English

Normal to Poisson phase transition for subgraph counting in the random-connection model

Probability 2025-11-11 v2

Abstract

We consider the limiting behavior of the count of subgraphs isomorphic to a graph GG with m0m\geq 0 fixed endpoints (or roots) in the random-connection model, as the intensity λ\lambda of the underlying Poisson point process tends to infinity. When connection probabilities are of order λα\lambda^{-\alpha} we identify a phase transition phenomenon depending on a critical decay rate αm(G)>0\alpha^\ast_m (G)>0 such that normal approximation for subgraph counts holds when α(0,αm(G))\alpha \in (0,\alpha^\ast_m (G) ), and a Poisson limit result holds if α=αm(G)\alpha = \alpha^\ast_m (G). Our approach relies on cumulant growth rates derived by the convex analysis of planar diagrams that enumerate the partitions involved in cumulant identities. As a result, by the cumulant method we obtain normal approximation results with convergence rates in the Kolmogorov distance, and a Poisson limit theorem, for subgraph counts.

Keywords

Cite

@article{arxiv.2409.16222,
  title  = {Normal to Poisson phase transition for subgraph counting in the random-connection model},
  author = {Qingwei Liu and Nicolas Privault},
  journal= {arXiv preprint arXiv:2409.16222},
  year   = {2025}
}
R2 v1 2026-06-28T18:55:31.049Z