Abstract
Let U and V be two independent N by N random matrices that are distributed according to Haar measure on U(N). Let Σ be a nonnegative deterministic N by N matrix. The single ring theorem [Ann. of Math. (2) 174 (2011) 1189-1217] asserts that the empirical eigenvalue distribution of the matrix X :=UΣV * converges weakly, in the limit of large N, to a deterministic measure which is supported on a single ring centered at the origin in . Within the bulk regime, that is, in the interior of the single ring, we establish the convergence of the empirical eigenvalue distribution on the optimal local scale of order N -1/2+ε and establish the optimal convergence rate. The same results hold true when U and V are Haar distributed on O(N).
| Original language | English |
|---|---|
| Pages (from-to) | 1270-1334 |
| Number of pages | 65 |
| Journal | Annals of Probability |
| Volume | 47 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - 1 May 2019 |
Bibliographical note
Publisher Copyright:© Institute of Mathematical Statistics, 2019.
Keywords
- Free convolution
- Local eigenvalue density
- Non-Hermitian random matrices
- Single ring theorem
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