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.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Jan 05, 2023
- Source ID
- 10.1063/5.0110873
Entities
People
- Daniel M Zuckerman
- David Aristoff
- Gideon Simpson
- Jeremy Copperman
- Robert J Webber
Organizations
- California Institute of Technology
- Colorado State University
- Damon Runyon Cancer Research Foundation
- Drexel University
- National Institutes of Health
- National Science Foundation
- Office of Naval Research
- Oregon Health & Science University