Stochastic Deformations of Sample Paths of Random Walks and Exclusion Models

TL;DR

This paper investigates stochastic deformations of random walk paths within multi-type exclusion particle systems, identifying conditions for reversibility, phase transitions, and linking limiting behaviors to nonlinear differential equations.

Contribution

It provides necessary and sufficient conditions for reversibility, explores phase transition scalings, and connects the dynamics to nonlinear differential systems like Lotka-Volterra.

Findings

Reversibility characterized by Gibbs measures.

Identification of phase transition scalings.

Limiting trajectories solve nonlinear differential equations.

Abstract

This study in centered on models accounting for stochastic deformations of sample paths of random walks, embedded either in $\mathbb{Z}^2$ or in $\mathbb{Z}^3$. These models are immersed in multi-type particle systems with exclusion. Starting from examples, we give necessary and sufficient conditions for the underlying Markov processes to be reversible, in which case their invariant measure has a Gibbs form. Letting the size of the sample path increase, we find the convenient scalings bringing to light phase transition phenomena. Stable and metastable configurations are bound to time-periods of limiting deterministic trajectories which are solution of nonlinear differential systems: in the example of the ABC model, a system of Lotka-Volterra class is obtained, and the periods involve elliptic, hyper-elliptic or more general functions. Lastly, we discuss briefly the contour of a general approach allowing to tackle the transient regime via differential equations of Burgers' type.