POSITIVE POLYNOMIALS AND PROJECTIONS OF SPECTRAHEDRA

被引:18
|
作者
Gouveia, Joao [1 ,2 ]
Netzer, Tim [3 ]
机构
[1] Univ Washington, Dept Math, Seattle, WA 98195 USA
[2] Univ Coimbra, CMUC, Dept Math, P-3001454 Coimbra, Portugal
[3] Univ Leipzig, Falkultat Math & Informat, D-04009 Leipzig, Germany
关键词
semidefinite programming; spectrahedra; convex sets; sums of squares; linear matrix inequalities; MOMENT PROBLEM; SEMIDEFINITE; REPRESENTATION; SQUARES; SUMS;
D O I
10.1137/100801913
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
This article is concerned with different aspects of spectrahedra and their projections, sets that are important in semidefinite optimization. We prove results on the limitations of so-called Lasserre and theta body relaxation methods for semialgebraic sets and varieties. As a special case we obtain the main result of Netzer, Plaumann, and Schweighofer [SIAM J. Optim., 20 (2010), pp. 1944-1955] on nonexposed faces. We also solve the open problems from that work. We further give a unified account of several results on convex hulls of curves and images of polynomial maps. We finally prove a Positivstellensatz for projections of spectrahedra, which exceeds the known results that only work for basic closed semialgebraic sets.
引用
收藏
页码:960 / 976
页数:17
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