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Paper detail

Convergence of SDP hierarchies for polynomial optimization on the hypersphere

We show how to bound the accuracy of a family of semi-definite programming relaxations for the problem of polynomial optimization on the hypersphere. Our method is inspired by a set of results from quantum information known as quantum de Finetti theorems. In particular, we prove a de Finetti theorem for a special class of real symmetric matrices to establish the existence of approximate representing measures for moment matrix relaxations.

preprint2013arXivOpen access
Andrew C. DohertyStephanie Wehner
math.OCmath-phData Structures and Algorithmsmath.MPquant-ph
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Andrew C. DohertyStephanie Wehner

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