Renormalization of Drift and Diffusivity in Random Gradient Flows

TL;DR

This paper studies how the effective drift and diffusivity of particles in a random medium are renormalized, confirming theoretical predictions through numerical simulations, especially in isotropic and anisotropic cases.

Contribution

It provides a theoretical and numerical analysis of the renormalization of drift and diffusivity in random gradient flows, including anisotropic effects.

Findings

Effective diffusivity and drift are renormalized by the same factor in isotropic cases.

Numerical simulations confirm theoretical renormalization group calculations.

Anisotropic cases show similar renormalization behavior for tensors.

Abstract

We investigate the relationship between the effective diffusivity and effective drift of a particle moving in a random medium. The velocity of the particle combines a white noise diffusion process with a local drift term that depends linearly on the gradient of a gaussian random field with homogeneous statistics. The theoretical analysis is confirmed by numerical simulation. For the purely isotropic case the simulation, which measures the effective drift directly in a constant gradient background field, confirms the result previously obtained theoretically, that the effective diffusivity and effective drift are renormalized by the same factor from their local values. For this isotropic case we provide an intuitive explanation, based on a {\it spatial} average of local drift, for the renormalization of the effective drift parameter relative to its local value. We also investigate situations in which the isotropy is broken by the tensorial relationship of the local drift to the gradient of the random field. We find that the numerical simulation confirms a relatively simple renormalization group calculation for the effective diffusivity and drift tensors.