Linganisha mbinu

	Algorithm ya Quantum Approximate Optimization	Ukadiriaji wa Awamu ya Kiasi
Nyanja	Ukokotoaji wa Kwantamu	Ukokotoaji wa Kwantamu
Familia	Machine learning	Machine learning
Mwaka wa asili	2014	1995
Mwanzilishi	Edward Farhi	Alexei Kitaev
Aina	Hybrid quantum-classical algorithm	Subroutine algorithm
Chanzo asilia	Farhi, E., Goldstone, J., Gutmann, S. (2014). A quantum approximate optimization algorithm. arXiv preprint arXiv:1411.4028.	Kitaev, A. Y. (1995). Quantum measurements and the Abelian stabilizer problem. arXiv preprint quant-ph/9511026.
Majina mbadala	QAOA, quantum alternating operator ansatz	QPE, phase kickback
Zinazohusiana	4	3
Muhtasari	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.	Quantum Phase Estimation (QPE) is a fundamental quantum subroutine that estimates the eigenvalues of a unitary operator. Developed by Alexei Kitaev in 1995, QPE combines controlled unitary evolution with the quantum Fourier transform to extract eigenvalues from quantum states with exponential precision scaling.