Memory-Induced Transport and Arrest in Flashing Ratchets: From Superdiffusion to Clustering

TL;DR

This paper explores how memory effects in colored noise influence particle transport in flashing ratchets, revealing a transition from superdiffusion to clustering that suppresses current in confined, crowded systems.

Contribution

It introduces a non-Markovian noise model in flashing ratchets and uncovers a novel transition from superdiffusive transport to clustering in single-file regimes.

Findings

Memory effects enhance current in non-interacting particles.

In single-file systems, noise induces clustering and suppresses net current.

Universal scaling behavior observed for mean square displacement across densities.

Abstract

We investigate the transport properties of particles driven by colored noise in a flashing ratchet potential, focusing on both non-interacting and single-file interacting regimes. The model incorporates memory effects via a non-Markovian friction kernel, leading to superdiffusive dynamics and enhanced currents in the absence of interactions. However, when particles are constrained to single-file motion with hard-core repulsion, the same non-Markovian noise induces a dynamical transition: initial superdiffusion gives way to the formation of static clusters, ultimately suppressing net current. This transition occurs without a critical density and results from the interplay between noise persistence and the ratchet's potential. Our numerical results reveal a universal scaling behavior for the mean square displacement across densities, suggesting robustness of the clustering mechanism. These findings have potential implications for transport in crowded or confined systems such as colloidal suspensions, molecular motors in cellular environments, or microfluidic devices, where controlling noise and crowding can be used to tune transport efficiency.