In:
Chaos: An Interdisciplinary Journal of Nonlinear Science, AIP Publishing, Vol. 29, No. 1 ( 2019-01-01)
Abstract:
Given a time-dependent stochastic process with trajectories x(t) in a space Ω, there may be sets such that the corresponding trajectories only very rarely cross the boundaries of these sets. We can analyze such a process in terms of metastability or coherence. Metastable sets M are defined in space M⊂Ω, and coherent sets M(t)⊂Ω are defined in space and time. Hence, if we extend the space Ω by the time-variable t, coherent sets are metastable sets in Ω×[0,∞) of an appropriate space-time process. This relation can be exploited, because there already exist spectral algorithms for the identification of metastable sets. In this article, we show that these well-established spectral algorithms (like PCCA+, Perron Cluster Cluster Analysis) also identify coherent sets of non-autonomous dynamical systems. For the identification of coherent sets, one has to compute a discretization (a matrix T) of the transfer operator of the process using a space-time-discretization scheme. The article gives an overview about different time-discretization schemes and shows their applicability in two different fields of application.
Type of Medium:
Online Resource
ISSN:
1054-1500
,
1089-7682
Language:
English
Publisher:
AIP Publishing
Publication Date:
2019
detail.hit.zdb_id:
1472677-4
SSG:
11
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