Stochastic transport of interacting particles in periodically driven ratchets.
An open system of overdamped, interacting Brownian particles diffusing on a periodic substrate potential U(x+l)=U(x) is studied in terms of an infinite set of coupled partial differential equations describing the time evolution of the relevant many-particle distribution functions. In the mean-field approximation, this hierarchy of equations can be replaced by a nonlinear integro-differential Fokker-Planck equation. This is applicable when the distance a between particles is much less than the interaction length lambda , i.e., a particle interacts with many others, resulting in averaging out fluctuations. The equation obtained in the mean-field approximation is applied to an ensemble of locally (a<<lambda<<l) interacting (either repelling or attracting) particles placed in an asymmetric one-dimensional substrate potential, either with an oscillating temperature (temperature rachet) or driven by an ac force (rocked ratchet). In both cases we focus on the high-frequency limit. For the temperature ratchet, we find that the net current is typically suppressed (or can even be inverted) with increasing density of the repelling particles. In contrast, the net current through a rocked ratchet can be enhanced by increasing the density of the repelling particles. In the case of attracting particles, our perturbation technique is valid up to a critical value of the particle density, above which a finite fraction of the particles starts condensing in a liquidlike state near the substrate minima. The dependence of the net transport current on the particle density and the interparticle potential is analyzed in detail for different values of the ratchet parameters.
Savel'ev
Sergey
S
Frontier Research System, The Institute of Physical and Chemical Research (RIKEN), Wako-shi, Saitama 351-0198, Japan.
Marchesoni
Fabio
F
Nori
Franco
F
D003198:Computer Simulation; D004058:Diffusion; D044085:Microfluidics / Q000379:methods*; D008956:Models, Chemical; D020409:Molecular Motor Proteins / Q000737:chemistry*; D010316:Particle Size; D010507:Periodicity; D013269:Stochastic Processes; D013314:Stress, Mechanical
D020409:Molecular Motor Proteins