A model of non-Gaussian diffusion in heterogeneous media

TL;DR

This paper introduces an ergodic model of non-Gaussian diffusion in complex media, capturing the effects of fluctuating diffusivity observed in biological and physical systems, with detailed analysis of its statistical properties.

Contribution

It presents a new, interpretable diffusing diffusivity model that explains non-Gaussian displacement distributions in heterogeneous environments.

Findings

Displacement distributions can be flat or peaked with exponential tails.

The model's distribution converges slowly to Gaussian behavior.

Statistical properties and asymptotic behaviors are analytically derived.

Abstract

Recent progresses in single particle tracking have shown evidences of non-Gaussian distribution of displacements in living cells, both near the cellular membrane and inside the cytoskeleton. A similar behavior has also been observed in granular media, turbulent flows, gels, and colloidal suspensions, suggesting that this is a general feature of diffusion in complex media. A possible interpretation of this phenomenon is that a tracer explores a medium with spatio-temporal fluctuations which result in local changes of diffusivity. We propose and investigate an ergodic, easily interpretable model, which implements the concept of diffusing diffusivity. Depending on the parameters, the distribution of displacements can be either flat or peaked at small displacements with an exponential tail at large displacements. We show that the distribution converges slowly to a Gaussian one. We calculate statistical properties, derive the asymptotic behavior, and discuss some implications and extensions.