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Edge Universality of Sparse Random Matrices

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arxiv 2206.06580 v2 pith:ECSEVNFE submitted 2022-06-14 math.PR math-phmath.COmath.MP

classification math.PRmath-phmath.COmath.MP
keywords randomeigenvaluesmatricesexplicitextremegraphholdsoptimal
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abstract

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 Erd{\H o}s-R{\'e}nyi graph $G(N,p)$. Recently, it was shown by Lee, up to an explicit random shift, the optimal rigidity of extreme eigenvalues holds, provided the averaged degree grows with the size of the graph, $pN>N^\varepsilon$. We prove in the same regime, (i) Optimal rigidity holds for all eigenvalues with respect to an explicit random measure. (ii) Up to an explicit random shift, the fluctuations of the extreme eigenvalues are given the Tracy-Widom distribution.

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Forward citations

Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Sharp Square Root Bounds for Edge Eigenvector Universality in Sparse Random Regular Graphs

    math.PR 2025-07 reject novelty 6.0 of 10

    A claimed optimal Berry-Esseen bound of order sqrt(d) N^{-1/6+eps} for eigenvector projections of random d-regular graphs, with a matching lower bound.

  2. Ramanujan Graphs and Interlacing Families

    math.CO 2024-12 accept

    A survey of the interlacing families method and the existence proofs it gives for bipartite Ramanujan graphs of all degrees and sizes.

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