Cokernel statistics for walk matrices of directed and weighted random graphs

Fuente: arXiv
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Main Author: Van Werde, Alexander
Format: Preprint
Published: 2024
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author Van Werde, Alexander
author_facet Van Werde, Alexander
contents The walk matrix associated to an $n\times n$ integer matrix $X$ and an integer vector $b$ is defined by $W := (b,X b, . . . ,X^{n-1} b)$. We study limiting laws for the cokernel of $W$ in the scenario where $X$ is a random matrix with independent entries and $b$ is deterministic. Our first main result provides a formula for the distribution of the $p^{m}$-torsion part of the cokernel, as a group, when $X$ has independent entries from a specific distribution. The second main result relaxes the distributional assumption and concerns the $\mathbb{Z}[x]$-module structure. The motivation for this work arises from an open problem in spectral graph theory which asks to show that random graphs are often determined up to isomorphism by their (generalized) spectrum. Sufficient conditions for generalized spectral determinacy can namely be stated in terms of the cokernel of a walk matrix. Extensions of our results could potentially be used to determine how often those conditions are satisfied. Some remaining challenges for such extensions are outlined in the paper
format Preprint
id arxiv_https___arxiv_org_abs_2401_12655
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Cokernel statistics for walk matrices of directed and weighted random graphs
Van Werde, Alexander
Combinatorics
Probability
05C50, 15B52, 60B20
The walk matrix associated to an $n\times n$ integer matrix $X$ and an integer vector $b$ is defined by $W := (b,X b, . . . ,X^{n-1} b)$. We study limiting laws for the cokernel of $W$ in the scenario where $X$ is a random matrix with independent entries and $b$ is deterministic. Our first main result provides a formula for the distribution of the $p^{m}$-torsion part of the cokernel, as a group, when $X$ has independent entries from a specific distribution. The second main result relaxes the distributional assumption and concerns the $\mathbb{Z}[x]$-module structure. The motivation for this work arises from an open problem in spectral graph theory which asks to show that random graphs are often determined up to isomorphism by their (generalized) spectrum. Sufficient conditions for generalized spectral determinacy can namely be stated in terms of the cokernel of a walk matrix. Extensions of our results could potentially be used to determine how often those conditions are satisfied. Some remaining challenges for such extensions are outlined in the paper
title Cokernel statistics for walk matrices of directed and weighted random graphs
topic Combinatorics
Probability
05C50, 15B52, 60B20
url https://arxiv.org/abs/2401.12655