Rare event computation in deterministic chaotic systems using genealogical particle analysis

Jeroen Wouters (1, 2, 3) , Freddy Bouchet (3)

1 School of Mathematics and statistics [Sydney]
2 Meteorologisches Institut [Hamburg]
3 Phys-ENS - Laboratoire de Physique de l'ENS Lyon

In this paper we address the use of rare event computation techniques to estimate small over-threshold probabilities of observables in determin-istic dynamical systems. We demonstrate that the 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.

Mots clés: rare event simulation; large deviation theory; genealogical particle analysis

Domaines: Mécanique statistique [cond-mat.stat-mech]; Calcul [stat.CO]

Jeroen Wouters, Freddy Bouchet. Rare event computation in deterministic chaotic systems using genealogical particle analysis. 2016. ⟨hal-01223006v2⟩