Multiclassification quantum neural network based on variational quantum circuits

Chuang Li; Zhaolin Liu; Shibin Zhang

doi:10.1117/12.3045429

30 September 2024 Multiclassification quantum neural network based on variational quantum circuits

Chuang Li, Zhaolin Liu, Shibin Zhang

Proceedings Volume 13286, Third International Conference on Electronics Technology and Artificial Intelligence (ETAI 2024); 132860E (2024) https://doi.org/10.1117/12.3045429
Event: Third International Conference on Electronics Technology and Artificial Intelligence (ETAI 2024), 2024, Guangzhou, China

Abstract

Multi classification tasks are an important direction for the application of classical convolutional neural networks. However, in the application research of quantum convolutional neural networks, due to limitations such as quantum bits, a large amount of research has focused on binary and ternary classification tasks, while few have studied the classification of four or more categories. This article presents an improved quantum neural network and uses it to accomplish multi classification tasks. We use the Pennylane library to implement our hybrid quantum classical neural network model, and experimental results show that our model performs slightly better than classical convolutional neural networks with comparable parameter quantities. We hope that our findings can provide some inspiration for the application research of quantum convolutional neural networks in the future.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Chuang Li, Zhaolin Liu, and Shibin Zhang "Multiclassification quantum neural network based on variational quantum circuits", Proc. SPIE 13286, Third International Conference on Electronics Technology and Artificial Intelligence (ETAI 2024), 132860E (30 September 2024); https://doi.org/10.1117/12.3045429

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KEYWORDS

Quantum modeling

Quantum convolutional neural networks

Quantum encoding

Quantum data

Quantum computing

Mathematical optimization

Quantum circuits

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