Rare transitions between collective states in an active fluid via a weakly nonlinear reduction

TL;DR

This paper models active fluid suspensions, analyzing bifurcations and rare transitions between collective states using a weakly nonlinear reduction and stochastic forcing, with results validated against full simulations.

Contribution

It introduces a low-dimensional amplitude equation framework incorporating stochastic forcing to study rare transitions in active fluids.

Findings

Identified bifurcation scenarios depending on particle swimming speed.

Derived analytical amplitude equations with stochastic forcing.

Quantified rare transition times and paths between collective states.

Abstract

We study a model for a dilute suspension of rod-like particles swimming at constant velocity in a Stokes flow. As the translational diffusivity of the particles decreases, a two-dimensional uniform concentration of randomly aligned particles undergoes either a codimension-2 pitchfork bifurcation or a codimension-4 Hopf bifurcation, depending on the particles' swimming speed. We use a weakly nonlinear expansion to reduce the system to a low-dimensional one for the amplitudes of the bifurcating eigenmodes. The originality of our calculations lies in incorporating spatio-temporal white noise forcing. The stochastic forcing terms in the amplitude equations are derived analytically from the noise acting on the original system. Past the onset of the bifurcations, the particles deterministically self-organize into steady or oscillating states of collective motion. For the Hopf bifurcation scenario, two stable periodic orbits are found to coexist, each corresponding to a distinct collective dynamics. The stochastic forcing induces rare transitions between them. Owing to the low dimensionality of amplitude equations, steady and dynamical statistics can be computed directly from the Fokker-Planck equation, or via the Adaptive Multilevel Splitting (AMS) rare-event algorithm. In particular, extremely long mean transition times and associated out-of-equilibrium paths between the periodic orbits are obtained. These paths can be understood in light of the invariant manifolds of the low-dimensional system, which brings insights into the mechanism behind the transitions. We also performed fully nonlinear stochastic simulations and used the AMS algorithm directly on the full system. The statistics are in good quantitative agreement with those computed on the reduced systems, the latter being obtained at a considerably lower numerical cost.