{"id":42213,"date":"2023-05-01T19:11:25","date_gmt":"2023-05-01T11:11:25","guid":{"rendered":"https:\/\/swarma.org\/?p=42213"},"modified":"2023-05-01T19:11:25","modified_gmt":"2023-05-01T11:11:25","slug":"prx-%e9%80%9f%e9%80%92%ef%bc%9a%e6%a8%a1%e6%8b%9f%e9%80%80%e7%81%ab%e7%ae%97%e6%b3%95%e5%9c%a8%e8%a7%a3%e5%86%b3%e7%a8%80%e7%96%8f%e7%a1%ac%e6%8e%a8%e7%90%86%e9%97%ae%e9%a2%98%e4%b8%ad%e7%9a%84","status":"publish","type":"post","link":"https:\/\/swarma.org\/?p=42213","title":{"rendered":"PRX \u901f\u9012\uff1a\u6a21\u62df\u9000\u706b\u7b97\u6cd5\u5728\u89e3\u51b3\u7a00\u758f\u786c\u63a8\u7406\u95ee\u9898\u4e2d\u7684\u5c40\u9650\u6027"},"content":{"rendered":"
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\u8bba\u6587\u9898\u76ee\uff1aLimits and Performances of Algorithms Based on Simulated Annealing in Solving Sparse Hard Inference Problems<\/span><\/section>\n
\u8bba\u6587\u6765\u6e90\uff1aPhysical Review X<\/em><\/span><\/section>\n
\u8bba\u6587\u94fe\u63a5\uff1ahttps:\/\/journals.aps.org\/prx\/abstract\/10.1103\/PhysRevX.13.021011<\/span><\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/blockquote>\n

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\u79cd\u690d\u7740\u8272\u95ee\u9898<\/span>\uff08the planted-coloring problem\uff0c\u56fe\u7740\u8272\u7b97\u6cd5\u7684\u4e00\u79cd\uff09<\/span>\u662f\u4e00\u4e2a\u5178\u578b\u7684\u63a8\u7406\u95ee\u9898\uff0c\u5bf9\u6b64\uff0c\u8d1d\u53f6\u65af\u6700\u4f18\u7b97\u6cd5\u7684\u9608\u503c\uff0c\u5982\u7f6e\u4fe1\u5ea6\u4f20\u64ad<\/span>\uff08belief propagation, BP\uff09<\/span>\u53ef\u4ee5\u89e3\u6790\u8ba1\u7b97\u3002\u6a21\u62df\u9000\u706b\u6cd5<\/span>\uff08simulated annealing\uff0cSA\uff09<\/span>\u662f\u4e00\u79cd\u57fa\u4e8e\u8499\u7279\u5361\u7f57\u7684\u7b97\u6cd5\uff0c\u6bd4\u7f6e\u4fe1\u5ea6\u4f20\u64ad\u66f4\u52a0\u901a\u7528\u548c\u7a33\u5065\uff0c\u56e0\u6b64\u5177\u6709\u66f4\u5e7f\u6cdb\u7684\u9002\u7528\u6027\u3002<\/span><\/section>\n

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\u8fd9\u7bc7 Physical Review X<\/em> \u6587\u7ae0\u5206\u6790\u4e86\u6a21\u62df\u9000\u706b\u6cd5\u7684\u5c40\u9650\u6027\u548c\u6027\u80fd\u3002\u4f5c\u8005\u8868\u660e\uff0c\u6a21\u62df\u9000\u706b\u5728\u6062\u590d\u79cd\u690d\u89e3\u65b9\u9762\u662f\u6b21\u4f18\u7684\uff0c\u56e0\u4e3a\u5b83\u88ab\u73bb\u7483\u6001\u6240\u5438\u5f15\uff0c\u800c\u73bb\u7483\u6001\u5e76\u4e0d\u5f71\u54cd\u7f6e\u4fe1\u5ea6\u4f20\u64ad\u7b97\u6cd5\u3002\u4e0e\u4ee5\u524d\u7684\u731c\u60f3\u4e0d\u540c\uff0c\u8be5\u7814\u7a76\u901a\u8fc7\u6bd4\u8f83\u987a\u78c1\u76f8\u7684\u62d0\u70b9\u548c\u52a8\u6001\u4e34\u754c\u6e29\u5ea6\uff0c\u63d0\u51fa\u4e86\u5bf9\u6a21\u62df\u9000\u706b\u6cd5\u7b97\u6cd5\u9608\u503c\u7684\u89e3\u6790\u4f30\u8ba1\u3002\u8fd9\u662f\u70ed\u529b\u5b66\u76f8\u53d8\u548c Glauber \u52a8\u529b\u5b66\u7684\u5931\u8861\u884c\u4e3a\u4e4b\u95f4\u7684\u4e00\u4e2a\u57fa\u672c\u8054\u7cfb\u3002<\/span><\/section>\n

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\u4f5c\u8005\u8fd8\u7814\u7a76\u4e86\u6a21\u62df\u9000\u706b\u6cd5\u7684\u6539\u8fdb\u7248\u672c\uff0c\u79f0\u4e3a\u526f\u672c\u6a21\u62df\u9000\u706b\u6cd5<\/span>\uff08replicated SA, RSA\uff09<\/span>\uff0c\u5176\u4e2d\u51e0\u4e2a\u5f31\u8026\u5408\u7684\u526f\u672c\u88ab\u4e00\u8d77\u51b7\u5374\u3002\u526f\u672c\u6a21\u62df\u9000\u706b\u6cd5\u7684\u7b97\u6cd5\u9608\u503c\u4e0e\u8d1d\u53f6\u65af\u6700\u4f18\u9608\u503c\u76f8\u543b\u5408\u3002\u6700\u540e\uff0c\u8be5\u7814\u7a76\u53d1\u5c55\u4e86\u4e00\u4e2a\u8fd1\u4f3c\u89e3\u6790\u7406\u8bba\uff0c\u89e3\u91ca\u4e86\u526f\u672c\u6a21\u62df\u9000\u706b\u6cd5\u7684\u6700\u4f73\u6027\u80fd\uff0c\u5e76\u9884\u6d4b\u4e86\u5728\u975e\u5e38\u591a\u526f\u672c\u7684\u6781\u9650\u4e0b\uff0c\u5411\u79cd\u690d\u89e3\u8f6c\u53d8\u7684\u4f4d\u7f6e\u3002\u5bf9\u526f\u672c\u6a21\u62df\u9000\u706b\u6cd5\u7684\u7814\u7a76\u7ed3\u679c\u652f\u6301\u8fd9\u6837\u7684\u89c2\u70b9\uff0c\u5373\u5148\u9a8c\u53c2\u6570\u4e0e\u751f\u6210\u6a21\u578b\u7684\u53c2\u6570\u4e0d\u5339\u914d\u53ef\u80fd\u4f1a\u4ea7\u751f\u4e00\u79cd\u6700\u4f73\u7684\u3001\u975e\u5e38\u7a33\u5065\u7684\u7b97\u6cd5\u3002<\/span><\/section>\n

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\u56fe1. \u73bb\u7483\u6001\u548c\u79cd\u690d\u6001\u793a\u610f\u56fe\u3002<\/span><\/section>\n

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\u56fe2. \u526f\u672c\u6a21\u62df\u9000\u706b\u4e2d\uff0c\u6539\u53d8\u590d\u5236\u7684\u6570\u91cfy\uff0c\u80fd\u91cf\u5bc6\u5ea6\u662f\u6e29\u5ea6\u7684\u51fd\u6570\u3002<\/span><\/section>\n

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\u56fe3. \u4e0d\u540c\u95ee\u9898\u5927\u5c0f\u7684\u79cd\u690d\u7740\u8272\uff0c\u6a21\u62df\u9000\u706b\u8fc7\u7a0b\u4e2d\u80fd\u91cf\u5bc6\u5ea6\u4e0e\u6e29\u5ea6\u7684\u51fd\u6570\u3002<\/span><\/section>\n

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\u56fe4. \u5bfb\u627e\u79cd\u690d\u7740\u8272\u4fe1\u53f7\u7684\u9000\u706b\u8fc7\u7a0b\u6240\u9762\u4e34\u7684\u4e00\u822c\u60c5\u666f\u7684\u793a\u610f\u56fe\u3002<\/span><\/section>\n


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\u56fe\u795e\u7ecf\u7f51\u7edc\u4e0e\u7ec4\u5408\u4f18\u5316\u8bfb\u4e66\u4f1a<\/strong><\/p>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n


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\u8be6\u60c5\u8bf7\u89c1\uff1a<\/span><\/span><\/section>\n
\u52a0\u901f\u7ecf\u5178\u7b97\u6cd5\u6548\u7387\uff0c\u7a81\u7834\u73b0\u5b9e\u6280\u672f\u74f6\u9888\uff1a\u56fe\u795e\u7ecf\u7f51\u7edc\u4e0e\u7ec4\u5408\u4f18\u5316\u8bfb\u4e66\u4f1a\u542f\u52a8<\/a><\/span><\/section>\n

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\u63a8\u8350\u9605\u8bfb<\/span><\/strong><\/strong><\/p>\n

1. <\/strong>\u6c6a\u52b2\uff1a\u751f\u547d\u7cfb\u7edf\u4e2d\u7684\u975e\u5e73\u8861\u7269\u7406\u5b66<\/a><\/strong><\/span><\/strong><\/strong><\/section>\n
2.<\/strong> AI\u751f\u6210\u827a\u672f\u7684\u5e95\u5c42\u539f\u7406\uff1a\u975e\u5e73\u8861\u7269\u7406\u7684\u6269\u6563\u6a21\u578b<\/a><\/strong><\/span><\/strong><\/section>\n
3. <\/strong><\/strong>PRL\u524d\u6cbf\uff1a\u63a2\u7a76\u975e\u5e73\u8861\u6001\u8f93\u8fd0\u4e3b\u5bfc\u8def\u5f84\u65b0\u65b9\u6cd5\u2014\u2014\u5708\u6d41\u6392\u5e8f<\/a><\/strong><\/strong><\/span><\/strong><\/strong><\/section>\n
4. \u300a\u5f20\u6c5f\u00b7\u590d\u6742\u79d1\u5b66\u524d\u6cbf27\u8bb2\u300b\u5b8c\u6574\u4e0a\u7ebf\uff01<\/strong><\/a><\/strong><\/strong><\/strong><\/section>\n
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5. \u6210\u4e3a\u96c6\u667aVIP\uff0c\u89e3\u9501\u5168\u7ad9\u8bfe\u7a0b\uff0f\u8bfb\u4e66\u4f1a<\/span><\/strong><\/a><\/strong><\/strong><\/strong><\/strong><\/section>\n
6.<\/strong><\/strong><\/strong> <\/strong><\/strong><\/strong>\u52a0\u5165\u96c6\u667a\uff0c\u4e00\u8d77\u590d\u6742\uff01<\/strong><\/a><\/strong><\/strong><\/strong><\/span><\/section>\n

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\u70b9\u51fb\u201c\u9605\u8bfb\u539f\u6587\u201d\uff0c\u62a5\u540d\u8bfb\u4e66\u4f1a<\/strong><\/span><\/strong><\/section>\n

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\u5173\u952e\u8bcd\uff1a\u6a21\u62df\u9000\u706b\u6cd5\u7b97\u6cd5\uff0c\u56fe\u7740\u8272\u95ee\u9898\uff0c\u73bb\u7483\u76f8\u53d8\uff0c\u975e\u5e73\u8861\u7edf\u8ba1\u7269\u7406\uff0c\u590d\u6742\u7cfb\u7edf \u8bba\u6587\u9898\u76ee\uff1aLimits and Performances of Algorithms Based on Simulated Annealing in Solving Sparse Hard Inference Problems …<\/p>\n","protected":false},"author":0,"featured_media":42205,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[1],"tags":[],"special":[],"_links":{"self":[{"href":"https:\/\/swarma.org\/index.php?rest_route=\/wp\/v2\/posts\/42213"}],"collection":[{"href":"https:\/\/swarma.org\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/swarma.org\/index.php?rest_route=\/wp\/v2\/types\/post"}],"replies":[{"embeddable":true,"href":"https:\/\/swarma.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=42213"}],"version-history":[{"count":0,"href":"https:\/\/swarma.org\/index.php?rest_route=\/wp\/v2\/posts\/42213\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/swarma.org\/index.php?rest_route=\/wp\/v2\/media\/42205"}],"wp:attachment":[{"href":"https:\/\/swarma.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=42213"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/swarma.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=42213"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/swarma.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=42213"},{"taxonomy":"special","embeddable":true,"href":"https:\/\/swarma.org\/index.php?rest_route=%2Fwp%2Fv2%2Fspecial&post=42213"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}