On the number of real eigenvalues of a product of truncated orthogonal random matrices
arXiv:2102.08842 · doi:10.1214/21-EJP732
Abstract
Let be chosen uniformly at random from the group of orthogonal matrices. Denote by the upper-left corner of , which we refer to as a truncation of . In this paper we prove two conjectures of Forrester, Ipsen and Kumar (2020) on the number of real eigenvalues of the product matrix , where the matrices are independent copies of . When grows in proportion to , we prove that We also prove the conjectured form of the limiting real eigenvalue distribution of the product matrix. Finally, we consider the opposite regime where is fixed with respect to , known as the regime of weak non-orthogonality. In this case each matrix in the product is very close to an orthogonal matrix. We show that as and compute the constant explicitly. These results generalise the known results in the one matrix case due to Khoruzhenko, Sommers and Życzkowski (2010).
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Cited by in corpus (5)
- Finite size corrections for real eigenvalues of the elliptic Ginibre matrices
- The Product of real Ginibre matrices: Real eigenvalues in the critical regime
- Real spectra of large real asymmetric random matrices
- Real eigenvalues of elliptic random matrices
- The probability of almost all eigenvalues being real for the elliptic real Ginibre ensemble