# Co-rank 1 projections and the randomised Horn problem

## TL;DR

This paper explains the similar eigenvalue distributions in rank 1 projections and perturbations of Hermitian matrices using secular equations, unifying different random matrix scenarios.

## Contribution

It provides a common derivation for eigenvalue PDFs in rank 1 projection and perturbation cases, extending to multiplicative settings with unitary matrices.

## Key findings

- Eigenvalue PDFs have similar structures in projection and perturbation cases.
- Secular equations and Jacobians unify different random matrix models.
- Results apply to complex and real Gaussian vectors, and multiplicative unitary models.

## Abstract

Let $\hat{\boldsymbol x}$ be a normalised standard complex Gaussian vector, and project an Hermitian matrix $A$ onto the hyperplane orthogonal to $\hat{\boldsymbol x}$. In a recent paper Faraut [Tunisian J. Math. \textbf{1} (2019), 585--606] has observed that the corresponding eigenvalue PDF has an almost identical structure to the eigenvalue PDF for the rank 1 perturbation $A + b \hat{\boldsymbol x} \hat{\boldsymbol x}^\dagger$, and asks for an explanation. We provide this by way of a common derivation involving the secular equations and associated Jacobians. This applies too in related setting, for example when $\hat{\boldsymbol x}$ is a real Gaussian and $A$ Hermitian, and also in a multiplicative setting $A U B U^\dagger$ where $A, B$ are fixed unitary matrices with $B$ a multiplicative rank 1 deviation from unity, and $U$ is a Haar distributed unitary matrix. Specifically, in each case there is a dual eigenvalue problem giving rise to a PDF of almost identical structure.