Optimal Prediction in Molecular Dynamics
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| 024 | 7 | 0 | |a 10.1515/156939604323091199 |2 doi |
| 035 | |a (NATIONALLICENCE)gruyter-10.1515/156939604323091199 | ||
| 100 | 1 | |a Seibold |D Benjamin |u Department of Mathematics, Technical University of Kaiserslautern, Gottlieb-Daimler-Straße, 67653 Kaiserslautern, Germany | |
| 245 | 1 | 0 | |a Optimal Prediction in Molecular Dynamics |h [Elektronische Daten] |c [Benjamin Seibold] |
| 520 | 3 | |a 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. | |
| 540 | |a Copyright 2004, Walter de Gruyter | ||
| 773 | 0 | |t Monte Carlo Methods and Applications |d Walter de Gruyter |g 10/1(2004-03-01), 25-50 |x 0929-9629 |q 10:1<25 |1 2004 |2 10 |o mcma | |
| 856 | 4 | 0 | |u https://doi.org/10.1515/156939604323091199 |q text/html |z Onlinezugriff via DOI |
| 908 | |D 1 |a research article |2 jats | ||
| 950 | |B NATIONALLICENCE |P 856 |E 40 |u https://doi.org/10.1515/156939604323091199 |q text/html |z Onlinezugriff via DOI | ||
| 950 | |B NATIONALLICENCE |P 100 |E 1- |a Seibold |D Benjamin |u Department of Mathematics, Technical University of Kaiserslautern, Gottlieb-Daimler-Straße, 67653 Kaiserslautern, Germany | ||
| 950 | |B NATIONALLICENCE |P 773 |E 0- |t Monte Carlo Methods and Applications |d Walter de Gruyter |g 10/1(2004-03-01), 25-50 |x 0929-9629 |q 10:1<25 |1 2004 |2 10 |o mcma | ||
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| 949 | |B NATIONALLICENCE |F NATIONALLICENCE |b NL-gruyter | ||