First Order Conditions for Semidefinite Representations of Convex Sets Defined by Rational or Singular Polynomials

dc.creatorNie, Jiawang
dc.date2008-06-28
dc.date.accessioned2026-07-07T09:47:22Z
dc.date.available2026-07-07T09:47:22Z
dc.descriptionA set is called semidefinite representable or semidefinite programming (SDP) representable if it can be represented as the projection of a higher dimensional set which is represented by some Linear Matrix Inequality (LMI). This paper discuss the semidefinite representability conditions for convex sets of the form S_D(f) = {x \in D: f(x) >= 0}. Here D={x\in R^n: g_1(x) >= 0, ..., g_m(x) >= 0} is a convex domain defined by some "nice" concave polynomials g_i(x) (they satisfy certain concavity certificates), and f(x) is a polynomial or rational function. When f(x) is concave over \mc{D}, we prove that S_D(f) has some explicit semidefinite representations under certain conditions called preordering concavity or q-module concavity, which are based on the Positivstellensatz certificates for the first order concavity criteria. When f(x) is a polynomial or rational function having singularities on the boundary of S_D(f), a perspective transformation is introduced to find some explicit semidefinite representations for S_D(f) under certain conditions. In the particular case n=2, if the Laurent expansion of f(x) around one singular point has only two consecutive homogeneous parts, we show that S_D(f) always admits an explicitly constructible semidefinite representation.
dc.description25 pages
dc.identifierhttps://arxiv.org/abs/0806.4721
dc.identifierhttp://arxiv.org/abs/0806.4721
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/163853
dc.subjectOptimization and Control
dc.subjectAlgebraic Geometry
dc.titleFirst Order Conditions for Semidefinite Representations of Convex Sets Defined by Rational or Singular Polynomials
dc.typetext

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