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 . For , 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.
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