Multi-scale multi-species modeling of emergent flows andactive mixing in confined bacterial swarms

Autonomous collective motion of identical agents in nonequilibrium is fundamental to many biological and engineering systems. An example from biology is bacterial swarms, that are prototypical dense multi-phase active fluids. Here we present a new method for modeling such fluids under confinement. We use a continuum multiscale mean-field approach to represent each phase by its first three orientational moments, and couple their evolution with those of the suspending fluid. The resulting coupled system is solved using a parallel level set based hybrid Finite Difference-Finite Volume solver on Quadtree meshes for high computational efficiency and maximal flexibility in the confinement geometry. Motivated by recent experimental work, we employ our method to study emergent flows in bacterial swarms. Our computational exploration demonstrate that we can reproduce the observed emergent collective patterns including active dissolution and crystallization. This work lays the foundation for a systematic characterization of natural and synthetic systems such as bacterial colonies, bird flocks, fish schools, colloidal swimmers, or programmable active matter.