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Efficient Sampling of the Stationary Distribution of Metastable Dynamical Systems

Please always quote using this URN: urn:nbn:de:0297-zib-9467
  • In this article we aim at an efficient sampling of the stationary distribution of dynamical systems in the presence of metastabilities. In the past decade many sophisticated algorithms have been inven ted in this field. We do not want to simply add a further one. We address the problem that one has applied a sampling algorithm for a dynamical system many times. This leads to different samplings which more or less represent the stationary distribution partially very well, but which are still far away from ergodicity or from the global stationary distribution. We will show how these samplings can be joined together in order to get one global sampling of the stationary distribution.

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Author:Marcus Weber, Susanna Kube, Alexander Riemer, Alexander Bujotzek
Document Type:ZIB-Report
Tag:cluster analysis; dynamical systems; metastability; rare events; stationary distribution
MSC-Classification:65-XX NUMERICAL ANALYSIS / 65Cxx Probabilistic methods, simulation and stochastic differential equations (For theoretical aspects, see 68U20 and 60H35) / 65C40 Computational Markov chains
82-XX STATISTICAL MECHANICS, STRUCTURE OF MATTER / 82Bxx Equilibrium statistical mechanics / 82B80 Numerical methods (Monte Carlo, series resummation, etc.) [See also 65-XX, 81T80]
Date of first Publication:2006/12/19
Series (Serial Number):ZIB-Report (07-03)
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