Random Diffusion Model with Structure Corrections

TL;DR

This paper extends the random diffusion model to include a more natural cutoff, investigates its dynamic features like slowing down and prepeak development, and proposes a method to detect hidden prepeaks in experimental data.

Contribution

The authors generalize the random diffusion model with a large-wavenumber cutoff and analyze its dynamic features, including a new method for identifying hidden prepeaks.

Findings

Slowing down of the system observed

Development of a prepeak in the dynamic structure factor

Method for detecting hidden prepeaks in experimental data

Abstract

The random diffusion model is a continuum model for a conserved scalar density field driven by diffusive dynamics where the bare diffusion coefficient is density dependent. We generalize the model from one with a sharp wavenumber cutoff to one with a more natural large-wavenumber cutoff. We investigate whether the features seen previously -- namely a slowing down of the system and the development of a prepeak in the dynamic structure factor at a wavenumber below the first structure peak -- survive in this model. A method for extracting information about a hidden prepeak in experimental data is presented.