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Extremal eigenvectors of sparse random matrices

Probability 2026-02-24 v2 Mathematical Physics math.MP

Abstract

We consider a class of sparse random matrices, which includes the adjacency matrix of Erd\H{o}s-R\'enyi graph G(N,p){\bf G}(N,p). For N1+o(1)p1/2N^{-1+o(1)}\leq p\leq 1/2, we show that the non-trivial edge eigenvectors are asymptotically jointly normal. The main ingredient of the proof is an algorithm that directly computes the joint eigenvector distributions, without comparisons with GOE. The method is applicable in general. As an illustration, we also use it to prove the normal fluctuation in quantum ergodicity at the edge for Wigner matrices. Another ingredient of the proof is the isotropic local law for sparse matrices, which at the same time improves several existing results.

Keywords

Cite

@article{arxiv.2501.16444,
  title  = {Extremal eigenvectors of sparse random matrices},
  author = {Yukun He and Jiaoyang Huang and Chen Wang},
  journal= {arXiv preprint arXiv:2501.16444},
  year   = {2026}
}

Comments

47 pages, to appear in PTRF

R2 v1 2026-06-28T21:20:38.278Z