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Spectrum of Directed Inhomogeneous Random Graphs

Probability 2026-07-09 v1

Abstract

We study the spectrum of the adjacency matrix AnA_n of directed inhomogeneous random graphs on nn vertices. We assume that AnA_n has independent entries and diverging average degree scale sns_n. This framework includes, as special cases, the directed Chung--Lu random graph and directed stochastic block models. Assuming boundedness of the variance profile and that sns_n diverges faster than a suitable logarithmic function of nn, we show that the rank-one Chung--Lu model satisfies a non-homogeneous version of the circular law, which in some situations allows for an explicit expression. Moreover, under mild conditions, we identify the asymptotic singular value distribution using tools from free probability. Finally, for finite-rank directed models, we prove the existence of eigenvalues outside the bulk and establish their joint Gaussian fluctuations at the scale sn/n\sqrt{s_n/n}, with an explicit covariance matrix. These results extend the theory of spectral outliers and their fluctuations to directed inhomogeneous random graphs.

Keywords

Cite

@article{arxiv.2607.08696,
  title  = {Spectrum of Directed Inhomogeneous Random Graphs},
  author = {Rajat Subhra Hazra and Giacomo Passuello},
  journal= {arXiv preprint arXiv:2607.08696},
  year   = {2026}
}

Comments

35 pages, 2 figures