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Border Correlations, Lattices, and the Subgraph Component Polynomial

机译:边界相关性,格和子图分量多项式

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We consider the border sets of partial words and study the combinatorics of specific representations of them, called border correlations, which are binary vectors of same length indicating the borders. We characterize precisely which of these vectors are valid border correlations, and establish a one-to-one correspondence between the set of valid border correlations and the set of valid period correlations of a given length, the latter being ternary vectors representing the strong and strictly weak period sets. It turns out that the sets of all border correlations of a given length form distributive lattices under suitably defined partial orderings. We also investigate the population size, i.e., the number of partial words sharing a given border correlation, and obtain formulas to compute it. We do so using the subgraph component polynomial of an undirected graph, introduced recently by Tittmann et al. (European Journal of Combinatorics, 2011), which counts the number of connected components in vertex induced subgraphs.
机译:我们考虑局部词的边界集,并研究它们的特定表示的组合,称为边界相关性,它们是表示边界的相同长度的二进制向量。我们精确地表征了这些向量中的哪些是有效边界相关性,并在一组有效边界相关性和一组给​​定长度的有效周期相关性之间建立了一对一的对应关系,后者是代表强且严格的三元向量弱期集。结果表明,给定长度的所有边界相关性的集合在适当定义的局部排序下形成了分布晶格。我们还研究了人口规模,即共享给定边界相关性的部分单词的数量,并获得了计算公式。我们使用Tittmann等人最近引入的无向图的子图分量多项式来实现。 (European Journal of Combinatorics,2011),它计算了顶点诱发的子图中的连通分量的数量。

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