Asymptotics of Green functions for Markov-additive processes: an approach via dyadic splitting of integrals

TL;DR

This paper derives the asymptotic behavior of Green functions for Markov-additive processes on integer lattices, generalizing classical results to non-homogeneous cases using dyadic integral splitting and Fourier analysis techniques.

Contribution

It provides a new proof of Green function asymptotics for Markov-additive processes, extending Ney and Spitzer's theorem to non-homogeneous settings with a novel dyadic splitting approach.

Findings

Asymptotic equivalent of the Green function derived

Generalization of Ney and Spitzer's theorem to non-homogeneous processes

Application of dyadic splitting of integrals for Fourier analysis

Abstract

We consider a discrete Markov-additive process, that is a Markov chain on a state space $\mathbb{Z}^d \times E$ with invariant jumps along the $\mathbb{Z}^d$ component. In the case where the set $E$ is finite, we derive an asymptotic equivalent of the Green function of the process, providing a new proof of a result obtained by Dussaule in 2020. This result generalizes the famous theorem of Ney and Spitzer of 1966, that deals with the sum of independent and identically distributed random variables, to a spatially non-homogeneous case. In this new proof, we generalize the arguments used in Woess's book Random Walks on Infinite Graphs and Groups to prove Ney and Spitzer's theorem, that consists in establishing an integral formula of the Green function from which we get the asymptotic equivalent. To do so, we use techniques developed by Babillot. In particular, we use dyadic splitting of integrals, a powerful Fourier analysis tool that enables us to control the Fourier transform of a function that has a singularity at the origin.