A variant of Horn's problem and derivative principle
Lin Zhang, Hua Xiang

TL;DR
This paper studies a variant of Horn's problem by deriving the probability density function of the diagonals of the sum of two random Hermitian matrices with fixed spectra, using the derivative principle to recover eigenvalue distributions.
Contribution
It introduces a novel approach to identify the diagonal distribution in a variant of Horn's problem and applies the derivative principle to derive eigenvalue distributions for various ensembles.
Findings
Derived the pdf of diagonals of sum of two Hermitian matrices with fixed spectra.
Re-derived the eigenvalue distribution of sums of random Hermitian matrices using the derivative principle.
Connected matrix exponential statistics with Golden-Thompson inequality and addressed a question by Forrester.
Abstract
Identifying the spectrum of the sum of two given Hermitian matrices with fixed eigenvalues is the famous Horn's problem.In this note, we investigate a variant of Horn's problem, i.e., we identify the probability density function (abbr. pdf) of the diagonals of the sum of two random Hermitian matrices with given spectra. We then use it to re-derive the pdf of the eigenvalues of the sum of two random Hermitian matrices with given eigenvalues via \emph{derivative principle}, a powerful tool used to get the exact probability distribution by reducing to the corresponding distribution of diagonal entries.We can recover Jean-Bernard Zuber's recent results on the pdf of the eigenvalues of two random Hermitian matrices with given eigenvalues. Moreover, as an illustration, we derive the analytical expressions of eigenvalues of the sum of two random Hermitian matrices from or…
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