Statistical aspects of nuclear mass models

• URL: http://arxiv.org/abs/2002.04151v3
• Date: Thu, 7 May 2020 00:39:02 GMT
• Title: Statistical aspects of nuclear mass models
• Authors: Vojtech Kejzlar, L\'eo Neufcourt, Witold Nazarewicz, Paul-Gerhard Reinhard
• Abstract summary: We study the information content of nuclear masses from the perspective of global models of nuclear binding energies. We employ a number of statistical methods and diagnostic tools, including Bayesian calibration, Bayesian model averaging, chi-square correlation analysis, principal component analysis, and empirical coverage probability.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We study the information content of nuclear masses from the perspective of global models of nuclear binding energies. To this end, we employ a number of statistical methods and diagnostic tools, including Bayesian calibration, Bayesian model averaging, chi-square correlation analysis, principal component analysis, and empirical coverage probability. Using a Bayesian framework, we investigate the structure of the 4-parameter Liquid Drop Model by considering discrepant mass domains for calibration. We then use the chi-square correlation framework to analyze the 14-parameter Skyrme energy density functional calibrated using homogeneous and heterogeneous datasets. We show that a quite dramatic parameter reduction can be achieved in both cases. The advantage of Bayesian model averaging for improving uncertainty quantification is demonstrated. The statistical approaches used are pedagogically described; in this context this work can serve as a guide for future applications.

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