46 citations · 128 across the 9 of their papers we have counts for
8 papers · 1 filter
Near-optimality of conservative driving in discrete systems
Jann van der Meer, Andreas Dechant
Transferring a physical system from an initial to a final state while minimizing energetic losses is an interdisciplinary control problem that bridges stochastic thermodynamics and…
Inferring kinetics and entropy production from observable transitions in partially accessible, periodically driven Markov networks
Alexander M. Maier, Julius Degünther, Jann van der Meer +1
For a network of discrete states with a periodically driven Markovian dynamics, we develop an inference scheme for an external observer who has access to some transitions. Based on…
General theory for localizing the where and when of entropy production meets single-molecule experiments
Julius Degünther, Jann van der Meer, Udo Seifert
The laws of thermodynamics apply to biophysical systems on the nanoscale as described by the framework of stochastic thermodynamics. This theory provides universal, exact relations…
Fluctuating Entropy Production on the Coarse-Grained Level: Inference and Localization of Irreversibility
Julius Degünther, Jann van der Meer, Udo Seifert
Stochastic thermodynamics provides the framework to analyze thermodynamic laws and quantities along individual trajectories of small but fully observable systems. If the observable…
Waiting time distributions in hybrid models of motor-bead assays: A concept and tool for inference
Benjamin Ertel, Jann van der Meer, Udo Seifert
In single-molecule experiments, the dynamics of molecular motors are often observed indirectly by measuring the trajectory of an attached bead in a motor-bead assay. In this work,…
Time-resolved statistics of snippets as general framework for model-free entropy estimators
Jann van der Meer, Julius Degünther, Udo Seifert
Irreversibility is commonly quantified by entropy production. An external observer can estimate it through measuring an observable that is antisymmetric under time-reversal like a…