Principal Components of Nuclear Mass Model Residuals

Fuente: arXiv
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Auteurs principaux: Huang, Y. Y., Wu, X. H.
Format: Preprint
Publié: 2025
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author Huang, Y. Y.
Wu, X. H.
author_facet Huang, Y. Y.
Wu, X. H.
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2510_03020
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Principal Components of Nuclear Mass Model Residuals
Huang, Y. Y.
Wu, X. H.
Nuclear Theory
Nuclear Experiment
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.
title Principal Components of Nuclear Mass Model Residuals
topic Nuclear Theory
Nuclear Experiment
url https://arxiv.org/abs/2510.03020