Compara mètodes

	Algorisme Aproximat Quàntic per a l'Optimització	Algorisme de Grover
Camp	Computació quàntica	Computació quàntica
Família	Machine learning	Machine learning
Any d'origen	2014	1996
Autor original	Edward Farhi	Lov Grover
Tipus	Hybrid quantum-classical algorithm	Quantum algorithm
Font seminal	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.
Àlies	QAOA, quantum alternating operator ansatz	quantum search, amplitude amplification
Relacionats	4	3
Resum	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.