4.5 Article

LOCAL LAW AND COMPLETE EIGENVECTOR DELOCALIZATION FOR SUPERCRITICAL ERDOS-RENYI GRAPHS

Journal

ANNALS OF PROBABILITY
Volume 47, Issue 5, Pages 3278-3302

Publisher

INST MATHEMATICAL STATISTICS
DOI: 10.1214/19-AOP1339

Keywords

Erdos-Renyi graph; sparse random matrix; local law; eigenvector delocalization

Funding

  1. Swiss National Science Foundation
  2. European Research Council

Ask authors/readers for more resources

We prove a local law for the adjacency matrix of the Erdos-Renyi graph G(N, p) in the supercritical regime pN >= C logN where G(N, p) has with high probability no isolated vertices. In the same regime, we also prove the complete delocalization of the eigenvectors. Both results are false in the complementary subcritical regime. Our result improves the corresponding results from (Ann. Probab. 41 (2013) 2279-2375) by extending them all the way down to the critical scale pN = O(logN). A key ingredient of our proof is a new family of multilinear large deviation estimates for sparse random vectors, which carefully balance mixed l(2) and l(infinity) norms of the coefficients with combinatorial factors, allowing us to prove strong enough concentration down to the critical scale pN = O(logN). These estimates are of independent interest and we expect them to be more generally useful in the analysis of very sparse random matrices.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.5
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available