Matrix Cubes Parametrized by Eigenvalues

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dc.creatorNie, Jiawang
dc.creatorSturmfels, Bernd
dc.date2008-04-28
dc.date.accessioned2026-07-07T09:35:39Z
dc.date.available2026-07-07T09:35:39Z
dc.descriptionAn elimination problem in semidefinite programming is solved by means of tensor algebra. It concerns families of matrix cube problems whose constraints are the minimum and maximum eigenvalue function on an affine space of symmetric matrices. An LMI representation is given for the convex set of all feasible instances, and its boundary is studied from the perspective of algebraic geometry. This generalizes the earlier work [12] with Parrilo on k-ellipses and k-ellipsoids.
dc.description12 pages, 1 figure
dc.identifierhttps://arxiv.org/abs/0804.4462
dc.identifierhttp://arxiv.org/abs/0804.4462
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/159901
dc.subjectOptimization and Control
dc.subjectAlgebraic Geometry
dc.titleMatrix Cubes Parametrized by Eigenvalues
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