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Postdoctoral Associate Chandler and Miller Research Groups Room 15, Pitzer Center for Theoretical Chemistry Department of Chemistry University of California at Berkeley Berkeley, CA 94720 Phone: (510) 643-1169 Fax: (510) 643-1566 Email: tfmiller@berkeley.edu |
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The figure at right shows the minimum free energy path for the collapse of an 8.6 nm hydrophobic chain in water, obtained in over 130,000 dimensions by coarse-graining all-atom simulations and using the string method in collective variables. Monomers in the idealized chain are shown in red, and regions of low water density are shown in white against the blue background. Above, a single peak in the free energy profile is seen at configuration 22. Below, the configurations of the path in the vicinity of the free-energy peak are shown with configuration numbers indicated in white text.
Read more at:
T. F. Miller, III, E. Vanden-Eijnden, and D. Chandler, PNAS, 104, 14559 (2007).
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In a collaboration with Cristian Predescu, I have developed a path integral
formulation of TPS that overcomes these difficulties.
Dynamical trajectories are represented as chains-of-states and sampled
using standard Metropolis Monte Carlo, which
naturally eliminates the difficulty of meta-stable
intermediates.
Large-scale parallelization is achieved with the aide of an additional technique that
we call Sliding and Sampling (S&S). The two step S&S process is illustrated in the movie,
where the dynamical trajectory is shown as a sequence of positions as a function of
time. In the first step, the ensemble of trajectories is divided into time-segments that are
independently sampled by different computer processors.
Then,
the time-segments are redistributed among the various processors by
sliding the sampling domains along the time coordinate.
The S&S algorithm is ergodic and relies only on the Markov property of the real-time dynamics.
It enables different processors to sample different regions of time,
thus enabling large-scale computers to probe dynamics on exceedingly
long timescales.
We have used this path-integral transition path sampling approach to study the phase-change dynamics of the 38-atom Lennard-Jones cluster, and we are pursuing its application in a variety of biological and material science contexts.
Read more at:
T. F. Miller, III and C. Predescu, J. Chem. Phys., 126, 144102 (2007).
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Last changed: 2/3/2008