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The eigenvalues of i.i.d. matrices are hyperuniform

Giorgio Cipolloni, László Erdős, Oleksii Kolupaiev

Abstract

We prove that the point process of the eigenvalues of real or complex non-Hermitian matrices $X$ with independent, identically distributed entries is hyperuniform: the variance of the number of eigenvalues in a subdomain $Ω$ of the spectrum is much smaller than the volume of $Ω$. Our main technical novelty is a very precise computation of the covariance between the resolvents of the Hermitization of $X-z_1, X-z_2$, for two distinct complex parameters $z_1,z_2$.

The eigenvalues of i.i.d. matrices are hyperuniform

Abstract

We prove that the point process of the eigenvalues of real or complex non-Hermitian matrices with independent, identically distributed entries is hyperuniform: the variance of the number of eigenvalues in a subdomain of the spectrum is much smaller than the volume of . Our main technical novelty is a very precise computation of the covariance between the resolvents of the Hermitization of , for two distinct complex parameters .
Paper Structure (56 sections, 45 theorems, 604 equations, 1 figure)

This paper contains 56 sections, 45 theorems, 604 equations, 1 figure.

Key Result

Theorem 1.1

Let $X$ be an i.i.d. matrix and consider any nice domain $\Omega\subset\mathbf{D}$. Then, there exists a $q>0$ such that

Figures (1)

  • Figure 1: In gray, we illustrated a macroscopic ($\alpha=0$) domain $\Omega_N$ in the case when it intersects the real line. The dashed lines correspond to $\Im z=\pm d_0$, where $d_0$ is given by Assumption \ref{['ass:Omega_real']}. In this example, the intersection of $\partial\Omega_N$ and the set $|\Im z|\le d_0$ consists of two curves transversely intersecting the real axis. Finally, the scattered dots depict the eigenvalues of a large real i.i.d. matrix $X$.

Theorems & Definitions (66)

  • Theorem 1.1: Informal statement
  • Remark 2.2
  • Theorem 2.4: Complex case
  • Theorem 2.6: Real case
  • Remark 2.7
  • Proposition 3.1
  • Proposition 3.2
  • Lemma 3.3: Portmanteau principle
  • Proposition 3.4
  • Proposition 3.5: Left tail of the smallest singular value distribution
  • ...and 56 more