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Army ants algorithm for rare event sampling of delocalized nonadiabatic transitions by trajectory surface hopping and the estimation of sampling errors by the bootstrap method

Nanjia, Shikha and Jasper, Ahren W. and Miller, Thomas F., III and Truhlar, Donald G. (2004) Army ants algorithm for rare event sampling of delocalized nonadiabatic transitions by trajectory surface hopping and the estimation of sampling errors by the bootstrap method. Journal of Chemical Physics, 120 (8). pp. 3586-3597. ISSN 0021-9606. http://resolver.caltech.edu/CaltechAUTHORS:NANjcp04

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Abstract

The most widely used algorithm for Monte Carlo sampling of electronic transitions in trajectory surface hopping (TSH) calculations is the so-called anteater algorithm, which is inefficient for sampling low-probability nonadiabatic events. We present a new sampling scheme (called the army ants algorithm) for carrying out TSH calculations that is applicable to systems with any strength of coupling. The army ants algorithm is a form of rare event sampling whose efficiency is controlled by an input parameter. By choosing a suitable value of the input parameter the army ants algorithm can be reduced to the anteater algorithm (which is efficient for strongly coupled cases), and by optimizing the parameter the army ants algorithm may be efficiently applied to systems with low-probability events. To demonstrate the efficiency of the army ants algorithm, we performed atom–diatom scattering calculations on a model system involving weakly coupled electronic states. Fully converged quantum mechanical calculations were performed, and the probabilities for nonadiabatic reaction and nonreactive deexcitation (quenching) were found to be on the order of 10^–8. For such low-probability events the anteater sampling scheme requires a large number of trajectories (~10^10) to obtain good statistics and converged semiclassical results. In contrast by using the new army ants algorithm converged results were obtained by running 10^5 trajectories. Furthermore, the results were found to be in excellent agreement with the quantum mechanical results. Sampling errors were estimated using the bootstrap method, which is validated for use with the army ants algorithm.


Item Type:Article
Additional Information:©2004 American Institute of Physics. Received 21 October 2003; accepted 21 November 2003. This work was supported in part by the National Science Foundation under Grant No. CHE00-92019.
Subject Keywords:atom-molecule collisions, potential energy surfaces, bootstrapping, Monte Carlo methods, excited states
Record Number:CaltechAUTHORS:NANjcp04
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:NANjcp04
Alternative URL:http://dx.doi.org/10.1063/1.1641019
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:11064
Collection:CaltechAUTHORS
Deposited By: Archive Administrator
Deposited On:25 Jun 2008
Last Modified:26 Dec 2012 10:08

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