Weapons and Materials Research Directorate, U.S. Army Research Laboratory, Aberdeen Proving Ground, Aberdeen, Maryland 21005, USA.
Phys Rev E. 2017 Jan;95(1-1):013303. doi: 10.1103/PhysRevE.95.013303. Epub 2017 Jan 17.
We derive alternative Markov approximations for the projected (stochastic) force and memory function in the coarse-grained (CG) generalized Langevin equation, which describes the time evolution of the center-of-mass coordinates of clusters of particles in the microscopic ensemble. This is done with the aid of the Mori-Zwanzig projection operator method based on the recently introduced projection operator [S. Izvekov, J. Chem. Phys. 138, 134106 (2013)10.1063/1.4795091]. The derivation exploits the "generalized additive fluctuating force" representation to which the projected force reduces in the adopted projection operator formalism. For the projected force, we present a first-order time expansion which correctly extends the static fluctuating force ansatz with the terms necessary to maintain the required orthogonality of the projected dynamics in the Markov limit to the space of CG phase variables. The approximant of the memory function correctly accounts for the momentum dependence in the lowest (second) order and indicates that such a dependence may be important in the CG dynamics approaching the Markov limit. In the case of CG dynamics with a weak dependence of the memory effects on the particle momenta, the expression for the memory function presented in this work is applicable to non-Markov systems. The approximations are formulated in a propagator-free form allowing their efficient evaluation from the microscopic data sampled by standard molecular dynamics simulations. A numerical application is presented for a molecular liquid (nitromethane). With our formalism we do not observe the "plateau-value problem" if the friction tensors for dissipative particle dynamics (DPD) are computed using the Green-Kubo relation. Our formalism provides a consistent bottom-up route for hierarchical parametrization of DPD models from atomistic simulations.
我们推导出了投影(随机)力和记忆函数在粗粒(CG)广义朗之万方程中的替代马尔可夫近似,该方程描述了粒子簇的质心坐标在微观系综中的时间演化。这是借助于 Mori-Zwanzig 投影算子方法完成的,该方法基于最近引入的投影算子 [S. Izvekov, J. Chem. Phys. 138, 134106 (2013)10.1063/1.4795091]。这种推导利用了“广义附加波动力”表示,在采用的投影算子形式中,投影力可以简化为这种表示。对于投影力,我们给出了一个一阶时间展开式,该展开式正确地扩展了静态波动力假设,增加了必要的项,以保持在马尔可夫极限下投影动力学的所需正交性,进入 CG 相变量空间。记忆函数的逼近正确地考虑了动量依赖关系的最低(二阶)阶,并表明在 CG 动力学接近马尔可夫极限的情况下,这种依赖关系可能很重要。在 CG 动力学中,记忆效应对粒子动量的依赖性较弱的情况下,本文提出的记忆函数表达式适用于非马尔可夫系统。这些逼近是在无传播子的形式下提出的,可以从标准分子动力学模拟采样的微观数据中高效地评估。我们给出了一个分子液体(硝基甲烷)的数值应用。使用我们的形式,我们没有观察到“平台值问题”,如果使用格林-库珀关系计算耗散粒子动力学(DPD)的摩擦张量。我们的形式为从原子模拟到 DPD 模型的层次参数化提供了一种一致的自下而上的方法。