English

Spectrahedral cones generated by rank 1 matrices

Optimization and Control 2015-04-08 v2

Abstract

Let S+nSn{\cal S}_+^n \subset {\cal S}^n be the cone of positive semi-definite matrices as a subset of the vector space of real symmetric n×nn \times n matrices. The intersection of S+n{\cal S}_+^n with a linear subspace of Sn{\cal S}^n is called a spectrahedral cone. We consider spectrahedral cones KK such that every element of KK can be represented as a sum of rank 1 matrices in KK. We shall call such spectrahedral cones rank one generated (ROG). We show that ROG cones which are linearly isomorphic as convex cones are also isomorphic as linear sections of the positive semi-definite matrix cone, which is not the case for general spectrahedral cones. We give many examples of ROG cones and show how to construct new ROG cones from given ones by different procedures. We provide classifications of some subclasses of ROG cones, in particular, we classify all ROG cones for matrix sizes not exceeding 4. Further we prove some results on the structure of ROG cones. We also briefly consider the case of complex or quaternionic matrices. ROG cones are in close relation with the exactness of semi-definite relaxations of quadratically constrained quadratic optimization problems or of relaxations approximating the cone of nonnegative functions in squared functional systems.

Keywords

Cite

@article{arxiv.1409.4781,
  title  = {Spectrahedral cones generated by rank 1 matrices},
  author = {Roland Hildebrand},
  journal= {arXiv preprint arXiv:1409.4781},
  year   = {2015}
}

Comments

Version 2: section on complex and quaternionic case added, many sections completely rewritten

R2 v1 2026-06-22T05:58:19.112Z