Application of Adaptive Multilevel Splitting to High-Dimensional Dynamical Systems
Publication date
2021-01-01
Authors
Baars, S.
Castellana, Daniele
Wubs, F. W.
Dijkstra, Henk
Editors
Advisors
Supervisors
Document Type
Article
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taverne
Abstract
Stochastic nonlinear dynamical systems can undergo rapid transitions relative to the change in their forcing, for example due to the occurrence of multiple equilibrium solutions for a specific interval of parameters. In this paper, we modify one of the methods developed to compute probabilities of such transitions, Trajectory-Adaptive Multilevel Sampling (TAMS), to be able to apply it to high-dimensional systems. The key innovation is a projected time-stepping approach, which leads to a strong reduction in computational costs, in particular memory usage. The performance of this new implementation of TAMS is studied through an example of the collapse of the Atlantic Ocean Circulation.
Keywords
Model order reduction, Multilevel splitting, Ocean circulation, Rare transitions, Stochastic dynamical systems, Taverne, Numerical Analysis, Modelling and Simulation, Physics and Astronomy (miscellaneous), General Physics and Astronomy, Computer Science Applications, Computational Mathematics, Applied Mathematics
Citation
Baars, S, Castellana, D, Wubs, F W & Dijkstra, H A 2021, 'Application of Adaptive Multilevel Splitting to High-Dimensional Dynamical Systems', Journal of Computational Physics, vol. 424, 109876, pp. 1-12. https://doi.org/10.1016/j.jcp.2020.109876