Title: Principal Components of Nuclear Mass Model Residuals Show Chinese title

Title: 核质量模型残差的主要成分

Abstract: Principal Component Analysis (PCA) is applied to the residuals of six widely used nuclear mass models to uncover systematic deviations and identify missing physical effects in theoretical nuclear mass predictions. By analyzing the principal components of nuclear mass model residuals, this study reveals that no single dominant pattern governs the discrepancies across models. Instead, the residual structures are largely uncorrelated, indicating that current nuclear mass models fail to capture underlying nuclear residual effects in distinct and model-specific ways. These findings suggest that improvements to nuclear mass models should be guided by model-specific residual analyses rather than a one-size-fits-all approach. Show Chinese abstract

Abstract: 主成分分析（PCA）被应用于六个广泛使用的核质量模型的残差，以揭示系统性偏差并确定理论核质量预测中缺失的物理效应。 通过分析核质量模型残差的主要成分，本研究发现没有单一的主要模式支配各模型之间的差异。 相反，残差结构在很大程度上是不相关的，这表明当前的核质量模型以不同且模型特定的方式未能捕捉到潜在的核残差效应。 这些发现表明，核质量模型的改进应由模型特定的残差分析来指导，而不是采用一刀切的方法。