Kinetics of self-induced aggregation of Brownian particles: Non-Markovian and non-Gaussian features

Abstract

In this paper we have explored a model for self-induced aggregation of Brownian particles incorporating non-Markovian and non-Gaussian character of the associated random noise processes. The time evolution of each individual is guided by an overdamped Langevin equation of motion with a nonlocal drift arising out of the imbalance in the local distribution of the other individuals. Our simulation results show that colored noise enhances the tendency of cluster formation. Another observation is that the critical noise variance decreases at first with increase in noise correlation time followed by an increase after exhibiting a minimum. Furthermore, in the long time limit the cluster number in the aggregation process exhibits depletion with time following a power law with an exponent which increases remarkably with non-Markovian character of the noise processes.