Mode selection in compressible active flow networks

TL;DR

This paper introduces an analytically tractable nonlinear model for compressible active flow networks, revealing how active friction selects discrete oscillation modes and predicting stationary states with good accuracy.

Contribution

The study presents a novel nonlinear model for active flow networks that predicts mode selection and stationary states, contrasting with thermal systems and applicable to various active matter phenomena.

Findings

Active friction leads to discrete mode selection.

Perturbation theory accurately predicts stationary states.

Active networks can be dominated by few modes, unlike thermal systems.

Abstract

Coherent, large scale dynamics in many nonequilibrium physical, biological, or information transport networks are driven by small-scale local energy input. Here, we introduce and explore an analytically tractable nonlinear model for compressible active flow networks. In contrast to thermally-driven systems, we find that active friction selects discrete states with a limited number of oscillation modes activated at distinct fixed amplitudes. Using perturbation theory, we systematically predict the stationary states of noisy networks and find good agreement with a Bayesian state estimation based on a hidden Markov model applied to simulated time series data. Our results suggest that the macroscopic response of active network structures, from actomyosin force networks to cytoplasmic flows, can be dominated by a significantly reduced number of modes, in contrast to energy equipartition in thermal equilibrium. The model is also well-suited to study topological sound modes and spectral band gaps in active matter.