Published January 7, 2023 | Version v2
Journal Article Open

Weighted ensemble: Recent mathematical developments

  • 1. ROR icon Colorado State University
  • 2. ROR icon Oregon Health & Science University
  • 3. ROR icon Drexel University
  • 4. ROR icon California Institute of Technology

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.

Additional 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's University Research Computing Facility. The authors are grateful to Mats Johnson for the preliminary numerical work related to the results in Sec. V.

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Additional details

Identifiers

Eprint ID
119083
Resolver ID
CaltechAUTHORS:20230207-728273600.4
DOI
10.1063/5.0110873
PMCID
PMC9822651

Funding

NSF
DMS-2111277
NSF
DMS-1818726
Damon Runyon Cancer Research Foundation
DRQ-09-20
Office of Naval Research (ONR)
N00014-18-1-2363
NSF
DMS-1952777
NIH
GM115805

Dates

Created
2023-03-14
Created from EPrint's datestamp field
Updated
2023-03-14
Created from EPrint's last_modified field