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Stochastic thermodynamics: From principles to the cost of precision

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  • Seifert, Udo

Abstract

In these lecture notes, the basic principles of stochastic thermodynamics are developed starting with a closed system in contact with a heat bath. A trajectory undergoes Markovian transitions between observable meso-states that correspond to a coarse-grained description of, e.g., a biomolecule or a biochemical network. By separating the closed system into a core system and into reservoirs for ligands and reactants that bind to, and react with the core system, a description as an open system controlled by chemical potentials and possibly an external force is achieved. Entropy production and further thermodynamic quantities defined along a trajectory obey various fluctuation theorems. For describing fluctuations in a non-equilibrium steady state in the long-time limit, the concept of a rate function for large deviations from the mean behavior is derived from the weight of a trajectory. Universal bounds on this rate function follow which prove and generalize the thermodynamic uncertainty relation that quantifies the inevitable trade-off between cost and precision of any biomolecular process. Specific illustrations are given for molecular motors, Brownian clocks and enzymatic networks that show how these tools can be used for thermodynamic inference of hidden properties of a system.

Suggested Citation

  • Seifert, Udo, 2018. "Stochastic thermodynamics: From principles to the cost of precision," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 504(C), pages 176-191.
  • Handle: RePEc:eee:phsmap:v:504:y:2018:i:c:p:176-191
    DOI: 10.1016/j.physa.2017.10.024
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    References listed on IDEAS

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    1. Van den Broeck, C. & Esposito, M., 2015. "Ensemble and trajectory thermodynamics: A brief introduction," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 418(C), pages 6-16.
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    Cited by:

    1. Wio, H.S. & Deza, J.I. & Sánchez, A.D. & García-García, R. & Gallego, R. & Revelli, J.A. & Deza, R.R., 2022. "The nonequilibrium potential today: A short review," Chaos, Solitons & Fractals, Elsevier, vol. 165(P1).
    2. Giulio Chiribella & Fei Meng & Renato Renner & Man-Hong Yung, 2022. "The nonequilibrium cost of accurate information processing," Nature Communications, Nature, vol. 13(1), pages 1-10, December.

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