The Circular Unitary Ensemble and the Riemann zeta function: the microscopic landscape and a new approach to ratios
Reda Chhaibi, Joseph Najnudel, Ashkan Nikeghbali

TL;DR
This paper demonstrates that the scaled characteristic polynomial of a random unitary matrix converges to a random analytic function with zeros forming a sine kernel determinantal point process, offering a new approach to ratios and insights into the Riemann zeta function.
Contribution
It introduces a novel microscopic scaling framework using virtual isometries, enabling strong convergence results and new methods for analyzing ratios of characteristic polynomials.
Findings
Convergence of scaled characteristic polynomial to a random analytic function
Explicit description of dependence relations on the microscopic scale
New conjectures for the value distribution of the Riemann zeta function
Abstract
We show in this paper that after proper scalings, the characteristic polynomial of a random unitary matrix converges almost surely to a random analytic function whose zeros, which are on the real line, form a determinantal point process with sine kernel. Our scaling is performed at the so-called "microscopic" level, that is we consider the characteristic polynomial at points which are of order distant. We prove this in the framework of virtual isometries to circumvent the fact that the rescaled characteristic polynomial does not even have a moment of order one, hence making the classical techniques of random matrix theory difficult to apply. The strong convergence results in this setup provide us with a new approach to ratios: we are able to solve open problems about the limiting distribution of ratios of characteristic polynomials evaluated at points of the form $\exp(2 i \pi…
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