Product Matrix Processes With Symplectic and Orthogonal Invariance via Symmetric Functions

Andrew Ahn, E. Strahov
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引用次数: 4

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.
具有辛不变性和正交不变性的对称函数积矩阵过程
应用对称函数理论研究了由Haar分布辛矩阵和正交矩阵截断积的奇异值构成的随机过程。这些乘积矩阵过程是Borodin和Corwin引入的Macdonald过程的退化。通过这种联系,我们得到了当截断哈尔正交矩阵或辛矩阵作为秩1扰动时,确定矩阵乘以截断哈尔正交矩阵或辛矩阵的奇异值分布的显式公式。因此,我们将截断酉矩阵乘积的联合奇异值密度的Kieburg-Kuijlaars-Stivigny公式推广到辛对称类和正交对称类。对于两个阶为$1扰动因子的辛矩阵的积,我们证明了平方奇异值形成一个Pfaffian点过程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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