Uniform regular weighted graphs with large degree: Wigner's law, asymptotic freeness and graphons limit

preprint2014arXivOpen access

Abstract

For each N≥1N\geq 1, let GNG_N be a simple random graph on the set of vertices [N]={1,2,...,N}[N]=\{1,2, ..., N\}, which is invariant by relabeling of the vertices. The asymptotic behavior as NN goes to infinity of correlation functions: CN(T)=E[∏(i,j)∈T(1({i,j}∈GN)−P({i,j}∈GN))], T⊂[N]2finite \mathfrak C_N(T)= \mathbb E\bigg[ \prod_{(i,j) \in T} \Big(\mathbf 1_{\big(\{i,j\} \in G_N \big)} - \mathbb P(\{i,j\} \in G_N) \Big)\bigg], \ T \subset [N]^2 \textrm{finite} furnishes informations on the asymptotic spectral properties of the adjacency matrix ANA_N of GNG_N. Denote by dN=N×P({i,j}∈GN)d_N = N\times \mathbb P(\{i,j\} \in G_N) and assume dN,N−dN⟶N→∞∞d_N, N-d_N\underset{N \rightarrow \infty}{\longrightarrow} \infty. If CN(T)=(dNN)∣T∣×O(dN−∣T∣2)\mathfrak C_N(T) =\big(\frac{d_N}N\big)^{|T|} \times O\big(d_N^{-\frac {|T|}2}\big) for any TT, the standardized empirical eigenvalue distribution of ANA_N converges in expectation to the semicircular law and the matrix satisfies asymptotic freeness properties in the sense of free probability theory. We provide such estimates for uniform dNd_N-regular graphs GN,dNG_{N,d_N}, under the additional assumption that ∣N2−dN−ηdN∣⟶N→∞∞|\frac N 2 - d_N- η\sqrt{d_N}| \underset{N \rightarrow \infty}{\longrightarrow} \infty for some η>0η>0. Our method applies also for simple graphs whose edges are labelled by i.i.d. random variables.

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