English

Matrix Convex Sets Without Absolute Extreme Points

Operator Algebras 2022-02-24 v1 Functional Analysis

Abstract

This article shows the existence of a class of closed bounded matrix convex sets which do not have absolute extreme points. The sets we consider are noncommutative sets, KXK_X, formed by taking matrix convex combinations of a single tuple XX. In the case that XX is a tuple of compact operators with no nontrivial finite dimensional reducing subspaces, KXK_X is a closed bounded matrix convex set with no absolute extreme points. A central goal in the theory of matrix convexity is to find a natural notion of an extreme point in the dimension free setting which is minimal with respect to spanning. Matrix extreme points are the strongest type of extreme point known to span matrix convex sets; however, they are not necessarily the smallest set which does so. Absolute extreme points, a more restricted type of extreme points that are closely related to Arveson's boundary, enjoy a strong notion of minimality should they span. This result shows that matrix convex sets may fail to be spanned by their absolute extreme points.

Keywords

Cite

@article{arxiv.1708.02331,
  title  = {Matrix Convex Sets Without Absolute Extreme Points},
  author = {Eric Evert},
  journal= {arXiv preprint arXiv:1708.02331},
  year   = {2022}
}

Comments

18 pages

R2 v1 2026-06-22T21:09:11.785Z