Generalized autocorrelation function in the family of deterministic and stochastic anomalous diffusion processes

TL;DR

This paper derives a generalized autocorrelation function for anomalous diffusion models, comparing deterministic and stochastic systems, and finds strong agreement between analytical and numerical results, revealing insights into their microscopic dynamics.

Contribution

It introduces an analytical form of the generalized position auto-correlation function for complex anomalous diffusion systems and compares it with numerical data, bridging deterministic and stochastic models.

Findings

Analytical derivation of the generalized position auto-correlation function.

Remarkable agreement between analytical and numerical 3-point correlations.

Position moments and auto-correlations scale similarly at large times.

Abstract

We investigate the observables of the one-dimensional model for anomalous transport in semiconductor devices where diffusion arises from scattering at dislocations at fixed random positions, known as L\'evy-Lorentz gas. To gain insight into the microscopic properties of such a stochastically complex system, deterministic dynamics known as the Slicer Map and Fly-and-Die dynamics are used. We analytically derive the generalized position auto-correlation function of these dynamics and study the special case, the $3$-point position correlation function. For this, we derive single parameter-dependent scaling and compare it with the numerically estimated $3$-point position auto-correlation of the L\'evy-Lorentz gas, for which the analytical expression is still an open question. Here we obtained a remarkable agreement between them, irrespective of any functional relationship with time. Moreover, we demonstrate that the position moments and the position auto-correlations of these systems scale in the same fashion, provided the times are large enough and far enough apart. Other observables, such as velocity moments and correlations, are reported to distinguish the systems.