  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.
