Determining optimal test functions for -level densities
arXiv:2011.10140 · doi:10.1007/s40993-022-00367-0
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 \[ \frac{1}{Φ(0, 0)} \int_{{\mathbb R}^2} W_{2,G} (x, y) Φ(x, y) dx dy \] over test functions with compactly supported Fourier transform. We study a restricted version of this optimization problem, imposing that our test functions take the form for some fixed admissible and . Extending results from the -level case, namely the functional analytic arguments of Iwaniec, Luo and Sarnak and the differential equations method introduced by Freeman and Miller, we explicitly solve for the optimal for appropriately chosen fixed test function . The solution allows us to deduce strong estimates for the proportion of newforms of rank or in the case of , rank or in the case of , and rank at most for , , and ; our estimates are a significant strengthening of the best known estimates obtained with the -level density. We conclude by discussing further improvements on estimates by the method of iteration.
arXiv comment18 pages
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