Exploring, exploiting, and ignoring history dependence in active droplet simulations

Active droplets are an appealing model system for studying self-propelled particles because of their high symmetry and simple composition. Nonetheless, their mechanism of action is complex - they are driven by a self-maintained concentration gradient that results in history-dependent motion.

This talk presents several formulations of this system which can be used to analyze and simulate active droplet systems. From these we establish how spherical droplets can emulate persistent motion of polar swimmers by storing orientation information in their local emission cloud. We show that this simplified picture of a droplet's dynamics is sufficient to describe its response to an external potential or time-dependent force.

Simulations of interacting droplets suggest that Vicsek-like variables are sufficient to describe the system's state. However, the pairwise interactions between particles are can be highly anisotropic and asymmetric, reflecting the system's history dependence at higher Péclet numbers.