Statistics of particle transport in a two-dimensional dusty plasma cluster

Abstract

Statistical analysis is performed on long time series of dust particle trajectories in a two-dimensional dusty plasma cluster. Particle transport is found to be superdiffusive on all time scales until the range of particle displacements approaches the size of the cluster. Analysis of probability distribution functions and rescaled range analysis of the position increments show that the signal is non-Gaussian self-similar with Hurst exponent H=0.6, indicating that the superdiffusion is caused by long-range dependencies in the system. Investigation of temporal and spatial characteristics of persistent particle slips demonstrates that they are associated with collective events present on all time scales and responsible for the non-Gaussianity and long-memory effects.