Log-concavity and concentration bounds for a single gap between GUE eigenvalues
Abstract
We observe that the distribution of the eigenvalues of an $N$-by-$N$ GUE random matrix is log-concave on $\mathbb{R}^N$, and that the same is true for the law of a single gap between two consecutive eigenvalues. We use this observation to prove several concentration bounds for the semicircle-renormalised eigengaps, improving on bounds recently obtained in [Tao (2024). On the distribution of eigenvalues of GUE and its minors at fixed index. [arXiv:2412.10889]].
Fields of Study & Subjects
Random Matrices and Applications
Markov Chains and Monte Carlo Methods
Matrix Theory and Algorithms
Publication details
- Journal / source
- arXiv (Cornell University)
- Publication date
- 8 January 2026
- Document type
- Preprint