8%e3%81%84%e3%82%8b%e5%ae%9f%e8%b7%b5%e7%b7%a8part2\/#%E7%9B%B8%E4%BA%92%E4%BD%9C%E7%94%A8%E3%81%8B%E3%82%89%E3%82%B9%E3%83%94%E3%83%B3%E9%85%8D%E4%BD%8D%E3%81%AE%E4%BD%9C%E6%88%90\" >\u76f8\u4e92\u4f5c\u7528\u304b\u3089\u30b9\u30d4\u30f3\u914d\u4f4d\u306e\u4f5c\u6210<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-11\" href=\"https:\/\/qard.is.tohoku.ac.jp\/T-Wave\/2022\/03\/03\/%e3%83%9c%e3%83%ab%e3%83%84%e3%83%9e%e3%83%b3%e6%a9%9f%e6%a2%b0%e5%ad%a6%e7%bf%92%e3%81%abd-wave%e3%83%9e%e3%82%b7%e3%83%b3%e3%82%92%e7%94%a8%e3%81%84%e3%82%8b%e5%ae%9f%e8%b7%b5%e7%b7%a8part2\/#%E6%AD%A3%E8%A7%A3%E3%81%A8%E3%81%AA%E3%82%8B%E5%B9%B3%E5%9D%87%E5%AF%BE%E6%95%B0%E5%B0%A4%E5%BA%A6%E3%81%AE%E8%A8%88%E7%AE%97\" >\u6b63\u89e3\u3068\u306a\u308b\u5e73\u5747\u5bfe\u6570\u5c24\u5ea6\u306e\u8a08\u7b97<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-12\" href=\"https:\/\/qard.is.tohoku.ac.jp\/T-Wave\/2022\/03\/03\/%e3%83%9c%e3%83%ab%e3%83%84%e3%83%9e%e3%83%b3%e6%a9%9f%e6%a2%b0%e5%ad%a6%e7%bf%92%e3%81%abd-wave%e3%83%9e%e3%82%b7%e3%83%b3%e3%82%92%e7%94%a8%e3%81%84%e3%82%8b%e5%ae%9f%e8%b7%b5%e7%b7%a8part2\/#QA%E3%81%AB%E3%82%88%E3%82%8B%E5%AD%A6%E7%BF%92\" >QA\u306b\u3088\u308b\u5b66\u7fd2<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-13\" href=\"https:\/\/qard.is.tohoku.ac.jp\/T-Wave\/2022\/03\/03\/%e3%83%9c%e3%83%ab%e3%83%84%e3%83%9e%e3%83%b3%e6%a9%9f%e6%a2%b0%e5%ad%a6%e7%bf%92%e3%81%abd-wave%e3%83%9e%e3%82%b7%e3%83%b3%e3%82%92%e7%94%a8%e3%81%84%e3%82%8b%e5%ae%9f%e8%b7%b5%e7%b7%a8part2\/#SA%E3%81%AB%E3%82%88%E3%82%8B%E5%AD%A6%E7%BF%92\" >SA\u306b\u3088\u308b\u5b66\u7fd2<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-14\" href=\"https:\/\/qard.is.tohoku.ac.jp\/T-Wave\/2022\/03\/03\/%e3%83%9c%e3%83%ab%e3%83%84%e3%83%9e%e3%83%b3%e6%a9%9f%e6%a2%b0%e5%ad%a6%e7%bf%92%e3%81%abd-wave%e3%83%9e%e3%82%b7%e3%83%b3%e3%82%92%e7%94%a8%e3%81%84%e3%82%8b%e5%ae%9f%e8%b7%b5%e7%b7%a8part2\/#%E5%8E%B3%E5%AF%86%E5%8B%BE%E9%85%8D%E3%81%AB%E3%82%88%E3%82%8B%E5%AD%A6%E7%BF%92\" >\u53b3\u5bc6\u52fe\u914d\u306b\u3088\u308b\u5b66\u7fd2<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-15\" href=\"https:\/\/qard.is.tohoku.ac.jp\/T-Wave\/2022\/03\/03\/%e3%83%9c%e3%83%ab%e3%83%84%e3%83%9e%e3%83%b3%e6%a9%9f%e6%a2%b0%e5%ad%a6%e7%bf%92%e3%81%abd-wave%e3%83%9e%e3%82%b7%e3%83%b3%e3%82%92%e7%94%a8%e3%81%84%e3%82%8b%e5%ae%9f%e8%b7%b5%e7%b7%a8part2\/#%E3%81%82%E3%81%A8%E3%81%8C%E3%81%8D\" >\u3042\u3068\u304c\u304d<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-16\" href=\"https:\/\/qard.is.tohoku.ac.jp\/T-Wave\/2022\/03\/03\/%e3%83%9c%e3%83%ab%e3%83%84%e3%83%9e%e3%83%b3%e6%a9%9f%e6%a2%b0%e5%ad%a6%e7%bf%92%e3%81%abd-wave%e3%83%9e%e3%82%b7%e3%83%b3%e3%82%92%e7%94%a8%e3%81%84%e3%82%8b%e5%ae%9f%e8%b7%b5%e7%b7%a8part2\/#%E6%9C%AC%E8%A8%98%E4%BA%8B%E3%81%AE%E6%8B%85%E5%BD%93%E8%80%85\" >\u672c\u8a18\u4e8b\u306e\u62c5\u5f53\u8005<\/a><\/li><\/ul><\/li><\/ul><\/nav><\/div>\n<h2><span class=\"ez-toc-section\" id=\"%E6%A6%82%E8%A6%81\"><\/span>\u6982\u8981<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">\n<p>\u672c\u8a18\u4e8b\u306f\u3001<a href=\"https:\/\/journals.aps.org\/prx\/abstract\/10.1103\/PhysRevX.7.041052#fulltext\">\u3053\u3061\u3089\u306e\u8ad6\u6587<\/a>\u306e\u518d\u73fe\u5b9f\u9a13\u3092\u884c\u3063\u305f\u3082\u306e\u3067\u3059\u3002\u5177\u4f53\u7684\u306b\u306f\u3001D-Wave\u30de\u30b7\u30f3\u3092\u7528\u3044\u3066\u3001\u30e9\u30f3\u30c0\u30e0\u306a\u30a4\u30b8\u30f3\u30b0\u6a21\u578b(SK\u6a21\u578b)\u3092\u5b66\u7fd2\u51fa\u6765\u308b\u304b\u691c\u8a3c\u3057\u307e\u3059\u3002<br \/>\n<a href=\"\/T-Wave\/?p=2683\">\u524d\u306e\u8a18\u4e8b<\/a>\u3067\u306f\u3001D-Wave\u30de\u30b7\u30f3\u3092\u7528\u3044\u305f\u624b\u66f8\u304d\u6570\u5b57\u306e\u751f\u6210\u30fb\u5fa9\u5143\u3092\u884c\u3063\u3066\u3044\u307e\u3059\u3002<\/p>\n<p>\u3053\u306e\u8ad6\u6587\u306b\u95a2\u3059\u308b\u8a73\u3057\u3044\u89e3\u8aac\u306f\u3001<a href=\"\/T-Wave\/\">T-Wave<\/a>\u3092\u3054\u89a7\u304f\u3060\u3055\u3044\u3002<\/p>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">\n<h2><span class=\"ez-toc-section\" id=\"%E6%96%87%E7%8C%AE%E6%83%85%E5%A0%B1\"><\/span>\u6587\u732e\u60c5\u5831<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<ul>\n<li>\u30bf\u30a4\u30c8\u30eb: Quantum-Assisted Learning of Hardware-Embedded Probabilistic Graphical Models<\/li>\n<li>\u8457\u8005: Marcello Benedetti, John Realpe-G\u00f3mez, Rupak Biswas and Alejandro Perdomo-Ortiz<\/li>\n<li>\u66f8\u8a8c\u60c5\u5831: Phys. Rev. X 7, 041052 (2017)<\/li>\n<li>DOI: <a href=\"https:\/\/link.aps.org\/doi\/10.1103\/PhysRevX.7.041052\">10.1103\/PhysRevX.7.041052<\/a><\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">\n<h2><span class=\"ez-toc-section\" id=\"%E5%95%8F%E9%A1%8C\"><\/span>\u554f\u984c<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">\n<h3><span class=\"ez-toc-section\" id=\"SK%E6%A8%A1%E5%9E%8B%E3%81%AE%E5%AD%A6%E7%BF%92\"><\/span>SK\u6a21\u578b\u306e\u5b66\u7fd2<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<p>SK\u6a21\u578b\u3068\u306f\u3001\u3059\u3079\u3066\u306e\u30b9\u30d4\u30f3\u9593\u306b\u5bfe\u3057\u3066\u540c\u3058\u78ba\u7387\u5206\u5e03\u306b\u5f93\u3063\u305f\u76f8\u4e92\u4f5c\u7528\u3092\u4e0e\u3048\u308b\u30a4\u30b8\u30f3\u30b0\u6a21\u578b\u3067\u3059\u3002\u672c\u8ad6\u6587\u3067\u306f\u3001\u6b21\u306e\u30d1\u30e9\u30e1\u30fc\u30bf\u3092\u7528\u3044\u3066SK\u6a21\u578b\u306e\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30bb\u30c3\u30c8\u3092\u4f5c\u6210\u3057\u307e\u3057\u305f\u3002<\/p>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">\n<table>\n<thead>\n<tr>\n<th style=\"text-align: center;\">\u30d1\u30e9\u30e1\u30fc\u30bf<\/th>\n<th style=\"text-align: center;\">\u00a0 \u5024<\/th>\n<th style=\"text-align: center;\">\u8aac\u660e<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td style=\"text-align: center;\">[latex]N[\/latex]<\/td>\n<td style=\"text-align: center;\">15<\/td>\n<td style=\"text-align: center;\">\u30b9\u30d4\u30f3\u6570<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: center;\">[latex]h[\/latex]<\/td>\n<td style=\"text-align: center;\">0<\/td>\n<td style=\"text-align: center;\">\u5c40\u6240\u78c1\u5834<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: center;\">[latex]\\beta[\/latex]<\/td>\n<td style=\"text-align: center;\">1<\/td>\n<td style=\"text-align: center;\">\u9006\u6e29\u5ea6<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: center;\">[latex]\\mu[\/latex]<\/td>\n<td style=\"text-align: center;\">0<\/td>\n<td style=\"text-align: center;\">\u5e73\u5747<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: center;\">[latex]\\sigma[\/latex]<\/td>\n<td style=\"text-align: center;\">[latex]2\/\\sqrt{\ud835\udc41}[\/latex]<\/td>\n<td style=\"text-align: center;\">\u6a19\u6e96\u504f\u5dee<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\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>\u672c\u5b9f\u9a13\u306f\u3001<\/p>\n<ul>\n<li>\u53b3\u5bc6\u52fe\u914d<\/li>\n<li>\u30b7\u30df\u30e5\u30ec\u30fc\u30c6\u30c3\u30c9\u30fb\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0(SA)<\/li>\n<li>\u91cf\u5b50\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0(QA)<\/li>\n<\/ul>\n<p>\u306e\uff13\u3064\u306e\u624b\u6cd5\u3067\u5b66\u7fd2\u3092\u884c\u3044\u307e\u3059\u3002QA\u306b\u95a2\u3057\u3066\u306f\u3001D-Wave\u30de\u30b7\u30f3\u3092\u7528\u3044\u3066\u5b9f\u9a13\u3092\u884c\u3044\u307e\u3059\u3002\u307e\u305f\u3001\u53ce\u675f\u306e\u901f\u3055\u3092\u6bd4\u8f03\u3059\u308b\u305f\u3081\u306e\u5c3a\u5ea6\u3068\u3057\u3066\u3001\u6b21\u306e\u5e73\u5747\u5bfe\u6570\u5c24\u5ea6\u3092\u7528\u3044\u307e\u3059\u3002<\/p>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">$$<br \/>\n\\begin{aligned}<br \/>\n\\Lambda_{\\mathrm{av}}(S) &amp;=\\frac{1}{L} \\sum_{l=1}^{L} \\log Q\\left(\\mathbf{s}^{(l)}\\right) \\\\<br \/>\n&amp;=-\\beta \\frac{1}{L} \\sum_{l=1}^{L} E\\left(\\mathbf{s}^{(l)}\\right)-\\log Z(\\beta)<br \/>\n\\end{aligned}<br \/>\n$$<\/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[latex]Q\\left(s^{(l)}\\right)[\/latex]\u306f\u3001\u30ab\u30ce\u30cb\u30ab\u30eb\u5206\u5e03\u3067\u3059\u3002<\/p>\n<p>$$<br \/>\nQ\\left(s^{(l)}\\right)=\\frac{1}{Z} \\exp (-\\beta E(s^{(l)})), \\quad Z=\\sum_{s^{(l)}} \\exp (-\\beta E(s^{(l)}))<br \/>\n$$<\/p>\n<p>\u307e\u305f\u3001\u672c\u5b9f\u9a13\u3067\u306f\u5c40\u6240\u78c1\u5834[latex]h_i=0[\/latex]\u3068\u3059\u308b\u305f\u3081\u3001\u30a4\u30b8\u30f3\u30b0\u6a21\u578b\u306e\u30a8\u30cd\u30eb\u30ae\u30fc[latex]E(s^{(l)})[\/latex]\u306f\u3001<\/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\">$$<br \/>\nE(s^{(l)})=-\\sum_{i, j} J_{i j} s_{i}^{(l)} s_{j}^{(l)}<br \/>\n$$\u3068\u306a\u308a\u307e\u3059\u3002\u3053\u3053\u3067\u3001[latex]s^{(l)}_{i}\u2208 \\lbrace -1, +1 \\rbrace[\/latex]\u306f\u3001\u30a4\u30b8\u30f3\u30b0\u5909\u6570\u3067\u3059\u3002<\/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%AD%A6%E7%BF%92%E6%96%B9%E6%B3%95\"><\/span>\u5b66\u7fd2\u65b9\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<p>\u672c\u5b9f\u9a13\u3067\u306f\u3001\u76f8\u4e92\u4f5c\u7528[latex]J[\/latex]\u3092\u6b21\u306e\u52fe\u914d\u6cd5\u3092\u7528\u3044\u3066\u5b66\u7fd2\u3055\u305b\u3066\u3044\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\">$$<br \/>\nJ_{i j}(t+1)=J_{i j}(t)+\\eta \\frac{\\partial S}{\\partial J_{i j}}<br \/>\n$$$$<br \/>\n\\frac{1}{\\beta} \\frac{\\partial S}{\\partial J_{i j}}=\\left\\langle s_{i} s_{j}\\right\\rangle_{\\rho _\\mathcal{D}}-\\left\\langle s_{i} s_{j}\\right\\rangle_{\\rho}<br \/>\n$$<\/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[latex]S[\/latex]\u306f\u91cf\u5b50\u76f8\u5bfe\u30a8\u30f3\u30c8\u30ed\u30d4\u30fc\u3067\u3059\u3002<\/p>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">$$<br \/>\nS\\left(\\rho_{{D}} \\| \\rho\\right)=\\operatorname{Tr} \\rho_{{D}} \\ln \\rho_{{D}}-\\operatorname{Tr} \\rho_{{D}} \\ln \\rho<br \/>\n$$<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">\n<p>\u307e\u305f\u3001\u30d1\u30e9\u30e1\u30fc\u30bf\u306e\u8aac\u660e\u306f\u6b21\u306e\u901a\u308a\u3067\u3059\u3002<\/p>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">\n<table>\n<thead>\n<tr>\n<th style=\"text-align: center;\">\u3000\u30d1\u30e9\u30e1\u30fc\u30bf<\/th>\n<th style=\"text-align: center;\">\u8aac\u660e<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td style=\"text-align: center;\">[latex]t[\/latex]<\/td>\n<td style=\"text-align: center;\">\u5b66\u7fd2\u56de\u6570<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: center;\">[latex]\\eta[\/latex]<\/td>\n<td style=\"text-align: center;\">\u5b66\u7fd2\u7387<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: center;\">[latex]\\beta[\/latex]<\/td>\n<td style=\"text-align: center;\">\u9006\u6e29\u5ea6<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: center;\">[latex]\\rho_D[\/latex]<\/td>\n<td style=\"text-align: center;\">\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306e\u5206\u5e03\u3092\u8868\u3059\u3001<br \/>\n\u5bfe\u89d2\u7dda\u4e0a\u306e\u5bc6\u5ea6\u884c\u5217<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: center;\">[latex]\\rho[\/latex]<\/td>\n<td style=\"text-align: center;\">\u30b5\u30f3\u30d7\u30eb\u306e\u5206\u5e03\u3092\u8868\u3059\u3001<br \/>\n\u5bfe\u89d2\u7dda\u4e0a\u306e\u5bc6\u5ea6\u884c\u5217<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">\n<h2><span class=\"ez-toc-section\" id=\"%E5%AE%9F%E9%A8%93\"><\/span>\u5b9f\u9a13<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">\n<h2><span class=\"ez-toc-section\" id=\"%E5%85%A8%E4%BD%93%E5%83%8F\"><\/span>\u5168\u4f53\u50cf<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">\n<p>\u5b9f\u9a13\u306e\u5168\u4f53\u50cf\u3092\u793a\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<div id=\"attachment_3010\" style=\"width: 675px\" class=\"wp-caption aligncenter\"><img loading=\"lazy\" decoding=\"async\" aria-describedby=\"caption-attachment-3010\" class=\"size-large wp-image-3010\" src=\"\/T-Wave\/wp-content\/uploads\/2022\/03\/e4c50f25246c07dd29b683ee648eb458-1024x370.png\" alt=\"\" width=\"665\" height=\"240\" \/><p id=\"caption-attachment-3010\" class=\"wp-caption-text\">\u56f31:\u5b9f\u9a13\u306e\u5168\u4f53\u50cf<\/p><\/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>\u307e\u305a\u6700\u521d\u306b\u3001\u30ac\u30a6\u30b9\u5206\u5e03\u306b\u5f93\u3046\u30b9\u30d4\u30f3\u914d\u4f4d(\u30c7\u30fc\u30bf)\u3092\u6e96\u5099\u3057\u307e\u3059\u3002\u6b21\u306b\u3001\u30ae\u30d6\u30b9\u30fb\u30dc\u30eb\u30c4\u30de\u30f3\u5206\u5e03\u306b\u5f93\u3046\u30b9\u30d4\u30f3\u914d\u4f4d(\u30b5\u30f3\u30d7\u30eb)\u3092\u4f5c\u6210\u3057\u307e\u3059\u3002\u3053\u306e\u30b5\u30f3\u30d7\u30eb\u304c\u3001\u30c7\u30fc\u30bf\u306b\u8fd1\u3065\u304f\u3088\u3046\u306b\u52fe\u914d\u6cd5\u3092\u7528\u3044\u3066\u76f8\u4e92\u4f5c\u7528[latex]J[\/latex]\u3092\u66f4\u65b0\u3057\u3066\u3044\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<h3><span class=\"ez-toc-section\" id=\"%E3%83%A9%E3%82%A4%E3%83%96%E3%83%A9%E3%83%AA%E3%81%AE%E3%82%A4%E3%83%B3%E3%82%B9%E3%83%88%E3%83%BC%E3%83%AB\"><\/span>\u30e9\u30a4\u30d6\u30e9\u30ea\u306e\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb<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<p>\u3053\u3053\u3067\u3001\u5fc5\u8981\u306a\u30e9\u30a4\u30d6\u30e9\u30ea\u3092\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3057\u307e\u3059\u3002<\/p>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing code_cell rendered\">\n<div class=\"input\">\n<div class=\"inner_cell\">\n<div class=\"input_area\">\n<div class=\" highlight hl-ipython3\">\n<pre><span class=\"o\">!<\/span>pip install numpy\n<span class=\"o\">!<\/span>pip install matplotlib\n<span class=\"o\">!<\/span>pip install scikit-learn\n<span class=\"o\">!<\/span>pip install dwave-ocean-sdk\n<span class=\"o\">!<\/span>pip install openjij\n<span class=\"o\">!<\/span>pip install tqdm\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-ipython3\">\n<pre><span class=\"kn\">import<\/span> <span class=\"nn\">random<\/span>\n<span class=\"kn\">import<\/span> <span class=\"nn\">itertools<\/span>\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\">matplotlib.pyplot<\/span> <span class=\"k\">as<\/span> <span class=\"nn\">plt<\/span>\n<span class=\"kn\">import<\/span> <span class=\"nn\">openjij<\/span> <span class=\"k\">as<\/span> <span class=\"nn\">oj<\/span>\n<span class=\"kn\">from<\/span> <span class=\"nn\">tqdm<\/span> <span class=\"kn\">import<\/span> <span class=\"n\">tqdm<\/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=\"%E3%82%AC%E3%82%A6%E3%82%B9%E5%88%86%E5%B8%83%E3%81%8B%E3%82%89%E7%9B%B8%E4%BA%92%E4%BD%9C%E7%94%A8%E3%81%AE%E4%BD%9C%E6%88%90\"><\/span>\u30ac\u30a6\u30b9\u5206\u5e03\u304b\u3089\u76f8\u4e92\u4f5c\u7528\u306e\u4f5c\u6210<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<p>\u307e\u305a\u3001\u30ac\u30a6\u30b9\u5206\u5e03\u304b\u3089\u76f8\u4e92\u4f5c\u7528[latex]J[\/latex]\uff08\u30a4\u30f3\u30b9\u30bf\u30f3\u30b9\uff09\u3092\uff11\u3064\u751f\u6210\u3057\u307e\u3059\u3002\u3053\u3053\u3067\u3001\u30d1\u30e9\u30e1\u30fc\u30bf\u306f\u4e0a\u8a18\u3057\u305f\u901a\u308a\u3001<\/p>\n<table>\n<thead>\n<tr>\n<th style=\"text-align: center;\">\u30d1\u30e9\u30e1\u30fc\u30bf<\/th>\n<th style=\"text-align: center;\">\u00a0 \u5024<\/th>\n<th style=\"text-align: center;\">\u8aac\u660e<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td style=\"text-align: center;\">[latex]N[\/latex]<\/td>\n<td style=\"text-align: center;\">15<\/td>\n<td style=\"text-align: center;\">\u30b9\u30d4\u30f3\u6570<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: center;\">[latex]h[\/latex]<\/td>\n<td style=\"text-align: center;\">0<\/td>\n<td style=\"text-align: center;\">\u5c40\u6240\u78c1\u5834<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: center;\">[latex]\\beta[\/latex]<\/td>\n<td style=\"text-align: center;\">1<\/td>\n<td style=\"text-align: center;\">\u9006\u6e29\u5ea6<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: center;\">[latex]\\mu[\/latex]<\/td>\n<td style=\"text-align: center;\">0<\/td>\n<td style=\"text-align: center;\">\u5e73\u5747<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: center;\">[latex]\\sigma[\/latex]<\/td>\n<td style=\"text-align: center;\">[latex]2\/\\sqrt{\ud835\udc41}[\/latex]<\/td>\n<td style=\"text-align: center;\">\u6a19\u6e96\u504f\u5dee<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>\u3068\u3057\u3066\u3044\u307e\u3059\u3002<\/p>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing code_cell rendered\">\n<div class=\"input\">\n<div class=\"inner_cell\">\n<div class=\"input_area\">\n<div class=\" highlight hl-ipython3\">\n<pre><span class=\"k\">def<\/span> <span class=\"nf\">J_generator<\/span><span class=\"p\">(<\/span><span class=\"n\">N<\/span><span class=\"p\">,<\/span> <span class=\"n\">mu<\/span><span class=\"p\">,<\/span> <span class=\"n\">sigma<\/span><span class=\"p\">):<\/span>\n    <span class=\"sd\">\"\"\"\u78ba\u7387\u5206\u5e03\u304b\u3089\u76f8\u4e92\u4f5c\u7528\u3092\u4f5c\u6210\"\"\"<\/span>\n    <span class=\"n\">J<\/span> <span class=\"o\">=<\/span> <span class=\"p\">{<\/span>\n        <span class=\"p\">(<\/span><span class=\"n\">i<\/span><span class=\"p\">,<\/span> <span class=\"n\">j<\/span><span class=\"p\">):<\/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\">mu<\/span><span class=\"p\">,<\/span> <span class=\"n\">scale<\/span><span class=\"o\">=<\/span><span class=\"n\">sigma<\/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=\"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=\"p\">}<\/span>\n    <span class=\"k\">return<\/span> <span class=\"n\">J<\/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-ipython3\">\n<pre><span class=\"n\">ans_J<\/span> <span class=\"o\">=<\/span> <span class=\"n\">J_generator<\/span><span class=\"p\">(<\/span><span class=\"n\">N<\/span><span class=\"o\">=<\/span><span class=\"mi\">15<\/span><span class=\"p\">,<\/span> <span class=\"n\">mu<\/span><span class=\"o\">=<\/span><span class=\"mi\">0<\/span><span class=\"p\">,<\/span> <span class=\"n\">sigma<\/span><span class=\"o\">=<\/span><span class=\"mi\">2<\/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=\"mi\">15<\/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<h3><span class=\"ez-toc-section\" id=\"%E7%9B%B8%E4%BA%92%E4%BD%9C%E7%94%A8%E3%81%8B%E3%82%89%E3%82%B9%E3%83%94%E3%83%B3%E9%85%8D%E4%BD%8D%E3%81%AE%E4%BD%9C%E6%88%90\"><\/span>\u76f8\u4e92\u4f5c\u7528\u304b\u3089\u30b9\u30d4\u30f3\u914d\u4f4d\u306e\u4f5c\u6210<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<p>\u6b21\u306b\u3001\u4f5c\u6210\u3057\u305f\u76f8\u4e92\u4f5c\u7528[latex]J[\/latex]\u3092\u7528\u3044\u3066\u3001SK\u6a21\u578b\u306e\u30b9\u30d4\u30f3\u914d\u4f4d\u3092150\u500b\u30b5\u30f3\u30d7\u30ea\u30f3\u30b0\u3057\u307e\u3059\u3002<\/p>\n<p>\u3053\u3053\u3067\u306f\u3001\u30b5\u30f3\u30d7\u30ea\u30f3\u30b0\u306bMCMC(\u30e1\u30c8\u30ed\u30dd\u30ea\u30b9\u6cd5)\u3092\u5229\u7528\u3057\u307e\u3059\u3002\u624b\u9806\u306f\u6b21\u306e\u901a\u308a\u3067\u3059\u3002<\/p>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">\n<blockquote>\n<ol>\n<li>\u5168\u30b5\u30a4\u30c8\u304b\u3089\u3042\u308b\uff11\u30b5\u30a4\u30c8\u3092\u4e71\u6570\u306b\u3088\u308a\u9078\u629e\u3057\u3001 \u305d\u306e\u30b5\u30a4\u30c8\u306e\u30b9\u30d4\u30f3\u306e\u5411\u304d\u3092\u53cd\u8ee2\u3055\u305b\u305f\u72b6\u614b\u3092\u8a66\u884c\u72b6\u614b\u3068\u3059\u308b<\/li>\n<li>\u8a66\u884c\u72b6\u614b\u306b\u304a\u3051\u308b\u30a8\u30cd\u30eb\u30ae\u30fc\u3068\u5143\u306e\u72b6\u614b\u306e\u30a8\u30cd\u30eb\u30ae\u30fc\u306e\u5dee[latex]\\Delta E[\/latex]\u3092\u6c42\u3081\u308b\u3002<\/li>\n<li>\u4ee5\u4e0b\u306e\u5224\u5b9a\u306b\u3088\u308a\u3001\u8a66\u884c\u72b6\u614b\u3092\u65b0\u305f\u306a\u72b6\u614b\u3068\u3059\u308b\u304b\u3001\u3082\u3068\u306e\u72b6\u614b\u3092\u7dad\u6301\u3059\u308b\u304b\u3092\u6c7a\u3081\u308b\u3002<\/li>\n<\/ol>\n<ul>\n<li>[latex]\\Delta E &lt; 0[\/latex]\u306e\u5834\u5408\u306b\u306f\u3001\u8a66\u884c\u72b6\u614b\u3092\u65b0\u305f\u306a\u72b6\u614b\u3068\u3059\u308b\u3002<\/li>\n<li>\u4e00\u65b9\u3001[latex]\\Delta E &gt; 0[\/latex]\u306e\u5834\u5408\u306b\u306f\u3001 \u4e71\u6570[latex]a[\/latex] \u3092 [latex]0\u2264a\u22641[\/latex] \u306e\u7bc4\u56f2\u3067\u751f\u6210\u3059\u308b\u3002 [latex]a&lt;\\exp(-\\beta \\Delta E)[\/latex] \u306e\u5834\u5408\u306b\u306f\u3001 \u8a66\u884c\u72b6\u614b\u3092\u65b0\u305f\u306a\u72b6\u614b\u3068\u3059\u308b\u3002\u305d\u3046\u3067\u306a\u3044\u5834\u5408\u306b\u306f\u3082\u3068\u306e\u72b6\u614b\u3092\u7dad\u6301\u3059\u308b\u3002<\/li>\n<\/ul>\n<ol>\n<li>1~3\u3092\u7e70\u308a\u8fd4\u3059\u3002<\/li>\n<\/ol>\n<p>\u5f15\u7528\u5143\uff1a<a href=\"http:\/\/www.cmpt.phys.tohoku.ac.jp\/~izumida\/Ising\/IsingMCMP.html\">http:\/\/www.cmpt.phys.tohoku.ac.jp\/~izumida\/Ising\/IsingMCMP.html<\/a><\/p><\/blockquote>\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-ipython3\">\n<pre><span class=\"k\">def<\/span> <span class=\"nf\">cal_energy<\/span><span class=\"p\">(<\/span><span class=\"n\">N<\/span><span class=\"p\">,<\/span> <span class=\"n\">J<\/span><span class=\"p\">,<\/span> <span class=\"n\">spin<\/span><span class=\"p\">):<\/span>\n    <span class=\"n\">energy<\/span> <span class=\"o\">=<\/span> <span class=\"n\">np<\/span><span class=\"o\">.<\/span><span class=\"n\">sum<\/span><span class=\"p\">(<\/span>\n        <span class=\"p\">[<\/span><span class=\"o\">-<\/span><span class=\"n\">J<\/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\">spin<\/span><span class=\"p\">[<\/span><span class=\"n\">i<\/span><span class=\"p\">]<\/span> <span class=\"o\">*<\/span> <span class=\"n\">spin<\/span><span class=\"p\">[<\/span><span class=\"n\">j<\/span><span class=\"p\">]<\/span> <span class=\"k\">for<\/span> <span class=\"n\">i<\/span> <span class=\"ow\">in<\/span> <span class=\"nb\">range<\/span><span class=\"p\">(<\/span><span class=\"n\">N<\/span><span class=\"p\">)<\/span> <span class=\"k\">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=\"p\">)<\/span>\n    <span class=\"k\">return<\/span> <span class=\"n\">energy<\/span>\n\n\n<span class=\"k\">def<\/span> <span class=\"nf\">MCMC<\/span><span class=\"p\">(<\/span><span class=\"n\">N<\/span><span class=\"p\">,<\/span> <span class=\"n\">J<\/span><span class=\"p\">,<\/span> <span class=\"nb\">iter<\/span><span class=\"p\">,<\/span> <span class=\"n\">beta<\/span><span class=\"o\">=<\/span><span class=\"mi\">1<\/span><span class=\"p\">):<\/span>\n    <span class=\"c1\"># \u30b9\u30d4\u30f3\u914d\u4f4d\u3092\u30e9\u30f3\u30c0\u30e0\u306b\u751f\u6210<\/span>\n    <span class=\"n\">minS<\/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\">choice<\/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> <span class=\"n\">size<\/span><span class=\"o\">=<\/span><span class=\"n\">N<\/span><span class=\"p\">)<\/span>\n    <span class=\"c1\"># \u521d\u671f\u72b6\u614b\u306e\u30a8\u30cd\u30eb\u30ae\u30fc<\/span>\n    <span class=\"n\">minE<\/span> <span class=\"o\">=<\/span> <span class=\"n\">cal_energy<\/span><span class=\"p\">(<\/span><span class=\"n\">N<\/span><span class=\"o\">=<\/span><span class=\"n\">N<\/span><span class=\"p\">,<\/span> <span class=\"n\">J<\/span><span class=\"o\">=<\/span><span class=\"n\">J<\/span><span class=\"p\">,<\/span> <span class=\"n\">spin<\/span><span class=\"o\">=<\/span><span class=\"n\">minS<\/span><span class=\"p\">)<\/span>\n\n    <span class=\"k\">for<\/span> <span class=\"n\">n<\/span> <span class=\"ow\">in<\/span> <span class=\"nb\">range<\/span><span class=\"p\">(<\/span><span class=\"nb\">iter<\/span><span class=\"p\">):<\/span>\n        <span class=\"c1\"># \u53cd\u8ee2\u3059\u308b\u30b9\u30d4\u30f3\u3092\u30e9\u30f3\u30c0\u30e0\u306b\u6c7a\u5b9a<\/span>\n        <span class=\"n\">i<\/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\">randint<\/span><span class=\"p\">(<\/span><span class=\"mi\">0<\/span><span class=\"p\">,<\/span> <span class=\"n\">N<\/span><span class=\"p\">)<\/span>\n\n        <span class=\"c1\"># \uff11\u3064\u306e\u30b9\u30d4\u30f3\u3092\u53cd\u8ee2<\/span>\n        <span class=\"n\">flipS<\/span> <span class=\"o\">=<\/span> <span class=\"n\">minS<\/span><span class=\"o\">.<\/span><span class=\"n\">copy<\/span><span class=\"p\">()<\/span>\n        <span class=\"n\">flipS<\/span><span class=\"p\">[<\/span><span class=\"n\">i<\/span><span class=\"p\">]<\/span> <span class=\"o\">*=<\/span> <span class=\"o\">-<\/span><span class=\"mi\">1<\/span>\n        <span class=\"n\">flipE<\/span> <span class=\"o\">=<\/span> <span class=\"n\">cal_energy<\/span><span class=\"p\">(<\/span><span class=\"n\">N<\/span><span class=\"o\">=<\/span><span class=\"n\">N<\/span><span class=\"p\">,<\/span> <span class=\"n\">J<\/span><span class=\"o\">=<\/span><span class=\"n\">J<\/span><span class=\"p\">,<\/span> <span class=\"n\">spin<\/span><span class=\"o\">=<\/span><span class=\"n\">flipS<\/span><span class=\"p\">)<\/span>\n\n        <span class=\"c1\"># \u53cd\u8ee2\u524d\u3068\u5f8c\u306e\u30a8\u30cd\u30eb\u30ae\u30fc\u306e\u5dee<\/span>\n        <span class=\"n\">deltaE<\/span> <span class=\"o\">=<\/span> <span class=\"n\">flipE<\/span> <span class=\"o\">-<\/span> <span class=\"n\">minE<\/span>\n        <span class=\"k\">if<\/span> <span class=\"n\">deltaE<\/span> <span class=\"o\">&lt;<\/span> <span class=\"mi\">0<\/span><span class=\"p\">:<\/span>\n            <span class=\"n\">minE<\/span> <span class=\"o\">=<\/span> <span class=\"n\">flipE<\/span>\n            <span class=\"n\">minS<\/span> <span class=\"o\">=<\/span> <span class=\"n\">flipS<\/span><span class=\"o\">.<\/span><span class=\"n\">copy<\/span><span class=\"p\">()<\/span>\n        <span class=\"k\">else<\/span><span class=\"p\">:<\/span>\n            <span class=\"n\">a<\/span> <span class=\"o\">=<\/span> <span class=\"n\">random<\/span><span class=\"o\">.<\/span><span class=\"n\">random<\/span><span class=\"p\">()<\/span>\n            <span class=\"n\">p<\/span> <span class=\"o\">=<\/span> <span class=\"n\">np<\/span><span class=\"o\">.<\/span><span class=\"n\">exp<\/span><span class=\"p\">(<\/span><span class=\"o\">-<\/span><span class=\"n\">beta<\/span> <span class=\"o\">*<\/span> <span class=\"n\">deltaE<\/span><span class=\"p\">)<\/span>\n            <span class=\"k\">if<\/span> <span class=\"n\">a<\/span> <span class=\"o\">&lt;<\/span> <span class=\"n\">p<\/span><span class=\"p\">:<\/span>\n                <span class=\"n\">minE<\/span> <span class=\"o\">=<\/span> <span class=\"n\">flipE<\/span>\n                <span class=\"n\">minS<\/span> <span class=\"o\">=<\/span> <span class=\"n\">flipS<\/span><span class=\"o\">.<\/span><span class=\"n\">copy<\/span><span class=\"p\">()<\/span>\n            <span class=\"k\">else<\/span><span class=\"p\">:<\/span>\n                <span class=\"k\">pass<\/span>\n\n    <span class=\"k\">return<\/span> <span class=\"n\">minS<\/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>\u6e96\u5099\u304c\u7d42\u308f\u308a\u307e\u3057\u305f\u3002<\/p>\n<p>150\u500b\u306e\u30b9\u30d4\u30f3\u914d\u4f4d\u3092\u4f5c\u6210\u3057\u307e\u3057\u3087\u3046\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-ipython3\">\n<pre><span class=\"k\">def<\/span> <span class=\"nf\">MCMC_sampling<\/span><span class=\"p\">(<\/span><span class=\"n\">num_instances<\/span><span class=\"p\">):<\/span>\n    <span class=\"n\">sample_lists<\/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\">num_instances<\/span><span class=\"p\">):<\/span>\n        <span class=\"n\">sample<\/span> <span class=\"o\">=<\/span> <span class=\"n\">MCMC<\/span><span class=\"p\">(<\/span><span class=\"n\">N<\/span><span class=\"o\">=<\/span><span class=\"mi\">15<\/span><span class=\"p\">,<\/span> <span class=\"n\">J<\/span><span class=\"o\">=<\/span><span class=\"n\">ans_J<\/span><span class=\"p\">,<\/span> <span class=\"nb\">iter<\/span><span class=\"o\">=<\/span><span class=\"mi\">100<\/span><span class=\"p\">)<\/span>\n        <span class=\"n\">sample_lists<\/span><span class=\"o\">.<\/span><span class=\"n\">append<\/span><span class=\"p\">(<\/span><span class=\"n\">sample<\/span><span class=\"p\">)<\/span>\n    <span class=\"k\">return<\/span> <span class=\"n\">sample_lists<\/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-ipython3\">\n<pre><span class=\"n\">data_lists<\/span> <span class=\"o\">=<\/span> <span class=\"n\">MCMC_sampling<\/span><span class=\"p\">(<\/span><span class=\"n\">num_instances<\/span><span class=\"o\">=<\/span><span class=\"mi\">150<\/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\u308c\u3067\u3001\u76f8\u4e92\u4f5c\u7528[latex]J[\/latex]\u304b\u3089\u30b9\u30d4\u30f3\u914d\u4f4d\u3092\u4f5c\u6210\u3067\u304d\u307e\u3057\u305f\u3002<\/p>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">\n<h3><span class=\"ez-toc-section\" id=\"%E6%AD%A3%E8%A7%A3%E3%81%A8%E3%81%AA%E3%82%8B%E5%B9%B3%E5%9D%87%E5%AF%BE%E6%95%B0%E5%B0%A4%E5%BA%A6%E3%81%AE%E8%A8%88%E7%AE%97\"><\/span>\u6b63\u89e3\u3068\u306a\u308b\u5e73\u5747\u5bfe\u6570\u5c24\u5ea6\u306e\u8a08\u7b97<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<p>\u3053\u3053\u3067\u306f\u3001\u4f5c\u6210\u3057\u305f\u30b9\u30d4\u30f3\u914d\u4f4d\u306b\u3088\u308b\u5e73\u5747\u5bfe\u6570\u5c24\u5ea6\u3092\u8a08\u7b97\u3057\u307e\u3059\u3002\u5e73\u5747\u5bfe\u6570\u5c24\u5ea6\u306f\u6b21\u3067\u8868\u305b\u307e\u3057\u305f\u3002<\/p>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">$$<br \/>\n\\begin{aligned}<br \/>\n\\Lambda_{\\mathrm{av}}(S) &amp;=\\frac{1}{L} \\sum_{l=1}^{L} \\log Q\\left(\\mathbf{s}^{(l}\\right) \\\\<br \/>\n&amp;=-\\beta \\frac{1}{L} \\sum_{l=1}^{L} E\\left(\\mathbf{s}^{(l)}\\right)-\\log Z(\\beta)<br \/>\n\\end{aligned}<br \/>\n$$<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">\n<p>\u307e\u305a\u3001\u5e73\u5747\u5bfe\u6570\u5c24\u5ea6\u306e\u7b2c\uff11\u9805\u90e8\u5206\u3092\u6c42\u3081\u307e\u3059\u3002<\/p>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing code_cell rendered\">\n<div class=\"input\">\n<div class=\"inner_cell\">\n<div class=\"input_area\">\n<div class=\" highlight hl-ipython3\">\n<pre><span class=\"k\">def<\/span> <span class=\"nf\">cal_first<\/span><span class=\"p\">(<\/span><span class=\"n\">beta<\/span><span class=\"p\">,<\/span> <span class=\"n\">J<\/span><span class=\"p\">,<\/span> <span class=\"n\">data_lists<\/span><span class=\"p\">):<\/span>\n    <span class=\"n\">energy_ave<\/span> <span class=\"o\">=<\/span> <span class=\"n\">np<\/span><span class=\"o\">.<\/span><span class=\"n\">average<\/span><span class=\"p\">(<\/span>\n        <span class=\"p\">[<\/span><span class=\"n\">cal_energy<\/span><span class=\"p\">(<\/span><span class=\"n\">N<\/span><span class=\"o\">=<\/span><span class=\"nb\">len<\/span><span class=\"p\">(<\/span><span class=\"n\">data_list<\/span><span class=\"p\">),<\/span> <span class=\"n\">J<\/span><span class=\"o\">=<\/span><span class=\"n\">J<\/span><span class=\"p\">,<\/span> <span class=\"n\">spin<\/span><span class=\"o\">=<\/span><span class=\"n\">data_list<\/span><span class=\"p\">)<\/span> <span class=\"k\">for<\/span> <span class=\"n\">data_list<\/span> <span class=\"ow\">in<\/span> <span class=\"n\">data_lists<\/span><span class=\"p\">]<\/span>\n    <span class=\"p\">)<\/span>\n    <span class=\"n\">first<\/span> <span class=\"o\">=<\/span> <span class=\"o\">-<\/span><span class=\"n\">beta<\/span> <span class=\"o\">*<\/span> <span class=\"n\">energy_ave<\/span>\n    <span class=\"k\">return<\/span> <span class=\"n\">first<\/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-ipython3\">\n<pre><span class=\"n\">data_first<\/span> <span class=\"o\">=<\/span> <span class=\"n\">cal_first<\/span><span class=\"p\">(<\/span><span class=\"n\">beta<\/span><span class=\"o\">=<\/span><span class=\"mi\">1<\/span><span class=\"p\">,<\/span> <span class=\"n\">J<\/span><span class=\"o\">=<\/span><span class=\"n\">ans_J<\/span><span class=\"p\">,<\/span> <span class=\"n\">data_lists<\/span><span class=\"o\">=<\/span><span class=\"n\">data_lists<\/span><span class=\"p\">)<\/span>\n<span class=\"nb\">print<\/span><span class=\"p\">(<\/span><span class=\"n\">data_first<\/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>16.03394926364786\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>\u7b2c\uff11\u9805\u304c\u8a08\u7b97\u3067\u304d\u307e\u3057\u305f\u3002\u7d9a\u3044\u3066\u3001\u5e73\u5747\u5bfe\u6570\u5c24\u5ea6\u306e\u7b2c\uff12\u9805\u3092\u6c42\u3081\u307e\u3059\u3002<\/p>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing code_cell rendered\">\n<div class=\"input\">\n<div class=\"inner_cell\">\n<div class=\"input_area\">\n<div class=\" highlight hl-ipython3\">\n<pre><span class=\"k\">def<\/span> <span class=\"nf\">cal_second<\/span><span class=\"p\">(<\/span><span class=\"n\">beta<\/span><span class=\"p\">,<\/span> <span class=\"n\">N<\/span><span class=\"p\">,<\/span> <span class=\"n\">J<\/span><span class=\"p\">):<\/span>\n    <span class=\"n\">state_sum<\/span> <span class=\"o\">=<\/span> <span class=\"n\">np<\/span><span class=\"o\">.<\/span><span class=\"n\">sum<\/span><span class=\"p\">(<\/span>\n        <span class=\"p\">[<\/span>\n            <span class=\"n\">np<\/span><span class=\"o\">.<\/span><span class=\"n\">exp<\/span><span class=\"p\">(<\/span><span class=\"o\">-<\/span><span class=\"n\">beta<\/span> <span class=\"o\">*<\/span> <span class=\"n\">cal_energy<\/span><span class=\"p\">(<\/span><span class=\"n\">N<\/span><span class=\"o\">=<\/span><span class=\"n\">N<\/span><span class=\"p\">,<\/span> <span class=\"n\">J<\/span><span class=\"o\">=<\/span><span class=\"n\">J<\/span><span class=\"p\">,<\/span> <span class=\"n\">spin<\/span><span class=\"o\">=<\/span><span class=\"n\">z<\/span><span class=\"p\">))<\/span>\n            <span class=\"k\">for<\/span> <span class=\"n\">z<\/span> <span class=\"ow\">in<\/span> <span class=\"n\">itertools<\/span><span class=\"o\">.<\/span><span class=\"n\">product<\/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> <span class=\"n\">repeat<\/span><span class=\"o\">=<\/span><span class=\"n\">N<\/span><span class=\"p\">)<\/span>\n        <span class=\"p\">]<\/span>\n    <span class=\"p\">)<\/span>\n    <span class=\"n\">second<\/span> <span class=\"o\">=<\/span> <span class=\"n\">np<\/span><span class=\"o\">.<\/span><span class=\"n\">log<\/span><span class=\"p\">(<\/span><span class=\"n\">state_sum<\/span><span class=\"p\">)<\/span>\n    <span class=\"k\">return<\/span> <span class=\"n\">second<\/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-ipython3\">\n<pre><span class=\"n\">data_second<\/span> <span class=\"o\">=<\/span> <span class=\"n\">cal_second<\/span><span class=\"p\">(<\/span><span class=\"n\">beta<\/span><span class=\"o\">=<\/span><span class=\"mi\">1<\/span><span class=\"p\">,<\/span> <span class=\"n\">N<\/span><span class=\"o\">=<\/span><span class=\"mi\">15<\/span><span class=\"p\">,<\/span> <span class=\"n\">J<\/span><span class=\"o\">=<\/span><span class=\"n\">ans_J<\/span><span class=\"p\">)<\/span>\n<span class=\"nb\">print<\/span><span class=\"p\">(<\/span><span class=\"n\">data_second<\/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>20.954922044868276\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>\uff12\u3064\u3092\u5408\u8a08\u3057\u3066\u5e73\u5747\u5bfe\u6570\u5c24\u5ea6\u3092\u6c42\u3081\u307e\u3057\u3087\u3046\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-ipython3\">\n<pre><span class=\"c1\"># \u6559\u5e2b\u30c7\u30fc\u30bf\u306e\u5e73\u5747\u5bfe\u6570\u5c24\u5ea6<\/span>\n<span class=\"n\">data_LH<\/span> <span class=\"o\">=<\/span> <span class=\"n\">data_first<\/span> <span class=\"o\">-<\/span> <span class=\"n\">data_second<\/span>\n<span class=\"nb\">print<\/span><span class=\"p\">(<\/span><span class=\"n\">data_LH<\/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>-4.920972781220417\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\u308c\u3067\u3001\u6b63\u89e3\u3068\u306a\u308b\u5e73\u5747\u5bfe\u6570\u5c24\u5ea6\u3092\u6c42\u3081\u308b\u3053\u3068\u304c\u51fa\u6765\u307e\u3057\u305f\u3002<\/p>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">\n<h3><span class=\"ez-toc-section\" id=\"QA%E3%81%AB%E3%82%88%E3%82%8B%E5%AD%A6%E7%BF%92\"><\/span>QA\u306b\u3088\u308b\u5b66\u7fd2<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<p>\u307e\u305a\u521d\u3081\u306b\u3001QA\u306b\u3088\u308b\u5b66\u7fd2\u3092\u884c\u3044\u307e\u3059\u3002\u4f7f\u7528\u3059\u308b\u52fe\u914d\u6cd5\u3092\u3082\u3046\u4e00\u5ea6\u8a18\u8f09\u3057\u307e\u3059\u3002<\/p>\n<p>$$<br \/>\nJ_{i j}(t+1)=J_{i j}(t)+\\eta \\frac{\\partial S}{\\partial J_{i j}}<br \/>\n$$$$<br \/>\n\\frac{1}{\\beta} \\frac{\\partial S}{\\partial J_{i j}}=\\left\\langle s_{i} s_{j}\\right\\rangle_{\\rho _\\mathcal{D}}-\\left\\langle s_{i} s_{j}\\right\\rangle_{\\rho}<br \/>\n$$<\/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>\u3053\u3053\u3067\u3001\u671f\u5f85\u5024[latex]\\left\\langle{}\\right\\rangle_{\\rho}[\/latex]\u306f<\/p>\n<p>$$<br \/>\n\\left\\langle s_{i} s_{j}\\right\\rangle_{\\rho} = \\frac{1}{L} \\sum_{l=1}^{L} s_{i}^{(l)} s_{j}^{(l)}<br \/>\n$$<\/p>\n<p>\u306e\u3088\u3046\u306b\u3001D-Wave\u30de\u30b7\u30f3\u3092\u30b5\u30f3\u30d7\u30e9\u30fc\u3068\u3057\u3066\u7528\u3044\u308b\u3053\u3068\u3067\u8fd1\u4f3c\u7684\u306b\u6c42\u3081\u3089\u308c\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-ipython3\">\n<pre><span class=\"k\">def<\/span> <span class=\"nf\">minus_J<\/span><span class=\"p\">(<\/span><span class=\"n\">num_spin<\/span><span class=\"p\">,<\/span> <span class=\"n\">J<\/span><span class=\"p\">):<\/span>\n    <span class=\"sd\">\"\"\"\u30b3\u30b9\u30c8\u95a2\u6570\u306e\u76f8\u4e92\u4f5c\u7528\u306b\u30de\u30a4\u30ca\u30b9\u304c\u3064\u3044\u3066\u3044\u308b\u305f\u3081\u3001\u305d\u308c\u306b\u5f93\u3063\u3066\u5b9f\u88c5\u3057\u307e\u3059\"\"\"<\/span>\n    <span class=\"n\">m_J<\/span> <span class=\"o\">=<\/span> <span class=\"p\">{<\/span>\n        <span class=\"p\">(<\/span><span class=\"n\">i<\/span><span class=\"p\">,<\/span> <span class=\"n\">j<\/span><span class=\"p\">):<\/span> <span class=\"n\">J<\/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=\"o\">-<\/span><span class=\"mi\">1<\/span> <span class=\"k\">for<\/span> <span class=\"n\">i<\/span> <span class=\"ow\">in<\/span> <span class=\"nb\">range<\/span><span class=\"p\">(<\/span><span class=\"n\">num_spin<\/span><span class=\"p\">)<\/span> <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\">num_spin<\/span><span class=\"p\">)<\/span>\n    <span class=\"p\">}<\/span>\n    <span class=\"k\">return<\/span> <span class=\"n\">m_J<\/span>\n\n\n<span class=\"k\">def<\/span> <span class=\"nf\">sampling<\/span><span class=\"p\">(<\/span><span class=\"n\">method<\/span><span class=\"p\">,<\/span> <span class=\"n\">h<\/span><span class=\"p\">,<\/span> <span class=\"n\">J<\/span><span class=\"p\">,<\/span> <span class=\"n\">Nsample<\/span><span class=\"p\">,<\/span> <span class=\"n\">beta<\/span><span class=\"p\">):<\/span>\n    <span class=\"k\">if<\/span> <span class=\"n\">method<\/span> <span class=\"o\">==<\/span> <span class=\"s2\">\"QA\"<\/span><span class=\"p\">:<\/span>\n        <span class=\"n\">sampleset<\/span> <span class=\"o\">=<\/span> <span class=\"n\">sampler<\/span><span class=\"o\">.<\/span><span class=\"n\">sample_ising<\/span><span class=\"p\">(<\/span>\n            <span class=\"n\">h<\/span><span class=\"o\">=<\/span><span class=\"n\">h<\/span><span class=\"p\">,<\/span>\n            <span class=\"n\">J<\/span><span class=\"o\">=<\/span><span class=\"n\">J<\/span><span class=\"p\">,<\/span>\n            <span class=\"n\">num_reads<\/span><span class=\"o\">=<\/span><span class=\"n\">Nsample<\/span><span class=\"p\">,<\/span>\n            <span class=\"n\">beta<\/span><span class=\"o\">=<\/span><span class=\"n\">beta<\/span><span class=\"p\">,<\/span>\n            <span class=\"n\">answer_mode<\/span><span class=\"o\">=<\/span><span class=\"s2\">\"raw\"<\/span><span class=\"p\">,<\/span>\n            <span class=\"n\">postprocess<\/span><span class=\"o\">=<\/span><span class=\"s2\">\"sampling\"<\/span><span class=\"p\">,<\/span>\n        <span class=\"p\">)<\/span>\n    <span class=\"k\">if<\/span> <span class=\"n\">method<\/span> <span class=\"o\">==<\/span> <span class=\"s2\">\"SA\"<\/span><span class=\"p\">:<\/span>\n        <span class=\"n\">sampleset<\/span> <span class=\"o\">=<\/span> <span class=\"n\">sampler<\/span><span class=\"o\">.<\/span><span class=\"n\">sample_ising<\/span><span class=\"p\">(<\/span>\n            <span class=\"n\">h<\/span><span class=\"o\">=<\/span><span class=\"n\">h<\/span><span class=\"p\">,<\/span> <span class=\"n\">J<\/span><span class=\"o\">=<\/span><span class=\"n\">J<\/span><span class=\"p\">,<\/span> <span class=\"n\">num_reads<\/span><span class=\"o\">=<\/span><span class=\"n\">Nsample<\/span><span class=\"p\">,<\/span> <span class=\"n\">beta_min<\/span><span class=\"o\">=<\/span><span class=\"n\">beta<\/span><span class=\"p\">,<\/span> <span class=\"n\">beta_max<\/span><span class=\"o\">=<\/span><span class=\"n\">beta<\/span>\n        <span class=\"p\">)<\/span>\n    <span class=\"k\">return<\/span> <span class=\"n\">sampleset<\/span>\n\n\n<span class=\"k\">def<\/span> <span class=\"nf\">train_model<\/span><span class=\"p\">(<\/span><span class=\"n\">method<\/span><span class=\"p\">,<\/span> <span class=\"n\">Tall<\/span><span class=\"p\">,<\/span> <span class=\"n\">Nsample<\/span><span class=\"p\">,<\/span> <span class=\"n\">beta<\/span><span class=\"p\">,<\/span> <span class=\"n\">eta<\/span><span class=\"p\">,<\/span> <span class=\"n\">data_lists<\/span><span class=\"p\">,<\/span> <span class=\"n\">sampler<\/span><span class=\"p\">):<\/span>\n    <span class=\"n\">num_data<\/span> <span class=\"o\">=<\/span> <span class=\"nb\">len<\/span><span class=\"p\">(<\/span><span class=\"n\">data_lists<\/span><span class=\"p\">)<\/span>\n    <span class=\"n\">num_spin<\/span> <span class=\"o\">=<\/span> <span class=\"nb\">len<\/span><span class=\"p\">(<\/span><span class=\"n\">data_lists<\/span><span class=\"p\">[<\/span><span class=\"mi\">0<\/span><span class=\"p\">])<\/span>\n\n    <span class=\"c1\"># \u30d1\u30e9\u30e1\u30fc\u30bf\u306e\u521d\u671f\u5024\u30920\u3068\u3059\u308b<\/span>\n    <span class=\"n\">train_J<\/span> <span class=\"o\">=<\/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=\"mi\">0<\/span> <span class=\"k\">for<\/span> <span class=\"n\">i<\/span> <span class=\"ow\">in<\/span> <span class=\"nb\">range<\/span><span class=\"p\">(<\/span><span class=\"n\">num_spin<\/span><span class=\"p\">)<\/span> <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\">num_spin<\/span><span class=\"p\">)}<\/span>\n    <span class=\"n\">h<\/span> <span class=\"o\">=<\/span> <span class=\"p\">{<\/span><span class=\"n\">i<\/span><span class=\"p\">:<\/span> <span class=\"mi\">0<\/span> <span class=\"k\">for<\/span> <span class=\"n\">i<\/span> <span class=\"ow\">in<\/span> <span class=\"nb\">range<\/span><span class=\"p\">(<\/span><span class=\"n\">num_spin<\/span><span class=\"p\">)}<\/span>\n\n    <span class=\"c1\"># \u6559\u5e2b\u30c7\u30fc\u30bf\u306e\u7d4c\u9a13\u5e73\u5747<\/span>\n    <span class=\"n\">data_ave<\/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\">num_spin<\/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\">num_spin<\/span><span class=\"p\">):<\/span>\n            <span class=\"n\">data_ave<\/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\">np<\/span><span class=\"o\">.<\/span><span class=\"n\">average<\/span><span class=\"p\">(<\/span>\n                <span class=\"p\">[<\/span><span class=\"n\">data_lists<\/span><span class=\"p\">[<\/span><span class=\"n\">k<\/span><span class=\"p\">][<\/span><span class=\"n\">i<\/span><span class=\"p\">]<\/span> <span class=\"o\">*<\/span> <span class=\"n\">data_lists<\/span><span class=\"p\">[<\/span><span class=\"n\">k<\/span><span class=\"p\">][<\/span><span class=\"n\">j<\/span><span class=\"p\">]<\/span> <span class=\"k\">for<\/span> <span class=\"n\">k<\/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\">data_lists<\/span><span class=\"p\">))]<\/span>\n            <span class=\"p\">)<\/span>\n\n    <span class=\"n\">LH_hists<\/span> <span class=\"o\">=<\/span> <span class=\"p\">{}<\/span>\n    <span class=\"k\">for<\/span> <span class=\"n\">t<\/span> <span class=\"ow\">in<\/span> <span class=\"n\">tqdm<\/span><span class=\"p\">(<\/span><span class=\"n\">np<\/span><span class=\"o\">.<\/span><span class=\"n\">arange<\/span><span class=\"p\">(<\/span><span class=\"n\">Tall<\/span><span class=\"p\">)):<\/span>\n        <span class=\"c1\"># \u30b5\u30f3\u30d7\u30ea\u30f3\u30b0<\/span>\n        <span class=\"n\">m_J<\/span> <span class=\"o\">=<\/span> <span class=\"n\">minus_J<\/span><span class=\"p\">(<\/span><span class=\"n\">num_spin<\/span><span class=\"o\">=<\/span><span class=\"n\">num_spin<\/span><span class=\"p\">,<\/span> <span class=\"n\">J<\/span><span class=\"o\">=<\/span><span class=\"n\">train_J<\/span><span class=\"p\">)<\/span>\n        <span class=\"n\">sampleset<\/span> <span class=\"o\">=<\/span> <span class=\"n\">sampling<\/span><span class=\"p\">(<\/span><span class=\"n\">method<\/span><span class=\"p\">,<\/span> <span class=\"n\">h<\/span><span class=\"p\">,<\/span> <span class=\"n\">m_J<\/span><span class=\"p\">,<\/span> <span class=\"n\">Nsample<\/span><span class=\"p\">,<\/span> <span class=\"n\">beta<\/span><span class=\"p\">)<\/span>\n        <span class=\"n\">sample_lists<\/span> <span class=\"o\">=<\/span> <span class=\"n\">sampleset<\/span><span class=\"o\">.<\/span><span class=\"n\">record<\/span><span class=\"o\">.<\/span><span class=\"n\">sample<\/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\">num_spin<\/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\">num_spin<\/span><span class=\"p\">):<\/span>\n                <span class=\"n\">sample_ave<\/span> <span class=\"o\">=<\/span> <span class=\"n\">np<\/span><span class=\"o\">.<\/span><span class=\"n\">average<\/span><span class=\"p\">(<\/span>\n                    <span class=\"p\">[<\/span>\n                        <span class=\"n\">sample_lists<\/span><span class=\"p\">[<\/span><span class=\"n\">k<\/span><span class=\"p\">][<\/span><span class=\"n\">i<\/span><span class=\"p\">]<\/span> <span class=\"o\">*<\/span> <span class=\"n\">sample_lists<\/span><span class=\"p\">[<\/span><span class=\"n\">k<\/span><span class=\"p\">][<\/span><span class=\"n\">j<\/span><span class=\"p\">]<\/span>\n                        <span class=\"k\">for<\/span> <span class=\"n\">k<\/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\">sample_lists<\/span><span class=\"p\">))<\/span>\n                    <span class=\"p\">]<\/span>\n                <span class=\"p\">)<\/span>\n                <span class=\"n\">train_J<\/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\">eta<\/span> <span class=\"o\">*<\/span> <span class=\"n\">beta<\/span> <span class=\"o\">*<\/span> <span class=\"p\">(<\/span><span class=\"n\">data_ave<\/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\">sample_ave<\/span><span class=\"p\">)<\/span>\n\n        <span class=\"c1\"># \u4e00\u5b9a\u306e\u5b66\u7fd2\u56de\u6570\u3054\u3068\u306b\u30d1\u30e9\u30e1\u30fc\u30bf\u3092\u4fdd\u5b58<\/span>\n        <span class=\"k\">if<\/span> <span class=\"p\">(<\/span><span class=\"n\">t<\/span> <span class=\"o\">+<\/span> <span class=\"mi\">1<\/span><span class=\"p\">)<\/span> <span class=\"o\">%<\/span> <span class=\"mi\">10<\/span> <span class=\"o\">==<\/span> <span class=\"mi\">0<\/span> <span class=\"ow\">or<\/span> <span class=\"p\">(<\/span><span class=\"n\">t<\/span> <span class=\"o\">+<\/span> <span class=\"mi\">1<\/span><span class=\"p\">)<\/span> <span class=\"o\">==<\/span> <span class=\"mi\">1<\/span><span class=\"p\">:<\/span>\n            <span class=\"n\">m_J<\/span> <span class=\"o\">=<\/span> <span class=\"n\">minus_J<\/span><span class=\"p\">(<\/span><span class=\"n\">num_spin<\/span><span class=\"o\">=<\/span><span class=\"n\">num_spin<\/span><span class=\"p\">,<\/span> <span class=\"n\">J<\/span><span class=\"o\">=<\/span><span class=\"n\">train_J<\/span><span class=\"p\">)<\/span>\n            <span class=\"n\">sampleset<\/span> <span class=\"o\">=<\/span> <span class=\"n\">sampling<\/span><span class=\"p\">(<\/span><span class=\"n\">method<\/span><span class=\"o\">=<\/span><span class=\"n\">method<\/span><span class=\"p\">,<\/span> <span class=\"n\">h<\/span><span class=\"o\">=<\/span><span class=\"n\">h<\/span><span class=\"p\">,<\/span> <span class=\"n\">J<\/span><span class=\"o\">=<\/span><span class=\"n\">m_J<\/span><span class=\"p\">,<\/span> <span class=\"n\">Nsample<\/span><span class=\"o\">=<\/span><span class=\"mi\">150<\/span><span class=\"p\">,<\/span> <span class=\"n\">beta<\/span><span class=\"o\">=<\/span><span class=\"n\">beta<\/span><span class=\"p\">)<\/span>\n            <span class=\"n\">sample_lists<\/span> <span class=\"o\">=<\/span> <span class=\"n\">sampleset<\/span><span class=\"o\">.<\/span><span class=\"n\">record<\/span><span class=\"o\">.<\/span><span class=\"n\">sample<\/span>\n            <span class=\"n\">first<\/span> <span class=\"o\">=<\/span> <span class=\"n\">cal_first<\/span><span class=\"p\">(<\/span><span class=\"n\">beta<\/span><span class=\"o\">=<\/span><span class=\"n\">beta<\/span><span class=\"p\">,<\/span> <span class=\"n\">J<\/span><span class=\"o\">=<\/span><span class=\"n\">train_J<\/span><span class=\"p\">,<\/span> <span class=\"n\">data_lists<\/span><span class=\"o\">=<\/span><span class=\"n\">sample_lists<\/span><span class=\"p\">)<\/span>\n            <span class=\"n\">second<\/span> <span class=\"o\">=<\/span> <span class=\"n\">cal_second<\/span><span class=\"p\">(<\/span><span class=\"n\">beta<\/span><span class=\"o\">=<\/span><span class=\"n\">beta<\/span><span class=\"p\">,<\/span> <span class=\"n\">N<\/span><span class=\"o\">=<\/span><span class=\"n\">num_spin<\/span><span class=\"p\">,<\/span> <span class=\"n\">J<\/span><span class=\"o\">=<\/span><span class=\"n\">train_J<\/span><span class=\"p\">)<\/span>\n            <span class=\"n\">LH_hists<\/span><span class=\"p\">[<\/span><span class=\"n\">t<\/span> <span class=\"o\">+<\/span> <span class=\"mi\">1<\/span><span class=\"p\">]<\/span> <span class=\"o\">=<\/span> <span class=\"n\">first<\/span> <span class=\"o\">-<\/span> <span class=\"n\">second<\/span>\n\n    <span class=\"k\">return<\/span> <span class=\"n\">train_J<\/span><span class=\"p\">,<\/span> <span class=\"n\">LH_hists<\/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\u308c\u3067\u3001\u5b66\u7fd2\u306e\u6e96\u5099\u304c\u7d42\u308f\u308a\u307e\u3057\u305f\u3002\u30d1\u30e9\u30e1\u30fc\u30bf\u306e\u5b66\u7fd2\u3092\u884c\u3044\u307e\u3057\u3087\u3046\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-ipython3\">\n<pre><span class=\"kn\">from<\/span> <span class=\"nn\">dwave.system<\/span> <span class=\"kn\">import<\/span> <span class=\"n\">DWaveSampler<\/span><span class=\"p\">,<\/span> <span class=\"n\">EmbeddingComposite<\/span><span class=\"p\">,<\/span> <span class=\"n\">DWaveCliqueSampler<\/span>\n\n<span class=\"n\">sampler_config<\/span> <span class=\"o\">=<\/span> <span class=\"p\">{<\/span><span class=\"s2\">\"solver\"<\/span><span class=\"p\">:<\/span> <span class=\"s2\">\"DW_2000Q_6\"<\/span><span class=\"p\">,<\/span> <span class=\"s2\">\"token\"<\/span><span class=\"p\">:<\/span> <span class=\"s2\">\"YOUR_TOKEN\"<\/span><span class=\"p\">}<\/span>\n<span class=\"n\">sampler<\/span> <span class=\"o\">=<\/span> <span class=\"n\">EmbeddingComposite<\/span><span class=\"p\">(<\/span><span class=\"n\">DWaveSampler<\/span><span class=\"p\">(<\/span><span class=\"o\">**<\/span><span class=\"n\">sampler_config<\/span><span class=\"p\">))<\/span>\n<\/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-ipython3\">\n<pre><span class=\"n\">QA_J<\/span><span class=\"p\">,<\/span> <span class=\"n\">LH_QAhists<\/span> <span class=\"o\">=<\/span> <span class=\"n\">train_model<\/span><span class=\"p\">(<\/span>\n    <span class=\"n\">method<\/span><span class=\"o\">=<\/span><span class=\"s2\">\"QA\"<\/span><span class=\"p\">,<\/span>\n    <span class=\"n\">Tall<\/span><span class=\"o\">=<\/span><span class=\"mi\">100<\/span><span class=\"p\">,<\/span>\n    <span class=\"n\">Nsample<\/span><span class=\"o\">=<\/span><span class=\"mi\">1000<\/span><span class=\"p\">,<\/span>\n    <span class=\"n\">beta<\/span><span class=\"o\">=<\/span><span class=\"mi\">1<\/span><span class=\"p\">,<\/span>\n    <span class=\"n\">eta<\/span><span class=\"o\">=<\/span><span class=\"mf\">0.01<\/span><span class=\"p\">,<\/span>\n    <span class=\"n\">data_lists<\/span><span class=\"o\">=<\/span><span class=\"n\">data_lists<\/span><span class=\"p\">,<\/span>\n    <span class=\"n\">sampler<\/span><span class=\"o\">=<\/span><span class=\"n\">sampler<\/span><span class=\"p\">,<\/span>\n<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_stderr output_text\">\n<pre>100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 100\/100 [03:29&lt;00:00,  2.10s\/it]\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-ipython3\">\n<pre><span class=\"n\">LH_QAlist<\/span> <span class=\"o\">=<\/span> <span class=\"n\">LH_QAhists<\/span><span class=\"o\">.<\/span><span class=\"n\">items<\/span><span class=\"p\">()<\/span>\n<span class=\"n\">QAx<\/span><span class=\"p\">,<\/span> <span class=\"n\">QAy<\/span> <span class=\"o\">=<\/span> <span class=\"nb\">zip<\/span><span class=\"p\">(<\/span><span class=\"o\">*<\/span><span class=\"n\">LH_QAlist<\/span><span class=\"p\">)<\/span>\n\n<span class=\"n\">plt<\/span><span class=\"o\">.<\/span><span class=\"n\">plot<\/span><span class=\"p\">(<\/span><span class=\"n\">QAx<\/span><span class=\"p\">,<\/span> <span class=\"n\">QAy<\/span><span class=\"p\">,<\/span> <span class=\"n\">label<\/span><span class=\"o\">=<\/span><span class=\"s2\">\"QA\"<\/span><span class=\"p\">,<\/span> <span class=\"n\">marker<\/span><span class=\"o\">=<\/span><span class=\"s2\">\"o\"<\/span><span class=\"p\">)<\/span>\n<span class=\"n\">plt<\/span><span class=\"o\">.<\/span><span class=\"n\">hlines<\/span><span class=\"p\">(<\/span><span class=\"n\">data_LH<\/span><span class=\"p\">,<\/span> <span class=\"mi\">0<\/span><span class=\"p\">,<\/span> <span class=\"mi\">100<\/span><span class=\"p\">,<\/span> <span class=\"n\">colors<\/span><span class=\"o\">=<\/span><span class=\"s2\">\"green\"<\/span><span class=\"p\">,<\/span> <span class=\"n\">label<\/span><span class=\"o\">=<\/span><span class=\"s2\">\"Training_set\"<\/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\">\"iteration\"<\/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\">\"likelihood\"<\/span><span class=\"p\">)<\/span>\n<span class=\"n\">plt<\/span><span class=\"o\">.<\/span><span class=\"n\">legend<\/span><span class=\"p\">(<\/span><span class=\"n\">loc<\/span><span class=\"o\">=<\/span><span class=\"s2\">\"center right\"<\/span><span class=\"p\">)<\/span>\n<span class=\"n\">plt<\/span><span class=\"o\">.<\/span><span class=\"n\">show<\/span><span class=\"p\">()<\/span>\n<\/pre>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"output_wrapper\">\n<div class=\"output\">\n<div class=\"output_area\">\n<div class=\"prompt\"><\/div>\n<div class=\"output_png output_subarea \"><img decoding=\"async\" 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\" \/><\/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\u3067\u3001QA\u306b\u3088\u308b\u5b66\u7fd2\u306f\u7d42\u308f\u308a\u3067\u3059\u3002<\/p>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">\n<h3><span class=\"ez-toc-section\" id=\"SA%E3%81%AB%E3%82%88%E3%82%8B%E5%AD%A6%E7%BF%92\"><\/span>SA\u306b\u3088\u308b\u5b66\u7fd2<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<p>\u6b21\u306b\u3001SA\u306b\u3088\u308b\u5b66\u7fd2\u3092\u884c\u3044\u307e\u3059\u3002SA\u3068QA\u306e\u9055\u3044\u306f\u30bd\u30eb\u30d0\u30fc\u3092\u5909\u66f4\u3059\u308b\u3060\u3051\u306a\u306e\u3067\u3001<\/p>\n<p>\u65e9\u901f\u3001\u5b66\u7fd2\u3092\u958b\u59cb\u3057\u307e\u3057\u3087\u3046\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-ipython3\">\n<pre><span class=\"n\">sampler<\/span> <span class=\"o\">=<\/span> <span class=\"n\">oj<\/span><span class=\"o\">.<\/span><span class=\"n\">SASampler<\/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-ipython3\">\n<pre><span class=\"n\">SA_J<\/span><span class=\"p\">,<\/span> <span class=\"n\">LH_SAhists<\/span> <span class=\"o\">=<\/span> <span class=\"n\">train_model<\/span><span class=\"p\">(<\/span>\n    <span class=\"n\">method<\/span><span class=\"o\">=<\/span><span class=\"s2\">\"SA\"<\/span><span class=\"p\">,<\/span>\n    <span class=\"n\">Tall<\/span><span class=\"o\">=<\/span><span class=\"mi\">100<\/span><span class=\"p\">,<\/span>\n    <span class=\"n\">Nsample<\/span><span class=\"o\">=<\/span><span class=\"mi\">1000<\/span><span class=\"p\">,<\/span>\n    <span class=\"n\">beta<\/span><span class=\"o\">=<\/span><span class=\"mi\">1<\/span><span class=\"p\">,<\/span>\n    <span class=\"n\">eta<\/span><span class=\"o\">=<\/span><span class=\"mf\">0.01<\/span><span class=\"p\">,<\/span>\n    <span class=\"n\">data_lists<\/span><span class=\"o\">=<\/span><span class=\"n\">data_lists<\/span><span class=\"p\">,<\/span>\n    <span class=\"n\">sampler<\/span><span class=\"o\">=<\/span><span class=\"n\">sampler<\/span><span class=\"p\">,<\/span>\n<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_stderr output_text\">\n<pre>100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 100\/100 [02:10&lt;00:00,  1.31s\/it]\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-ipython3\">\n<pre><span class=\"n\">LH_SAlist<\/span> <span class=\"o\">=<\/span> <span class=\"n\">LH_SAhists<\/span><span class=\"o\">.<\/span><span class=\"n\">items<\/span><span class=\"p\">()<\/span>\n<span class=\"n\">SAx<\/span><span class=\"p\">,<\/span> <span class=\"n\">SAy<\/span> <span class=\"o\">=<\/span> <span class=\"nb\">zip<\/span><span class=\"p\">(<\/span><span class=\"o\">*<\/span><span class=\"n\">LH_SAlist<\/span><span class=\"p\">)<\/span>\n\n<span class=\"n\">plt<\/span><span class=\"o\">.<\/span><span class=\"n\">plot<\/span><span class=\"p\">(<\/span><span class=\"n\">QAx<\/span><span class=\"p\">,<\/span> <span class=\"n\">QAy<\/span><span class=\"p\">,<\/span> <span class=\"n\">label<\/span><span class=\"o\">=<\/span><span class=\"s2\">\"QA\"<\/span><span class=\"p\">,<\/span> <span class=\"n\">marker<\/span><span class=\"o\">=<\/span><span class=\"s2\">\"o\"<\/span><span class=\"p\">)<\/span>\n<span class=\"n\">plt<\/span><span class=\"o\">.<\/span><span class=\"n\">plot<\/span><span class=\"p\">(<\/span><span class=\"n\">SAx<\/span><span class=\"p\">,<\/span> <span class=\"n\">SAy<\/span><span class=\"p\">,<\/span> <span class=\"n\">label<\/span><span class=\"o\">=<\/span><span class=\"s2\">\"SA\"<\/span><span class=\"p\">,<\/span> <span class=\"n\">marker<\/span><span class=\"o\">=<\/span><span class=\"s2\">\"o\"<\/span><span class=\"p\">)<\/span>\n<span class=\"n\">plt<\/span><span class=\"o\">.<\/span><span class=\"n\">hlines<\/span><span class=\"p\">(<\/span><span class=\"n\">data_LH<\/span><span class=\"p\">,<\/span> <span class=\"mi\">0<\/span><span class=\"p\">,<\/span> <span class=\"mi\">100<\/span><span class=\"p\">,<\/span> <span class=\"n\">colors<\/span><span class=\"o\">=<\/span><span class=\"s2\">\"green\"<\/span><span class=\"p\">,<\/span> <span class=\"n\">label<\/span><span class=\"o\">=<\/span><span class=\"s2\">\"Training_set\"<\/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\">\"iteration\"<\/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\">\"likelihood\"<\/span><span class=\"p\">)<\/span>\n<span class=\"n\">plt<\/span><span class=\"o\">.<\/span><span class=\"n\">legend<\/span><span class=\"p\">(<\/span><span class=\"n\">loc<\/span><span class=\"o\">=<\/span><span class=\"s2\">\"lower right\"<\/span><span class=\"p\">)<\/span>\n<span class=\"n\">plt<\/span><span class=\"o\">.<\/span><span class=\"n\">show<\/span><span class=\"p\">()<\/span>\n<\/pre>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"output_wrapper\">\n<div class=\"output\">\n<div class=\"output_area\">\n<div class=\"prompt\"><\/div>\n<div class=\"output_png output_subarea \"><img decoding=\"async\" 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\" \/><\/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>SA\u306b\u3088\u308b\u5b66\u7fd2\u306f\u3001\u3053\u308c\u3067\u7d42\u4e86\u3067\u3059\u3002<\/p>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">\n<h3><span class=\"ez-toc-section\" id=\"%E5%8E%B3%E5%AF%86%E5%8B%BE%E9%85%8D%E3%81%AB%E3%82%88%E3%82%8B%E5%AD%A6%E7%BF%92\"><\/span>\u53b3\u5bc6\u52fe\u914d\u306b\u3088\u308b\u5b66\u7fd2<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<p>\u6700\u5f8c\u306b\u3001\u671f\u5f85\u5024\u306e\u8a08\u7b97\u3092\u30b5\u30f3\u30d7\u30ea\u30f3\u30b0\u306b\u3088\u308b\u8fd1\u4f3c\u3067\u306f\u306a\u304f\u3001\u53b3\u5bc6\u306b\u8a08\u7b97\u3059\u308b\u3053\u3068\u3067\u5b66\u7fd2\u3092\u884c\u3044\u307e\u3059\u3002<\/p>\n<p>\u52fe\u914d\u6cd5\u3092\u3001\u3082\u3046\u4e00\u5ea6\u8a18\u8f09\u3057\u307e\u3059\u3002<\/p>\n<p>$$<br \/>\nJ_{i j}(t+1)=J_{i j}(t)+\\eta \\frac{\\partial S}{\\partial J_{i j}}<br \/>\n$$$$<br \/>\n\\frac{1}{\\beta} \\frac{\\partial S}{\\partial J_{i j}}=\\left\\langle s_{i} s_{j}\\right\\rangle_{\\rho _\\mathcal{D}}-\\left\\langle s_{i} s_{j}\\right\\rangle_{\\rho}<br \/>\n$$<\/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>QA\u3001SA\u306e\u5834\u5408\u3001\u671f\u5f85\u5024[latex]\\left\\langle{}\\right\\rangle_{\\rho}[\/latex]\u306f<\/p>\n<p>$$<br \/>\n\\left\\langle s_{i} s_{j}\\right\\rangle_{\\rho} = \\frac{1}{L} \\sum_{l=1}^{L} s_{i}^{(l)} s_{j}^{(l)}<br \/>\n$$<\/p>\n<p>\u3068\u3057\u3066\u8fd1\u4f3c\u7684\u306b\u6c42\u3081\u307e\u3057\u305f\u3002\u3053\u3053\u3067\u306f\u3001\u3053\u306e\u90e8\u5206\u3092\u53b3\u5bc6\u306b\u8a08\u7b97\u3057\u3066\u3044\u304d\u307e\u3059\u3002<\/p>\n<p>\u5177\u4f53\u7684\u306b\u306f\u3001\u6b21\u306e\u5f0f\u3067\u6c42\u3081\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\">$$<br \/>\n\\left\\langle s_{i} s_{j}\\right\\rangle_{\\rho}=\\sum_{s_{i}=\\pm 1} \\sum_{s_{j}=\\pm 1} s_{i} \u30fb s_{j} \u30fb P\\left(s_{i}, s_{j}\\right)<br \/>\n$$<\/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[latex]P\\left(s_{i}, s_{j}\\right)[\/latex]\u306f\u540c\u6642\u78ba\u7387\u3067<br \/>\n$$<br \/>\nP\\left(s_{i}, s_{j}\\right) = \\sum_{\\mathbf{s} \\backslash s_i, s_j} P(\\mathbf{s})<br \/>\n$$<br \/>\n\u3068\u3057\u3066\u6c42\u3081\u3089\u308c\u307e\u3059\u3002[latex]\\mathbf{s} \\backslash s_i, s_j[\/latex]\u3000\u306f\u3001[latex]s_i, s_j[\/latex]\u4ee5\u5916\u5168\u3066\u306e[latex]\\mathbf{s}[\/latex]\u3092\u8868\u3057\u3066\u3044\u307e\u3059\u3002<\/p>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">\n<p>\u4f8b)\u3000[latex]N=3, i=1, j=2[\/latex]\u306e\u5834\u5408<\/p>\n<p>$$<br \/>\n\\left\\langle s_{1} s_{2}\\right\\rangle_{\\rho}=\\sum_{s_{1}=\\pm 1} \\sum_{s_{2}=\\pm 1} s_{1} \u30fb s_{2} \u30fb P\\left(s_{1,} s_{2}\\right)<br \/>\n$$<\/p>\n<p>\u3053\u3053\u3067\u3001[latex]P\\left(s_{1}, s_{2}\\right)[\/latex]\u306f<br \/>\n$$<br \/>\nP\\left(s_{1}, s_{2}\\right) = \\sum_{\\mathbf{s} \\backslash s_1 s_2} P(\\mathbf{s}) = P(s_1, s_2, -1) + P(s_1, s_2, +1)<br \/>\n$$<\/p>\n<p>\u3068\u306a\u308a\u307e\u3059\u3002[latex]P(s_1, s_2, s_3)[\/latex]\u306f\u3001\u30ab\u30ce\u30cb\u30ab\u30eb\u5206\u5e03<br \/>\n$$<br \/>\nP(\\mathbf{s})=\\frac{1}{Z} \\exp (-\\beta E(\\mathbf{s})), \\quad Z=\\sum_{\\mathbf{s}} \\exp (-\\beta E(\\mathbf{s}))<br \/>\n$$<\/p>\n<p>\u304b\u3089\u6c42\u3081\u3089\u308c\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-ipython3\">\n<pre><span class=\"k\">def<\/span> <span class=\"nf\">cal_statesum<\/span><span class=\"p\">(<\/span><span class=\"n\">N<\/span><span class=\"p\">,<\/span> <span class=\"n\">J<\/span><span class=\"p\">,<\/span> <span class=\"n\">beta<\/span><span class=\"p\">):<\/span>\n    <span class=\"sd\">\"\"\"\u5206\u914d\u95a2\u6570\u306e\u8a08\u7b97\"\"\"<\/span>\n    <span class=\"n\">statesum<\/span> <span class=\"o\">=<\/span> <span class=\"n\">np<\/span><span class=\"o\">.<\/span><span class=\"n\">sum<\/span><span class=\"p\">(<\/span>\n        <span class=\"p\">[<\/span>\n            <span class=\"n\">np<\/span><span class=\"o\">.<\/span><span class=\"n\">exp<\/span><span class=\"p\">(<\/span><span class=\"o\">-<\/span><span class=\"n\">beta<\/span> <span class=\"o\">*<\/span> <span class=\"n\">cal_energy<\/span><span class=\"p\">(<\/span><span class=\"n\">N<\/span><span class=\"o\">=<\/span><span class=\"n\">N<\/span><span class=\"p\">,<\/span> <span class=\"n\">J<\/span><span class=\"o\">=<\/span><span class=\"n\">J<\/span><span class=\"p\">,<\/span> <span class=\"n\">spin<\/span><span class=\"o\">=<\/span><span class=\"n\">spin_list<\/span><span class=\"p\">))<\/span>\n            <span class=\"k\">for<\/span> <span class=\"n\">spin_list<\/span> <span class=\"ow\">in<\/span> <span class=\"n\">itertools<\/span><span class=\"o\">.<\/span><span class=\"n\">product<\/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> <span class=\"n\">repeat<\/span><span class=\"o\">=<\/span><span class=\"n\">N<\/span><span class=\"p\">)<\/span>\n        <span class=\"p\">]<\/span>\n    <span class=\"p\">)<\/span>\n    <span class=\"k\">return<\/span> <span class=\"n\">statesum<\/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-ipython3\">\n<pre><span class=\"k\">def<\/span> <span class=\"nf\">arg_lists<\/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=\"n\">N<\/span><span class=\"p\">):<\/span>\n    <span class=\"sd\">\"\"\"\u540c\u6642\u78ba\u7387\u306e\u5f15\u6570\"\"\"<\/span>\n    <span class=\"n\">arg_lists<\/span> <span class=\"o\">=<\/span> <span class=\"p\">[]<\/span>\n    <span class=\"k\">for<\/span> <span class=\"n\">z<\/span> <span class=\"ow\">in<\/span> <span class=\"n\">itertools<\/span><span class=\"o\">.<\/span><span class=\"n\">product<\/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> <span class=\"n\">repeat<\/span><span class=\"o\">=<\/span><span class=\"n\">N<\/span> <span class=\"o\">-<\/span> <span class=\"mi\">2<\/span><span class=\"p\">):<\/span>\n        <span class=\"n\">arg_list<\/span> <span class=\"o\">=<\/span> <span class=\"nb\">list<\/span><span class=\"p\">(<\/span><span class=\"n\">z<\/span><span class=\"p\">)<\/span>\n        <span class=\"n\">arg_list<\/span><span class=\"o\">.<\/span><span class=\"n\">insert<\/span><span class=\"p\">(<\/span><span class=\"n\">i<\/span><span class=\"p\">,<\/span> <span class=\"s2\">\"zi\"<\/span><span class=\"p\">)<\/span>\n        <span class=\"n\">arg_list<\/span><span class=\"o\">.<\/span><span class=\"n\">insert<\/span><span class=\"p\">(<\/span><span class=\"n\">j<\/span><span class=\"p\">,<\/span> <span class=\"s2\">\"zj\"<\/span><span class=\"p\">)<\/span>\n        <span class=\"n\">arg_lists<\/span><span class=\"o\">.<\/span><span class=\"n\">append<\/span><span class=\"p\">(<\/span><span class=\"n\">arg_list<\/span><span class=\"p\">)<\/span>\n    <span class=\"k\">return<\/span> <span class=\"n\">arg_lists<\/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-ipython3\">\n<pre><span class=\"k\">def<\/span> <span class=\"nf\">canonical<\/span><span class=\"p\">(<\/span><span class=\"n\">statesum<\/span><span class=\"p\">,<\/span> <span class=\"n\">beta<\/span><span class=\"p\">,<\/span> <span class=\"n\">N<\/span><span class=\"p\">,<\/span> <span class=\"n\">J<\/span><span class=\"p\">,<\/span> <span class=\"n\">arg_list<\/span><span class=\"p\">):<\/span>\n    <span class=\"sd\">\"\"\"\u30ab\u30ce\u30cb\u30ab\u30eb\u5206\u5e03\"\"\"<\/span>\n    <span class=\"n\">energy<\/span> <span class=\"o\">=<\/span> <span class=\"n\">cal_energy<\/span><span class=\"p\">(<\/span><span class=\"n\">N<\/span><span class=\"o\">=<\/span><span class=\"n\">N<\/span><span class=\"p\">,<\/span> <span class=\"n\">J<\/span><span class=\"o\">=<\/span><span class=\"n\">J<\/span><span class=\"p\">,<\/span> <span class=\"n\">spin<\/span><span class=\"o\">=<\/span><span class=\"n\">arg_list<\/span><span class=\"p\">)<\/span>\n    <span class=\"n\">canonical<\/span> <span class=\"o\">=<\/span> <span class=\"n\">np<\/span><span class=\"o\">.<\/span><span class=\"n\">exp<\/span><span class=\"p\">(<\/span><span class=\"o\">-<\/span><span class=\"n\">beta<\/span> <span class=\"o\">*<\/span> <span class=\"n\">energy<\/span><span class=\"p\">)<\/span> <span class=\"o\">\/<\/span> <span class=\"n\">statesum<\/span>\n    <span class=\"k\">return<\/span> <span class=\"n\">canonical<\/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-ipython3\">\n<pre><span class=\"k\">def<\/span> <span class=\"nf\">joint_prob<\/span><span class=\"p\">(<\/span><span class=\"n\">N<\/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=\"n\">arg_lists<\/span><span class=\"p\">,<\/span> <span class=\"n\">zi<\/span><span class=\"p\">,<\/span> <span class=\"n\">zj<\/span><span class=\"p\">,<\/span> <span class=\"n\">ca_dict<\/span><span class=\"p\">):<\/span>\n    <span class=\"sd\">\"\"\"\u540c\u6642\u78ba\u7387\"\"\"<\/span>\n    <span class=\"n\">joint_prob<\/span> <span class=\"o\">=<\/span> <span class=\"mi\">0<\/span>\n    <span class=\"k\">for<\/span> <span class=\"n\">arg_list<\/span> <span class=\"ow\">in<\/span> <span class=\"n\">arg_lists<\/span><span class=\"p\">:<\/span>\n        <span class=\"n\">arg_list<\/span><span class=\"p\">[<\/span><span class=\"n\">i<\/span><span class=\"p\">],<\/span> <span class=\"n\">arg_list<\/span><span class=\"p\">[<\/span><span class=\"n\">j<\/span><span class=\"p\">]<\/span> <span class=\"o\">=<\/span> <span class=\"n\">zi<\/span><span class=\"p\">,<\/span> <span class=\"n\">zj<\/span>\n        <span class=\"n\">joint_prob<\/span> <span class=\"o\">+=<\/span> <span class=\"n\">ca_dict<\/span><span class=\"p\">[<\/span><span class=\"nb\">tuple<\/span><span class=\"p\">(<\/span><span class=\"n\">arg_list<\/span><span class=\"p\">)]<\/span>\n    <span class=\"k\">return<\/span> <span class=\"n\">joint_prob<\/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-ipython3\">\n<pre><span class=\"k\">def<\/span> <span class=\"nf\">exact_grad<\/span><span class=\"p\">(<\/span><span class=\"n\">Tall<\/span><span class=\"p\">,<\/span> <span class=\"n\">beta<\/span><span class=\"p\">,<\/span> <span class=\"n\">N<\/span><span class=\"p\">,<\/span> <span class=\"n\">eta<\/span><span class=\"p\">):<\/span>\n    <span class=\"c1\"># \u30d1\u30e9\u30e1\u30fc\u30bf\u306e\u521d\u671f\u5024\u30920\u3068\u3059\u308b<\/span>\n    <span class=\"n\">train_J<\/span> <span class=\"o\">=<\/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=\"mi\">0<\/span> <span class=\"k\">for<\/span> <span class=\"n\">i<\/span> <span class=\"ow\">in<\/span> <span class=\"nb\">range<\/span><span class=\"p\">(<\/span><span class=\"n\">N<\/span><span class=\"p\">)<\/span> <span class=\"k\">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\n    <span class=\"c1\"># \u6559\u5e2b\u30c7\u30fc\u30bf\u306e\u7d4c\u9a13\u5e73\u5747<\/span>\n    <span class=\"n\">data_ave<\/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=\"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\">data_ave<\/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\">np<\/span><span class=\"o\">.<\/span><span class=\"n\">average<\/span><span class=\"p\">(<\/span>\n                <span class=\"p\">[<\/span><span class=\"n\">data_lists<\/span><span class=\"p\">[<\/span><span class=\"n\">k<\/span><span class=\"p\">][<\/span><span class=\"n\">i<\/span><span class=\"p\">]<\/span> <span class=\"o\">*<\/span> <span class=\"n\">data_lists<\/span><span class=\"p\">[<\/span><span class=\"n\">k<\/span><span class=\"p\">][<\/span><span class=\"n\">j<\/span><span class=\"p\">]<\/span> <span class=\"k\">for<\/span> <span class=\"n\">k<\/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\">data_lists<\/span><span class=\"p\">))]<\/span>\n            <span class=\"p\">)<\/span>\n\n    <span class=\"n\">LH_hists<\/span> <span class=\"o\">=<\/span> <span class=\"p\">{}<\/span>\n    <span class=\"k\">for<\/span> <span class=\"n\">t<\/span> <span class=\"ow\">in<\/span> <span class=\"n\">tqdm<\/span><span class=\"p\">(<\/span><span class=\"n\">np<\/span><span class=\"o\">.<\/span><span class=\"n\">arange<\/span><span class=\"p\">(<\/span><span class=\"n\">Tall<\/span><span class=\"p\">)):<\/span>\n        <span class=\"c1\"># \u4f7f\u7528\u3059\u308b\u30ab\u30ce\u30cb\u30ab\u30eb\u5206\u5e03\u3092\u5148\u306b\u8a08\u7b97<\/span>\n        <span class=\"n\">statesum<\/span> <span class=\"o\">=<\/span> <span class=\"n\">cal_statesum<\/span><span class=\"p\">(<\/span><span class=\"n\">N<\/span><span class=\"o\">=<\/span><span class=\"n\">N<\/span><span class=\"p\">,<\/span> <span class=\"n\">J<\/span><span class=\"o\">=<\/span><span class=\"n\">train_J<\/span><span class=\"p\">,<\/span> <span class=\"n\">beta<\/span><span class=\"o\">=<\/span><span class=\"mi\">1<\/span><span class=\"p\">)<\/span>\n        <span class=\"n\">ca_dict<\/span> <span class=\"o\">=<\/span> <span class=\"p\">{}<\/span>\n        <span class=\"k\">for<\/span> <span class=\"n\">spin_list<\/span> <span class=\"ow\">in<\/span> <span class=\"n\">itertools<\/span><span class=\"o\">.<\/span><span class=\"n\">product<\/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> <span class=\"n\">repeat<\/span><span class=\"o\">=<\/span><span class=\"n\">N<\/span><span class=\"p\">):<\/span>\n            <span class=\"n\">ca_dict<\/span><span class=\"p\">[<\/span><span class=\"n\">spin_list<\/span><span class=\"p\">]<\/span> <span class=\"o\">=<\/span> <span class=\"n\">canonical<\/span><span class=\"p\">(<\/span>\n                <span class=\"n\">statesum<\/span><span class=\"o\">=<\/span><span class=\"n\">statesum<\/span><span class=\"p\">,<\/span> <span class=\"n\">beta<\/span><span class=\"o\">=<\/span><span class=\"mi\">1<\/span><span class=\"p\">,<\/span> <span class=\"n\">N<\/span><span class=\"o\">=<\/span><span class=\"n\">N<\/span><span class=\"p\">,<\/span> <span class=\"n\">J<\/span><span class=\"o\">=<\/span><span class=\"n\">train_J<\/span><span class=\"p\">,<\/span> <span class=\"n\">arg_list<\/span><span class=\"o\">=<\/span><span class=\"n\">spin_list<\/span>\n            <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\">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\">exact_exval<\/span> <span class=\"o\">=<\/span> <span class=\"mi\">0<\/span>\n                <span class=\"k\">for<\/span> <span class=\"n\">z<\/span> <span class=\"ow\">in<\/span> <span class=\"n\">itertools<\/span><span class=\"o\">.<\/span><span class=\"n\">product<\/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> <span class=\"n\">repeat<\/span><span class=\"o\">=<\/span><span class=\"mi\">2<\/span><span class=\"p\">):<\/span>\n                    <span class=\"n\">zi<\/span><span class=\"p\">,<\/span> <span class=\"n\">zj<\/span> <span class=\"o\">=<\/span> <span class=\"n\">z<\/span><span class=\"p\">[<\/span><span class=\"mi\">0<\/span><span class=\"p\">],<\/span> <span class=\"n\">z<\/span><span class=\"p\">[<\/span><span class=\"mi\">1<\/span><span class=\"p\">]<\/span>\n                    <span class=\"n\">jp<\/span> <span class=\"o\">=<\/span> <span class=\"n\">joint_prob<\/span><span class=\"p\">(<\/span>\n                        <span class=\"n\">N<\/span><span class=\"o\">=<\/span><span class=\"n\">N<\/span><span class=\"p\">,<\/span>\n                        <span class=\"n\">i<\/span><span class=\"o\">=<\/span><span class=\"n\">i<\/span><span class=\"p\">,<\/span>\n                        <span class=\"n\">j<\/span><span class=\"o\">=<\/span><span class=\"n\">j<\/span><span class=\"p\">,<\/span>\n                        <span class=\"n\">arg_lists<\/span><span class=\"o\">=<\/span><span class=\"n\">arg_lists<\/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=\"n\">N<\/span><span class=\"p\">),<\/span>\n                        <span class=\"n\">zi<\/span><span class=\"o\">=<\/span><span class=\"n\">zi<\/span><span class=\"p\">,<\/span>\n                        <span class=\"n\">zj<\/span><span class=\"o\">=<\/span><span class=\"n\">zj<\/span><span class=\"p\">,<\/span>\n                        <span class=\"n\">ca_dict<\/span><span class=\"o\">=<\/span><span class=\"n\">ca_dict<\/span><span class=\"p\">,<\/span>\n                    <span class=\"p\">)<\/span>\n                <span class=\"c1\"># \u76f8\u4e92\u4f5c\u7528\u306e\u66f4\u65b0<\/span>\n                <span class=\"n\">train_J<\/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\">eta<\/span> <span class=\"o\">*<\/span> <span class=\"n\">beta<\/span> <span class=\"o\">*<\/span> <span class=\"p\">(<\/span><span class=\"n\">data_ave<\/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\">exact_exval<\/span><span class=\"p\">)<\/span>\n\n        <span class=\"c1\"># \u4e00\u5b9a\u306e\u5b66\u7fd2\u56de\u6570\u3054\u3068\u306b\u30d1\u30e9\u30e1\u30fc\u30bf\u3092\u4fdd\u5b58<\/span>\n        <span class=\"k\">if<\/span> <span class=\"p\">(<\/span><span class=\"n\">t<\/span> <span class=\"o\">+<\/span> <span class=\"mi\">1<\/span><span class=\"p\">)<\/span> <span class=\"o\">%<\/span> <span class=\"mi\">1<\/span> <span class=\"o\">==<\/span> <span class=\"mi\">0<\/span> <span class=\"ow\">or<\/span> <span class=\"p\">(<\/span><span class=\"n\">t<\/span> <span class=\"o\">+<\/span> <span class=\"mi\">1<\/span><span class=\"p\">)<\/span> <span class=\"o\">==<\/span> <span class=\"mi\">1<\/span><span class=\"p\">:<\/span>\n            <span class=\"n\">first<\/span> <span class=\"o\">=<\/span> <span class=\"n\">cal_first<\/span><span class=\"p\">(<\/span><span class=\"n\">beta<\/span><span class=\"o\">=<\/span><span class=\"n\">beta<\/span><span class=\"p\">,<\/span> <span class=\"n\">J<\/span><span class=\"o\">=<\/span><span class=\"n\">train_J<\/span><span class=\"p\">,<\/span> <span class=\"n\">data_lists<\/span><span class=\"o\">=<\/span><span class=\"n\">data_lists<\/span><span class=\"p\">)<\/span>\n            <span class=\"n\">second<\/span> <span class=\"o\">=<\/span> <span class=\"n\">cal_second<\/span><span class=\"p\">(<\/span><span class=\"n\">beta<\/span><span class=\"o\">=<\/span><span class=\"n\">beta<\/span><span class=\"p\">,<\/span> <span class=\"n\">N<\/span><span class=\"o\">=<\/span><span class=\"n\">N<\/span><span class=\"p\">,<\/span> <span class=\"n\">J<\/span><span class=\"o\">=<\/span><span class=\"n\">train_J<\/span><span class=\"p\">)<\/span>\n            <span class=\"n\">LH_hists<\/span><span class=\"p\">[<\/span><span class=\"n\">t<\/span> <span class=\"o\">+<\/span> <span class=\"mi\">1<\/span><span class=\"p\">]<\/span> <span class=\"o\">=<\/span> <span class=\"n\">first<\/span> <span class=\"o\">-<\/span> <span class=\"n\">second<\/span>\n\n    <span class=\"k\">return<\/span> <span class=\"n\">train_J<\/span><span class=\"p\">,<\/span> <span class=\"n\">LH_hists<\/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\u308c\u3067\u3001\u6e96\u5099\u304c\u7d42\u308f\u308a\u307e\u3057\u305f\u3002\u5b9f\u884c\u3057\u3066\u307f\u307e\u3057\u3087\u3046\u3002<\/p>\n<p>QA\u3084SA\u3088\u308a\u8a08\u7b97\u91cf\u304c\u591a\u3044\u305f\u3081\u3001\u6642\u9593\u304c\u304b\u304b\u308a\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-ipython3\">\n<pre><span class=\"n\">exact_J<\/span><span class=\"p\">,<\/span> <span class=\"n\">exact_hists<\/span> <span class=\"o\">=<\/span> <span class=\"n\">exact_grad<\/span><span class=\"p\">(<\/span><span class=\"n\">Tall<\/span><span class=\"o\">=<\/span><span class=\"mi\">100<\/span><span class=\"p\">,<\/span> <span class=\"n\">beta<\/span><span class=\"o\">=<\/span><span class=\"mi\">1<\/span><span class=\"p\">,<\/span> <span class=\"n\">N<\/span><span class=\"o\">=<\/span><span class=\"mi\">15<\/span><span class=\"p\">,<\/span> <span class=\"n\">eta<\/span><span class=\"o\">=<\/span><span class=\"mf\">0.01<\/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_stderr output_text\">\n<pre>100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 100\/100 [37:48&lt;00:00, 22.69s\/it]\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>\u305d\u308c\u3067\u306f\u3001\u5168\u3066\u306e\u7d50\u679c\u3092\u540c\u3058\u30b0\u30e9\u30d5\u306b\u30d7\u30ed\u30c3\u30c8\u3057\u3066\u307f\u307e\u3057\u3087\u3046\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-ipython3\">\n<pre><span class=\"n\">exact_list<\/span> <span class=\"o\">=<\/span> <span class=\"n\">exact_hists<\/span><span class=\"o\">.<\/span><span class=\"n\">items<\/span><span class=\"p\">()<\/span>\n<span class=\"n\">EXx<\/span><span class=\"p\">,<\/span> <span class=\"n\">EXy<\/span> <span class=\"o\">=<\/span> <span class=\"nb\">zip<\/span><span class=\"p\">(<\/span><span class=\"o\">*<\/span><span class=\"n\">exact_list<\/span><span class=\"p\">)<\/span>\n\n<span class=\"n\">plt<\/span><span class=\"o\">.<\/span><span class=\"n\">hlines<\/span><span class=\"p\">(<\/span><span class=\"n\">data_LH<\/span><span class=\"p\">,<\/span> <span class=\"mi\">0<\/span><span class=\"p\">,<\/span> <span class=\"mi\">100<\/span><span class=\"p\">,<\/span> <span class=\"n\">colors<\/span><span class=\"o\">=<\/span><span class=\"s2\">\"green\"<\/span><span class=\"p\">,<\/span> <span class=\"n\">label<\/span><span class=\"o\">=<\/span><span class=\"s2\">\"Training_set\"<\/span><span class=\"p\">)<\/span>\n<span class=\"n\">plt<\/span><span class=\"o\">.<\/span><span class=\"n\">plot<\/span><span class=\"p\">(<\/span><span class=\"n\">QAx<\/span><span class=\"p\">,<\/span> <span class=\"n\">QAy<\/span><span class=\"p\">,<\/span> <span class=\"n\">label<\/span><span class=\"o\">=<\/span><span class=\"s2\">\"QA\"<\/span><span class=\"p\">,<\/span> <span class=\"n\">marker<\/span><span class=\"o\">=<\/span><span class=\"s2\">\"o\"<\/span><span class=\"p\">)<\/span>\n<span class=\"n\">plt<\/span><span class=\"o\">.<\/span><span class=\"n\">plot<\/span><span class=\"p\">(<\/span><span class=\"n\">SAx<\/span><span class=\"p\">,<\/span> <span class=\"n\">SAy<\/span><span class=\"p\">,<\/span> <span class=\"n\">label<\/span><span class=\"o\">=<\/span><span class=\"s2\">\"SA\"<\/span><span class=\"p\">,<\/span> <span class=\"n\">marker<\/span><span class=\"o\">=<\/span><span class=\"s2\">\"o\"<\/span><span class=\"p\">)<\/span>\n<span class=\"n\">plt<\/span><span class=\"o\">.<\/span><span class=\"n\">plot<\/span><span class=\"p\">(<\/span><span class=\"n\">EXx<\/span><span class=\"p\">,<\/span> <span class=\"n\">EXy<\/span><span class=\"p\">,<\/span> <span class=\"n\">label<\/span><span class=\"o\">=<\/span><span class=\"s2\">\"Exact Gradient\"<\/span><span class=\"p\">,<\/span> <span class=\"n\">color<\/span><span class=\"o\">=<\/span><span class=\"s2\">\"purple\"<\/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\">\"iteration\"<\/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\">\"likelihood\"<\/span><span class=\"p\">)<\/span>\n<span class=\"n\">plt<\/span><span class=\"o\">.<\/span><span class=\"n\">legend<\/span><span class=\"p\">(<\/span><span class=\"n\">loc<\/span><span class=\"o\">=<\/span><span class=\"s2\">\"lower right\"<\/span><span class=\"p\">)<\/span>\n<span class=\"n\">plt<\/span><span class=\"o\">.<\/span><span class=\"n\">show<\/span><span class=\"p\">()<\/span>\n<\/pre>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"output_wrapper\">\n<div class=\"output\">\n<div class=\"output_area\">\n<div class=\"prompt\"><\/div>\n<div class=\"output_png output_subarea \"><img decoding=\"async\" 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