Forward-flux sampling with jumpy order parameters
Forward-flux sampling with jumpy order parameters
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DOI：
10.1063/1.5018303
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发表时间：
2018-08-21
影响因子：
4.4
通讯作者：
Haji-Akbari, Amir
中科院分区：
文献类型：
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作者：
Haji-Akbari, Amir
前向通量采样 (FFS) 是一种路径采样技术，近年来越来越受欢迎，已用于计算结晶、冷凝、疏水蒸发、DNA 杂交和蛋白质折叠等罕见事件现象的速率。 FFS 的流行不仅是因为它易于实现，还因为它对订单参数的特定选择不是很敏感。然而，传统 FFS 中使用的顺序参数仍然需要满足严格的平滑标准，以确保顺序跨越 FFS 里程碑。对于用于描述聚集现象（例如结晶）的有序参数，通常会违反此条件。在这里，我们提出了一种不再需要这种平滑准则的广义 FFS 算法，并将其应用于计算多个系统中的均匀晶体成核速率。我们的数值测试表明，传统的 FFS 有时会低估成核率几个数量级。由 AIP 出版社出版。
Forward-flux sampling (FFS) is a path sampling technique that has gained increased popularity in recent years and has been used to compute rates of rare event phenomena such as crystallization, condensation, hydrophobic evaporation, DNA hybridization, and protein folding. The popularity of FFS is not only due to its ease of implementation but also because it is not very sensitive to the particular choice of an order parameter. The order parameter utilized in conventional FFS, however, still needs to satisfy a stringent smoothness criterion in order to assure sequential crossing of FFS milestones. This condition is usually violated for order parameters utilized for describing aggregation phenomena such as crystallization. Here, we present a generalized FFS algorithm for which this smoothness criterion is no longer necessary and apply it to compute homogeneous crystal nucleation rates in several systems. Our numerical tests reveal that conventional FFS can sometimes underestimate the nucleation rate by several orders of magnitude. Published by AIP Publishing.