Non-equilibrium dynamics of isostatic spring networks

TL;DR

This paper explores how the critical isostatic point influences the non-equilibrium behavior of active spring networks, revealing critical scaling in their dynamics through a mean-field theoretical approach.

Contribution

It introduces a theoretical framework to understand the non-equilibrium dynamics of active isostatic networks and identifies critical scaling behavior.

Findings

Distribution of cycling frequencies exhibits critical scaling.

Mean-field approach successfully describes the critical behavior.

Active noise drives the system into a non-equilibrium steady state.

Abstract

Marginally stable systems exhibit rich critical mechanical behavior. Such isostatic assemblies can be driven out of equilibrium by internal activity, but it remains unclear how the isostatic and critical nature of such systems affects their non-equilibrium dynamics. Here, we investigate the influence of the isostatic threshold on the non-equilibrium dynamics of active diluted spring networks. In our model, heterogeneously distributed active noise sources drive the system into a non-equilibrium steady state. We quantify the non-equilibrium dynamics of nearest-neighbor network nodes by the characteristic cycling frequency $\omega$---a measure of the circulation of the associated phase space currents. The distribution of these nearest-neighbor cycling frequencies exhibits critical scaling, which we describe using a mean-field approach. Overall, our work provides a theoretical approach to elucidate the role of marginality in active disordered systems.