Extreme points of matrix convex sets and their spanning properties

TL;DR

This survey explores the properties of extreme points in matrix convex sets, examining their roles and the applicability of a Krein-Milman theorem in the noncommutative setting, especially focusing on free spectrahedra.

Contribution

It provides a comprehensive analysis of different notions of extreme points in matrix convex sets and their relation to the Krein-Milman theorem, highlighting finite-dimensional aspects.

Findings

Different notions of extreme points have distinct strengths and limitations.

The Krein-Milman theorem does not straightforwardly extend to all types of matrix extreme points.

Free spectrahedra are central to understanding matrix convex sets and their extreme points.

Abstract

This expository article gives a survey of matrix convex sets, a natural generalization of convex sets to the noncommutative (dimension-free) setting, with a focus on their extreme points. Mirroring the classical setting, extreme points play an important role in matrix convexity, and a natural question is, ``are matrix convex sets the (closed) matrix convex hull of their extreme points?" That is, does a Krein-Milman theorem hold in this setting? This question requires some care, as there are several notions of extreme points for matrix convex sets. Three of the most prevalent notions are matrix extreme points, matrix exposed points, and free extreme points. For each of these types of extreme points, we examine strengths and shortcomings in terms of a Krein-Milman theorem. Of particular note is the fact that these extreme points are all finite-dimensional in nature. As such, a large amount of our discussion is about free spectrahedra, which are matrix convex sets determined by a linear matrix inequality.