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Beyond QAOA: A Review of AI and Quantum Computing for Adaptive Combinatorial Optimization
Near-term quantum approaches to combinatorial optimization are limited by qubit counts, circuit fidelity, sampling cost, and the difficulty of encoding constraints, while machine learning is increasingly used to configure and control quantum optimization workflows. We call such workflows adaptive: d
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