caa a22 4500 378921177 CHVBK 20180305123605.0 cr unu---uuuuu 161128e20040301xx s 000 0 eng 10.1515/156939604323091199 doi (NATIONALLICENCE)gruyter-10.1515/156939604323091199 Seibold Benjamin Department of Mathematics, Technical University of Kaiserslautern, Gottlieb-Daimler-Straße, 67653 Kaiserslautern, Germany Optimal Prediction in Molecular Dynamics [Elektronische Daten] [Benjamin Seibold] 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. Copyright 2004, Walter de Gruyter Monte Carlo Methods and Applications Walter de Gruyter 10/1(2004-03-01), 25-50 0929-9629 10:1<25 2004 10 mcma https://doi.org/10.1515/156939604323091199 text/html Onlinezugriff via DOI 1 research article jats NATIONALLICENCE 856 40 https://doi.org/10.1515/156939604323091199 text/html Onlinezugriff via DOI NATIONALLICENCE 100 1- Seibold Benjamin Department of Mathematics, Technical University of Kaiserslautern, Gottlieb-Daimler-Straße, 67653 Kaiserslautern, Germany NATIONALLICENCE 773 0- Monte Carlo Methods and Applications Walter de Gruyter 10/1(2004-03-01), 25-50 0929-9629 10:1<25 2004 10 mcma CC0 http://creativecommons.org/publicdomain/zero/1.0 nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-gruyter