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Title:
Extreme gaps in the spectrum of Random Matrices

Speaker:
Gerard Ben Arous

Abstract:
I will present a joint work with Paul Bourgade (Harvard) about the extreme gaps between eigenvalues of random matrices. We give the joint limiting law of the smallest gaps for Haar-distributed unitary matrices (CUE) and matrices from the Gaussian Unitary Ensemble. In particular, we show that the smallest gaps when rescaled by N-4/3, are Poissonian and we give the limiting distribution of the kth smallest gap. We also show that the largest gap, when normalized by √log N/N, converges in L^p to a constant for all p > 0. These results are compared with the extreme gaps between zeros of the Riemann zeta function.

Link:
https://www.msri.org/workshops/508/schedules/12418

Workshop:
MSRI- Random Matrix Theory and Its Applications I