Abstract

We study occupancy counts for the critical nearest-neighbor branching random walk on the $d$-dimensional lattice, conditioned on non-extinction. For $d\geq 3$, Lalley and Zheng [4] showed that the properly scaled joint distribution of the number of sites occupied by $j$ generation-$n$ particles, $j=1,2,\ldots $, converges in distribution as $n$ goes to infinity, to a deterministic multiple of a single exponential random variable. The limiting exponential variable can be understood as the classical Yaglom limit of the total population size of generation $n$. Here we study the second order fluctuations around this limit, first, by providing a rate of convergence in the Wasserstein metric that holds for all $d\geq 3$, and second, by showing that for $d\geq 7$, the weak limit of the scaled joint differences between the number of occupancy-$j$ sites and appropriate multiples of the total population size converge in the Wasserstein metric to a multivariate symmetric Laplace distribution. We also provide a rate of convergence for this latter result.

Highlights

  • Branching random walk (BRW) is a fundamental mathematical model of a population evolving in time and space, which has been intensely studied for more than 50 years due to its connection to population genetics and superprocesses; see, e.g., [1, Chapter 9] and references

  • Exponential and Laplace approximation for branching random walk which states that the exponential distribution arises asymptotically for certain occupation statistics of a critical BRW conditioned on non-extinction

  • Their result is closely related to the classical theorem of Yaglom [13], which says that the distribution of the size of a critical Galton-Watson process, properly scaled and conditioned on non-extinction, converges to the exponential distribution

Read more

Summary

Introduction

Branching random walk (BRW) is a fundamental mathematical model of a population evolving in time and space, which has been intensely studied for more than 50 years due to its connection to population genetics and superprocesses; see, e.g., [1, Chapter 9] and references. To construct Mn(j) conditional on Zn > 0, first generate Tn from the size-bias tree section above Since this tree is distributed as the Galton-Watson tree given Zn > 0, we construct the conditional BRW by attaching a random direction to each offspring, chosen uniformly and independently from the 2d + 1 available directions for the nearest-neighbor random walk. Zm, let Zni ,m be the number of generation n offspring of the ith particle in generation m of the modified BRW construction; here the labelling is left to right (so particle 1 is always the marked particle), and note these are distributed as the sizes of the (n − m)th generations of i.i.d. Galton-Watson trees with offspring distribution L (X).

Laplace distribution approximation
CLT with error
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call