Determining optimal test functions for $2$-level densities
El\.zbieta Bo{\l}dyriew, Fangu Chen, Charles Devlin VI, Steven J., Miller, Jason Zhao

TL;DR
This paper optimizes test functions for 2-level density statistics of zeros of L-functions to improve bounds on the average rank of families, extending previous 1-level results and providing stronger estimates for various symmetry types.
Contribution
It explicitly solves for optimal test functions in the 2-level case under certain restrictions, extending previous 1-level methods and improving bounds on the rank distribution of L-function families.
Findings
Stronger bounds on the proportion of low-rank L-function families.
Explicit solutions for optimal test functions in the 2-level density case.
Enhanced estimates over previous 1-level density results.
Abstract
Katz and Sarnak conjectured a correspondence between the -level density statistics of zeros from families of -functions with eigenvalues from random matrix ensembles. In many cases the sums of smooth test functions, whose Fourier transforms are finitely supported, over scaled zeros in a family converge to an integral of the test function against a density depending on the symmetry of the family (unitary, symplectic or orthogonal). This integral bounds the average order of vanishing at the central point of the corresponding family of -functions. We can obtain better estimates on this vanishing by finding better test functions to minimize the integral. We pursue this problem when , minimizing \[ \frac{1}{\Phi(0, 0)} \int_{{\mathbb R}^2} W_{2,G} (x, y) \Phi(x, y) dx dy \] over test functions with compactly supported…
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Taxonomy
TopicsAnalytic Number Theory Research · Advanced Mathematical Identities · Advanced Algebra and Geometry
