@article{b78afad6459f4edabfedfcca0d7759ca,
title = "Weighted ensemble: Recent mathematical developments",
abstract = "Weighted ensemble (WE) is an enhanced sampling method based on periodically replicating and pruning trajectories generated in parallel. WE has grown increasingly popular for computational biochemistry problems due, in part, to improved hardware and accessible software implementations. Algorithmic and analytical improvements have 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 that enhance the computational efficiency. The mathematical theory reveals a new strategy for optimizing trajectory management that approaches the best possible variance while generalizing to systems of arbitrary dimension.",
author = "D. Aristoff and J. Copperman and G. Simpson and Webber, {R. J.} and Zuckerman, {D. M.}",
note = "Funding Information: D. Aristoff and G. Simpson acknowledge the support from the National Science Foundation via Awards Nos DMS 2111277 and DMS 1818726. J. Copperman is a Damon Runyon Fellow supported by the Damon Runyon Cancer Research Foundation (DRQ-09-20). R. J. Webber was supported by the Office of Naval Research through BRC award N00014-18-1-2363 and the National Science Foundation through FRG award 1952777 under the aegis of Joel A. Tropp. D. M. Zuckerman was supported by the NIH under Grant No. GM115805. Computational resources were provided by Drexel{\textquoteright}s University Research Computing Facility. The authors are grateful to Mats Johnson for the preliminary numerical work related to the results in Sec. . Publisher Copyright: {\textcopyright} 2023 Author(s).",
year = "2023",
month = jan,
day = "7",
doi = "10.1063/5.0110873",
language = "English (US)",
volume = "158",
journal = "Journal of Chemical Physics",
issn = "0021-9606",
publisher = "American Institute of Physics Publising LLC",
number = "1",
}