Approaches to Exceptional Points in the Framework of Non-Hermitian Random Matrices

We explore how easy it is to enforce the advent of exceptional points starting from random matrices of non-Hermitian nature. We use the Petermann factor, whose mathematical version is called "overlap", for guidance, as well as simple pseudo-spectral tools. We attempt to proceed in the most agnostic way, by adding random perturbation and checking basic metrics such as the sum of all vectors' Petermann factors, equivalently the sum of diagonal overlaps. Issues such as the location of high Petermann factors vs. the modulus of eigenvalue are addressed. We contrast the fate of exploratory approaches in the Ginibre set (real matrices) and complex matrices, noting the special role of exceptional points on the real axis for the Ginibre matrices, completely absent in complex matrices.

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Publication Details

Journal
Entropy
Published
2026-01-29
DOI
https://doi.org/10.3390/e28020149
Primary Topic
Random Matrices and Applications
Type
article
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article

Approaches to Exceptional Points in the Framework of Non-Hermitian Random Matrices

H. Benisty
Entropy
Random Matrices and Applications
article

Approaches to Exceptional Points in the Framework of Non-Hermitian Random Matrices

H. Benisty
article en

Abstract

We explore how easy it is to enforce the advent of exceptional points starting from random matrices of non-Hermitian nature. We use the Petermann factor, whose mathematical version is called "overlap", for guidance, as well as simple pseudo-spectral tools. We attempt to proceed in the most agnostic way, by adding random perturbation and checking basic metrics such as the sum of all vectors' Petermann factors, equivalently the sum of diagonal overlaps. Issues such as the location of high Petermann factors vs. the modulus of eigenvalue are addressed. We contrast the fate of exploratory approaches in the Ginibre set (real matrices) and complex matrices, noting the special role of exceptional points on the real axis for the Ginibre matrices, completely absent in complex matrices.

EntropyVol. 28(2)
Université Paris Cité (FR), Université Paris-Saclay (FR), Sorbonne Paris Cité (FR), Laboratoire Charles Fabry (FR)
Reduced inequalities
Openalex Percentile: Top 76%
Random Matrices and Applications
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Approaches to Exceptional Points in the Framework of Non-Hermitian Random Matrices — H. Benisty · Entropy (2026) | TGRS Research Map | TGRS