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Benchmarking the quantum approximate optimization algorithm

Published in Quantum Information Processing • Jun 2, 2020
NobleIDNI0P48W38R82S51
Authors:
Madita Willsch
,
Dennis Willsch
,
Fengping Jin

Abstract

Abstract 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 ...

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