Journal
ANNALS OF APPLIED PROBABILITY
Volume 31, Issue 5, Pages 2441-2477Publisher
INST MATHEMATICAL STATISTICS-IMS
DOI: 10.1214/20-AAP1652
Keywords
Adaptive biasing dynamics; metadynamics; Ray-Knight representation; self-repelling diffusions
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Funding
- European Research Council under the European Union [614492]
- European Research Council (ERC) [614492] Funding Source: European Research Council (ERC)
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By drawing a parallel between metadynamics and self interacting models for polymers, the study focuses on the longtime convergence of the original metadynamics algorithm in the adiabatic setting, and discusses the bias introduced when the adiabatic assumption does not hold.
By drawing a parallel between metadynamics and self interacting models for polymers, we study the longtime convergence of the original metadynamics algorithm in the adiabatic setting, namely when the dynamics along the collective variables decouples from the dynamics along the other degrees of freedom. We also discuss the bias which is introduced when the adiabatic assumption does not hold.
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