CLT for LES of real valued random centrosymmetric matrices

We study the fluctuations of the eigenvalues of real valued large centrosymmetric random matrices via its linear eigenvalue statistic. This is essentially a central limit theorem (CLT) for sums of dependent random variables. The dependence among them leads to behavior that differs from the classical CLT. The main contribution of this article is finding the expression of the variance of the limiting Gaussian distribution. The crux of the proof lies in combinatorial arguments that involve counting overlapping loops in complete undirected weighted graphs with growing degrees.