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改进全局变量:以结晶为例。

Improving collective variables: The case of crystallization.

机构信息

Department of Chemistry and Applied Biosciences, ETH Zurich, c/o USI Campus, Via Giuseppe Buffi 13, CH-6900 Lugano, Ticino, Switzerland.

出版信息

J Chem Phys. 2019 Mar 7;150(9):094509. doi: 10.1063/1.5081040.

Abstract

Several enhanced sampling methods, such as umbrella sampling or metadynamics, rely on the identification of an appropriate set of collective variables. Recently two methods have been proposed to alleviate the task of determining efficient collective variables. One is based on linear discriminant analysis; the other is based on a variational approach to conformational dynamics and uses time-lagged independent component analysis. In this paper, we compare the performance of these two approaches in the study of the homogeneous crystallization of two simple metals. We focus on Na and Al and search for the most efficient collective variables that can be expressed as a linear combination of X-ray diffraction peak intensities. We find that the performances of the two methods are very similar. Wherever the different metastable states are well-separated, the method based on linear discriminant analysis, based on its harmonic version, is to be preferred because simpler to implement and less computationally demanding. The variational approach, however, has the potential to discover the existence of different metastable states.

摘要

几种增强采样方法,如伞状采样或元动力学,依赖于识别一组合适的广义坐标。最近提出了两种方法来减轻确定有效广义坐标的任务。一种方法基于线性判别分析,另一种方法基于构象动力学的变分方法,并使用时间滞后独立成分分析。在本文中,我们比较了这两种方法在两种简单金属均匀结晶研究中的性能。我们专注于钠和铝,并寻找最有效的广义坐标,可以表示为 X 射线衍射峰强度的线性组合。我们发现这两种方法的性能非常相似。只要不同的亚稳态分离良好,基于线性判别分析的方法,基于其谐波版本,是首选的,因为它更简单实现,计算要求更低。然而,变分方法有可能发现不同亚稳态的存在。

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