Local circular law for the product of a deterministic matrix with a random matrix
Haokai Xi, Fan Yang, Jun Yin

TL;DR
This paper establishes a local circular law for the eigenvalues of the product of a deterministic matrix and a random matrix with independent entries, valid away from the unit circle and at small scales, under certain moment conditions.
Contribution
It extends the circular law to a local regime for products of deterministic and random matrices, detailing the spectral distribution behavior at fine scales.
Findings
Convergence of empirical spectral distribution to a rotation-invariant measure.
Validity of the local circular law at scales up to (N∧M)^{-1/4+ε}.
Enhanced scale validity to (N∧M)^{-1/2+ε} under specific conditions.
Abstract
It is well known that the spectral measure of eigenvalues of a rescaled square non-Hermitian random matrix with independent entries satisfies the circular law. We consider the product , where is a deterministic matrix and is a random matrix with independent entries having zero mean and variance . We prove a general local circular law for the empirical spectral distribution (ESD) of at any point away from the unit circle under the assumptions that , and the matrix entries have sufficiently high moments. More precisely, if satisfies for arbitrarily small , the ESD of converges to , where is a rotation-invariant function determined by the singular values of and denotes the Lebesgue measure on .…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
