English

Cokernel statistics for walk matrices of directed and weighted random graphs

Combinatorics 2025-07-14 v2 Probability

Abstract

The walk matrix associated to an n×nn\times n integer matrix XX and an integer vector bb is defined by W:=(b,Xb,...,Xn1b)W := (b,X b, . . . ,X^{n-1} b). We study limiting laws for the cokernel of WW in the scenario where XX is a random matrix with independent entries and bb is deterministic. Our first main result provides a formula for the distribution of the pmp^{m}-torsion part of the cokernel, as a group, when XX has independent entries from a specific distribution. The second main result relaxes the distributional assumption and concerns the Z[x]\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

Keywords

Cite

@article{arxiv.2401.12655,
  title  = {Cokernel statistics for walk matrices of directed and weighted random graphs},
  author = {Alexander Van Werde},
  journal= {arXiv preprint arXiv:2401.12655},
  year   = {2025}
}

Comments

19 pages

R2 v1 2026-06-28T14:24:34.121Z