English

Local Tail Statistics of Heavy-Tailed Random Matrix Ensembles with Unitary Invariance

Mathematical Physics 2021-09-27 v1 Disordered Systems and Neural Networks math.MP Probability Statistics Theory Statistics Theory

Abstract

We study heavy-tailed Hermitian random matrices that are unitarily invariant. The invariance implies that the eigenvalue and eigenvector statistics are decoupled. The motivating question has been whether a freely stable random matrix has stable eigenvalue statistics for the largest eigenvalues in the tail. We investigate this question through the use of both numerical and analytical means, the latter of which makes use of the supersymmetry method. A surprising behaviour is uncovered in that a freely stable random matrix does not necessarily yield stable statistics and if it does then it might exhibit Poisson or Poisson-like statistics. The Poisson statistics have been already observed for heavy-tailed Wigner matrices. We conclude with two conjectures on this peculiar behaviour.

Keywords

Cite

@article{arxiv.2103.00817,
  title  = {Local Tail Statistics of Heavy-Tailed Random Matrix Ensembles with Unitary Invariance},
  author = {Mario Kieburg and Adam Monteleone},
  journal= {arXiv preprint arXiv:2103.00817},
  year   = {2021}
}

Comments

30 pages, 7 figures