Analytic insights on the information content of new observables

TL;DR

This paper develops an analytic framework to evaluate how new experimental data can reduce uncertainties in nuclear physics models, focusing on symmetry energy and neutron matter pressure.

Contribution

It introduces simple expressions to quantify the impact of new observables on reducing uncertainties in key nuclear matter properties.

Findings

Derived formulas for uncertainty reduction in symmetry energy slope.

Quantified how new data affects neutron matter pressure estimates.

Provided insights into optimizing experimental efforts for model constraints.

Abstract

Uncertainty quantification has emerged as a rapidly growing field in nuclear science. 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 limited value. Also, one often deals with theoretical constructs that involve fundamental quantities that are not accessible to experiment or observation. Particularly relevant in this context is the pressure of pure neutron matter. In this contribution we develop an analytic framework to answer the question of "How can new data reduce uncertainties of current theoretical models?" [P.-G. Reinhard and W. Nazarewicz, Phys. Rev. C81, 051303(R) (2010)]. Simple and insightful expressions are obtained to quantify the impact of one or two new observables on theoretical uncertainties in two critical quantities: the slope of the symmetry energy at saturation density and the pressure of pure neutron matter at twice nuclear matter saturation density.