Variance Reduction in Stochastic Homogenization Using Antithetic Variables
نویسنده
چکیده
Some theoretical issues related to the problem of variance reduction in numerical approaches for stochastic homogenization are examined. On some simple, yet representative cases, it is demonstrated theoretically that a technique based on antithetic variables can indeed reduce the variance of the output of the computation, and decrease the overall computational cost of such a multiscale problem. The theoretical considerations presented here are companion to numerical experiments presented in [7, 16] that corroborate the theoretical results enclosed.
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