Abstract
We consider a class of sparse random matrices, which includes the adjacency matrix of the Erdős-Rényi graph G(N, p). For N−1+o(1) ⩽ p ⩽ 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. © The Author(s) 2026.
| Original language | English |
|---|---|
| Number of pages | 58 |
| Journal | Probability Theory and Related Fields |
| Online published | 6 Mar 2026 |
| DOIs | |
| Publication status | Online published - 6 Mar 2026 |
Funding
YH and CW are supported by National Key R&D Program of China No. pg 2023YFA1010400, NSFC No. 12322121 and Hong Kong RGC Grant No. 21300223. The research of JH is supported by NSF grants DMS-2331096 and DMS-2337795, and the Sloan Research Award. The authors thank the reviewers for their careful reading of the manuscript and for their helpful comments.
RGC Funding Information
- RGC-funded
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Dive into the research topics of 'Extremal eigenvectors of sparse random matrices'. Together they form a unique fingerprint.Projects
- 1 Finished
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ECS: The Spectrum and Eigenvectors of Random Graphs
HE, Y. (Principal Investigator / Project Coordinator)
1/07/23 → 7/05/26
Project: Research
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