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arXiv 1810.04670cs.CCcs.DS
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算法$\mathcal{B}$ -分区,参数化复杂性的矩阵行列式和永久

Algorithm for $\mathcal{B}$-partitions, parameterized complexity of the matrix determinant and permanent

Ranveer Singh, Vivek Vijay, RB Bapat

摘要:

每个方阵$A=(a_{uv})\in \mathcal{C}^{n\times n}$可以表示为具有$n$顶点的有向图。在有向图中,块(或2-连通分支)是没有割点的最大连通子有向图。矩阵的行列式和积和式可以根据有向图中块的某些特定导出子图的行列式和积和式来计算。有趣的是,这些诱导子图是顶点不相交的,它们划分有向图。有向图的这种划分称为$\mathcal{B}$ -划分。在本文中,首先,我们开发了一个算法来找到$\mathcal{B}$ -划分。其次,我们分析了矩阵行列式和积和式的参数化复杂性,其中参数是图的块大小和割点个数。我们给出了一类割点和块大小的组合,其参数化的复杂性击败了行列式和积和式的最新复杂性。

英文摘要:

Every square matrix $A=(a_{uv})\in \mathcal{C}^{n\times n}$ can be represented as a digraph having $n$ vertices. In the digraph, a block (or 2-connected component) is a maximally connected subdigraph that has no cut-vertex. The determinant and the permanent of a matrix can be calculated in terms of the determinant and the permanent of some specific induced subdigraphs of the blocks in the digraph. Interestingly, these induced subdigraphs are vertex-disjoint and they partition the digraph. Such partitions of the digraph are called the $\mathcal{B}$-partitions. In this paper, first, we develop an algorithm to find the $\mathcal{B}$-partitions. Next, we analyze the parameterized complexity of matrix determinant and permanent, where, the parameters are the sizes of blocks and the number of cut-vertices of the digraph. We give a class of combinations of cut-vertices and block sizes for which the parametrized complexities beat the state of art complexities of the determinant and the permanent.

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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