Abstract
We define the empirical spectral distribution (ESD) of a random matrix polynomial with invertible leading coefficient, and we study it for complex n× n Gaussian monic matrix polynomials of degree k. We obtain exact formulae for the almost sure limit of the ESD in two distinct scenarios: (1) n→ ∞ with k constant and (2) k→ ∞ with n constant. The main tool for our approach is the replacement principle by Tao, Vu and Krishnapur. Along the way, we also develop some auxiliary results of potential independent interest: We slightly extend a result by Bürgisser and Cucker on the tail bound for the norm of the pseudoinverse of a nonzero mean matrix, and we obtain several estimates on the singular values of certain structured random matrices.
Original language | English |
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Pages (from-to) | 99–133 |
Number of pages | 35 |
Journal | JOURNAL OF THEORETICAL PROBABILITY |
Volume | 36 |
Issue number | 1 |
Early online date | 16 Feb 2022 |
DOIs | |
Publication status | Published - Mar 2023 |
MoE publication type | A1 Journal article-refereed |
Keywords
- Companion matrix
- Empirical spectral distribution
- Polynomial eigenvalue problem
- Random matrix polynomial
- Strong circle law