English

Fractal fluctuations at mixed-order transitions in interdependent networks

Disordered Systems and Neural Networks 2023-01-04 v1 Statistical Mechanics

Abstract

We study the geometrical features of the order parameter's fluctuations near the critical point of mixed-order phase transitions in randomly interdependent spatial networks. In contrast to continuous transitions, where the structure of the order parameter at criticality is fractal, in mixed-order transitions the structure of the order parameter is known to be compact. Remarkably, we find that although being compact, the fluctuations of the order parameter close to mixed-order transitions are fractal up to a well-defined correlation length ξ\xi', which diverges when approaching the critical threshold. We characterize the self-similar nature of these critical fluctuations through their fractal dimension, df=3d/4d_f'=3d/4, and correlation length exponent, ν=2/d\nu'=2/d, where dd is the dimension of the system. By means of percolation and magnetization, we demonstrate that dfd_f' and ν\nu' are independent on the symmetry of the underlying process for any dd of the underlying networks.

Keywords

Cite

@article{arxiv.2208.00440,
  title  = {Fractal fluctuations at mixed-order transitions in interdependent networks},
  author = {Bnaya Gross and Ivan Bonamassa and Shlomo Havlin},
  journal= {arXiv preprint arXiv:2208.00440},
  year   = {2023}
}
R2 v1 2026-06-25T01:21:40.555Z