Numerical benchmarks identify a minimum problem size where variational quantum circuits for Max-Cut outperform sampling on average, with quantified separation from greedy methods and instance-level performance correlations.
H˚ astad, Some optimal inapproximability results, Jour- nal of the ACM 48, 798 (2001)
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Benchmarking Variational Quantum Algorithms for Combinatorial Optimization in Practice
Numerical benchmarks identify a minimum problem size where variational quantum circuits for Max-Cut outperform sampling on average, with quantified separation from greedy methods and instance-level performance correlations.