We develop a numerical algorithm for computing the effective drift and diffusivity of the steady-state behavior of an overdamped particle driven by a periodic potential whose amplitude is modulated in time by multiplicative noise and forced by additive Gaussian noise (the mathematical structure of a flashing Brownian motor). The numerical algorithm is based on a spectral decomposition of the solutions to two equations arising from homogenization theory: the stationary Fokker-Planck equation with periodic boundary conditions and a cell problem taking the form of a generalized Poisson equation. We also show that the numerical method of Wang, Peskin, Elston (WPE, 2003) for computing said quantities is equivalent to that resulting from ho-✩ The research of JCL was supported by the DFG Research Center Matheon "Mathematics for Key Technologies" (FZT86) in Berlin and partially supported by NSF CAREER grant DMS-0449717. The work of PRK was partially supported by NSF CAREER grant DMS-0449717. PRK wishes to thank the Zentrum für Interdisziplinäre Forschung (ZiF) for its hospitality and support during its "Stochastic Dynamics: Mathematical Theory and Applications" program, at which part of this work was completed. The research of GP is partially supported by the EPSRC, Grant No. EP/H034587 and EP/J009636/1. GP wishes to thank the Biocomputing group at the Institute of Mathematics, FU Berlin for its hospitality and support during a visit at which part of this work was completed.* Corresponding author: Phone +001 (518) 276-6896, Fax +001 (518) 276-4824 Email addresses: jlatorre@zedat.fu-berlin.de (Juan C. Latorre), kramep@rpi.edu (Peter R. Kramer), g.pavliotis@imperial.ac.uk (Grigorios A. Pavliotis)
Preprint submitted to Journal of Computational PhysicsJanuary 25, 2018 mogenization theory. We show how to adapt the WPE numerical method to this problem by means of discretizing the multiplicative noise via a finitevolume method into a discrete-state Markov jump process which preserves many important properties of the original continuous-state process, such as its invariant distribution and detailed balance. Our numerical experiments show the effectiveness of both methods, and that the spectral method can have some efficiency advantages when treating multiplicative random noise, particularly with strong volatility.