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一种用于界定二分图中独立集数量的广义信息论方法。

A Generalized Information-Theoretic Approach for Bounding the Number of Independent Sets in Bipartite Graphs.

作者信息

Sason Igal

机构信息

Department of Electrical Engineering, Technion-Israel Institute of Technology, Haifa 3200003, Israel.

出版信息

Entropy (Basel). 2021 Feb 25;23(3):270. doi: 10.3390/e23030270.

Abstract

This paper studies the problem of upper bounding the number of independent sets in a graph, expressed in terms of its degree distribution. For bipartite regular graphs, Kahn (2001) established a tight upper bound using an information-theoretic approach, and he also conjectured an upper bound for general graphs. His conjectured bound was recently proved by Sah et al. (2019), using different techniques not involving information theory. The main contribution of this work is the extension of Kahn's information-theoretic proof technique to handle irregular bipartite graphs. In particular, when the bipartite graph is regular on one side, but may be irregular on the other, the extended entropy-based proof technique yields the same bound as was conjectured by Kahn (2001) and proved by Sah et al. (2019).

摘要

本文研究了根据图的度分布来确定图中独立集数量上限的问题。对于二分正则图,卡恩(2001年)使用信息论方法建立了一个紧的上限,并且他还对一般图提出了一个上限猜想。他的猜想上限最近由萨赫等人(2019年)通过不涉及信息论的不同技术得到了证明。这项工作的主要贡献是将卡恩的信息论证明技术扩展到处理非正则二分图。特别地,当二分图在一侧是正则的,但在另一侧可能是非正则的时,基于扩展熵的证明技术给出了与卡恩(2001年)猜想并由萨赫等人(2019年)证明的相同上限。

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