Benchmarking the quantum approximate optimization algorithm

The performance of the quantum approximate optimization algorithm is evaluated by using three different measures: the probability of finding the ground state, the energy expectation value, and a ratio closely related to the approximation ratio. The set of problem instances studied consists of weight...

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Veröffentlicht in:	Quantum information processing Jg. 19; H. 7
Hauptverfasser:	Willsch, Madita, Willsch, Dennis, Jin, Fengping, De Raedt, Hans, Michielsen, Kristel
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.07.2020 Springer Nature B.V
Schlagworte:	Algorithms Computer simulation Data Structures and Information Theory Ground state Ising model Mathematical Physics Optimization Optimization algorithms Physics Physics and Astronomy Quantum computers Quantum Computing Quantum Information Technology Quantum Physics Simulators Spintronics Quantum annealing Quantum computation Optimization problems QAOA
ISSN:	1570-0755, 1573-1332
Online-Zugang:	Volltext
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