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양자 위상 추정×양자 근사 최적화 알고리즘×
분야양자컴퓨팅양자컴퓨팅
계열Machine learningMachine learning
기원 연도19952014
창시자Alexei KitaevEdward Farhi
유형Subroutine algorithmHybrid quantum-classical algorithm
원전Kitaev, A. Y. (1995). Quantum measurements and the Abelian stabilizer problem. arXiv preprint quant-ph/9511026. link ↗Farhi, E., Goldstone, J., Gutmann, S. (2014). A quantum approximate optimization algorithm. arXiv preprint arXiv:1411.4028. DOI ↗
별칭QPE, phase kickbackQAOA, quantum alternating operator ansatz
관련34
요약Quantum 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.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.
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ScholarGate방법 비교: Quantum Phase Estimation · Quantum Approximate Optimization Algorithm. 2026-06-15에 다음에서 검색함: https://scholargate.app/ko/compare