Learning general pair interactions between self-propelled particles

TL;DR

This paper employs Stochastic Force Inference to learn and validate complex pair interactions in active matter systems, revealing the dominant hydrodynamic nature of these interactions through experimental data and simulations.

Contribution

It introduces a method to infer general pair interactions, including transverse forces and torques, from experimental trajectories of self-propelled particles, highlighting the hydrodynamic component.

Findings

Radial interactions are mostly repulsive and isotropic.

Angular interactions exhibit complex angular dependence.

Interactions cannot be solely electrostatic, indicating hydrodynamic effects.

Abstract

Synthetic active matter systems, such as active colloids, often have complex interactions, which can be of hydrodynamic, chemical or electrostatic origin and cannot be computed from first principles. Here, we use Stochastic Force Inference to learn general pair interactions, including transverse forces and torques, between self-propelled Janus particles from experimental trajectories. We use data from two experiments: one where the particles flock, and one where the system remains disordered. The learned interactions are then fed to numerical simulations, which reproduce all the experimental observables and could be extrapolated to different densities. Overall, we find that the radial interaction is mostly repulsive and isotropic, while the angular interaction has a richer angular dependence, which controls the behavior of the system; the transverse interaction is negligible. Finally, testing the symmetry relations obeyed by the inferred interactions allows us to show that they cannot come from electrostatics only, so that they must have a hydrodynamic component.