Occupation Statistics of Critical Branching Random Walks in Two or Higher Dimensions

TL;DR

This paper studies the behavior of critical branching random walks in two or more dimensions, providing limit theorems for occupation statistics conditioned on survival, revealing how these quantities scale with the generation number.

Contribution

It offers new limit theorems for occupation statistics of critical branching random walks in higher dimensions, detailing their asymptotic behavior conditioned on survival.

Findings

Maximal particles at a site grow as n^{1/α} or log n depending on offspring tail

Number of multiplicity-j sites converges to exponential variables

Particles at a typical site grow as log n in dimension 2

Abstract

Consider a critical nearest neighbor branching random walk on the $d$-dimensional integer lattice initiated by a single particle at the origin. Let $G_{n}$ be the event that the branching random walk survives to generation $n$. We obtain limit theorems conditional on the event $G_{n}$ for a variety of occupation statistics: (1) Let $V_{n}$ be the maximal number of particles at a single site at time $n$. If the offspring distribution has finite $\alpha$th moment for some integer $\alpha\geq 2$, then in dimensions 3 and higher, $V_n=O_p(n^{1/\alpha})$; and if the offspring distribution has an exponentially decaying tail, then $V_n=O_p(\log n)$ in dimensions 3 and higher, and $V_n=O_p((\log n)^2)$ in dimension 2. Furthermore, if the offspring distribution is non-degenerate then $P(V_n\geq \delta \log n | G_{n})\to 1$ for some $\delta >0$. (2) Let $M_{n} (j)$ be the number of multiplicity-$j$ sites in the $n$th generation, that is, sites occupied by exactly $j$ particles. In dimensions 3 and higher, the random variables $M_{n} (j)/n$ converge jointly to multiples of an exponential random variable. (3) In dimension 2, the number of particles at a "typical" site (that is, at the location of a randomly chosen particle of the $n$th generation) is of order $O_p(\log n)$, and the number of occupied sites is $O_p(n/\log n)$.