Information and statistics: a new paradigm in theoretical nuclear physics

TL;DR

This paper introduces a new statistical approach using maximum-likelihood estimation to quantify theoretical errors and correlations in nuclear physics models, enhancing the reliability of predictions for physical observables.

Contribution

It develops a Gaussian approximation to the likelihood function for creating a relativistic effective interaction constrained by nuclear and astrophysical data.

Findings

Effective interaction constrained by nuclear and neutron star data

Quantified theoretical errors and correlations in predictions

Demonstrated methods with pedagogical and realistic examples

Abstract

Theoretical predictions of physical observables often involve extrapolations to regions that are poorly constrained by laboratory experiments and astrophysical observations. Without properly quantified theoretical errors, such model predictions are of very limited utility. In this contribution we use maximum-likelihood estimation to compute theoretical errors and assess correlations between physical observables. We illustrate the power and elegance of these methods using examples of both pedagogical and realistic interest. In particular, we implement a gaussian approximation to the likelihood function to develop a new relativistic effective interaction constrained by ground-state properties of finite nuclei, their monopole response, and masses of neutron stars.