Compară metode

	Algoritmul cu Aproximare Cuantică pentru Optimizare	Algoritmul lui Grover
Domeniu	Calcul cuantic	Calcul cuantic
Familie	Machine learning	Machine learning
Anul apariției	2014	1996
Autorul original	Edward Farhi	Lov Grover
Tip	Hybrid quantum-classical algorithm	Quantum algorithm
Sursa seminală	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.
Denumiri alternative	QAOA, quantum alternating operator ansatz	quantum search, amplitude amplification
Înrudite	4	3
Rezumat	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.