Pattern, Growth and Aging in a Colony of Clustering Active Swimmers

TL;DR

This study uses molecular dynamics simulations to analyze pattern formation, growth, and aging in active matter, revealing self-similar dynamics, power-law growth, and significant differences from passive systems due to rapid particle motion.

Contribution

It provides the first detailed quantitative analysis of pattern kinetics in active matter, highlighting unique scaling behaviors and growth laws distinct from passive phase separation.

Findings

Pattern formation exhibits self-similarity and power-law growth.

Correlation functions follow scaling laws with Porod law agreement.

Active particles show rapid growth and multiple displacement regimes.

Abstract

Via molecular dynamics simulations, we study the kinetics in a phase separating active matter model. Quantitative results for the isotropic bicontinuous pattern formation, its growth and aging, studied, respectively, via the two-point equal-time density-density correlation function, the average domain length and the two-time density autocorrelation function, are presented. Both the correlation functions exhibit basic scaling properties, implying self-similarity in the pattern dynamics, for which the average domain size exhibits a power-law growth in time. The equal-time correlation has a short distance behavior that provides reasonable agreement of the corresponding structure factor tail with the Porod law. The autocorrelation decay is a power-law in the average domain size. Apart from these basic similarities, the quantitative behavior of the above mentioned observables are found to be vastly different from those of the corresponding passive limit of the model which also undergoes phase separation. The functional forms of these have been quantified. An exceptionally rapid growth in the active system occurs due to fast coherent motion of the particles, mean-squared-displacements of which exhibit multiple scaling regimes, including a long time ballistic one.