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<p>This paper benchmarks quantum, classical, and hybrid solvers on NP-hard Max-Cut and QUBO problems, emphasizing solution quality relative to known global optima. We evaluate D-Wave’s fast annealing QPU and Hybrid solver against classical simulated annealing (SA) and Toshiba’s simulated bifurcation machine (SBM) using 139 Max-Cut instances (100 to 10,000 nodes). For small instances (<InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(\le \)</EquationSource> <EquationSource Format="MATHML"><math> <mo>≤</mo> </math></EquationSource> </InlineEquation> 250 nodes) with known global optima, Hybrid and SA consistently achieve optimal solutions, outperforming the QPU. For larger instances, SBM and slower SA yield superior solutions, while Hybrid and faster SA perform less effectively. Computation time varies across solvers.</p>

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Accuracy and performance evaluation of quantum, classical and hybrid solvers for the Max-Cut problem

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月3日

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  • Jaka Vodeb,
  • Vid Eržen,
  • Timotej Hrga,
  • Janez Povh

摘要

This paper benchmarks quantum, classical, and hybrid solvers on NP-hard Max-Cut and QUBO problems, emphasizing solution quality relative to known global optima. We evaluate D-Wave’s fast annealing QPU and Hybrid solver against classical simulated annealing (SA) and Toshiba’s simulated bifurcation machine (SBM) using 139 Max-Cut instances (100 to 10,000 nodes). For small instances ( \(\le \) ≤ 250 nodes) with known global optima, Hybrid and SA consistently achieve optimal solutions, outperforming the QPU. For larger instances, SBM and slower SA yield superior solutions, while Hybrid and faster SA perform less effectively. Computation time varies across solvers.