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以经典动力学速度重现量子概率分布:开发力场函子的新方法。

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

作者信息

Sundar Vikram, Gelbwaser-Klimovsky David, Aspuru-Guzik Alán

机构信息

Department of Chemistry and Chemical Biology , Harvard University , Cambridge , Massachusetts 02138 , United States.

Senior Fellow, Canadian Institute for Advanced Research , Toronto , Ontario M5G 1Z8 , Canada.

出版信息

J Phys Chem Lett. 2018 Apr 5;9(7):1721-1727. doi: 10.1021/acs.jpclett.7b03254. Epub 2018 Mar 21.

DOI:10.1021/acs.jpclett.7b03254
PMID:29528650
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. 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.

摘要

对于分子的精确分子动力学(MD)模拟而言,模拟核量子效应是必要的。该领域特别关注表现出氢键作用的水和其他生物分子。像环聚合物分子动力学(RPMD)这样的核量子效应建模标准方法,其计算成本比运行经典轨迹更高。力场函子(FFF)是一种替代方法,它计算一个有效力场,该力场复制原始力场的量子特性。在这项工作中,我们提出了一种使用维格纳 - 柯克伍德展开来计算FFF的有效方法。作为一个测试案例,我们计算了一系列氖的热力学性质,获得了与RPMD相同的精度水平,但具有经典模拟更短的运行时间。通过修改现有的MD程序,所提出的方法未来可用于提高涉及水和蛋白质的MD模拟的效率和精度。

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