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Autors principals: Chorin, Alexandre J., Hald, Ole H., Kupferman, Raz
Format: Preprint
Publicat: 2001
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Accés en línia:https://arxiv.org/abs/math/0101022
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author Chorin, Alexandre J.
Hald, Ole H.
Kupferman, Raz
author_facet Chorin, Alexandre J.
Hald, Ole H.
Kupferman, Raz
contents Optimal prediction methods compensate for a lack of resolution in the numerical solution of complex problems through the use of prior statistical information. We know from previous work that in the presence of strong underresolution a good approximation needs a non-Markovian "memory", determined by an equation for the "orthogonal", i.e., unresolved, dynamics. We present a simple approximation of the orthogonal dynamics, which involves an ansatz and a Monte-Carlo evaluation of autocorrelations. The analysis provides a new understanding of the fluctuation-dissipation formulas of statistical physics. An example is given.
format Preprint
id arxiv_https___arxiv_org_abs_math_0101022
institution arXiv
publishDate 2001
record_format arxiv
spellingShingle Non-Markovian Optimal Prediction
Chorin, Alexandre J.
Hald, Ole H.
Kupferman, Raz
Numerical Analysis
Optimal prediction methods compensate for a lack of resolution in the numerical solution of complex problems through the use of prior statistical information. We know from previous work that in the presence of strong underresolution a good approximation needs a non-Markovian "memory", determined by an equation for the "orthogonal", i.e., unresolved, dynamics. We present a simple approximation of the orthogonal dynamics, which involves an ansatz and a Monte-Carlo evaluation of autocorrelations. The analysis provides a new understanding of the fluctuation-dissipation formulas of statistical physics. An example is given.
title Non-Markovian Optimal Prediction
topic Numerical Analysis
url https://arxiv.org/abs/math/0101022