A random walker on a ratchet potential: Effect of a non Gaussian noise

TL;DR

This paper investigates how colored non-Gaussian noise influences a random walker in a ratchet potential, revealing enhanced current effects and optimal noise conditions relevant to biological motors and technological applications.

Contribution

It introduces the impact of correlated non-Gaussian noise on ratchet models, extending previous white noise studies to more realistic noise conditions.

Findings

Identification of a second optimal current value due to non-Gaussian noise

Enhanced transport current when departing from Gaussian behavior

Relevance to biological motor proteins and technological systems

Abstract

We analyze the effect of a colored non Gaussian noise on a model of a random walker moving along a ratchet potential. Such a model was motivated by the transport properties of motor proteins, like kinesin and myosin. Previous studies have been realized assuming white noises. However, for real situations, in general we could expect that those noises be correlated and non Gaussian. Among other aspects, in addition to a maximum in the current as the noise intensity is varied, we have also found another optimal value of the current when departing from Gaussian behavior. We show the relevant effects that arise when departing from Gaussian behavior, particularly related to current's enhancement, and discuss its relevance for both biological and technological situations.