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Criticality in a hybrid spin model with Fermi–Dirac statistics

Author

Listed:
  • Contoyiannis, Y.F.
  • Potirakis, S.M.
  • Diakonos, F.K.
  • Kosmidis, E.K.

Abstract

Combining concepts of artificial neural networks (ANNs) with the stochastic dynamics of Ising spin lattices we introduce a hybrid model, the hybrid spin model (HSM). We find that the HSM carries the critical/tricritical fluctuations of the 2D Ising model and allows for an accurate estimation of the isothermal critical/tricritical exponents of 2D Ising universality class. Our work clearly demonstrates that HSM launches a new category of models supporting alternative pathways for the realization of criticality in complex networks artificial or real.

Suggested Citation

  • Contoyiannis, Y.F. & Potirakis, S.M. & Diakonos, F.K. & Kosmidis, E.K., 2021. "Criticality in a hybrid spin model with Fermi–Dirac statistics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 577(C).
    • Handle: RePEc:eee:phsmap:v:577:y:2021:i:c:s0378437121003460
    DOI: 10.1016/j.physa.2021.126073
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    Cited by:

    1. Contoyiannis, Yiannis F. & Kosmidis, Efstratios K. & Diakonos, Fotios K. & Kampitakis, Myron & Potirakis, Stelios M., 2022. "A hybrid artificial neural network for the generation of critical fluctuations and inter-spike intervals," Chaos, Solitons & Fractals, Elsevier, vol. 159(C).
    2. Zitis, Pavlos I. & Contoyiannis, Yiannis & Potirakis, Stelios M., 2022. "Critical dynamics related to a recent Bitcoin crash," International Review of Financial Analysis, Elsevier, vol. 84(C).

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