Lieb's concavity theorem, matrix geometric means, and semidefinite optimization
Optimization and Control
2020-04-14 v3 Quantum Physics
Abstract
A famous result of Lieb establishes that the map is jointly concave in the pair of positive definite matrices, where is a fixed matrix and . In this paper we show that Lieb's function admits an explicit semidefinite programming formulation for any rational . Our construction makes use of a semidefinite formulation of weighted matrix geometric means. We provide an implementation of our constructions in Matlab.
Keywords
Cite
@article{arxiv.1512.03401,
title = {Lieb's concavity theorem, matrix geometric means, and semidefinite optimization},
author = {Hamza Fawzi and James Saunderson},
journal= {arXiv preprint arXiv:1512.03401},
year = {2020}
}
Comments
17 pages; minor modifications in the presentation + added reference to [G. Sagnol, On the semidefinite representation of real functions applied to symmetric matrices, Linear Algebra Appl., 2013] which gives an alternative semidefinite representation of weighted matrix geometric means; v3: Fixed a mistake in Lemma 4