Condensed Matter - Statistical Mechanics, Condensed Matter - Disordered Systems and Neural Networks, Nonlinear Sciences - Adaptation and Self-Organizing Systems, Quantitative Biology - Neurons and Cognition

Scale invariance profoundly influences the dynamics and structure of complex systems, spanning from critical phenomena to network architecture. Here, we propose a precise definition of scale-invariant networks by leveraging the concept of a constant entropy-loss rate across scales in a renormalization-group coarse-graining setting. This framework enables us to differentiate between scale-free and scale-invariant networks, revealing distinct characteristics within each class. Furthermore, we offer a comprehensive inventory of genuinely scale-invariant networks, both natural and artificially constructed, demonstrating, e.g., that the human connectome exhibits notable features of scale invariance. Our findings open new avenues for exploring the scale-invariant structural properties crucial in biological and socio-technological systems.
Comment: 6 pages, 3 figures and Supplemental Material