Toward a global description of nuclear charge radii: Exploring the Fayans energy density functional
Toward a global description of nuclear charge radii: Exploring the Fayans energy density functional
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DOI：
10.1103/physrevc.95.064328
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发表时间：
2017-04
影响因子：
3.1
通讯作者：
P. Reinhard;W. Nazarewicz
中科院分区：
文献类型：
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作者：
P. Reinhard;W. Nazarewicz
在这项工作中，我们研究了结合能和电荷半径的奇偶效应，以及微分半径的系统行为，以确定有效核相互作用的潜在成分。我们应用核密度泛函理论，使用一族Fayans和Skyrme能量密度泛函，适用于相似的数据集，但使用不同的优化方案。我们考察了微分电荷半径、能量和半径的奇偶交错与核物质性质之间的各种关联。对中等质量半幻核和重半幻核进行了详细的分析，特别是对钙链进行了分析。通过使表面项和配对项依赖于密度梯度，Fayans泛函提供了对能量和电荷半径中奇偶交错效应的极佳同时描述。相反，当将关于微分半径的数据添加到拟合可观测池中时，决定Fayans泛函梯度项强度的耦合常数增加了数量级。在这项工作中优化的Skyrme泛函与广义Fayans对项提供了类似质量的结果。我们通过基于统计线性回归技术进行相关分析来量化这些发现。对相似数据集进行优化的Fayans泛函和Skyrme泛函的核物质参数相当接近。
In this work, we study the odd-even effect in binding energies and charge radii, and systematic behavior of differential radii, to identify the underlying components of the effective nuclear interaction. We apply nuclear density functional theory using a family of Fayans and Skyrme energy density functionals fitted to similar datasets but using different optimization protocols. We inspect various correlations between differential charge radii, odd-even staggering in energies and radii, and nuclear matter properties. Detailed analysis is carried out for medium-mass and heavy semi-magic nuclei with a particular focus on the Ca chain. By making the surface and pairing terms dependent on density gradients, the Fayans functional offers the superb simultaneous description of odd-even staggering effects in energies and charge radii. Conversely, when the data on differential radii are added to the pool of fit-observables, the coupling constants determining the strengths of the gradient terms of Fayans functional are increased by orders of magnitude. The Skyrme functional optimized in this work with the generalized Fayans pairing term offers results of similar quality. We quantify these findings by performing correlation analysis based on the statistical linear regression technique. The nuclear matter parameters characterizing Fayans and Skyrme functionals optimized to similar datasets are fairly close.