Trajectory stratification of stochastic dynamics
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.
Duke Scholars
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Related Subject Headings
- Numerical & Computational Mathematics
- 4901 Applied mathematics
- 0906 Electrical and Electronic Engineering
- 0102 Applied Mathematics
Citation
Published In
ISSN
Publication Date
Publisher
Related Subject Headings
- Numerical & Computational Mathematics
- 4901 Applied mathematics
- 0906 Electrical and Electronic Engineering
- 0102 Applied Mathematics