重尾机制中最小生成树的几何:新的普遍性类别

IF 1.5 1区 数学 Q2 STATISTICS & PROBABILITY Probability Theory and Related Fields Pub Date : 2024-02-17 DOI:10.1007/s00440-024-01259-3
Shankar Bhamidi, Sanchayan Sen
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引用次数: 0

摘要

统计物理学家提出了一个关于强无序机制下随机图中最优路径行为的著名开放性问题,并在过去十年中得到了大量数值证据的支持(Braunstein 等,发表于 Phys Rev Lett 91(16):168701, 2003;Braunstein 等,发表于 Int J Bifurc Chaos 17(07):2215-2255, 2007;Chen 等,发表于 Phys Rev Lett 96(6):068702, 2006;Wu 等,发表于 Phys Rev Lett 96(14):148702, 2006)。在 Phys Rev Lett 96(6):068702, 2006;Wu 等人在 Phys Rev Lett 96(14):148702, 2006)的结论如下:对于一大类具有度指数 ((\tau \in (3,4)\)的随机图模型,在超临界机制中巨型分量上的最小生成树(MST)中的距离就像\(n^{(\tau -3)/(\tau-1)}\)一样缩放。本文的目的是在证明这一猜想方面取得进展。我们考虑了一个超临界非均质随机图模型,该模型的度指数((\tau \ in (3, 4)\)与阿尔道斯的乘法凝聚密切相关,并证明了通过给边缘分配 i.i.d.(n^{-(\tau-3)/(\tau-1)}\)缩放的树距离,在分布上相对于格罗莫夫-豪斯多夫拓扑学(Gromov-Hausdorff topology)收敛于随机紧凑实树。此外,几乎可以肯定的是,这个极限空间中的每个点要么度数为一(树叶),要么度数为二,要么度数为无穷大(树枢),树叶集合和树枢集合在这个空间中都是密集的,而且这个空间的闵科夫斯基维度等于 \((\tau-1)/(\tau-3)\)。在渐近的意义上,乘法凝聚力描述了各种近临界随机图过程的分量大小的演化。我们希望本文中的极限空间能够成为为其他一系列重尾随机图模型构建的 MST 的缩放极限的候选空间。
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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Geometry of the minimal spanning tree in the heavy-tailed regime: new universality classes

A well-known open problem on the behavior of optimal paths in random graphs in the strong disorder regime, formulated by statistical physicists, and supported by a large amount of numerical evidence over the last decade (Braunstein et al. in Phys Rev Lett 91(16):168701, 2003; Braunstein et al. in Int J Bifurc Chaos 17(07):2215–2255, 2007; Chen et al. in Phys Rev Lett 96(6):068702, 2006; Wu et al. in Phys Rev Lett 96(14):148702, 2006) is as follows: for a large class of random graph models with degree exponent \(\tau \in (3,4)\), distances in the minimal spanning tree (MST) on the giant component in the supercritical regime scale like \(n^{(\tau -3)/(\tau -1)}\). The aim of this paper is to make progress towards a proof of this conjecture. We consider a supercritical inhomogeneous random graph model with degree exponent \(\tau \in (3, 4)\) that is closely related to Aldous’s multiplicative coalescent, and show that the MST constructed by assigning i.i.d. continuous weights to the edges in its giant component, endowed with the tree distance scaled by \(n^{-(\tau -3)/(\tau -1)}\), converges in distribution with respect to the Gromov–Hausdorff topology to a random compact real tree. Further, almost surely, every point in this limiting space either has degree one (leaf), or two, or infinity (hub), both the set of leaves and the set of hubs are dense in this space, and the Minkowski dimension of this space equals \((\tau -1)/(\tau -3)\). The multiplicative coalescent, in an asymptotic sense, describes the evolution of the component sizes of various near-critical random graph processes. We expect the limiting spaces in this paper to be the candidates for the scaling limit of the MST constructed for a wide array of other heavy-tailed random graph models.

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来源期刊
Probability Theory and Related Fields
Probability Theory and Related Fields 数学-统计学与概率论
CiteScore
3.70
自引率
5.00%
发文量
71
审稿时长
6-12 weeks
期刊介绍: Probability Theory and Related Fields publishes research papers in modern probability theory and its various fields of application. Thus, subjects of interest include: mathematical statistical physics, mathematical statistics, mathematical biology, theoretical computer science, and applications of probability theory to other areas of mathematics such as combinatorics, analysis, ergodic theory and geometry. Survey papers on emerging areas of importance may be considered for publication. The main languages of publication are English, French and German.
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