arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2002.04151nucl-thstat.APstat.ML
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核质量模型的统计问题

Statistical aspects of nuclear mass models

Vojtech Kejzlar, Léo Neufcourt, Witold Nazarewicz, Paul-Gerhard Reinhard

摘要:

我们从核结合能整体模型的角度研究了核质量的信息含量。为此,我们采用了一些统计方法和诊断工具,包括贝叶斯校准,贝叶斯模型平均,卡方相关分析,主成分分析和经验覆盖概率。使用贝叶斯框架,我们调查的结构的4参数液滴模型考虑不一致的质量域进行校准。然后,我们使用卡方相关框架来分析14参数Skyrme能量密度功能校准使用同质和异构数据集。我们表明,在这两种情况下,可以实现一个相当显着的参数减少。证明了贝叶斯模型平均法在改善不确定性量化方面的优势。所使用的统计方法的教学描述;在这方面,这项工作可以作为未来应用的指南。

英文摘要:

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.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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