Generalized persistence dynamics for active motion

TL;DR

This paper develops a general theoretical framework for active particle motion that incorporates persistence through a memory function, enabling analytical predictions of key statistical measures without relying on explicit orientational dynamics models.

Contribution

It introduces a novel formalism using a two-time memory function to describe persistence in active motion, applicable in arbitrary dimensions, and derives analytical expressions for observable quantities.

Findings

Analytical formulas for the intermediate scattering function.

Derived mean-squared displacement over time.

Kurtosis behavior in active motion patterns.

Abstract

We analyze the statistical physics of self-propelled particles from a general theoretical framework that properly describes the most salient characteristic of active motion, $persistence$, in arbitrary spatial dimensions. Such a framework allows the development of a Smoluchowski-like equation for the probability density of finding a particle at a given position and time, without assuming an explicit orientational dynamics of the self-propelling velocity as Langevin-like equation-based models do. Also, the Brownian motion due to thermal fluctuations and the active one due to a general intrinsic persistent motion of the particle are taken into consideration on an equal footing. The persistence of motion is introduced in our formalism in the form of a \emph{two-time memory function}, $K(t,t^{\prime})$. We focus on the consequences when $K(t,t^{\prime})\sim (t/t^{\prime})^{-\eta}\exp[-\Gamma(t-t^{\prime})]$, $\Gamma$ being the characteristic persistence time, and show that it precisely describes a variety of active motion patterns characterized by $\eta$. We find analytical expressions for the experimentally obtainable intermediate scattering function, the time dependence of the mean-squared displacement, and the kurtosis.