Large Deviations for Subgraphs in Inhomogeneous Random Graphs | Journal of Statistical Physics | Springer Nature Link (opens in new tab)

"Inhomogeneous random graphs are fundamental models for real-world networks, where prescribed degrees are imposed as soft constraints. A common assumption in such models is that the degree distribution follows a power-law, capturing the heavy-tailed nature observed in many contexts. While various graph functionals have been studied in this setting, inhomogeneity makes their analysis significantly more challenging. Here, we investigate the large deviations of subgraph counts in inhomogeneous r...