2024/12/06 by Adami, V., Emdadi-Mahdimahalleh, S., Herrmann, H. J. +1
#Computational Physics (physics.comp-ph) #Data Analysis #FOS: Physical sciences #Physics and Society (physics.soc-ph) #Statistical Mechanics (cond-mat.stat-mech) #Statistics and Probability (physics.data-an)
paper · doi:10.48550/arxiv.2412.10406
We propose a novel paradigm for modeling real-world scale-free networks, where the integration of new nodes is driven by the combined attractiveness of degree and betweenness centralities, the competition of which (expressed by a parameter 0≤ p≤ 1) shapes the structure of the evolving network. We reveal the ability to seamlessly explore a vast landscape of scale-free networks, unlocking an entirely new class of complex networks that we call stars-with-filament structure. Remarkably, the average degree k of these networks grows like log t to some power, where t is time and the average shortest path length grows logarithmically with the system size for intermediate p values, offering fresh insights into the structural dynamics of scale-free systems. Our approach is backed by a robust mean-field theory, which nicely captures the dynamics of k. We further unveil a rich, p-dependent phase diagram, encompassing 47 real-world scale-free networks, shedding light on previously hidden patterns. This work opens exciting new avenues for understanding the universal properties of complex networks.