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The Kramers turnover in terms of a macro-state projection on phase space

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  • We have investigated how Langevin dynamics is affected by the friction coefficient using the novel algorithm ISOKANN, which combines the transfer operator approach with modern machine learning techniques. ISOKANN describes the dynamics in terms of an invariant subspace projection of the Koopman operator defined in the entire state space, avoiding approximations due to dimensionality reduction and discretization. Our results are consistent with the Kramers turnover and show that in the low and moderate friction regimes, metastable macro-states and transition rates are defined in phase space, not only in position space.
Author:Luca DonatiORCiD, Christof Schütte, Marcus WeberORCiD
Document Type:Article
Parent Title (English):Molecular Physics
Issue:Ciccotti Special Issue (by invitation only)
First Page:e2356748
Publisher:Taylor & Francis
Year of first publication:2024
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