From Sine kernel to Poisson statistics

Abstract

We study the Sine${}_{\beta }$ process introduced in [B. Valkó and B. Virág. Invent. math. (2009)] when the inverse temperature $\beta$ tends to 0. This point process has been shown to be the scaling limit of the eigenvalues point process in the bulk of $\beta$-ensembles and its law is characterized in terms of the winding numbers of the Brownian carrousel at different angular speeds. After a careful analysis of this family of coupled diffusion processes, we prove that the Sine${}_{\beta }$ point process converges weakly to a Poisson point process on $\mathbb{R}$. Thus, the Sine${}_{\beta }$ point processes establish a smooth crossover between the rigid clock (or picket fence) process (corresponding to $\beta =\infty$) and the Poisson process.

24 pages, 5 figures

References in corpus (3)

• From Random Matrices to Stochastic Operators
• Invariant $\beta$-ensembles and the Gauss-Wigner crossover
• Invariant $\beta$-Wishart ensembles, crossover densities and asymptotic corrections to the Marchenko-Pastur law

Cited by in corpus (1)

• The eigenvectors of Gaussian matrices with an external source