Analysis and optimization of weighted ensemble sampling
For researchers in molecular dynamics, this work provides theoretical guarantees and optimization strategies for WE sampling, though it is an incremental extension of existing methods.
The paper provides a mathematical framework for weighted ensemble (WE) sampling, proving its unbiasedness in a general setting including adaptive binning, and shows that coarse models can optimize replica allocation for stationary calculations.
We give a mathematical framework for weighted ensemble (WE) sampling, a binning and resampling technique for efficiently computing probabilities in molecular dynamics. We prove that WE sampling is unbiased in a very general setting that includes adaptive binning. We show that when WE is used for stationary calculations in tandem with a coarse model, the coarse model can be used to optimize the allocation of replicas in the bins.