Department of Chemical and Environmental Engineering, Yale University, New Haven, Connecticut 06520, USA.
J Chem Phys. 2018 Aug 21;149(7):072303. doi: 10.1063/1.5018303.
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.
前向通量抽样（FFS）是一种路径抽样技术，近年来越来越受欢迎，并被用于计算罕见事件现象的速率，如结晶、冷凝、疏水性蒸发、DNA 杂交和蛋白质折叠。FFS 的流行不仅是因为它易于实现，还因为它对选择特定的序参量不那么敏感。然而，传统 FFS 中使用的序参量仍然需要满足严格的平滑性准则，以确保 FFS 里程碑的顺序穿越。对于用于描述结晶等聚集现象的序参量，通常会违反此条件。在这里，我们提出了一种广义的 FFS 算法，该算法不再需要此平滑性准则，并将其应用于计算几个系统中的均相晶体成核速率。我们的数值测试表明，传统的 FFS 有时会低估成核速率几个数量级。
