Steered transition path sampling

Nicholas Guttenberg, Aaron R. Dinner, Jonathan Weare

Research output: Contribution to journalReview article

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

Fingerprint

sampling
Sampling
transition probabilities
estimating
trajectories
occurrences
intervals
Trajectories

ASJC Scopus subject areas

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

Cite this

Guttenberg, N., Dinner, A. R., & Weare, J. (2012). Steered transition path sampling. Journal of Chemical Physics, 136(23), [234103]. https://doi.org/10.1063/1.4724301

Steered transition path sampling. / Guttenberg, Nicholas; Dinner, Aaron R.; Weare, Jonathan.

In: Journal of Chemical Physics, Vol. 136, No. 23, 234103, 21.06.2012.

Research output: Contribution to journalReview article

Guttenberg, N, Dinner, AR & Weare, J 2012, 'Steered transition path sampling', Journal of Chemical Physics, vol. 136, no. 23, 234103. https://doi.org/10.1063/1.4724301
Guttenberg N, Dinner AR, Weare J. Steered transition path sampling. Journal of Chemical Physics. 2012 Jun 21;136(23). 234103. https://doi.org/10.1063/1.4724301
Guttenberg, Nicholas ; Dinner, Aaron R. ; Weare, Jonathan. / Steered transition path sampling. In: Journal of Chemical Physics. 2012 ; Vol. 136, No. 23.
@article{6cd00d11daf44cca8e05327b316c9b50,
title = "Steered transition path sampling",
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.",
author = "Nicholas Guttenberg and Dinner, {Aaron R.} and Jonathan Weare",
year = "2012",
month = "6",
day = "21",
doi = "10.1063/1.4724301",
language = "English (US)",
volume = "136",
journal = "Journal of Chemical Physics",
issn = "0021-9606",
publisher = "American Institute of Physics Publising LLC",
number = "23",

}

TY - JOUR

T1 - Steered transition path sampling

AU - Guttenberg, Nicholas

AU - Dinner, Aaron R.

AU - Weare, Jonathan

PY - 2012/6/21

Y1 - 2012/6/21

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=84863743810&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84863743810&partnerID=8YFLogxK

U2 - 10.1063/1.4724301

DO - 10.1063/1.4724301

M3 - Review article

C2 - 22779577

AN - SCOPUS:84863743810

VL - 136

JO - Journal of Chemical Physics

JF - Journal of Chemical Physics

SN - 0021-9606

IS - 23

M1 - 234103

ER -