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Journal articles
Using Bayes formula to estimate rates of rare events in transition path sampling simulations
Abstract : transition path sampling is a method for estimating the rates of rare events in molecular systems based on the gradual transformation of a path distribution containing a small fraction of reactive trajectories into a biased distribution in which these rare trajectories have become frequent. Then, a multistate reweighting scheme is implemented to postprocess data collected from the staged simulations. Herein, we show how Bayes formula allows to directly construct a biased sample containing an enhanced fraction of reactive trajectories and to concomitantly estimate the transition rate from this sample. The approach can remediate the convergence issues encountered in free energy perturbation or umbrella sampling simulations when the transformed distribution insufficiently overlaps with the reference distribution.
Keywords :
Molecular simulations
Markov processes
https://hal-cea.archives-ouvertes.fr/cea-02382868
Contributor : Amplexor Amplexor <>
Submitted on : Wednesday, November 27, 2019 - 1:59:49 PM
Last modification on : Wednesday, May 19, 2021 - 3:39:02 AM
Contributor : Amplexor Amplexor <>
Submitted on : Wednesday, November 27, 2019 - 1:59:49 PM
Last modification on : Wednesday, May 19, 2021 - 3:39:02 AM
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