Author

Hao-Zhao Liang

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Preprint Sep 2026

Quantum convolutional neural network for predicting nuclear charge radii

Quantum machine learning has the potential to become a new tool for understanding complex nuclear structures. In this work, we apply a hybrid quantum convolutional neural network (QCNN) to nuclear charge-radius prediction for the first time, aiming to explore the feasibility of quantum machine learning in nuclear-physi...

Jin-Zhe Wu, Jian-Ping Zhao, Tian-Shuai Shang et al. · 0 citations

#machine learning Preprint Mar 2026

Bridging Theory and Data: Correcting Nuclear Mass Models with Interpretable Machine Learning

This study introduces the Kolmogorov-Arnold Network (KAN) into the refinement of nuclear mass models, proposing an efficient and interpretable solution that provides a novel approach to small-sample, high-complexity scientific problems.

Yan-Hua Lu, Tian-Shuai Shang, Peng-Xiang Du et al. · 0 citations