Scarce defects induce anomalous deterministic diffusion

TL;DR

This paper models particles moving in a disordered medium with scarce defects, revealing a transition from normal to anomalous diffusion based on defect scarcity, and provides analytical and numerical insights into the diffusion regimes.

Contribution

The study introduces a simple deterministic particle model with heavy-tailed defect distributions, identifying a transition from normal to anomalous diffusion and deriving analytical expressions for diffusion behavior.

Findings

Transition from normal to anomalous diffusion as defect scarcity increases

Analytical expressions for diffusion coefficients and exponents in different regimes

Numerical simulations confirm theoretical predictions

Abstract

We introduce a simple model of deterministic particles in weakly disordered media which exhibits a transition from normal to anomalous diffusion. The model consists of a set of non-interacting overdamped particles moving on a disordered potential. The disordered potential can be thought as a substrate having some "defects" scattered along a one-dimensional line. The distance between two contiguous defects is assumed to have a heavy-tailed distribution with a given exponent $\alpha$, which means that the defects along the substrate are scarce if $\alpha$ is small. We prove that this system exhibits a transition from normal to anomalous diffusion when the distribution exponent $\alpha$ decreases, i.e., when the defects become scarcer. Thus we identify three distinct scenarios: a normal diffusive phase for $\alpha>2$, a superdiffusive phase for $1/2<\alpha\leq 2$, and a subdiffusive phase for $\alpha \leq 1/2$. We also prove that the particle current is finite for all the values of $\alpha$, which means that the transport is normal independently of the diffusion regime (normal, subdiffusive, or superdiffusive). We give analytical expressions for the effective diffusion coefficient for the normal diffusive phase and analytical expressions for the diffusion exponent in the case of anomalous diffusion. We test all these predictions by means of numerical simulations.