Karabin Mariia, Stuart Steven J
Department of Chemistry, Clemson University, Clemson, South Carolina 29634, USA.
J Chem Phys. 2020 Sep 21;153(11):114103. doi: 10.1063/5.0018725.
As one of the most robust global optimization methods, simulated annealing has received considerable attention with many variations that attempt to improve the cooling schedule. This paper introduces a variant of molecular dynamics-based simulated annealing that is useful for optimizing atomistic structures, and makes use of the heat capacity of the system, determined on the fly during optimization, to adaptively control the cooling rate. This adaptive cooling approach is demonstrated to be more computationally efficient than classical simulated annealing when applied to Lennard-Jones clusters. The increase in efficiency is approximately a factor of two for clusters with 25-40 atoms, and improves as the size of the system increases.
作为最强大的全局优化方法之一,模拟退火受到了广泛关注,有许多变体试图改进冷却策略。本文介绍了一种基于分子动力学的模拟退火变体,它对于优化原子结构很有用,并利用在优化过程中实时确定的系统热容量来自适应地控制冷却速率。当应用于 Lennard-Jones 团簇时,这种自适应冷却方法被证明比经典模拟退火在计算上更高效。对于含有 25 - 40 个原子的团簇,效率提高了约两倍,并且随着系统规模的增加而提高。