Dynamical crossovers and correlations in a harmonic chain of active particles

TL;DR

This paper investigates the dynamics of a tracer in an active particle harmonic chain, revealing various diffusion regimes, distribution transitions, and correlation behaviors through analytic and numerical methods.

Contribution

It provides new analytic expressions for crossovers in MSD, distribution shapes, and displacement correlations in active harmonic chains with different time scales.

Findings

Tagged-particle MSD shows ballistic, diffusive, and SFD scaling with crossovers.

Distribution transitions from bimodal to Gaussian with regimes of finite support and negative kurtosis.

Steady-state correlations match simulations and converge to equilibrium at low persistence.

Abstract

We explore the dynamics of a tracer in an active particle harmonic chain, investigating the influence of interactions. Our analysis involves calculating mean-squared displacements (MSD) and space-time correlations through Green's function techniques and numerical simulations. Depending on chain characteristics, i.e., different time scales determined by interaction stiffness and persistence of activity, tagged-particle MSD exhibit ballistic, diffusive, and single-file diffusion (SFD) scaling over time, with crossovers explained by our analytic expressions. Our results reveal transitions in bulk particle displacement distributions from an early-time bimodal to late-time Gaussian, passing through regimes of unimodal distributions with finite support and negative excess kurtosis and longer-tailed distributions with positive excess kurtosis. The distributions exhibit data collapse, aligning with ballistic, diffusive, and SFD scaling in the appropriate time regimes. However, at much longer times, the distributions become Gaussian. Finally, we derive expressions for steady-state static and dynamic two-point displacement correlations, consistent with simulations and converging to equilibrium results for small persistence. Additionally, the two-time stretch correlation extends to longer separation at later times, while the autocorrelation for the bulk particle shows diffusive scaling beyond the persistence time.