English

Correlation kernels for sums and products of random matrices

Probability 2019-03-22 v2 Mathematical Physics Classical Analysis and ODEs math.MP

Abstract

Let XX be a random matrix whose squared singular value density is a polynomial ensemble. We derive double contour integral formulas for the correlation kernels of the squared singular values of GXGX and TXTX, where GG is a complex Ginibre matrix and TT is a truncated unitary matrix. We also consider the product of XX and several complex Ginibre/truncated unitary matrices. As an application, we derive the precise condition for the squared singular values of the product of several truncated unitary matrices to follow a polynomial ensemble. We also consider the sum H+MH + M where HH is a GUE matrix and MM is a random matrix whose eigenvalue density is a polynomial ensemble. We show that the eigenvalues of H+MH + M follow a polynomial ensemble whose correlation kernel can be expressed as a double contour integral. As an application, we point out a connection to the two-matrix model.

Keywords

Cite

@article{arxiv.1505.00610,
  title  = {Correlation kernels for sums and products of random matrices},
  author = {Tom Claeys and Arno B. J. Kuijlaars and Dong Wang},
  journal= {arXiv preprint arXiv:1505.00610},
  year   = {2019}
}

Comments

33 pages, some changes suggested by the referee is made and some references are added

R2 v1 2026-06-22T09:27:36.120Z