English

p-star models, mean field random networks and the heat hierarchy

Statistical Mechanics 2022-01-26 v1 Pattern Formation and Solitons Exactly Solvable and Integrable Systems

Abstract

We consider the mean field analog of the p-star model for homogeneous random networks, and compare its behaviour with that of the p-star model and its classical mean field approximation in the thermodynamic regime. We show that the partition function of the mean field model satisfies a sequence of partial differential equations known as the heat hierarchy, and the models connectance is obtained as a solution of a hierarchy of nonlinear viscous PDEs. In the thermodynamic limit, the leading order solution develops singularities in the space of parameters that evolve as classical shocks regularised by a viscous term. Shocks are associated with phase transitions and stable states are automatically selected consistently with the Maxwell construction. The case p = 3 is studied in detail. Monte Carlo simulations show an excellent agreement between the p-star model and its mean field analog at the macroscopic level, although significant discrepancies arise when local features are compared.

Keywords

Cite

@article{arxiv.2105.09479,
  title  = {p-star models, mean field random networks and the heat hierarchy},
  author = {Gino Biondini and Antonio Moro and Barbara Prinari and Oleg Senkevich},
  journal= {arXiv preprint arXiv:2105.09479},
  year   = {2022}
}

Comments

12 pages, 9 figures