Leo Liberti, James Ostrowski
Journal of Global Optimization
Characters of irreducible representations are ubiquitous in group theory. However, computing characters of some groups such as the symmetric group Sn is a challenging problem known to be #P-hard in the worst case. Here we describe a matrix product state (MPS) algorithm for characters of Sn. The algorithm computes an MPS encoding all irreducible characters of a given permutation. It relies on a mapping from characters of Sn to quantum spin chains proposed by Crichigno and Prakash. We also provide a simpler derivation of this mapping. We complement this result by presenting a poly(n) size quantum circuit that prepares the corresponding MPS obtaining an efficient quantum algorithm for certain sampling problems based on characters of Sn. To assess classical hardness of these problems, we present a general reduction from strong simulation (computing a given probability) to weak simulation (sampling with a small error). This reduction applies to any sampling problem with a certain granularity structure and may be of independent interest.
Leo Liberti, James Ostrowski
Journal of Global Optimization
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