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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