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arXiv 1807.07809math.CO
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图的权正则划分的一个特征及其应用

A characterization and an application of weight-regular partitions of graphs

Aida Abiad

摘要:

图的规则(或公平)划分的自然推广(其对于非正则图也有意义)是所谓的权重规则划分,其向每个顶点$u\in V$赋予等于Perron特征向量$\mathbfν$的对应条目$ν_u$的权重。本文主要研究了图的权正则划分问题。第一个是用双随机阵刻画权正则分拆。受Hoffman对正则图的一个刻画的启发,我们利用Hoffman多项式给出了权正则图的一个新的刻画.作为推论,我们得到了正则图的Hoffman结果.此外,我们展示了一个应用程序的重量定期分区研究图,达到平等的经典霍夫曼的下界的色数的一个图,我们表明,重量正则性提供了一个条件下,霍夫曼的界限可以得到改善。

英文摘要:

A natural generalization of a regular (or equitable) partition of a graph, which makes sense also for non-regular graphs, is the so-called weight-regular partition, which gives to each vertex $u\in V$ a weight that equals the corresponding entry $ν_u$ of the Perron eigenvector $\mathbfν$. This paper contains three main results related to weight-regular partitions of a graph. The first is a characterization of weight-regular partitions in terms of double stochastic matrices. Inspired by a characterization of regular graphs by Hoffman, we also provide a new characterization of weight-regularity by using a Hoffman-like polynomial. As a corollary, we obtain Hoffman's result for regular graphs. In addition, we show an application of weight-regular partitions to study graphs that attain equality in the classical Hoffman's lower bound for the chromatic number of a graph, and we show that weight-regularity provides a condition under which Hoffman's bound can be improved.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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