Semidefinite characterization of sum-of-squares cones in algebras

Dávid Papp, Farid Alizadeh

Research output: Contribution to journalArticle

3 Scopus citations

Abstract

We extend Nesterov's semidefinite programming characterization of squared functional systems, and Faybusovich's abstraction to bilinear symmetric maps, to cones of sum-of-squares elements in general abstract algebras. Using algebraic techniques such as isomorphism, linear isomorphism, tensor products, sums, and direct sums, we show that many concrete cones are in fact sum-of-squares cones with respect to some algebra and thus are epresentable by the cone of positive semidefinite matrices. We also consider nonnegativity with respect to a proper cone K and show that in some cases cones of K-nonnegative functions are either sum of squares or at least semidefinite representable. For example, we show that some well-known Chebyshev systems, when extended to Euclidean Jordan algebras, induce cones that are semidefinite representable. Finally we will discuss some concrete examples and applications, including minimum ellipsoid enclosing given space curves, minimization of eigenvalues of polynomial matrix pencils, approximation of functions by shapeconstrained functions, and approximation of combinatorial optimization problems by olynomial programming.

Original languageEnglish (US)
Pages (from-to)1398-1423
Number of pages26
JournalSIAM Journal on Optimization
Volume23
Issue number3
DOIs
StatePublished - 2013

All Science Journal Classification (ASJC) codes

  • Software
  • Theoretical Computer Science

Keywords

  • Nonnegative polynomials
  • Semidefinite programming
  • Semidefinite representability
  • Sum of squares
  • Sum-of-squares functional systems

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