Pi-QEM selects dominant low-weight Pauli strings for ML training in quantum error mitigation, reducing ground-state energy estimation error by up to 34.01% using a single observable in molecular simulations on noisy IBM backends.
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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.
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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.