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Nonequilibrium thermodynamics of the asymmetric Sherrington-Kirkpatrick model

Author

Listed:
  • Miguel Aguilera

    (BCAM – Basque Center for Applied Mathematics
    IKERBASQUE, Basque Foundation for Science
    University of Sussex)

  • Masanao Igarashi

    (Hokkaido University)

  • Hideaki Shimazaki

    (Kyoto University
    Hokkaido University)

Abstract

Most natural systems operate far from equilibrium, displaying time-asymmetric, irreversible dynamics characterized by a positive entropy production while exchanging energy and matter with the environment. Although stochastic thermodynamics underpins the irreversible dynamics of small systems, the nonequilibrium thermodynamics of larger, more complex systems remains unexplored. Here, we investigate the asymmetric Sherrington-Kirkpatrick model with synchronous and asynchronous updates as a prototypical example of large-scale nonequilibrium processes. Using a path integral method, we calculate a generating functional over trajectories, obtaining exact solutions of the order parameters, path entropy, and steady-state entropy production of infinitely large networks. Entropy production peaks at critical order-disorder phase transitions, but is significantly larger for quasi-deterministic disordered dynamics. Consequently, entropy production can increase under distinct scenarios, requiring multiple thermodynamic quantities to describe the system accurately. These results contribute to developing an exact analytical theory of the nonequilibrium thermodynamics of large-scale physical and biological systems and their phase transitions.

Suggested Citation

  • Miguel Aguilera & Masanao Igarashi & Hideaki Shimazaki, 2023. "Nonequilibrium thermodynamics of the asymmetric Sherrington-Kirkpatrick model," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
  • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-39107-y
    DOI: 10.1038/s41467-023-39107-y
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    References listed on IDEAS

    as
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    4. Touchette, Hugo, 2018. "Introduction to dynamical large deviations of Markov processes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 504(C), pages 5-19.
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