Limiting spectra of inhomogeneous random graphs

In this paper, we consider sparse inhomogeneous Erdős–Rényi random graph ensembles where edges are connected independently with probability [Formula: see text]. We assume that [Formula: see text] where [Formula: see text] is a sequence of deterministic weights, [Formula: see text] is a bounded function and [Formula: see text]. We characterize the limiting moments in terms of graph homomorphisms and also classify the contributing partitions. We present an analytic way to determine the Stieltjes transform of the limiting measure. The convergence of the empirical distribution function follows from the theory of local weak convergence in many examples but we do not rely on this theory and exploit combinatorial and analytic techniques to derive some interesting properties of the limit. We extend the methods of O. Khorunzhy et al. [Eigenvalue distribution of large weighted random graphs, J. Math. Phys. 45(4) (2004) 1648–1672, https://doi.org/10.1063/1.1667610] and show that a fixed point equation determines the limiting measure. The limiting measure crucially depends on [Formula: see text] and it is known that in the homogeneous case, if [Formula: see text], the measure converges weakly to the semicircular law [P. Jung and J. Lee, Delocalization and limiting spectral distribution of Erdős–Rényi graphs with constant expected degree, Electron. Commun. Probab. 23 (2018) 92, https://doi.org/10.1214/18-ECP198]. We extend this result of interpolating between the sparse and dense regimes to the inhomogeneous setting and show that as [Formula: see text], the measure converges weakly to a measure which is known as the operator-valued semicircular law.