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标题：Fast Algorithms for General Spin Systems on Bipartite Expanders
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作者：Andreas Galanis ; Leslie Ann Goldberg ; James Stewart 等
期刊名称：LIPIcs : Leibniz International Proceedings in Informatics
电子版ISSN：1868-8969
出版年度：2020
卷号：170
页码：37:1-37:14
DOI：10.4230/LIPIcs.MFCS.2020.37
出版社：Schloss Dagstuhl -- Leibniz-Zentrum fuer Informatik
摘要：A spin system is a framework in which the vertices of a graph are assigned spins from a finite set. The interactions between neighbouring spins give rise to weights, so a spin assignment can also be viewed as a weighted graph homomorphism. The problem of approximating the partition function (the aggregate weight of spin assignments) or of sampling from the resulting probability distribution is typically intractable for general graphs. In this work, we consider arbitrary spin systems on bipartite expander Î"-regular graphs, including the canonical class of bipartite random Î"-regular graphs. We develop fast approximate sampling and counting algorithms for general spin systems whenever the degree and the spectral gap of the graph are sufficiently large. Our approach generalises the techniques of Jenssen et al. and Chen et al. by showing that typical configurations on bipartite expanders correspond to "bicliques" of the spin system; then, using suitable polymer models, we show how to sample such configurations and approximate the partition function in OÌf(nÂ²) time, where n is the size of the graph.
关键词：bipartite expanders; approximate counting; spin systems