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A Numerical Procedure to Evaluate Memory Effects in Non‐Equilibrium Coarse‐Grained Models
Advanced Theory and Simulations ( IF 2.9 ) Pub Date : 2020-11-03 , DOI: 10.1002/adts.202000197
Hugues Meyer 1 , Steffen Wolf 2 , Gerhard Stock 2 , Tanja Schilling 2
Affiliation  

When developing coarse‐grained models of complex processes out of equilibrium, one encounters the non‐stationary generalized Langevin equation. The most important feature of this equation is the presence of a non‐stationary memory kernel. Here, a method is presented to infer this memory kernel from MD simulation data in non‐equilibrium processes. The method provides an improvement of a previously published numerical scheme, the applicability of which is limited by a truncation problem. As an illustration, the method is applied to ion dissociation of NaCl in water, for which non‐trivial dampened oscillations are observed in the memory kernel.

中文翻译:

评估非平衡粗粒模型中记忆效应的数值过程

当开发不平衡的复杂过程的粗粒度模型时,会遇到非平稳的广义Langevin方程。该方程式的最重要特征是存在一个非平稳的内存内核。这里,提出了一种从非平衡过程中的MD仿真数据推断此内存内核的方法。该方法提供了对先前公开的数值方案的改进,其适用性受到截断问题的限制。作为说明,该方法适用于水中NaCl的离子解离,为此在内存内核中观察到了非平凡的阻尼振荡。
更新日期:2020-11-03
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