Mutually unbiased bases: polynomial optimization and symmetry
Abstract
A set of orthonormal bases of is called mutually unbiased if whenever and are basis vectors in distinct bases. A natural question is for which pairs there exist~ mutually unbiased bases in dimension . The (well-known) upper bound is attained when~ is a power of a prime. For all other dimensions it is an open problem whether the bound can be attained. Navascu\'es, Pironio, and Ac\'in showed how to reformulate the existence question in terms of the existence of a certain -algebra. This naturally leads to a noncommutative polynomial optimization problem and an associated hierarchy of semidefinite programs. The problem has a symmetry coming from the wreath product of and . We exploit this symmetry (analytically) to reduce the size of the semidefinite programs making them (numerically) tractable. A key step is a novel explicit decomposition of the -module into irreducible modules. We present numerical results for small and low levels of the hierarchy. In particular, we obtain sum-of-squares proofs for the (well-known) fact that there do not exist mutually unbiased bases in dimensions~. Moreover, our numerical results indicate that a sum-of-squares refutation, in the above-mentioned framework, of the existence of more than MUBs in dimension requires polynomials of total degree at least~.
Cite
@article{arxiv.2111.05698,
title = {Mutually unbiased bases: polynomial optimization and symmetry},
author = {Sander Gribling and Sven Polak},
journal= {arXiv preprint arXiv:2111.05698},
year = {2024}
}
Comments
34 pages