Best linear unbiased estimation of the nuclear masses

TL;DR

This paper introduces a data assimilation method called BLUE to optimally evaluate nuclear masses, combining experimental and model data to improve accuracy and reduce uncertainties, especially for less-known nuclei.

Contribution

The paper applies the BLUE data assimilation technique to nuclear mass evaluation, offering a novel approach for more accurate and consistent mass estimates.

Findings

Improved nuclear mass evaluations with reduced uncertainties.

Enhanced accuracy for less well-known nuclear masses.

Demonstrated effectiveness of BLUE in nuclear data assimilation.

Abstract

This paper presents methods to provide an optimal evaluation of the nuclear masses. The techniques used for this purpose come from data assimilation that allows combining, in an optimal and consistent way, information coming from experiment and from numerical model. Using all the available information, it leads to improve not only masses evaluations, but also to decrease uncertainties. Each newly evaluated mass value is associated with some accuracy that is sensibly reduced with respect to the values given in tables, especially in the case of the less well-known masses. In this paper, we first introduce a useful tool of data assimilation, the Best Linear Unbiased Estimation (BLUE). This BLUE method is applied to nuclear mass tables and some results of improvement are shown.