Nonequilibrium phase transitions and finite size scaling in weighted scale-free networks

TL;DR

This paper investigates nonequilibrium phase transitions in weighted scale-free networks, analyzing how immunization of early nodes affects epidemic spreading through mean-field theory and simulations.

Contribution

It introduces a finite-size scaling framework for weighted scale-free networks with immunization, combining analytical and simulation approaches.

Findings

Local scaling exponents differ between typical and highly connected nodes.

Theoretical predictions align with large-scale Monte Carlo simulation results.

Immunization impacts phase transition behavior in weighted networks.

Abstract

We consider nonequilibrium phase transitions in weighted scale-free networks, in which highly connected nodes, which are created earlier in time are partially immunized. For epidemic spreading we solve the dynamical mean-field equations and discuss finite-size scaling theory. The theoretical predictions are confronted with the results of large scale Monte Carlo simulations on the weighted Barab\'asi-Albert network. Local scaling exponents are found different at a typical site and at a node with very large connectivity.