Integrating amplitude estimation into QNN readout achieves O(1/N) estimation error with one shot instead of the usual O(1/sqrt(N)) Monte Carlo scaling.
Noisy intermediate-scale quan- tum computers
2 Pith papers cite this work, alongside 123 external citations. Polarity classification is still indexing.
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GPU-based quantum-annealing-inspired algorithms outperform both quantum processors and industry classical solvers in sampling speed and full runtime on MO-MaxCut instances.
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Single-shot quantum neural networks with amplitude estimation
Integrating amplitude estimation into QNN readout achieves O(1/N) estimation error with one shot instead of the usual O(1/sqrt(N)) Monte Carlo scaling.
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Multi-Objective Optimization by Quantum-Annealing-Inspired Algorithms
GPU-based quantum-annealing-inspired algorithms outperform both quantum processors and industry classical solvers in sampling speed and full runtime on MO-MaxCut instances.