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Analyses and Implementations of Chordality-Preserving Top-Down Algorithms for Triangular Decomposition

  • Beihang University

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

When the input polynomial set has a chordal associated graph, top-down algorithms for triangular decomposition are proved to preserve the chordal structure. Based on these theoretical results, sparse algorithms for triangular decomposition were proposed and demonstrated with experiments to be more efficient in case of sparse polynomial sets. However, existing implementations of top-down triangular decomposition are not guaranteed to be chordality-preserving due to operations which potentially destroy the chordality. In this paper, we first analyze the current implementations of typical top-down algorithms for triangular decomposition in the Epsilon package to identify these chordality-destroying operations. Then modifications are made accordingly to guarantee new implementations of such algorithms are chordality-preserving. In particular, the technique of dynamic checking is introduced to ensure that the modifications also keep the computational efficiency. Experimental results with polynomial sets from biological systems are also reported.

源语言英语
主期刊名Computer Algebra in Scientific Computing - 24th International Workshop, CASC 2022, Proceedings
编辑François Boulier, Matthew England, Timur M. Sadykov, Evgenii V. Vorozhtsov
出版商Springer Science and Business Media Deutschland GmbH
124-142
页数19
ISBN(印刷版)9783031147876
DOI
出版状态已出版 - 2022
活动24th International Workshop on Computer Algebra in Scientific Computing, CASC 2022 - Gebze, 土耳其
期限: 22 8月 202226 8月 2022

出版系列

姓名Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
13366 LNCS
ISSN(印刷版)0302-9743
ISSN(电子版)1611-3349

会议

会议24th International Workshop on Computer Algebra in Scientific Computing, CASC 2022
国家/地区土耳其
Gebze
时期22/08/2226/08/22

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