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Multiscale Modeling & Simulation / Volume 6 / Issue 1

Multiscale Model. Simul. 6, pp. 70-89 (20 pages)

Variance Reduction for the Equation‐Free Simulation of Multiscale Stochastic Systems

Anastasia Papavasiliou and Ioannis G. Kevrekidis

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We study the problem of simulating the slow observable of a multiscale diffusion process. In particular, we extend previous algorithms to the case where the simulation of the different scales cannot be uncoupled and we have no explicit knowledge of the drift or the variance of the multiscale diffusion. This is the case when the simulation data come from a black box “legacy code,” or possibly from a fine scale simulator (e.g., MD, kMC) which we want to effectively model as a diffusion process. We improve the algorithm, using the past simulations as control variates, in order to reduce the variance of the subsequent simulations.

© 2007 Society for Industrial and Applied Mathematics

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KEYWORDS

AMS Subject Headings

60J60, 65C05, 34E13

PUBLICATION DATA

ISSN

1540-3459 (print)  
1540-3467 (online)

Publisher

$abstract.society.value is a Member of CrossRef Society for Industrial and Applied Mathematics

ARTICLE DATA

History
Received January 23, 2006
Accepted October 13, 2006
Published online February 02, 2007
Digital Object Identifier
http://dx.doi.org/10.1137/060650635

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