Jordan-algebraic approach to convexity theorem for quadratic mappings

  • Leonid Faybusovich
    • Categories Linear, Cone and Semidefinite Programming Tags , , Short URL: https://optimization-online.org/?p=9006

    We describe a Jordan-algebraic version of results related to convexity of images of quadratic mappings as well as related results on exactness of symmetric relaxations of certain classes of nonconvex optimization problems. The exactness of relaxations is proved based on rank estimates. Our approach provides a unifying viewpoint on a large number of classical results related to cones of Hermitian matrices over real and complex numbers. We describe (apparently new) results related to cones of Hermitian matrices with quaternion entries and the exceptional 27-dimensional Jordan algebra

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