Finite-size scaling of percolation on scale-free networks

TL;DR

This paper investigates how finite-size effects influence percolation on scale-free networks, revealing two main pathways to mean-field behavior driven by network heterogeneity parameters.

Contribution

It provides a unified framework for understanding the crossover from heterogeneous to homogeneous criticality in scale-free networks through finite-size scaling analysis.

Findings

Identification of two crossover routes to mean-field behavior

Rich finite-size phenomena including susceptibility transition

Clarification of theoretical predictions with numerical results

Abstract

Critical phenomena on scale-free networks with a degree distribution $p_k \sim k^{-\lambda}$ exhibit rich finite-size effects due to its structural heterogeneity. We systematically study the finite-size scaling of percolation and identify two distinct crossover routes to mean-field behavior: one controlled by the degree exponent $\lambda$, the other by the degree cutoff $K \sim V^{\kappa}$, where $V$ is the system size and $\kappa \in [0,1]$ is the cutoff exponent. Increasing $\lambda$ or decreasing $\kappa$ suppresses heterogeneity and drives the system toward mean-field behavior, with logarithmic corrections near the marginal case. These findings provide a unified picture of the crossover from heterogeneous to homogeneous criticality. In the crossover regime, we observe rich finite-size phenomena, including the transition from vanishing to divergent susceptibility, distinct exponents for the shift and fluctuation of pseudocritical points, and a numerical clarification of previous theoretical predictions.