Using Bayes formula to estimate rates of rare events in transition path sampling simulations

Pierre Terrier (1, 2) , Mihai-Cosmin Marinica (3, 2) , Manuel Athènes (4, 2)

1 ENPC - École des Ponts ParisTech
2 CEA-DES (ex-DEN) - CEA-Direction des Energies (ex-Direction de l'Energie Nucléaire)
3 DRECAM - Département de Recherche sur l'Etat Condensé, les Atomes et les Molécules
4 SRMP - Service de recherches de métallurgie physique

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

Domains: Physics [physics]; Nuclear Theory [nucl-th]; Physics [physics]; Nuclear Experiment [nucl-ex]

Pierre Terrier, Mihai-Cosmin Marinica, Manuel Athènes. Using Bayes formula to estimate rates of rare events in transition path sampling simulations. Journal of Chemical Physics, 2015, 143 (13), pp.134121. ⟨10.1063/1.4932389⟩. ⟨cea-02382868⟩