Abstract
Principal component analysis (PCA) is employed to extract the principal components (PCs) present in nuclear mass models for the first time. The effects from different nuclear mass models are reintegrated and reorganized in the extracted PCs. These PCs are recombined to build new mass models, which achieve better accuracy than the original theoretical mass models. This comparison indicates that using the PCA approach, the effects contained in different mass models can be collaborated to improve nuclear mass predictions.
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This work was supported by the State Key Laboratory of Nuclear Physics and Technology, Peking University (Grant No. NPT2023KFY02), the China Postdoctoral Science Foundation (Grant No. 2021M700256), the National Key R&D Program of China (Grant No. 2018YFA0404400), the National Natural Science Foundation of China (Grant Nos. 11935003, 11975031, 12141501, and 12070131001), and the High-performance Computing Platform of Peking University.
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Wu, XH., Zhao, P. Principal components of nuclear mass models. Sci. China Phys. Mech. Astron. 67, 272011 (2024). https://doi.org/10.1007/s11433-023-2342-4
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DOI: https://doi.org/10.1007/s11433-023-2342-4