A Data-Driven Statistical Description for the Hydrodynamics of Active Matter
arXiv:2103.03461 · doi:10.1088/1367-2630/ac23c4
Abstract
Modeling living systems at the collective scale can be very challenging because the individual constituents can themselves be complex and the respective interactions between the constituents are not fully understood. With the advent of high throughput experiments and in the age of big data, data-driven methods are on the rise to overcome these challenges. To directly uncover the underlying physical principles, we present a data-driven method for obtaining the phase-space density such that the solution to the stochastic dynamic equation for active matter readily emerges, from which time and space dependence of physical order parameters can be readily extracted. If the system is near a steady state, we illuminate how to construct a field theory to subsequently make physical predictions about the system. The method is first developed analytically and subsequently calibrated using simulated data. The method is then applied to an experimental system of particles actively driven by a {\it Serratia marcescens} bacterial swarm and in the presence of spatially localized UV light. The analysis demonstrates that the particles are in the steady-state before and sometime after the UV light and obey a Gaussian field theory with a spatially-varying "mass" in those regimes. This novel, yet simple, finding is surprising given the complex dynamics of the bacterial swarm. In response to the UV light, we demonstrate that there is a net flow of the particles away from the UV light and that the entropy of the particles increases away from the light. We conclude with a discussion of additional potential applications of our data-driven method such as when the internal structure of the individual constituents dynamically changes to result in a modified stochastic dynamic equation governing the system.
15 pages, 9 figures, comments are welcome
References in corpus (13)
- Meso-scale turbulence in living fluids
- Hydrodynamic equations for self-propelled particles: microscopic derivation and stability analysis
- Phototaxis of synthetic microswimmers in optical landscapes
- Enhanced diffusion and ordering of self-propelled rods
- Hydrodynamics of self-propelled hard rods
- Nonequilibrium equation of state in suspensions of active colloids
- Data-driven quantitative modeling of bacterial active nematics
- Boltzmann-Ginzburg-Landau approach for continuous descriptions of generic Vicsek-like models
- Light-switchable propulsion of active particles with reversible interactions
- Swarming, swirling and stasis in sequestered bristle-bots
- From scalar to polar active matter: Connecting simulations with mean-field theory
- Numerical treatment of the Boltzmann equation for self-propelled particle systems
- Phase-space structures I: A comparison of 6D density estimators