From Stochastic Thermodynamics to Thermodynamic Inference

By U. Seifert. Annual Review of Condensed Matter Physics, 2019

235 citations recorded by the source corpus.

For a large class of nonequilibrium systems, thermodynamic notions like work, heat, and, in particular, entropy production can be identified on the level of fluctuating dynamical trajectories. Within stochastic thermodynamics various fluctuation theorems relating these quantities have been proven. Their application to experimental systems requires that all relevant mesostates are accessible. Recent advances address the typical situation that only partial, or coarse-grained, information about a system is available. Thermodynamic inference as a general strategy uses consistency constraints derived from stochastic thermodynamics to infer otherwise hidden properties of nonequilibrium systems. An important class in this respect are active particles, for which we resolve the conflicting strategies that have been proposed to identify entropy production. As a paradigm for thermodynamic inference, the thermodynamic uncertainty relation provides a lower bound on the entropy production through measurements of the dispersion of any current in the system. Likewise, it quantifies the cost of precision for biomolecular processes. Generalizations and ramifications allow the inference of, inter alia, model-free upper bounds on the efficiency of molecular motors and of the minimal number of intermediate states in enzymatic networks.

Subfields: Atomic and Molecular Physics, and Optics, Physical and Theoretical Chemistry, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/24f0a8a4fdeb58dae1b519d51b6cd22cec04c7e9

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Atomic and Molecular Physics, and Optics

1. P. Hänggi
2. P. Talkner
3. V. Vitelli
4. M. Cristina Marchetti
5. M. Bowick

In Physical and Theoretical Chemistry

1. V. Vitelli
2. P. Talkner
3. M. Cristina Marchetti
4. M. Bowick
5. P. Hänggi

In Statistical and Nonlinear Physics

1. P. Hänggi
2. P. Talkner
3. V. Vitelli
4. Anton Souslov
5. M. Cristina Marchetti
6. M. Bowick

Citations in the corpus

• Colloquium : Statistical mechanics and thermodynamics at strong coupling: Quantum and classical (2019, background): “(102), in a recent review of stochastic thermodynamics (Seifert, 2019) the fluctuating internal energy is proposed to agree with the conditional total system energy 〈Htot|x〉, i.e., without the subtraction of the 21 Once a fluctuating internal energy is assigned to the state of the total system, the…”
• Topological active matter (2020, background): “For example, active media can violate reciprocity 32,33 and detailed balance 34,35 .”