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Develop and evaluate π-Girsanov, a kinetic reweighting framework designed to construct Markov state models from biased, non-equilibrium, and multiensemble molecular dynamics simulations.

August 20, 2026The Journal of Chemical Physics

π -Girsanov: A generalized method to construct Markov state models from non-equilibrium and multiensemble biased simulations

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Authors

MZMingyuan ZhangUniversitat de Barcelona YWYong WangZhejiang University BKBettina G. KellerFreie Universität Berlin

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Overview

Computational study demonstrates accurate Markov state model construction across non-equilibrium and multiensemble simulations, highlighting enhanced kinetic reweighting.

Key Points

Develop and evaluate π-Girsanov, a kinetic reweighting framework designed to construct Markov state models from biased, non-equilibrium, and multiensemble molecular dynamics simulations.
Formulated π-Girsanov by decoupling the reweighting of the stationary density from the reweighting of the dynamical correlation function.
Benchmarked the framework against standard Girsanov reweighting using several analytical potential landscapes and a model biomolecular system across single-ensemble, multiensemble, and non-equilibrium trajectories.
π-Girsanov enhanced the accuracy of transition matrix and kinetic estimations in single-ensemble biased molecular simulations.
The method resolved critical estimation challenges when reconstructing equilibrium kinetics from complex multiensemble and non-equilibrium biased datasets.

Cite This Study

Zhang et al. (2026) studied this question.

synapsesocial.com/papers/6a86b56c8a91293e6a1ccd08 https://doi.org/10.1063/5.0335247

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August 20, 2026The Journal of Chemical Physics

π -Girsanov: A generalized method to construct Markov state models from non-equilibrium and multiensemble biased simulations

View Full Paper

Ask AI

Bookmark

Authors

MZMingyuan ZhangUniversitat de Barcelona YWYong WangZhejiang University BKBettina G. KellerFreie Universität Berlin

Discussion

Member takes

Overview

Computational study demonstrates accurate Markov state model construction across non-equilibrium and multiensemble simulations, highlighting enhanced kinetic reweighting.

Key Points

Develop and evaluate π-Girsanov, a kinetic reweighting framework designed to construct Markov state models from biased, non-equilibrium, and multiensemble molecular dynamics simulations.
Formulated π-Girsanov by decoupling the reweighting of the stationary density from the reweighting of the dynamical correlation function.
Benchmarked the framework against standard Girsanov reweighting using several analytical potential landscapes and a model biomolecular system across single-ensemble, multiensemble, and non-equilibrium trajectories.
π-Girsanov enhanced the accuracy of transition matrix and kinetic estimations in single-ensemble biased molecular simulations.
The method resolved critical estimation challenges when reconstructing equilibrium kinetics from complex multiensemble and non-equilibrium biased datasets.

Cite This Study

Zhang et al. (2026) studied this question.

synapsesocial.com/papers/6a86b56c8a91293e6a1ccd08 https://doi.org/10.1063/5.0335247

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