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https://dspace.iiti.ac.in/handle/123456789/4847
Title: | Parameterized complexity of determinant and permanent |
Authors: | Singh, Ranveer |
Keywords: | Computational methods;Computer science;Block sizes;Cut vertex;Matrix determinant;Parameterized complexity;Parametrized complexity;Square matrices;Vertex disjoint;Directed graphs |
Issue Date: | 2020 |
Publisher: | Elsevier B.V. |
Citation: | Singh, R. (2020). Parameterized complexity of determinant and permanent. Theoretical Computer Science, 845, 50-58. doi:10.1016/j.tcs.2020.08.031 |
Abstract: | Every square matrix A=(auv)∈Cn×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 B-partitions. In this paper, first, we develop an algorithm to find the 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. © 2020 Elsevier B.V. |
URI: | https://doi.org/10.1016/j.tcs.2020.08.031 https://dspace.iiti.ac.in/handle/123456789/4847 |
ISSN: | 0304-3975 |
Type of Material: | Journal Article |
Appears in Collections: | Department of Computer Science and Engineering |
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