# Spin-glass transition in the Ising model on multiplex networks

## TL;DR

This paper investigates the phase transitions of the Ising model on multiplex networks with two layers, analyzing how network structure and degree correlations influence critical temperatures and phases, supported by analytical and simulation methods.

## Contribution

It provides a semi-analytic analysis of critical temperatures and phase behavior of the Ising model on multiplex networks with scale-free layers, highlighting the impact of degree correlations.

## Key findings

- Critical temperature is finite if degree distributions have finite second moments.
- Transition can be to ferromagnetic or spin glass phase depending on parameters.
- Degree correlations significantly influence critical temperatures and phase diagram.

## Abstract

Multiplex networks consist of a fixed set of nodes connected by several sets of edges which are generated separately and correspond to different networks ("layers"). Here, the Ising model on multiplex networks with two layers is considered, with spins located in the nodes and edges corresponding to ferromagnetic or antiferromagnetic interactions between them. Critical temperatures for the spin glass and ferromagnetic transitions are evaluated for the layers in the form of random Erd\"os-R\'enyi graphs or heterogeneous scale-free networks using the replica method, from the replica symmetric solution. For the Ising model on multiplex networks with scale-free layers it is shown that the critical temperature is finite if the distributions of the degrees of nodes within both layers have a finite second moment, and that depending on the model parameters the transition can be to the ferromagnetic or spin glass phase. It is also shown that the correlation between the degrees of nodes within different layers significantly influences the critical temperatures for both transitions and thus the phase diagram. The scaling behavior for the spin glass order parameter is determined by a semi-analytic procedure and it is shown that for the Ising model on multiplex networks with scale-free layers the scaling exponent can depend on the distributions of the degrees of nodes within layers. The analytic results are partly confirmed by Monte Carlo simulations using the parallel tempering algorithm.