Rare event computation in deterministic chaotic systems using genealogical particle analysis

2015/11/30 by Jeroen Wouters, J Wouters, Freddy Bouchet +1
Mathematics · Physics and Astronomy · #Chaotic #Computation #Estimator #Event (particle physics) #Markov Chains and Monte Carlo Methods #Observable #Particle filter #Path (computing) #Quantum chaos and dynamical systems #Rare events #cond-mat.stat-mech #stat.CO #stochastic dynamics and bifurcation

paper · pdf · doi:10.1088/1751-8113/49/37/374002

arxiv created 2016/06/20 · openalex created_date 2016/06/24 · openalex publication_date 2016/08/24 · arxiv updated 2016/09/21 · openalex updated_date 2026/08/06

Abstract

In this paper we address the use of rare event computation techniques to estimate small over-threshold probabilities of observables in deterministic dynamical systems. We demonstrate that genealogical particle analysis algorithms can be successfully applied to a toy model of atmospheric dynamics, the Lorenz '96 model. We furthermore use the Ornstein–Uhlenbeck system to illustrate a number of implementation issues. We also show how a time-dependent objective function based on the fluctuation path to a high threshold can greatly improve the performance of the estimator compared to a fixed-in-time objective function.

Citations

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• A numerical approach to large deviations in continuous time
• Genealogical particle analysis of rare events
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