Run, Tumble and Paint

TL;DR

This paper develops a field-theoretic approach to calculate state-dependent visit probabilities for Run-and-Tumble particles, revealing how internal states influence first passage times and coverage in active matter.

Contribution

It introduces a novel field-theoretic method to analyze state-dependent visit probabilities for active particles, extending previous tracer models to include internal state tracking.

Findings

Derived explicit expressions for state-dependent visit probabilities.

Connected active particle behavior to classical Brownian motion results.

Provided a framework for analyzing coverage and first passage in active matter.

Abstract

The visit probability, quantifying whether a particle has reached a given point for the first time by a specified time, provides access to various extreme value statistics and serves as a fundamental tool for characterising active matter models. However, previous studies have largely neglected how the visit probability depends on the internal degree of freedom driving the active particle. To address this, we calculate the "state-dependent'' visit probability for a Run-and-Tumble particle, that is the probability that the particle first passes through $x$ before time $t$, keeping track of its internal state during first passage. This process may be thought of as the particle "painting'' the positions it passes through for the time in the colour of its self-propulsion state. We perform this calculation in one dimension using Doi-Peliti field theory, by extending the tracer mechanism from previous works to incorporate such "polar deposition'' and demonstrate that state-dependent visit probabilities can be elegantly captured within this field-theoretic framework. We further derive the total volume covered by a right- (or left-) moving Run-and-Tumble particle and compare our results with known expressions for Brownian motion.