Hyperbolic polynomials, interlacers, and sums of squares

TL;DR

This paper explores the structure of hyperbolic polynomials and their interlacers, connecting them to sums of squares and spectrahedral approximations, with applications to stable polynomials and determinantal representations.

Contribution

It establishes a link between hyperbolicity cones and nonnegative polynomials, and introduces a sums of squares relaxation for approximating these cones.

Findings

Hyperbolicity cones can be realized as slices of the cone of nonnegative polynomials.

The sums of squares relaxation approximates hyperbolicity cones via spectrahedra, but is not always exact.

Characterization and construction of definite determinantal representations for stable multiaffine polynomials.

Abstract

Hyperbolic polynomials are real polynomials whose real hypersurfaces are nested ovaloids, the inner most of which is convex. These polynomials appear in many areas of mathematics, including optimization, combinatorics and differential equations. Here we investigate the special connection between a hyperbolic polynomial and the set of polynomials that interlace it. This set of interlacers is a convex cone, which we write as a linear slice of the cone of nonnegative polynomials. In particular, this allows us to realize any hyperbolicity cone as a slice of the cone of nonnegative polynomials. Using a sums of squares relaxation, we then approximate a hyperbolicity cone by the projection of a spectrahedron. A multiaffine example coming from the Vamos matroid shows that this relaxation is not always exact. Using this theory, we characterize the real stable multiaffine polynomials that have a definite determinantal representation and construct one when it exists.