Literature DB >> 29448440

Thermodynamics and computation during collective motion near criticality.

Emanuele Crosato1, Richard E Spinney1, Ramil Nigmatullin1, Joseph T Lizier1, Mikhail Prokopenko1.   

Abstract

We study self-organization of collective motion as a thermodynamic phenomenon in the context of the first law of thermodynamics. It is expected that the coherent ordered motion typically self-organises in the presence of changes in the (generalized) internal energy and of (generalized) work done on, or extracted from, the system. We aim to explicitly quantify changes in these two quantities in a system of simulated self-propelled particles and contrast them with changes in the system's configuration entropy. In doing so, we adapt a thermodynamic formulation of the curvatures of the internal energy and the work, with respect to two parameters that control the particles' alignment. This allows us to systematically investigate the behavior of the system by varying the two control parameters to drive the system across a kinetic phase transition. Our results identify critical regimes and show that during the phase transition, where the configuration entropy of the system decreases, the rates of change of the work and of the internal energy also decrease, while their curvatures diverge. Importantly, the reduction of entropy achieved through expenditure of work is shown to peak at criticality. We relate this both to a thermodynamic efficiency and the significance of the increased order with respect to a computational path. Additionally, this study provides an information-geometric interpretation of the curvature of the internal energy as the difference between two curvatures: the curvature of the free entropy, captured by the Fisher information, and the curvature of the configuration entropy.

Year:  2018        PMID: 29448440     DOI: 10.1103/PhysRevE.97.012120

Source DB:  PubMed          Journal:  Phys Rev E        ISSN: 2470-0045            Impact factor:   2.529


  5 in total

1.  Thermodynamic efficiency of contagions: a statistical mechanical analysis of the SIS epidemic model.

Authors:  Nathan Harding; Ramil Nigmatullin; Mikhail Prokopenko
Journal:  Interface Focus       Date:  2018-10-19       Impact factor: 3.906

2.  Phase Transitions in Spatial Connectivity during Influenza Pandemics.

Authors:  Nathan Harding; Richard Spinney; Mikhail Prokopenko
Journal:  Entropy (Basel)       Date:  2020-01-22       Impact factor: 2.524

3.  On critical dynamics and thermodynamic efficiency of urban transformations.

Authors:  Emanuele Crosato; Ramil Nigmatullin; Mikhail Prokopenko
Journal:  R Soc Open Sci       Date:  2018-10-17       Impact factor: 2.963

4.  A least microenvironmental uncertainty principle (LEUP) as a generative model of collective cell migration mechanisms.

Authors:  Arnab Barua; Josue M Nava-Sedeño; Michael Meyer-Hermann; Haralampos Hatzikirou
Journal:  Sci Rep       Date:  2020-12-22       Impact factor: 4.379

5.  Scale-Free Dynamics in Animal Groups and Brain Networks.

Authors:  Tiago L Ribeiro; Dante R Chialvo; Dietmar Plenz
Journal:  Front Syst Neurosci       Date:  2021-01-20
  5 in total

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