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Title: Reproducing Quantum Probability Distributions at the Speed of Classical Dynamics: A New Approach for Developing Force-Field Functors

Abstract

Modeling nuclear quantum effects is required for accurate molecular dynamics (MD) simulations of molecules. The community has paid special attention to water and other biomolecules that show hydrogen bonding. Standard methods of modeling nuclear quantum effects like Ring Polymer Molecular Dynamics (RPMD) are computationally costlier than running classical trajectories. A force-field functor (FFF) is an alternative method that computes an effective force field that replicates quantum properties of the original force field. In this work, we propose an efficient method of computing FFF using the Wigner–Kirkwood expansion. As a test case, we calculate a range of thermodynamic properties of Neon, obtaining the same level of accuracy as RPMD, but with the shorter runtime of classical simulations. Lastly, by modifying existing MD programs, the proposed method could be used in the future to increase the efficiency and accuracy of MD simulations involving water and proteins.

Authors:
 [1];  [1]; ORCiD logo [2]
  1. Harvard Univ., Cambridge, MA (United States). Dept. of Chemistry and Chemical Biology
  2. Harvard Univ., Cambridge, MA (United States). Dept. of Chemistry and Chemical Biology; Canadian Inst. for Advanced Research, Toronto, ON (Canada)
Publication Date:
Research Org.:
Energy Frontier Research Centers (EFRC) (United States). Center for Excitonics (CE)
Sponsoring Org.:
USDOE Office of Science (SC), Basic Energy Sciences (BES) (SC-22)
OSTI Identifier:
1470507
Grant/Contract Number:  
SC0001088
Resource Type:
Accepted Manuscript
Journal Name:
Journal of Physical Chemistry Letters
Additional Journal Information:
Journal Volume: 9; Journal Issue: 7; Related Information: CE partners with Massachusetts Institute of Technology (lead); Brookhaven National Laboratory; Harvard University; Journal ID: ISSN 1948-7185
Publisher:
American Chemical Society
Country of Publication:
United States
Language:
English
Subject:
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY; solar (photovoltaic); solid state lighting; photosynthesis (natural and artificial); charge transport; optics; synthesis (novel materials); synthesis (self-assembly); synthesis (scalable processing)

Citation Formats

Sundar, Vikram, Gelbwaser-Klimovsky, David, and Aspuru-Guzik, Alán. Reproducing Quantum Probability Distributions at the Speed of Classical Dynamics: A New Approach for Developing Force-Field Functors. United States: N. p., 2018. Web. doi:10.1021/acs.jpclett.7b03254.
Sundar, Vikram, Gelbwaser-Klimovsky, David, & Aspuru-Guzik, Alán. Reproducing Quantum Probability Distributions at the Speed of Classical Dynamics: A New Approach for Developing Force-Field Functors. United States. doi:10.1021/acs.jpclett.7b03254.
Sundar, Vikram, Gelbwaser-Klimovsky, David, and Aspuru-Guzik, Alán. Mon . "Reproducing Quantum Probability Distributions at the Speed of Classical Dynamics: A New Approach for Developing Force-Field Functors". United States. doi:10.1021/acs.jpclett.7b03254. https://www.osti.gov/servlets/purl/1470507.
@article{osti_1470507,
title = {Reproducing Quantum Probability Distributions at the Speed of Classical Dynamics: A New Approach for Developing Force-Field Functors},
author = {Sundar, Vikram and Gelbwaser-Klimovsky, David and Aspuru-Guzik, Alán},
abstractNote = {Modeling nuclear quantum effects is required for accurate molecular dynamics (MD) simulations of molecules. The community has paid special attention to water and other biomolecules that show hydrogen bonding. Standard methods of modeling nuclear quantum effects like Ring Polymer Molecular Dynamics (RPMD) are computationally costlier than running classical trajectories. A force-field functor (FFF) is an alternative method that computes an effective force field that replicates quantum properties of the original force field. In this work, we propose an efficient method of computing FFF using the Wigner–Kirkwood expansion. As a test case, we calculate a range of thermodynamic properties of Neon, obtaining the same level of accuracy as RPMD, but with the shorter runtime of classical simulations. Lastly, by modifying existing MD programs, the proposed method could be used in the future to increase the efficiency and accuracy of MD simulations involving water and proteins.},
doi = {10.1021/acs.jpclett.7b03254},
journal = {Journal of Physical Chemistry Letters},
number = 7,
volume = 9,
place = {United States},
year = {2018},
month = {3}
}

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