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Trajectory stratification of stochastic dynamics

dc.contributor.author Tempkin, JOB
dc.contributor.author Koten, BV
dc.contributor.author Mattingly, Jonathan Christopher
dc.contributor.author Dinner, AR
dc.contributor.author Weare, J
dc.date.accessioned 2016-11-08T10:37:44Z
dc.date.issued 2016
dc.identifier http://arxiv.org/abs/1610.09426v1
dc.identifier.uri https://hdl.handle.net/10161/12995
dc.description.abstract We present a general mathematical framework for trajectory stratification for simulating rare events. Trajectory stratification involves decomposing trajectories of the underlying process into fragments limited to restricted regions of state space (strata), computing averages over the distributions of the trajectory fragments within the strata with minimal communication between them, and combining those averages with appropriate weights to yield averages with respect to the original underlying process. Our framework reveals the full generality and flexibility of trajectory stratification, and it illuminates a common mathematical structure shared by existing algorithms for sampling rare events. We demonstrate the power of the framework by defining strata in terms of both points in time and path-dependent variables for efficiently estimating averages that were not previously tractable.
dc.format.extent 18 pages, 8 figures
dc.subject cond-mat.stat-mech
dc.subject cond-mat.stat-mech
dc.title Trajectory stratification of stochastic dynamics
dc.type Journal article
pubs.author-url http://arxiv.org/abs/1610.09426v1
pubs.organisational-group Duke
pubs.organisational-group Mathematics
pubs.organisational-group Statistical Science
pubs.organisational-group Trinity College of Arts & Sciences


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