STRONG APPROXIMATION OF GAUSSIAN ? ENSEMBLE CHARACTERISTIC POLYNOMIALS: THE HYPERBOLIC REGIME

• 成果类型: Article
• 署名作者: Lambert, Gaultier; Paquette, Elliot
• 署名单位: University of Zurich; McGill University
• 刊物名称: ANNALS OF APPLIED PROBABILITY
• ISSN/ISSBN: 1050-5164
• DOI: 10.1214/22-AAP1823
• 发表日期: 2023
• 页码: 549-612
• 关键词: log-correlated fields; maximum; asymptotics; eigenvalues; Respect; sums

摘要

We investigate the characteristic polynomials phi N of the Gaussian beta ensemble for general beta > 0 through its transfer matrix recurrence. Our motivation is to obtain a (probabilistic) approximation for phi N in terms of a Gaussian log-correlated field. We distinguish between different types of transfer matrices and analyze completely the hyperbolic part of the recurrence. As a result, we obtain a new coupling between phi N and a Gaussian analytic function with an error which is uniform away from the support of the semicircle law. We use this as input to give the almost sure scaling limit of the characteristic polynomial at the edge in (Lambert and Paquette (2020)). This is also required to obtain analogous strong approximations inside of the bulk of the semicircle law. Our analysis relies on moderate deviation estimates for the product of transfer matrices and this approach might also be useful in different contexts.