Splitting algorithms for rare event simulation over long time intervals

Anne Buijsrogge, Paul Dupuis, Michael Snarski

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In this paper we study the performance of splitting algorithms, and in particular the RESTART method, for the numerical approximation of the probability that a process leaves a neighborhood of a metastable point during some long time interval [0,T]. We show that, in contrast to alternatives such as importance sampling, the decay rate of the second moment does not degrade as T → ∞. In the course of the analysis we develop some related large deviation estimates that apply when the time interval of interest depends on the large deviation parameter.

Original languageEnglish
Pages (from-to)2963-2998
Number of pages36
JournalAnnals of applied probability
Issue number6
Publication statusPublished - Dec 2020


  • Large deviations
  • Metastable points
  • Monte Carlo methods
  • Splitting algorithms
  • 22/2 OA procedure


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