Relaxations and Exact Solutions to Quantum Max Cut via the Algebraic Structure of Swap Operators
Adam Bene Watts, Anirban Chowdhury, Aidan Epperly, J. William Helton,, Igor Klep

TL;DR
This paper introduces a new algebraic hierarchy of relaxations for Quantum Max Cut using swap operators, proving some levels are numerically exact and providing an efficient eigenvalue computation method for specific graph classes.
Contribution
It extends non-commutative Sum of Squares techniques with a swap operator-based hierarchy and develops a polynomial-time eigenvalue algorithm for certain graph structures.
Findings
Level-2 hierarchy is numerically exact for small graphs.
Polynomial-time eigenvalue algorithm for graphs decomposable into cliques.
Representation theory generalizes Lieb-Mattis results.
Abstract
The Quantum Max Cut (QMC) problem has emerged as a test-problem for designing approximation algorithms for local Hamiltonian problems. In this paper we attack this problem using the algebraic structure of QMC, in particular the relationship between the quantum max cut Hamiltonian and the representation theory of the symmetric group. The first major contribution of this paper is an extension of non-commutative Sum of Squares (ncSoS) optimization techniques to give a new hierarchy of relaxations to Quantum Max Cut. The hierarchy we present is based on optimizations over polynomials in the qubit swap operators. This is in contrast to the "standard" quantum Lasserre Hierarchy, which is based on polynomials expressed in terms of the Pauli matrices. To prove correctness of this hierarchy, we exploit a finite presentation of the algebra generated by the qubit swap operators. This…
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Taxonomy
TopicsQuantum Computing Algorithms and Architecture · Low-power high-performance VLSI design · Quantum Information and Cryptography
