Limiting distribution of eigenvalues in the large sieve matrix
Abstract
The large sieve inequality is equivalent to the bound for the largest eigenvalue of the by matrix , naturally associated to the positive definite quadratic form arising in the inequality. For arithmetic applications the most interesting range is . Based on his numerical data Ramar\'e conjectured that when as for some finite positive constant , the limiting distribution of the eigenvalues of , scaled by , exists and is non-degenerate. In this paper we prove this conjecture by establishing the convergence of all moments of the eigenvalues of as . Previously only the second moment was known, due to Ramar\'e. Furthermore, we obtain an explicit description of the moments of the limiting distribution, and establish that they vary continuously with . Some of the main ingredients in our proof include the large-sieve inequality and results on -correlations of Farey fractions.
Keywords
Cite
@article{arxiv.1609.05843,
title = {Limiting distribution of eigenvalues in the large sieve matrix},
author = {Florin P. Boca and Maksym Radziwiłł},
journal= {arXiv preprint arXiv:1609.05843},
year = {2018}
}
Comments
42 pages; section 5 re-written following referee report