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	Quantum Approximate Optimization Algorithm	グローバーのアルゴリズム
分野	量子コンピューティング	量子コンピューティング
系統	Machine learning	Machine learning
提唱年	2014	1996
提唱者	Edward Farhi	Lov Grover
種類	Hybrid quantum-classical algorithm	Quantum algorithm
原典	Farhi, E., Goldstone, J., Gutmann, S. (2014). A quantum approximate optimization algorithm. arXiv preprint arXiv:1411.4028.	Grover, L. K. (1996). A fast quantum mechanical algorithm for database search. Proceedings of the 28th Annual ACM Symposium on Theory of Computing (STOC), 212–219.
別名	QAOA, quantum alternating operator ansatz	quantum search, amplitude amplification
関連	4	3
概要	The Quantum Approximate Optimization Algorithm (QAOA) is a hybrid quantum-classical algorithm designed to solve combinatorial optimization problems on near-term quantum devices. Introduced by Farhi, Goldstone, and Gutmann in 2014, QAOA encodes optimization problems into quantum circuits and uses classical optimization to tune circuit parameters, aiming to find approximately optimal solutions for problems like MaxCut, graph coloring, and scheduling.	Grover's Algorithm is a quantum algorithm for searching an unsorted database, offering a quadratic speedup over classical linear search. Proposed by Lov Grover in 1996, it exploits quantum superposition and amplitude amplification to find a target item among N items in O(√N) queries, compared to the classical O(N) requirement.