English

Eigenvector Statistics of Sparse Random Matrices

Probability 2017-06-30 v3

Abstract

We prove that the bulk eigenvectors of sparse random matrices, i.e. the adjacency matrices of Erd\H{o}s-R\'enyi graphs or random regular graphs, are asymptotically jointly normal, provided the averaged degree increases with the size of the graphs. Our methodology follows [6] by analyzing the eigenvector flow under Dyson Brownian motion, combining with an isotropic local law for Green's function. As an auxiliary result, we prove that for the eigenvector flow of Dyson Brownian motion with general initial data, the eigenvectors are asymptotically jointly normal in the direction qq after time ηtr\eta_*\ll t\ll r, if in a window of size rr, the initial density of states is bounded below and above down to the scale η\eta_*, and the initial eigenvectors are delocalized in the direction qq down to the scale η\eta_*.

Keywords

Cite

@article{arxiv.1609.09022,
  title  = {Eigenvector Statistics of Sparse Random Matrices},
  author = {Paul Bourgade and Jiaoyang Huang and Horng-Tzer Yau},
  journal= {arXiv preprint arXiv:1609.09022},
  year   = {2017}
}
R2 v1 2026-06-22T16:04:26.724Z