title: Steady-state simulations using weighted ensemble path sampling.
abstract: We extend the weighted ensemble (WE) path sampling method to perform rigorous statistical sampling for systems at steady state. A straightforward steady-state implementation of WE is directly practical for simple landscapes, but not when significant metastable intermediates states are present. We therefore develop an enhanced WE scheme, building on existing ideas, which accelerates attainment of steady state in complex systems. We apply both WE approaches to several model systems, confirming their correctness and efficiency by comparison with brute-force results. The enhanced version is significantly faster than the brute force and straightforward WE for systems with WE bins that accurately reflect the reaction coordinate(s). The new WE methods can also be applied to equilibrium sampling, since equilibrium is a steady state.
authors.affiliation: Department of Computational Biology, University of Pittsburgh, Pennsylvania 15260, USA.
authors.forename: Divesh
authors.initials: D
authors.lastname: Bhatt
authors.forename: Bin W
authors.initials: BW
authors.lastname: Zhang
authors.forename: Daniel M
authors.initials: DM
authors.lastname: Zuckerman
mesh_terms: D004151:Dipeptides / Q000737:chemistry; D008962:Models, Theoretical; D011336:Probability; D013696:Temperature; D013816:Thermodynamics
chemical_list: D004151:Dipeptides; C002956:alanylalanine