Pattern Formation in Driven Particulate Suspensions

Systems that are driven by energy from external sources are ubiquitous, and the rich phenomenology they display (e.g., ordered phases and pattern formation of bacteria, or nanoparticles in a fluid) is described by physical models that do not rely on conventional equilibrium physics. We study theoretically and computationally a class of such active-matter models with self-propelled motion and interactions and classify the resulting non-equilibrium ordered states using techniques from statistical physics.