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Correlation kernels for sums and products of random matrices

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arxiv 1505.00610 v2 pith:LDIM4NPY submitted 2015-05-04 math.PR math-phmath.CAmath.MP

classification math.PRmath-phmath.CAmath.MP
keywords matrixensemblepolynomialcorrelationmatricesrandomsingularsquared
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abstract

Let $X$ 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 $GX$ and $TX$, where $G$ is a complex Ginibre matrix and $T$ is a truncated unitary matrix. We also consider the product of $X$ 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 $H + M$ where $H$ is a GUE matrix and $M$ is a random matrix whose eigenvalue density is a polynomial ensemble. We show that the eigenvalues of $H + M$ 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.

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  1. Products of Complex Rectangular and Hermitian Random Matrices

    math.PR 2019-08 conditional novelty 7.0 of 10

    A new spherical transform with sign parameters gives the joint eigenvalue density and kernels for products of Pólya ensembles with Hermitian matrices.

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