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A Subspace Approach to Molecular Markov State Models via a New Infinitesimal Generator

Please always quote using this URN:urn:nbn:de:0296-matheon-10427
  • Supercomputers can simulate complex molecular systems. However, there is a very large gap between the fastest oscillations of covalent bonds of a molecule and the time-scale of the dominant processes. In order to extract the dominant time-scales and to identify the dominant processes, a clustering of information is needed. This thesis shows that only the subspace-based Robust Perron Cluster Analysis (PCCA+) can solve this problem correctly by the construction of a Markov State Model. PCCA+ allows for time-extrapolation in molecular kinetics. This thesis shows the difference between molecular dynamics and molecular kinetics. Only in the molecular kinetics framework a definition of transition rates is possible. In this context, the existence of an infinitesimal generator of the dynamical processes is discussed. If the existence is assumed, the Theorem of Gauß can be applied in order to compute transition rates efficiently. Molecular dynamics, however, is not able to provide a suitable statistical basis for the determination of the transition pattern.

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  • Habilitationsschrift von Marcus Weber. Auch online unter http://opus4.kobv.de/opus4-zib/frontdoor/index/index/docId/1402

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Metadaten
Author:Marcus Weber
URN:urn:nbn:de:0296-matheon-10427
Referee:Peter Deuflhard
Document Type:Preprint, Research Center Matheon
Language:English
Date of first Publication:2012/01/31
Release Date:2012/01/31
Tag:Conformation Dynamics; Markov State Models; Molecular Kinetics; Transition Rates
Institute:Zuse Institute Berlin (ZIB)
MSC-Classification:60-XX PROBABILITY THEORY AND STOCHASTIC PROCESSES (For additional applications, see 11Kxx, 62-XX, 90-XX, 91-XX, 92-XX, 93-XX, 94-XX) / 60Jxx Markov processes / 60J25 Continuous-time Markov processes on general state spaces
Preprint Number:905
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