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

## TL;DR

This paper extends the analysis of nuclear energy density functionals by applying the manifold boundary approximation method to finite nuclei data, reducing model complexity and identifying effective lower-dimensional functionals.

## Contribution

It introduces a systematic approach to simplify nuclear density functionals using MBAM and information geometry, focusing on finite nuclei data.

## Key findings

- Reduced the parameter space dimension of functionals
- Identified effective lower-dimensional functionals
- Optimized functional form of density dependence

## 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.