群中算法问题的线性平均复杂度

IF 0.8 2区 数学 Q2 MATHEMATICS Journal of Algebra Pub Date : 2025-04-15 Epub Date: 2025-01-23 DOI:10.1016/j.jalgebra.2025.01.013
Alexander Olshanskii , Vladimir Shpilrain
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引用次数: 0

摘要

群论算法的最坏情况复杂度问题已经被研究了很长时间。一般情况复杂度,即随机输入上的复杂度,是最近才被引入和研究的。在本文中,我们讨论了若干类组中单词问题的平均情况时间复杂度,并表明通常情况下,平均情况复杂度与输入单词的长度呈线性关系。我们考虑的群的种类包括有理数上的矩阵群(特别是多环群),一些可解群的种类,以及自由积。在此过程中,我们改进了矩阵群中词问题的最坏情况复杂度的几个界限,特别是在幂零群中。对于免费产品,我们还处理了子组成员问题的平均情况复杂度,并表明它通常也是线性的。最后,我们讨论了以前没有考虑过的恒等问题的复杂性。
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Linear average-case complexity of algorithmic problems in groups
The worst-case complexity of group-theoretic algorithms has been studied for a long time. Generic-case complexity, or complexity on random inputs, was introduced and studied relatively recently. In this paper, we address the average-case time complexity of the word problem in several classes of groups and show that it is often the case that the average-case complexity is linear with respect to the length of an input word. The classes of groups that we consider include groups of matrices over rationals (in particular, polycyclic groups), some classes of solvable groups, as well as free products. Along the way, we improve several bounds for the worst-case complexity of the word problem in groups of matrices, in particular in nilpotent groups. For free products, we also address the average-case complexity of the subgroup membership problem and show that it is often linear, too. Finally, we discuss complexity of the identity problem that has not been considered before.
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来源期刊
Journal of Algebra
Journal of Algebra 数学-数学
CiteScore
1.50
自引率
22.20%
发文量
414
审稿时长
2-4 weeks
期刊介绍: The Journal of Algebra is a leading international journal and publishes papers that demonstrate high quality research results in algebra and related computational aspects. Only the very best and most interesting papers are to be considered for publication in the journal. With this in mind, it is important that the contribution offer a substantial result that will have a lasting effect upon the field. The journal also seeks work that presents innovative techniques that offer promising results for future research.
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