从近似辅助动力学中得出非平衡定态的精确涨落。

Exact Fluctuations of Nonequilibrium Steady States from Approximate Auxiliary Dynamics.

机构信息

Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, California 91125, USA.

Department of Chemistry, University of California, Berkeley, California 94609, USA; Kavli Energy NanoScience Institute, Berkeley, California 94609, USA; and Materials Science Division, Lawrence Berkeley National Laboratory, Berkeley, California 94609, USA.

出版信息

Phys Rev Lett. 2018 May 25;120(21):210602. doi: 10.1103/PhysRevLett.120.210602.

DOI:10.1103/PhysRevLett.120.210602

PMID:29883166

Abstract

We describe a framework to reduce the computational effort to evaluate large deviation functions of time integrated observables within nonequilibrium steady states. We do this by incorporating an auxiliary dynamics into trajectory based Monte Carlo calculations, through a transformation of the system's propagator using an approximate guiding function. This procedure importance samples the trajectories that most contribute to the large deviation function, mitigating the exponential complexity of such calculations. We illustrate the method by studying driven diffusion and interacting lattice models in one and two spatial dimensions. Our work offers an avenue to calculate large deviation functions for high dimensional systems driven far from equilibrium.

摘要

我们描述了一种框架，用于降低评估非平衡稳态中时间积分可观测量的大偏差函数的计算工作量。我们通过使用近似引导函数对系统的传播子进行变换，在基于轨迹的蒙特卡罗计算中引入辅助动力学来实现这一点。该过程通过重要性采样对大偏差函数贡献最大的轨迹，减轻了此类计算的指数复杂度。我们通过研究一维和二维的驱动扩散和相互作用晶格模型来说明该方法。我们的工作为计算远离平衡驱动的高维系统的大偏差函数提供了一种途径。