English

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 (A,B)tr[KA1tKBt](A,B) \mapsto \text{tr}\left[K^* A^{1-t} K B^t\right] is jointly concave in the pair (A,B)(A,B) of positive definite matrices, where KK is a fixed matrix and t[0,1]t \in [0,1]. In this paper we show that Lieb's function admits an explicit semidefinite programming formulation for any rational t[0,1]t \in [0,1]. 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

R2 v1 2026-06-22T12:06:41.736Z