DOI: 10.1063/1.1396672. Parallel-hat tempering: A Monte Carlo search scheme for the identification of low-energy structures

Parallel-hat tempering: A Monte Carlo search scheme for the identification of low-energy structures

10.1063/1.1396672

Crossref journal-article

AIP Publishing

The Journal of Chemical Physics (317)

Abstract

A new parallel-hat tempering algorithm has been developed for Monte Carlo simulations, in which a composite ensemble of noninteracting replicas of the molecule system at different temperatures is simulated, and the Markov process of each replica is driven by a hatlike weight factor with exponentially enhanced probability in both low- and high-energy regions. To test the algorithm, the methodology is applied to a homopolymeric protein chain located on a face-centered cubic lattice. We demonstrate that the ability of the current approach to search for low-energy molecule structures is significantly better than other Monte Carlo techniques found in the literature.

Bibliography

Zhang, Y., & Skolnick, J. (2001). Parallel-hat tempering: A Monte Carlo search scheme for the identification of low-energy structures. The Journal of Chemical Physics, 115(11), 5027â5032.

Authors 2

Yang Zhang (first)
Jeffrey Skolnick (additional)

References 21 Referenced 12

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Dates

Type	When
Created	23 years, 1 month ago (July 26, 2002, 10:16 a.m.)
Deposited	2 years, 1 month ago (July 9, 2023, 11:42 p.m.)
Indexed	1 year, 3 months ago (May 2, 2024, 12:35 a.m.)
Issued	23 years, 11 months ago (Sept. 15, 2001)
Published	23 years, 11 months ago (Sept. 15, 2001)
Published Print	23 years, 11 months ago (Sept. 15, 2001)

Funders 0

None

BibTeX

@article{Zhang_2001, title={Parallel-hat tempering: A Monte Carlo search scheme for the identification of low-energy structures}, volume={115}, ISSN={1089-7690}, url={http://dx.doi.org/10.1063/1.1396672}, DOI={10.1063/1.1396672}, number={11}, journal={The Journal of Chemical Physics}, publisher={AIP Publishing}, author={Zhang, Yang and Skolnick, Jeffrey}, year={2001}, month=sep, pages={5027–5032} }

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