The Wasserstein distance to the Circular Law
Probability
2022-10-31 v3
Abstract
We investigate the Wasserstein distance between the empirical spectral distribution of non-Hermitian random matrices and the Circular Law. For general entry distributions, we obtain a nearly optimal rate of convergence in 1-Wasserstein distance of order and we prove that the optimal rate is attained by Ginibre matrices. This shows that the expected transport cost of complex eigenvalues to the uniform measure on the unit disk decays faster compared to that of i.i.d. points, which is known to include a logarithmic factor.
Keywords
Cite
@article{arxiv.2111.03595,
title = {The Wasserstein distance to the Circular Law},
author = {Jonas Jalowy},
journal= {arXiv preprint arXiv:2111.03595},
year = {2022}
}
Comments
26p, 3 Figures, comments always welcome! Version 3: minor changes, final version to be published in AIHP