"Sloppy" nuclear energy density functionals (II): Finite nuclei

Abstract

A study of parameter sensitivity of nuclear energy density functionals, initiated in the first part of this work \cite{NV.16}, is extended by the inclusion of data on ground-state properties of finite nuclei in the application of the manifold boundary approximation method (MBAM). Density functionals used in self-consistent mean-field calculations, and nuclear structure models based on them, are generally "sloppy" and exhibit an exponential range of sensitivity to parameter variations. Concepts of information geometry are used to identify the presence of effective functionals of lower dimension in parameter space associated with parameter combinations that can be tightly constrained by data. The MBAM is used in an iterative procedure that systematically reduces the complexity and the dimension of parameter space of a sloppy functional, with properties of nuclear matter and data on finite nuclei determining not only the values of model parameters, but also the optimal functional form of the density dependence.

Accepted for publication in Physical Review C. arXiv admin note: text overlap with arXiv:1606.08617

References in corpus (4)

• Relativistic Nuclear Energy Density Functionals: adjusting parameters to binding energies
• Global performance of covariant energy density functionals: ground state observables of even-even nuclei and the estimate of theoretical uncertainties
• The sloppy model universality class and the Vandermonde matrix
• Sloppy nuclear energy density functionals: effective model reduction

Cited by in corpus (7)

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• Statistical aspects of nuclear mass models
• The propagation of statistical errors in covariant density functional theory: ground state observables and single-particle properties
• Covariant density functional theory input for r-process simulations in actinides and superheavy nuclei: the ground state and fission properties
• Nuclear energy density functionals from empirical ground-state densities
• Stability of the manifold boundary approximation method for reductions of nuclear structure models
• Classical and Bayesian error analysis of the relativistic mean-field model for doubly magic nuclei