链接的随机蜿蜒模型

IF 0.6 3区 数学 Q4 COMPUTER SCIENCE, THEORY & METHODS Discrete & Computational Geometry Pub Date : 2024-06-11 DOI:10.1007/s00454-024-00663-9
Nicholas Owad, Anastasiia Tsvietkova
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引用次数: 0

摘要

我们提出了一种基于蜿蜒图和图形的新链接随机模型。然后我们证明,在这个模型中,琐碎链接出现的概率为零,没有链接 L 出现的概率为 1,并且在交叉次数固定的情况下,非异位结的数量有一个下限。随机蜿蜒图是通过匹配括号对得到的,这是一个在组合学中研究得很透彻的问题。因此,组合学中的工具可以用来研究这个模型中随机链接的性质,以及作为 3 球中链接互补的相应 3 球的性质。我们利用这一点来探索链接补集的几何性质。具体来说,我们给出了链接图的预期扭曲数,并用它来约束随机链接的预期双曲体积和单曲体积。我们使用的组合学工具包括卡塔兰数和纳拉亚纳数以及蔡尔伯格算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Random Meander Model for Links

We suggest a new random model for links based on meander diagrams and graphs. We then prove that trivial links appear with vanishing probability in this model, no link L is obtained with probability 1, and there is a lower bound for the number of non-isotopic knots obtained for a fixed number of crossings. A random meander diagram is obtained through matching pairs of parentheses, a well-studied problem in combinatorics. Hence tools from combinatorics can be used to investigate properties of random links in this model, and, moreover, of the respective 3-manifolds that are link complements in 3-sphere. We use this for exploring geometric properties of a link complement. Specifically, we give expected twist number of a link diagram and use it to bound expected hyperbolic and simplicial volume of random links. The tools from combinatorics that we use include Catalan and Narayana numbers, and Zeilberger’s algorithm.

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来源期刊
Discrete & Computational Geometry
Discrete & Computational Geometry 数学-计算机:理论方法
CiteScore
1.80
自引率
12.50%
发文量
99
审稿时长
6-12 weeks
期刊介绍: Discrete & Computational Geometry (DCG) is an international journal of mathematics and computer science, covering a broad range of topics in which geometry plays a fundamental role. It publishes papers on such topics as configurations and arrangements, spatial subdivision, packing, covering, and tiling, geometric complexity, polytopes, point location, geometric probability, geometric range searching, combinatorial and computational topology, probabilistic techniques in computational geometry, geometric graphs, geometry of numbers, and motion planning.
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