Central limit theorem for fluctuations of linear eigenvalue statistics of large random graphs

preprint2009arXivOpen access

Abstract

We consider the adjacency matrix AA of a large random graph and study fluctuations of the function fn(z,u)=1n∑k=1nexp⁡{−uGkk(z)}f_n(z,u)=\frac{1}{n}\sum_{k=1}^n\exp\{-uG_{kk}(z)\} with G(z)=(z−iA)−1G(z)=(z-iA)^{-1}. We prove that the moments of fluctuations normalized by n−1/2n^{-1/2} in the limit n→∞n\to\infty satisfy the Wick relations for the Gaussian random variables. This allows us to prove central limit theorem for TrG(z)\hbox{Tr}G(z) and then extend the result on the linear eigenvalue statistics Trϕ(A)\hbox{Tr}ϕ(A) of any function ϕ:R→Rϕ:\mathbb{R}\to\mathbb{R} which increases, together with its first two derivatives, at infinity not faster than an exponential.

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