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 language | English (US) |
|---|---|
| Article number | 234103 |
| Journal | Journal of Chemical Physics |
| Volume | 136 |
| Issue number | 23 |
| DOIs | |
| State | Published - Jun 21 2012 |
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ASJC Scopus subject areas
- Physics and Astronomy(all)
- Physical and Theoretical Chemistry
Cite this
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 journal › Review article
}
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 -