Finite-time and finite-size scalings in the evaluation of large-deviation functions: Numerical approach in continuous time

Finite-time and finite-size scalings in the evaluation of large-deviation functions: Numerical... Rare trajectories of stochastic systems are important to understand because of their potential impact. However, their properties are by definition difficult to sample directly. Population dynamics provides a numerical tool allowing their study, by means of simulating a large number of copies of the system, which are subjected to selection rules that favor the rare trajectories of interest. Such algorithms are plagued by finite simulation time and finite population size, effects that can render their use delicate. In this paper, we present a numerical approach which uses the finite-time and finite-size scalings of estimators of the large deviation functions associated to the distribution of rare trajectories. The method we propose allows one to extract the infinite-time and infinite-size limit of these estimators, which—as shown on the contact process—provides a significant improvement of the large deviation function estimators compared to the standard one. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Physical Review E American Physical Society (APS)

Finite-time and finite-size scalings in the evaluation of large-deviation functions: Numerical approach in continuous time

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Finite-time and finite-size scalings in the evaluation of large-deviation functions: Numerical approach in continuous time

Abstract

Rare trajectories of stochastic systems are important to understand because of their potential impact. However, their properties are by definition difficult to sample directly. Population dynamics provides a numerical tool allowing their study, by means of simulating a large number of copies of the system, which are subjected to selection rules that favor the rare trajectories of interest. Such algorithms are plagued by finite simulation time and finite population size, effects that can render their use delicate. In this paper, we present a numerical approach which uses the finite-time and finite-size scalings of estimators of the large deviation functions associated to the distribution of rare trajectories. The method we propose allows one to extract the infinite-time and infinite-size limit of these estimators, which—as shown on the contact process—provides a significant improvement of the large deviation function estimators compared to the standard one.
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Publisher
American Physical Society (APS)
Copyright
Copyright © ©2017 American Physical Society
ISSN
1539-3755
eISSN
550-2376
D.O.I.
10.1103/PhysRevE.95.062134
Publisher site
See Article on Publisher Site

Abstract

Rare trajectories of stochastic systems are important to understand because of their potential impact. However, their properties are by definition difficult to sample directly. Population dynamics provides a numerical tool allowing their study, by means of simulating a large number of copies of the system, which are subjected to selection rules that favor the rare trajectories of interest. Such algorithms are plagued by finite simulation time and finite population size, effects that can render their use delicate. In this paper, we present a numerical approach which uses the finite-time and finite-size scalings of estimators of the large deviation functions associated to the distribution of rare trajectories. The method we propose allows one to extract the infinite-time and infinite-size limit of these estimators, which—as shown on the contact process—provides a significant improvement of the large deviation function estimators compared to the standard one.

Journal

Physical Review EAmerican Physical Society (APS)

Published: Jun 28, 2017

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