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Sampling diffusive transition paths

Miller, Thomas F., III and Predescu, Cristian (2007) Sampling diffusive transition paths. Journal of Chemical Physics, 126 (14). Art. No. 144102. ISSN 0021-9606.

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The authors address the problem of sampling double-ended diffusive paths. The ensemble of paths is expressed using a symmetric version of the Onsager-Machlup formula, which only requires evaluation of the force field and which, upon direct time discretization, gives rise to a symmetric integrator that is accurate to second order. Efficiently sampling this ensemble requires avoiding the well-known stiffness problem associated with the sampling of infinitesimal Brownian increments of the path, as well as a different type of stiffness associated with the sampling of the coarse features of long paths. The fine-feature sampling stiffness is eliminated with the use of the fast sampling algorithm, and the coarse-feature sampling stiffness is avoided by introducing the sliding and sampling (S&S) algorithm. A key feature of the S&S algorithm is that it enables massively parallel computers to sample diffusive trajectories that are long in time. The authors use the algorithm to sample the transition path ensemble for the structural interconversion of the 38-atom Lennard-Jones cluster at low temperature.

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Miller, Thomas F., III0000-0002-1882-5380
Additional Information:© 2007 American Institute of Physics. Received 12 October 2006; accepted 6 February 2007; published 10 April 2007. This work was supported in part by the National Science Foundation Grant No. CHE-0345280 and by the Director, Office of Science, Office of Basic Energy Sciences, Chemical Sciences, Geosciences, and Biosciences Division, U.S. Department of Energy under Contract No. DE-AC02-05CH11231. Computing resources were provided by NERSC. The authors thank D. Chandler, J.D. Doll, E. Vanden-Eijnden, and W.H. Miller for many helpful discussions. Special thanks is given to D.J. Wales for providing the results of his DPS calculations.
Subject Keywords:atomic clusters, physics computing, sampling methods, molecular force constants, Brownian motion, Lennard-Jones potential, parallel algorithms, molecular configurations
Issue or Number:14
Record Number:CaltechAUTHORS:MILjcp07
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Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:11035
Deposited By: Archive Administrator
Deposited On:24 Jun 2008
Last Modified:03 Oct 2019 00:15

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