Principal components of nuclear mass models
作者机构:Department of PhysicsFuzhou UniversityFuzhou 350108China State Key Laboratory of Nuclear Physics and TechnologySchool of PhysicsPeking UniversityBeijing 100871China
出 版 物:《Science China(Physics,Mechanics & Astronomy)》 (中国科学:物理学、力学、天文学(英文版))
年 卷 期:2024年第67卷第7期
页 面:65-71页
核心收录:
学科分类:08[工学] 0827[工学-核科学与技术] 082701[工学-核能科学与工程] 0702[理学-物理学]
基 金: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) the High-performance Computing Platform of Peking University
主 题:nuclear mass principal component analysis nuclear models statistical methods
摘 要:Principal component analysis(PCA)is employed to extract the principal components(PCs)present in nuclear mass models for the first *** effects from different nuclear mass models are reintegrated and reorganized in the extracted *** PCs are recombined to build new mass models,which achieve better accuracy than the original theoretical mass *** comparison indicates that using the PCA approach,the effects contained in different mass models can be collaborated to improve nuclear mass predictions.