Clustering and finite size effects in a two-species exclusion process

TL;DR

This paper analyzes the cluster size distribution in a two-species exclusion process with asymmetric transport and stochastic switching, revealing different regimes and scaling behaviors depending on the ratio of translation to switching rates.

Contribution

It provides a detailed characterization of cluster size distributions and scaling laws in a two-species exclusion process, connecting to persistent exclusion processes and active particle systems.

Findings

Cluster size distribution is exponential for small Q, similar to TASEP.

Average cluster size scales as Q^{1/2} for large Q.

Probability of the largest cluster exhibits scaling collapse with system parameters.

Abstract

We study the cluster size distribution of particles for a two-species exclusion process which involves totally asymmetric transport process of two oppositely directed species with stochastic directional switching of the species on a 1D lattice. As a function of $Q$ - the ratio of the translation rate and directional switching rate of particles, in the limit of $Q \rightarrow 0$, the probability distribution of the cluster size is an exponentially decaying function of cluster size $m$ and is exactly similar to the cluster size distribution of a TASEP. For $Q>>1$, the model can be mapped to persistent exclusion process (PEP) and the average cluster size, $\langle m \rangle \propto Q^{1/2} $. We obtain an approximate expression for the average cluster size in this limit. For finite system size system of $L$ lattice sites, for a particle number density $\rho$, the probability distribution of cluster sizes exhibits a distinct peak which corresponds to the formation of a single cluster of size $m_s = \rho L$. However this peak vanishes in the thermodynamic limit $ L \rightarrow \infty$. Interestingly, the probability of this largest size cluster, $P(m_s)$, exhibits scaling behaviour such that in terms of scaled variable $Q_1 \equiv Q/L^2 \rho(1-\rho)$, data collapse is observed for the probability of this cluster. The statistical features related to clustering observed for this minimal model may also be relevant for understanding clustering characteristics in {\it active } particles systems in confined 1D geometry.