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Optimal Prediction in Molecular Dynamics

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  • Seibold Benjamin

Abstract

Optimal prediction approximates the average solution of a large system of ordinary differential equations by a smaller system. We present how optimal prediction can be applied to a typical problem in the field of molecular dynamics, in order to reduce the number of particles to be tracked in the computations. We consider a model problem, which describes a surface coating process, and show how asymptotic methods can be employed to approximate the high dimensional conditional expectations, which arise in optimal prediction. The thus derived smaller system is compared to the original system in terms of statistical quantities, such as diffusion constants. The comparison is carried out by Monte-Carlo simulations, and it is shown under which conditions optimal prediction yields a valid approximation to the original system.

Suggested Citation

  • Seibold Benjamin, 2004. "Optimal Prediction in Molecular Dynamics," Monte Carlo Methods and Applications, De Gruyter, vol. 10(1), pages 25-50, March.
    • Handle: RePEc:bpj:mcmeap:v:10:y:2004:i:1:p:25-50:n:2
    DOI: 10.1515/156939604323091199
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    References listed on IDEAS

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    1. Chorin Alexandre J. & Hald Ole H. & Kupferman Raz, 2001. "Non-Markovian Optimal Prediction," Monte Carlo Methods and Applications, De Gruyter, vol. 7(1-2), pages 99-110, December.
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