A spectrahedral representation of the first derivative relaxation of the positive semidefinite cone

Abstract

If $X$ is an $n\times n$ symmetric matrix, then the directional derivative of $X\mapsto \det (X)$ in the direction $I$ is the elementary symmetric polynomial of degree $n-1$ in the eigenvalues of $X$. This is a polynomial in the entries of $X$ with the property that it is hyperbolic with respect to the direction $I$. The corresponding hyperbolicity cone is a relaxation of the positive semidefinite (PSD) cone known as the first derivative relaxation (or Renegar derivative) of the PSD cone. A spectrahedal cone is a convex cone that has a representation as the intersection of a subspace with the cone of PSD matrices in some dimension. We show that the first derivative relaxation of the PSD cone is a spectrahedral cone, and give an explicit spectrahedral description of size $\left(\genfrac{}{}{0ex}{}{n+1}{2}\right)-1$. The construction provides a new explicit example of a hyperbolicity cone that is also a spectrahedron. This is consistent with the generalized Lax conjecture, which conjectures that every hyperbolicity cone is a spectrahedron.

10 pages, fixed typos, more direct proof of Lemma 4

References in corpus (3)

• The Lax conjecture is true
• Positive semidefinite rank
• Two results on the size of spectrahedral descriptions

Cited by in corpus (2)

• Spectral linear matrix inequalities
• Automorphisms of rank-one generated hyperbolicity cones and their derivative relaxations