Weighted ensemble: Recent mathematical developments

被引:8
|
作者
Aristoff, D. [1 ]
Copperman, J. [2 ]
Simpson, G. [3 ]
Webber, R. J. [4 ]
Zuckerman, D. M. [2 ]
机构
[1] Colorado State Univ, Math, Ft Collins, CO 80521 USA
[2] Oregon Hlth & Sci Univ, Biomed Engn, Portland, OR 97239 USA
[3] Drexel Univ, Math, Philadelphia, PA 19104 USA
[4] CALTECH, Comp & Math Sci, Pasadena, CA 91125 USA
来源
JOURNAL OF CHEMICAL PHYSICS | 2023年 / 158卷 / 01期
基金
美国国家科学基金会;
关键词
MOLECULAR-DYNAMICS; SIMULATIONS;
D O I
10.1063/5.0110873
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
The weighted ensemble (WE) method, an enhanced sampling approach based on periodically replicating and pruning trajectories in a set of parallel simulations, has grown increasingly popular for computational biochemistry problems, due in part to improved hardware and the availability of modern software. Algorithmic and analytical improvements have also played an important role, and progress has accelerated in recent years. Here, we discuss and elaborate on the WE method from a mathematical perspective, highlighting recent results which have begun to yield greater computational efficiency. Notable among these innovations are variance reduction approaches that optimize trajectory management for systems of arbitrary dimensionality.
引用
收藏
页数:13
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