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采用 Mori-Zwanzig 形式主义和迭代 Boltzmann 反演构建非马尔可夫粗粒模型。

Construction of non-Markovian coarse-grained models employing the Mori-Zwanzig formalism and iterative Boltzmann inversion.

机构信息

Department of Mechanical Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan.

Division of Applied Mathematics, Brown University, Providence, Rhode Island 02912, USA.

出版信息

J Chem Phys. 2017 Dec 28;147(24):244110. doi: 10.1063/1.5009041.

Abstract

We propose a new coarse-grained (CG) molecular simulation technique based on the Mori-Zwanzig (MZ) formalism along with the iterative Boltzmann inversion (IBI). Non-Markovian dissipative particle dynamics (NMDPD) taking into account memory effects is derived in a pairwise interaction form from the MZ-guided generalized Langevin equation. It is based on the introduction of auxiliary variables that allow for the replacement of a non-Markovian equation with a Markovian one in a higher dimensional space. We demonstrate that the NMDPD model exploiting MZ-guided memory kernels can successfully reproduce the dynamic properties such as the mean square displacement and velocity autocorrelation function of a Lennard-Jones system, as long as the memory kernels are appropriately evaluated based on the Volterra integral equation using the force-velocity and velocity-velocity correlations. Furthermore, we find that the IBI correction of a pair CG potential significantly improves the representation of static properties characterized by a radial distribution function and pressure, while it has little influence on the dynamic processes. Our findings suggest that combining the advantages of both the MZ formalism and IBI leads to an accurate representation of both the static and dynamic properties of microscopic systems that exhibit non-Markovian behavior.

摘要

我们提出了一种新的粗粒(CG)分子模拟技术,该技术基于 Mori-Zwanzig(MZ)形式主义和迭代 Boltzmann 反演(IBI)。考虑到记忆效应的非马尔可夫耗散粒子动力学(NMDPD)从 MZ 引导的广义朗之万方程以成对相互作用的形式推导得出。它基于辅助变量的引入,允许在更高维空间中用马尔可夫方程替换非马尔可夫方程。我们证明,只要根据 Volterra 积分方程使用力-速度和速度-速度相关函数适当地评估记忆核,利用 MZ 引导的记忆核的 NMDPD 模型就可以成功地再现例如 Lennard-Jones 系统的均方位移和速度自相关函数等动态特性。此外,我们发现对 CG 对势的 IBI 修正显著改善了由径向分布函数和压力表征的静态特性的表示,而对动态过程几乎没有影响。我们的研究结果表明,将 MZ 形式主义和 IBI 的优势相结合,可以准确地表示表现出非马尔可夫行为的微观系统的静态和动态特性。

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