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Chin. Phys. B, 2023, Vol. 32(10): 100308    DOI: 10.1088/1674-1056/acb75e
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Single-qubit quantum classifier based on gradient-free optimization algorithm

Anqi Zhang(张安琪)1, Kelun Wang(王可伦)1, Yihua Wu(吴逸华)1, and Sheng-Mei Zhao(赵生妹)1,2,†
1 Institute of Signal Processing and Transmission, Nanjing University of Posts and Telecommunications, Nanjing 210003, China;
2 Key Laboratory of Broadband Wireless Communication and Sensor Network Technology, Ministry of Education, Nanjing 210003, China
Abstract  A single-qubit quantum classifier (SQC) based on a gradient-free optimization (GFO) algorithm, named the GFO-based SQC, is proposed to overcome the effects of barren plateaus caused by quantum devices. Here, a rotation gate $R_{X}(\phi)$ is applied on the single-qubit binary quantum classifier, and the training data and parameters are loaded into $\phi$ in the form of vector multiplication. The cost function is decreased by finding the value of each parameter that yields the minimum expectation value of measuring the quantum circuit. The algorithm is performed iteratively for all parameters one by one until the cost function satisfies the stop condition. The proposed GFO-based SQC is demonstrated for classification tasks in Iris and MNIST datasets and compared with the Adam-based SQC and the quantum support vector machine (QSVM). Furthermore, the performance of the GFO-based SQC is discussed when the rotation gate in the quantum device is under different types of noise. The simulation results show that the GFO-based SQC can reach a high accuracy in reduced time. Additionally, the proposed GFO algorithm can quickly complete the training process of the SQC. Importantly, the GFO-based SQC has a good performance in noisy environments.
Keywords:  single-qubit quantum classifier      gradient-free      parameters optimizing      barren plateau      quantum noise  
Received:  03 October 2022      Revised:  16 January 2023      Accepted manuscript online:  31 January 2023
PACS:  03.67.Ac (Quantum algorithms, protocols, and simulations)  
Fund: Project supported by the National Natural Science Foundation of China (Grant No. 62375140) and Postgraduate Research & Practice Innovation Program of Jiangsu Province (Grant No. KYCX19 0900).
Corresponding Authors:  Sheng-Mei Zhao     E-mail:  zhaosm@njupt.edu.cn

Cite this article: 

Anqi Zhang(张安琪), Kelun Wang(王可伦), Yihua Wu(吴逸华), and Sheng-Mei Zhao(赵生妹) Single-qubit quantum classifier based on gradient-free optimization algorithm 2023 Chin. Phys. B 32 100308

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