Right-Most Position of a Last Progeny Modified Time Inhomogeneous Branching Random Walk

TL;DR

This paper studies a modified inhomogeneous branching random walk where the maximum displacement converges to a limit influenced only by initial increments, with results on point process convergence to a decorated Poisson process.

Contribution

It introduces the last progeny modified time inhomogeneous branching random walk (LPMTI-BRW) and establishes convergence results for maximum displacement and point processes under minimal assumptions.

Findings

Maximum displacement converges to a limit after linear or logarithmic correction.

Limiting distribution depends only on the first set of increments.

Point process converges to a decorated Poisson point process.

Abstract

In this work, we consider a modification of time \emph{inhomogeneous} branching random walk, where the driving increment distribution changes over time macroscopically. Following Bandyopadhyay and Ghosh (2021), we give certain independent and identically distributed (i.i.d.) displacements to all the particles at the last generation. We call this process \emph{last progeny modified time inhomogeneous branching random walk (LPMTI-BRW)}. Under very minimal assumptions on the underlying point processes of the displacements, we show that the maximum displacement converges to a limit after only an appropriate centering which is either linear or linear with a logarithmic correction. Interestingly, the limiting distribution depends only on the first set of increments. We also derive Brunet-Derrida-type results of point process convergence of our LPMTI-BRW to a decorated Poisson point process. As in the case of the maximum, the limiting point process also depends only on the first set of increments. Our proofs are based on the method of coupling the maximum displacement with the smoothing transformation, which was introduced by Bandyopadhyay and Ghosh (2021).