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An Improved Approximation Algorithm for Quantum Max-Cut

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arxiv 2209.02589 v3 pith:5DNMY5AE submitted 2022-09-06 quant-ph

classification quant-ph
keywords approximationquantumalgorithmhamiltonianstatecircuitentangledgive
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abstract

We give an approximation algorithm for Quantum Max-Cut which works by rounding an SDP relaxation to an entangled quantum state. The SDP is used to choose the parameters of a variational quantum circuit. The entangled state is then represented as the quantum circuit applied to a product state. It achieves an approximation ratio of 0.582 on triangle-free graphs. The previous best algorithms of Anshu, Gosset, Morenz, and Parekh, Thompson achieved approximation ratios of 0.531 and 0.533 respectively. In addition, we study the EPR Hamiltonian, which we argue is a natural intermediate problem which isolates some key quantum features of local Hamiltonian problems. For the EPR Hamiltonian, we give an approximation algorithm with approximation ratio $1 / \sqrt{2}$ on all graphs.

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Cited by 3 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. On the Approximability of Boolean Max-$k$-CSP

    cs.CC 2026-08 conditional novelty 7.0 of 10

    A new Gaussian comparison inequality yields a randomized k/2^k approximation for Boolean Max-k-CSP for every fixed k>=10, the first algorithm to reach the asymptotic optimum constant.

  2. A Refined Algorithm For the EPR model

    quant-ph 2025-06 conditional novelty 6.0 of 10

    A refined algorithm for the EPR model using homogeneous and quasi-homogeneous fractional matchings achieves improved approximation ratios on regular graphs, e.g., 0.872 for 2-regular graphs.

  3. Testing APS conjecture on regular graphs

    quant-ph 2025-07 conditional novelty 5.0 of 10

    The FED algorithm's energy estimates on Henning-Yeo regular graphs never exceed the APS conjecture's predicted bound, so the tests find no violation.

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