Spectral moments of complex and symplectic non-Hermitian random matrices
Gernot Akemann, Sung-Soo Byun, Seungjoon Oh

TL;DR
This paper develops a unified framework for analyzing spectral moments of non-Hermitian random matrices in complex and symplectic classes, revealing their relation to Hermitian limits and providing explicit formulas and asymptotic results.
Contribution
It introduces a systematic approach to compute mixed spectral moments, including explicit formulas and large-N asymptotics for key non-Hermitian ensembles.
Findings
Holomorphic spectral moments match Hermitian limits up to a constant.
Spectral moments of symplectic ensemble decompose into complex and correction parts.
Large-N analysis reveals connections to elliptic and non-Hermitian Marchenko–Pastur laws.
Abstract
We study non-Hermitian random matrices belonging to the symmetry classes of the complex and symplectic Ginibre ensemble, and present a unifying and systematic framework for analysing mixed spectral moments involving both holomorphic and anti-holomorphic parts. For weight functions that induce a recurrence relation of the associated planar orthogonal polynomials, we derive explicit formulas for the spectral moments in terms of their orthogonal norms. This includes exactly solvable models such as the elliptic Ginibre ensemble and non-Hermitian Wishart matrices. In particular, we show that the holomorphic spectral moments of complex non-Hermitian random matrices coincide with those of their Hermitian limit up to a multiplicative constant, determined by the non-Hermiticity parameter. Moreover, we show that the spectral moments of the symplectic non-Hermitian ensemble admit a decomposition…
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.
