Non Gaussian information of heterogeneity in Soft Matter

TL;DR

This paper introduces an information-theoretic measure to quantify non-Gaussian heterogeneity in soft matter, demonstrating its superiority over traditional moment-based methods in two generic random walk scenarios.

Contribution

It proposes a novel information-theoretic approach for quantifying non-Gaussian heterogeneity in soft matter dynamics, improving upon existing methods.

Findings

The measure effectively captures heterogeneity in molecular displacements.

It outperforms conventional moment ratio methods in quantifying non-Gaussianity.

The approach is validated in two generic random walk scenarios.

Abstract

Heterogeneity in dynamics in the form of non-Gaussian molecular displacement distributions appears ubiquitously in soft matter. We address the quantification of such heterogeneity using an information-theoretic measure of the distance between the actual displacement distribution and its nearest Gaussian estimation. We explore the usefulness of this measure in two generic scenarios of random walkers in heterogeneous media. We show that our proposed measure leads to a better quantification of non-Gaussianity than the conventional ones based on moment ratios.