Application of adaptive multilevel splitting to high-dimensional dynamical systems

被引：11
|
作者：
Baars, S. [1 ]
Castellana, D. [2 ]
Wubs, F. W. [1 ]
Dijkstra, H. A. [2 ,3 ]
机构：
[1] Univ Groningen, Bernoulli Inst Math Comp Sci & Artificial Intelli, POB 407, NL-9700 AK Groningen, Netherlands
[2] Univ Utrecht, Dept Phys, Inst Marine & Atmospher Res Utrecht, Princetonpl 5, NL-3584 CC Utrecht, Netherlands
[3] Univ Utrecht, Ctr Complex Syst Studies, Leuvenlaan 4, NL-3584 CE Utrecht, Netherlands
来源：
JOURNAL OF COMPUTATIONAL PHYSICS | 2021年 / 424卷
关键词：
Rare transitions; Multilevel splitting; Model order reduction; Stochastic dynamical systems; Ocean circulation; MODEL; DECOMPOSITION; ALGORITHMS;
D O I：
10.1016/j.jcp.2020.109876
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
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. (C) 2020 Elsevier Inc. All rights reserved.
引用
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页数：12
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