Bifractality of fractal scale-free networks (2304.13438v2)

Abstract: The presence of large-scale real-world networks with various architectures has motivated an active research towards a unified understanding of diverse topologies of networks. Such studies have revealed that many networks with the scale-free and fractal properties exhibit the structural multifractality, some of which are actually bifractal. Bifractality is a particular case of the multifractal property, where only two local fractal dimensions $d_{\text{f}}^{\text{min}}$ and $d_{\text{f}}^{\text{max}} (>d_{\text{f}}^{\text{min}})$ suffice to explain the structural inhomogeneity of a network. In this work, we investigate analytically and numerically the multifractal property of a wide range of fractal scale-free networks (FSFNs) including deterministic hierarchical, stochastic hierarchical, non-hierarchical, and real-world FSFNs. Then we demonstrate how commonly FSFNs exhibit the bifractal property. The results show that all these networks possess the bifractal nature. We conjecture from our findings that any FSFN is bifractal. Furthermore, we find that in the thermodynamic limit the lower local fractal dimension $d_{\text{f}}^{\text{min}}$ describes substructures around infinitely high-degree hub nodes and finite-degree nodes at finite distances from these hub nodes, whereas $d_{\text{f}}^{\text{max}}$ characterizes local fractality around finite-degree nodes infinitely far from the infinite-degree hub nodes. Since the bifractal nature of FSFNs may strongly influence time-dependent phenomena on FSFNs, our results will be useful for understanding dynamics such as information diffusion and synchronization on FSFNs from a unified perspective.