Outliers for deformed inhomogeneous random matrices

Abstract: Inhomogeneous random matrices with a non-trivial variance profile determined by a symmetric stochastic matrix and with independent symmetrically sub-Gaussian entries up to Hermitian symmetry, include many prominent examples, such as remarkable sparse Wigner matrices and random band matrices in dimension d, and have been of great interest recently. The maximum of entry variances as a natural proxy of sparsity is both a key feature and a significant obstacle. In this paper, we study low-rank additive perturbations of such random matrices, and establish a sharp BBP phase transition for extreme eigenvalues at the level of law of large numbers. Under suitable conditions on the variance profile and the finite-rank perturbation, we also establish the fluctuations of spectral outliers that may be characterized by the general inhomogeneous random matrices. This reveals the strong non-universality phenomena, which may depend on eigenvectors, sparsity or geometric structure. Our proofs rely on ribbon graph expansions, upper bounds for diagram functions, large moment estimates and counting of typical diagrams.