Improved Algorithms for Quantum MaxCut via Partially Entangled Matchings

We introduce a $0.611$-approximation algorithm for Quantum MaxCut and a $\frac{1+\sqrt{5}}{4} \approx 0.809$-approximation algorithm for the EPR Hamiltonian of [arXiv:2209.02589]. A novel ingredient in both of these algorithms is to partially entangle pairs of qubits associated to edges in a matching, while preserving the direction of their single-qubit Bloch vectors. This allows us to interpolate between product states and matching-based states with a tunable parameter.

Publication Details

Journal
ArXiv.org
Published
2025-04-21
Primary Topic
Quantum Computing Algorithms and Architecture
Type
article
Field-Weighted Citation Impact
0.00

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article

Improved Algorithms for Quantum MaxCut via Partially Entangled Matchings

ArXiv.org
Quantum Computing Algorithms and Architecture
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Improved Algorithms for Quantum MaxCut via Partially Entangled Matchings

article en

Abstract

We introduce a $0.611$-approximation algorithm for Quantum MaxCut and a $\frac{1+\sqrt{5}}{4} \approx 0.809$-approximation algorithm for the EPR Hamiltonian of [arXiv:2209.02589]. A novel ingredient in both of these algorithms is to partially entangle pairs of qubits associated to edges in a matching, while preserving the direction of their single-qubit Bloch vectors. This allows us to interpolate between product states and matching-based states with a tunable parameter.

ArXiv.org
National Science Foundation, U.S. Department of Energy, University of Chicago, Office of Science, Advanced Scientific Computing Research, Air Force Office of Scientific Research, Sandia National Laboratories
Openalex Percentile: Top 73%
Quantum Computing Algorithms and Architecture
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Improved Algorithms for Quantum MaxCut via Partially Entangled Matchings · ArXiv.org (2025) | TGRS Research Map | TGRS