Steered transition path sampling

Nicholas Guttenberg, Aaron R. Dinner, Jonathan Weare

Research output: Contribution to journalReview articlepeer-review

Abstract

We introduce a path sampling method for obtaining statistical properties of an arbitrary stochastic dynamics. The method works by decomposing a trajectory in time, estimating the probability of satisfying a progress constraint, modifying the dynamics based on that probability, and then reweighting to calculate averages. Because the progress constraint can be formulated in terms of occurrences of events within time intervals, the method is particularly well suited for controlling the sampling of currents of dynamic events. We demonstrate the method for calculating transition probabilities in barrier crossing problems and survival probabilities in strongly diffusive systems with absorbing states, which are difficult to treat by shooting. We discuss the relation of the algorithm to other methods.

Original languageEnglish (US)
Article number234103
JournalJournal of Chemical Physics
Volume136
Issue number23
DOIs
StatePublished - Jun 21 2012

ASJC Scopus subject areas

  • Physics and Astronomy(all)
  • Physical and Theoretical Chemistry

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