English

Monochromatic Subgraphs in Randomly Colored Dense Multiplex Networks

Probability 2025-01-20 v2 Combinatorics

Abstract

Given a sequence of graphs GnG_n and a fixed graph HH, denote by T(H,Gn)T(H, G_n) the number of monochromatic copies of the graph HH in a uniformly random cc-coloring of the vertices of GnG_n. In this paper we study the joint distribution of a finite collection of monochromatic graph counts in networks with multiple layers (multiplex networks). Specifically, given a finite collection of graphs H1,H2,,HdH_1, H_2, \ldots, H_d we derive the joint distribution of (T(H1,Gn(1)),T(H2,Gn(2)),,T(Hd,Gn(d)))(T(H_1, G_n^{(1)}), T(H_2, G_n^{(2)}), \ldots, T(H_d, G_n^{(d)})), where Gn=(Gn(1),Gn(2),,Gn(d))\boldsymbol{G}_n = (G_n^{(1)}, G_n^{(2)}, \ldots, G_n^{(d)}) is a collection of dense graphs on the same vertex set converging in the joint cut-metric. The limiting distribution is the sum of 2 independent components: a multivariate Gaussian and a sum of independent bivariate stochastic integrals. This extends previous results on the marginal convergence of monochromatic subgraphs in a sequence of graphs to the joint convergence of a finite collection of monochromatic subgraphs in a sequence of multiplex networks. Several applications and examples are discussed.

Keywords

Cite

@article{arxiv.2501.07821,
  title  = {Monochromatic Subgraphs in Randomly Colored Dense Multiplex Networks},
  author = {Mauricio Daros Andrade and Bhaswar B. Bhattacharya},
  journal= {arXiv preprint arXiv:2501.07821},
  year   = {2025}
}

Comments

31 pages, 3 figures

R2 v1 2026-06-28T21:05:27.735Z