References & Citations
Quantum Physics
Title: Recursive QAOA outperforms the original QAOA for the MAX-CUT problem on complete graphs
(Submitted on 28 Nov 2022 (v1), last revised 21 Feb 2023 (this version, v2))
Abstract: Quantum approximate optimization algorithms are hybrid quantum-classical variational algorithms designed to approximately solve combinatorial optimization problems such as the MAX-CUT problem. In spite of its potential for near-term quantum applications, it has been known that quantum approximate optimization algorithms have limitations for certain instances to solve the MAX-CUT problem, at any constant level $p$. Recently, the recursive quantum approximate optimization algorithm, which is a non-local version of quantum approximate optimization algorithm, has been proposed to overcome these limitations. However, it has been shown by mostly numerical evidences that the recursive quantum approximate optimization algorithm outperforms the original quantum approximate optimization algorithm for specific instances. In this paper, we analytically prove that the recursive quantum approximate optimization algorithm is more competitive than the original one to solve the MAX-CUT problem for complete graphs with respect to the approximation ratio.
Submission history
From: Eunok Bae [view email][v1] Mon, 28 Nov 2022 23:51:02 GMT (601kb,D)
[v2] Tue, 21 Feb 2023 12:17:37 GMT (161kb,D)
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