Statistical aspects of nuclear mass models

Kejzlar V, Neufcourt L, Nazarewicz W, Reinhard PG (2020)

Publication Type: Journal article

Publication year: 2020

Journal

Journal of Physics G: Nuclear and Particle Physics IOP Publishing: arXiv

Book Volume: 47

Article Number: 094001

Journal Issue: 9

DOI: 10.1088/1361-6471/ab907c

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 four-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 quite a 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.

Authors with CRIS profile

Paul-Gerhard Reinhard Naturwissenschaftliche Fakultät

Additional Organisation(s)

Institut für Theoretische Physik

Involved external institutions

Michigan State University US United States (USA) (US)

How to cite

APA:

Kejzlar, V., Neufcourt, L., Nazarewicz, W., & Reinhard, P.-G. (2020). Statistical aspects of nuclear mass models. Journal of Physics G: Nuclear and Particle Physics, 47(9). https://doi.org/10.1088/1361-6471/ab907c

MLA:

Kejzlar, V., et al. "Statistical aspects of nuclear mass models." Journal of Physics G: Nuclear and Particle Physics 47.9 (2020).

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