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Título

Sampling rare trajectories using stochastic bridges

AutorAguilar-Sánchez, Javier CSIC ORCID; Baron, Joseph W. CSIC ORCID; Galla, Tobias CSIC ORCID; Toral, Raúl CSIC ORCID
Palabras clavePhysics - Statistical Mechanics
Physics - Statistical Mechanics
Fecha de publicación30-jun-2022
EditorAmerican Physical Society
CitaciónPhysical Review E 105(6):064138 (2022)
ResumenThe numerical quantification of the statistics of rare events in stochastic processes is a challenging computational problem. We present a sampling method that constructs an ensemble of stochastic trajectories that are constrained to have fixed start and end points (so-called stochastic bridges). We then show that by carefully choosing a set of such bridges and assigning an appropriate statistical weight to each bridge, one can focus more processing power on the rare events of a target stochastic process while faithfully preserving the statistics of these rare trajectories. Further, we also compare the stochastic bridges we produce to the Wentzel-Kramers-Brillouin (WKB) optimal paths of the target process, derived in the limit of low noise. We see that the generated paths, encoding the full statistics of the process, collapse onto the WKB optimal path as the level of noise is reduced. We propose that the method can also be used to judge the accuracy of the WKB approximation at finite levels of noise.
Versión del editorhttps://doi.org/10.1103/PhysRevE.105.064138
URIhttp://hdl.handle.net/10261/287061
DOI10.1103/PhysRevE.105.064138
ISSN2470-0045
E-ISSN2470-0053
ReferenciasAguilar-Sánchez, Javier; Baron, Joseph W.; Galla, Tobias; Toral, Raúl; 2021; Sampling rare trajectories using stochastic bridges [Preprint]; arXiv; Version 1; https://doi.org/10.48550/arXiv.2112.08252
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