Heavy-tailed configuration models at criticality
Souvik Dhara, Remco van der Hofstad, Johan S.H. van Leeuwaarden and, Sanchayan Sen

TL;DR
This paper investigates the critical behavior of component sizes in heavy-tailed configuration models with degree distributions having a power-law tail, revealing a different universality class from Erdős-Rényi graphs and confirming a conjecture about their scaling limits.
Contribution
It establishes the scaling limits of component sizes in heavy-tailed configuration models, proving convergence to a thinned Lévy process and resolving a conjecture from prior work.
Findings
Component sizes scale as n^{( au-2)/( au-1)}L(n)^{-1}.
Rescaled component sizes converge to excursions of a thinned Lévy process.
The joint distribution of component sizes and surplus edges converges under a strong topology.
Abstract
We study the critical behavior of the component sizes for the configuration model when the tail of the degree distribution of a randomly chosen vertex is a regularly-varying function with exponent , where . The component sizes are shown to be of the order for some slowly-varying function . We show that the re-scaled ordered component sizes converge in distribution to the ordered excursions of a thinned L\'evy process. This proves that the scaling limits for the component sizes for these heavy-tailed configuration models are in a different universality class compared to the Erd\H{o}s-R\'enyi random graphs. Also the joint re-scaled vector of ordered component sizes and their surplus edges is shown to have a distributional limit under a strong topology. Our proof resolves a conjecture by Joseph, Ann. Appl. Probab. (2014)…
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