# Detailed illustration of accuracy of presently used nuclear-mass models

## TL;DR

This study evaluates the accuracy and predictive power of twelve nuclear-mass models across different nuclear regions, highlighting the superior performance of recent Chinese models WS3+ and WS4+ and analyzing correlations between accuracy and predictive capability.

## Contribution

It provides a comprehensive, region-specific comparison of multiple nuclear-mass models, including detailed visual maps and analysis of their predictive power and accuracy.

## Key findings

- WS3+ and WS4+ models show highest accuracy
- No universal correlation between accuracy and predictive power
- Accuracy varies significantly across different nuclear regions

## Abstract

The accuracy of description of measured nuclear masses by presently used nuclear-mass models is studied. Twelve models of various kinds are considered, eleven of the global character and one local model specially adapted to description of heavy nuclei. To decrease the number of nuclei over which the accuracy is averaged, the global region (Z,N >= 8) is divided into four subregions, in which the accuracy is studied separately. Still, to reach the best precision, the accuracy is finally investigated without any averaging, for each nucleus separately. The results are presented in a form of colored maps, large enough to be easily and accurately read. Besides the accuracy of the studied models, also their predictive power is considered. It is found that the accuracy of description of mass strongly depends on a nuclear-mass model and on the region of nuclei to which the model is applied. The best accuracy is obtained by the recent two Chinese models WS3+ and WS4+. Generally, no clear, strong correlation between the accuracy of description of already known masses by a given model and its predictive power for new masses is observed. Still, such correlation is found for separate models and in separate regions of nuclei. More often for the macroscopic-microscopic models than for the other approaches.

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Source: https://tomesphere.com/paper/1903.00886