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交流:多尺度模拟中的自适应边界。

Communication: Adaptive boundaries in multiscale simulations.

机构信息

Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, New York 11794, USA.

Department of Chemistry, Department of Structural Biology, and Department of Computer Science, Stanford University, Stanford, California 94305, USA.

出版信息

J Chem Phys. 2018 Apr 14;148(14):141104. doi: 10.1063/1.5025826.

Abstract

Combined-resolution simulations are an effective way to study molecular properties across a range of length and time scales. These simulations can benefit from adaptive boundaries that allow the high-resolution region to adapt (change size and/or shape) as the simulation progresses. The number of degrees of freedom required to accurately represent even a simple molecular process can vary by several orders of magnitude throughout the course of a simulation, and adaptive boundaries react to these changes to include an appropriate but not excessive amount of detail. Here, we derive the Hamiltonian and distribution function for such a molecular simulation. We also design an algorithm that can efficiently sample the boundary as a new coordinate of the system. We apply this framework to a mixed explicit/continuum simulation of a peptide in solvent. We use this example to discuss the conditions necessary for a successful implementation of adaptive boundaries that is both efficient and accurate in reproducing molecular properties.

摘要

联合分辨率模拟是研究跨越一系列长度和时间尺度的分子性质的有效方法。这些模拟可以受益于自适应边界,这些边界允许高分辨率区域在模拟过程中自适应(改变大小和/或形状)。即使是一个简单的分子过程,准确表示所需的自由度数量在整个模拟过程中也可能相差几个数量级,自适应边界会对这些变化做出反应,以包含适当但不过量的细节。在这里,我们推导出了这样一个分子模拟的哈密顿量和分布函数。我们还设计了一种算法,可以有效地对边界进行采样作为系统的一个新坐标。我们将这个框架应用于溶剂中肽的混合显式/连续模拟。我们使用这个例子来讨论成功实现自适应边界所需的条件,这些边界在复制分子性质方面既高效又准确。

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