Kronecker-product random matrices and a matrix least squares problem

Abstract

We study the eigenvalue distribution and resolvent of a Kronecker-product random matrix model A In × n+In × n B+ ∈ Cn2 × n2, where A,B are independent Wigner matrices and , are deterministic and diagonal. For fixed spectral arguments, we establish a quantitative approximation for the Stieltjes transform by that of an approximating free operator, and a diagonal deterministic equivalent approximation for the resolvent. We further obtain sharp estimates in operator norm for the n × n resolvent blocks, and show that off-diagonal resolvent entries fall on two differing scales of n-1/2 and n-1 depending on their locations in the Kronecker structure. Our study is motivated by consideration of a matrix-valued least-squares optimization problem X ∈ Rn × n 12\|XA+BX\|F2+12Σij iθj xij2 subject to a linear constraint. For random instances of this problem defined by Wigner inputs A,B, our analyses imply an asymptotic characterization of the minimizer X and its associated minimum objective value as n ∞.

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