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Variational quantum semi-supervised classifier based on label propagation |
Yan-Yan Hou(侯艳艳)1,2, Jian Li(李剑)3,†, Xiu-Bo Chen(陈秀波)4, and Chong-Qiang Ye(叶崇强)2 |
1 College of Information Science and Engineering, ZaoZhuang University, Zaozhuang 277160, China; 2 School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing 100876, China; 3 School of Cyberspace Security, Beijing University of Posts and Telecommunications, Beijing 100876, China; 4 Information Security Center, State Key Laboratory Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China |
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Abstract Label propagation is an essential semi-supervised learning method based on graphs, which has a broad spectrum of applications in pattern recognition and data mining. This paper proposes a quantum semi-supervised classifier based on label propagation. Considering the difficulty of graph construction, we develop a variational quantum label propagation (VQLP) method. In this method, a locally parameterized quantum circuit is created to reduce the parameters required in the optimization. Furthermore, we design a quantum semi-supervised binary classifier based on hybrid Bell and Z bases measurement, which has a shallower circuit depth and is more suitable for implementation on near-term quantum devices. We demonstrate the performance of the quantum semi-supervised classifier on the Iris data set, and the simulation results show that the quantum semi-supervised classifier has higher classification accuracy than the swap test classifier. This work opens a new path to quantum machine learning based on graphs.
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Received: 10 October 2022
Revised: 14 January 2023
Accepted manuscript online: 08 February 2023
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PACS:
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03.67.Ac
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(Quantum algorithms, protocols, and simulations)
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03.67.Lx
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(Quantum computation architectures and implementations)
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Fund: Project supported by the Open Fund of Advanced Cryptography and System Security Key Laboratory of Sichuan Province (Grant No. SKLACSS-202108), the National Natural Science Foundation of China (Grant No. U162271070), Scientific Research Fund of Zaozhuang University (Grant No. 102061901). |
Corresponding Authors:
Jian Li
E-mail: lijian@bupt.edu.cn
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Cite this article:
Yan-Yan Hou(侯艳艳), Jian Li(李剑), Xiu-Bo Chen(陈秀波), and Chong-Qiang Ye(叶崇强) Variational quantum semi-supervised classifier based on label propagation 2023 Chin. Phys. B 32 070309
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