Diffusion of inhomogeneous populations - a computational study

A system made up of a homogeneous population of identical objects undergoing Brownian motion can be precisely characterized by an average diffusion coefficient. A multicomponent (two or more) system can also be characterized by an average diffusion coefficient, but in this case the measurement and interpretation of that diffusion coefficient represents a mixture of different dynamics. At the microscopic scale, similar objects are expected to diffuse at similar rates (determined by thermal noise), but at the macroscopic scale Brownian-like "diffusion" of particles (e.g. hexbugs) is driven by active noise and may differ even for similar-sized objects. We study a variety of systems made up of inhomogeneous populations undergoing diffusion using a simple computational approach. We analyze their motion using Dynamic Differential Microscopy as well as single particle tracking. We characterize the dynamics of these systems using two statistics, namely Mean Squared Displacement (MSD) and Mean Back Relaxation (MBR). We relate these statistics to the diffusion coefficient.