Factorised stationary states for a long range misanthrope process

TL;DR

This paper introduces a long-range misanthrope process model with inhomogeneous parameters, deriving conditions for factorised stationary distributions, and applies it to the discrete Hammersley--Aldous--Diaconis process.

Contribution

It provides necessary and sufficient conditions for factorised stationary states in a new long-range, inhomogeneous misanthrope process model, including asymmetric and symmetric variants.

Findings

Derived conditions for factorised stationary distributions.

Extended the model to include long-range and inhomogeneous interactions.

Applied the framework to the discrete Hammersley--Aldous--Diaconis process.

Abstract

The misanthrope process is an interacting particle system where particles move between neighbouring sites with hop rates depending only on the number of particles at the departure and arrival sites. Motivated by a discretised version of the Hammersley--Aldous--Diaconis process, we introduce a partially asymmetric long range misanthrope process (PALRMP) on a finite one-dimensional lattice with periodic boundary conditions where particles can move between sites that are not necessarily neighbours, as long as there are no particles in between the departure and arrival sites. In this model, each site $\ell$ has an inhomogeneous rate parameter $x_\ell$ associated to it, and the hop rate of a particle moving from site $k$ to site $\ell$ depends upon the parameter associated to the target site $x_\ell$, the direction the particle moves, and the number of particles at sites $k$ and $\ell$. We also consider the homogeneous PALRMP, where all the $x_\ell$'s are 1. We find necessary and sufficient conditions on the hop rates under which the stationary distribution is of factorised form for both the PALRMP and the homogeneous PALRMP, as well as the extreme variants, namely the ones where the particle motion is totally asymmetric (TALRMP) and symmetric (SLRMP). As an illustrative example, we study in detail the discrete Hammersley--Aldous--Diaconis process.