Number fluctuations distinguish different self-propelling dynamics

TL;DR

This paper develops a theory to extract dynamic parameters of self-propelled particle models from number fluctuation signals, enabling differentiation of models based on subtle reorientation dynamics in dense nonequilibrium suspensions.

Contribution

It introduces a novel approach to analyze number fluctuations for understanding self-propelling particle dynamics, surpassing traditional trajectory-based methods.

Findings

Number fluctuations can distinguish different self-propelling models.

The theory captures subtle reorientation dynamics affecting number re-entrance events.

This approach enables quantification of complex dynamic features in dense suspensions.

Abstract

In nonequilibrium suspensions, static number fluctuations $N$ in virtual observation boxes reveal remarkable structural properties, but the dynamic potential of $N(t)$ signals remains unexplored. Here, we develop a theory to learn the dynamical parameters of self-propelled particle models from $N(t)$ statistics. Unlike traditional trajectory analysis, $N(t)$ statistics distinguish between models, by sensing subtle differences in reorientation dynamics that govern re-entrance events in boxes. This paves the way for quantifying advanced dynamic features in dense nonequilibrium suspensions.