Motif enrichment as a driver of scale-free behavior in rewired random regular graphs
Pawat Akara-pipattana, Sergei Nechaev

TL;DR
This paper investigates how motif enrichment, specifically triangles, induces scale-free behavior in rewired random regular graphs through a phase transition, revealing an emergent preferential attachment mechanism.
Contribution
It introduces a phase transition model in rewired regular graphs driven by triangle motifs, explaining the emergence of scale-free degree distributions with a mean-field derivation.
Findings
Identifies a critical fugacity $r$ triggering a phase transition.
Shows the degree distribution follows a power law with exponent pprox 2.
Reveals most inter-cluster triangles are isosceles, linking motifs to network structure.
Abstract
We study the statistics of rewired random regular graphs (RRGs) in a mixed ensemble, where the average number of triangles is controlled by the fugacity , while the number of vertices and the vertex degree are fixed. This model exhibits a phase transition at critical fugacity from a triangle-poor phase (TPP), in which the number of triangles is independent of the system size, to a triangle-rich phase (TRP), in which the number of triangles scales linearly with the system size. We estimate by comparing the entropy of TPP with the energy of TRP. Above , the RRG becomes a two-phase system in which dense clusters are connected by a sparse scale-free sub-network characterized by a degree distribution, , with , independent of the size of the whole graph and its degree. We attribute this behavior to…
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