Berlin 2024 – scientific programme

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DY: Fachverband Dynamik und Statistische Physik

DY 31: Poster: Statistical Physics

DY 31.11: Poster

Wednesday, March 20, 2024, 15:00–18:00, Poster C

Entropy estimators based on waiting-time distributions for overdamped Langevin dynamics — •Ellen Meyberg and Udo Seifert — II. Institut für Theoretische Physik, Universität Stuttgart, Deutschland

Stochastic systems are usually only accessible on the meso-scale rather than on the micro-scale leading to the need of an effective, coarse-grained description that is often only partially accessible. Usually, coarse-graining is done by lumping many states together into one compound state. Recently, it has been shown that a complementary coarse-graining based on transitions between Markov states can provide bounds on the entropy production [1]. The logarithmic ratio of waiting-time distributions between two successive transitions in forward and backward direction is a measure of time-irreversibility and thus yields a lower bound on the entropy production. This bound is exact in the case of a uni-cyclic network and can be applied without knowing the steady-state distribution. How can the result obtained for Markov jump processes be applied to an overdamped Langevin dynamics? We explain how transitions can be defined for a continuous dynamics using the milestoning approach [2] and show that the entropy estimator for a uni-cyclic network based on this definition yields the full one.

[1] J. van der Meer, B. Ertel, and U. Seifert, Phys. Rev. X 12, 031025 (2022).

[2] D. Hartich and A. Godec, Phys. Rev. X 11, 041047 (2021).

Keywords: Stochastic Thermodynamics; Coarse-Graining; Entropy estimator