The effective diffusion constant of stochastic processes with spatially periodic noise

TL;DR

This paper derives a general formula for the effective diffusion constant of stochastic processes with spatially periodic noise, accounting for different discretization schemes and including drift, with analytical and numerical validation.

Contribution

It provides a unified derivation of the effective diffusion constant for spatially periodic noise, valid for any discretization rule and including drift effects, extending previous results like the Lifson-Jackson theorem.

Findings

Derived a general expression for $D_{eff}$ valid for any discretization parameter $eta$.

Established a relationship between $D_{eff}$ and Legendre functions for sinusoidal diffusion.

Validated results through analytical and numerical calculations on periodic drift and diffusion models.

Abstract

We discuss the effective diffusion constant $D_{{\it eff}}$ for stochastic processes with spatially-dependent noise. Starting from a stochastic process given by a Langevin equation, different drift-diffusion equations can be derived depending on the choice of the discretization rule $ 0 \leq \alpha \leq 1$. We initially study the case of periodic heterogeneous diffusion without drift and we determine a general result for the effective diffusion coefficient $D_{{\it eff}}$, which is valid for any value of $\alpha$. We study the case of periodic sinusoidal diffusion in detail and we find a relationship with Legendre functions. Then, we derive $D_{{\it eff}}$ for general $\alpha$ in the case of diffusion with periodic spatial noise and in the presence of a drift term, generalizing the Lifson-Jackson theorem. Our results are illustrated by analytical and numerical calculations on generic periodic choices for drift and diffusion terms.