Product Matrix Processes With Symplectic and Orthogonal Invariance via Symmetric Functions

Andrew Ahn*, Eugene Strahov

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

We apply symmetric function theory to study random processes formed by singular values of products of truncations of Haar distributed symplectic and orthogonal matrices. These product matrix processes are degenerations of Macdonald processes introduced by Borodin and Corwin. Through this connection, we obtain explicit formulae for the distribution of singular values of a deterministic matrix multiplied by a truncated Haar orthogonal or symplectic matrix under conditions where the latter factor acts as a rank 1 perturbation. Consequently, we generalize the recent Kieburg-Kuijlaars-Stivigny formula for the joint singular value density of a product of truncated unitary matrices to symplectic and orthogonal symmetry classes. Specializing to products of two symplectic matrices with a rank 1 perturbative factor, we show that the squared singular values form a Pfaffian point process.

Original languageEnglish
Pages (from-to)10767-10821
Number of pages55
JournalInternational Mathematics Research Notices
Volume2022
Issue number14
DOIs
StatePublished - 1 Jul 2022

Bibliographical note

Publisher Copyright:
© 2021 The Author(s). Published by Oxford University Press. All rights reserved.

Fingerprint

Dive into the research topics of 'Product Matrix Processes With Symplectic and Orthogonal Invariance via Symmetric Functions'. Together they form a unique fingerprint.

Cite this