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We consider an inhomogeneous ErdH{o}s-Renyi random graph $G_N$ with vertex set $[N] = {1,dots,N}$ for which the pair of vertices $i,j in [N]$, $i eq j$, is connected by an edge with probability $r(tfrac{i}{N},tfrac{j}{N})$, independently of other pairs of vertices. Here, $rcolon,[0,1]^2 to (0,1)$ is a symmetric function that plays the role of a reference graphon. Let $lambda_N$ be the maximal eigenvalue of the adjacency matrix of $G_N$. It is known that $lambda_N/N$ satisfies a large deviation principle as $N to infty$. The associated rate function $psi_r$ is given by a variational formula that involves the rate function $I_r$ of a large deviation principle on graphon space. We analyse this variational formula in order to identify the properties of $psi_r$, specially when the reference graphon is of rank 1.
We consider a dynamic ErdH{o}s-Renyi random graph (ERRG) on $n$ vertices in which each edge switches on at rate $lambda$ and switches off at rate $mu$, independently of other edges. The focus is on the analysis of the evolution of the associated empi
We develop a quantitative large deviations theory for random Bernoulli tensors. The large deviation principles rest on a decomposition theorem for arbitrary tensors outside a set of tiny measure, in terms of a novel family of norms generalizing the c
We consider the statistics of the extreme eigenvalues of sparse random matrices, a class of random matrices that includes the normalized adjacency matrices of the ErdH{o}s-Renyi graph $G(N,p)$. Tracy-Widom fluctuations of the extreme eigenvalues for
A wide array of random graph models have been postulated to understand properties of observed networks. Typically these models have a parameter $t$ and a critical time $t_c$ when a giant component emerges. It is conjectured that for a large class of
We consider the empirical eigenvalue distribution of an $mtimes m$ principal submatrix of an $ntimes n$ random unitary matrix distributed according to Haar measure. For $n$ and $m$ large with $frac{m}{n}=alpha$, the empirical spectral measure is well