Udo Seifert - From stochastic thermodynamics to thermodynamic inference

This talk was part of the Thematic Programme on "Large Deviations, Extremes and Anomalous Transport in Non-equilibrium Systems" held at the ESI September 19 to October 14, 2022.

Stochastic thermodynamics provides a universal framework for analyzing
nano- and micro-sized non-equilibrium systems. Prominent examples are
single molecules, molecular machines, colloidal particles in time-dependent
laser traps and biochemical networks. Thermodynamic notions like work, heat and entropy can be identified on the level of individual fluctuating
trajectories. They obey universal relations like the fluctuation theorem.
Thermodynamic inference as a general strategy uses consistency constraints derived from stochastic thermodynamics to infer otherwise hidden properties of non-equilibrium systems. As a paradigm for thermodynamic inference, the thermodynamic uncertainty relation provides a lower bound on the entropy production through measurements of the mean and dispersion of any current in the system. Likewise, it provides a model-free bound on the thermodynamic efficiency of molecular motors. Waiting-time distributions between consecutive transitions in a discrete Markov network yield an even better estimator of entropy production. Moreover, they reveal further information about the topology of the underlying network. From the observation of coherent oscillations, a universal bound on their thermodynamic cost can be deduced.

Видео Udo Seifert - From stochastic thermodynamics to thermodynamic inference канала Erwin Schrödinger International Institute for Mathematics and Physics (ESI)