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Higher order fluctuations of extremal eigenvalues of sparse random matrices

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arxiv 2108.11634 v4 pith:SAQ25WZO submitted 2021-08-26 math.PR

classification math.PR
keywords randomeigenvaluesextremalmatricesepsilonfluctuationsordercorrection
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abstract

We consider extremal eigenvalues of sparse random matrices, a class of random matrices including the adjacency matrices of Erd\H{o}s-R\'{e}nyi graphs $\mathcal{G}(N,p)$. Recently, it was shown that the leading order fluctuations of extremal eigenvalues are given by a single random variable associated with the total degree of the graph (Ann. Probab., 48(2):916-962, 2020; Probab. Theory Related Fields, 180:985-1056, 2021). We construct a sequence of random correction terms to capture higher (sub-leading) order fluctuations of extremal eigenvalues in the regime $N^{\epsilon} < pN < N^{1/3-\epsilon}$. Using these random correction terms, we prove a local law up to a shifted edge and recover the rigidity of extremal eigenvalues under some corrections for $pN>N^{\epsilon}$.

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Cited by 2 Pith papers

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

  1. Quantitative Tracy-Widom laws for sparse random matrices

    math.PR 2025-07 conditional novelty 7.0 of 10

    For sparse random matrices with q ≥ N^{1/6+δ}, the largest eigenvalue, after a small model-dependent correction, converges to Tracy-Widom at rate almost N^{-1/3} + N^{2/3}/q^4.

  2. Matrix Completion via Residual Spectral Matching

    stat.ML 2024-12 reject novelty 7.0 of 10

    A residual spectral matching estimator for noisy matrix completion matches the singular values of residuals to those of sparse random matrices and claims minimax optimal error rates.

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