Uncertainty quantification in nuclear shell model

TL;DR

This paper introduces a new method for quantifying uncertainties in nuclear shell-model calculations by analyzing the probability distribution of effective interaction parameters, aiding in better comparison with experimental data and revealing potential exotic nuclear properties.

Contribution

A novel approach to uncertainty quantification in nuclear shell-model effective interactions using parameter probability distributions and confidence intervals.

Findings

Large variations in confidence intervals highlight uncertainties in theoretical predictions.

Deviations in confidence intervals can indicate exotic nuclear properties like alpha clustering.

Method provides a statistical framework for assessing agreement between theory and experiment.

Abstract

The uncertainty quantifications of theoretical results are of great importance to make meaningful comparisons of those results with experimental data and to make predictions in experimentally unknown regions. By quantifying uncertainties, one can make more solid statements about, e.g., origins of discrepancy in some quantities between theory and experiment. We propose a novel method for uncertainty quantification for the effective interactions of nuclear shell-model calculations as an example. The effective interaction is specified by a set of parameters, and its probability distribution in the multi-dimensional parameter space is considered. This enables us to quantify the agreement with experimental data in a statistical manner and the resulting confidence intervals show unexpectedly large variations. Moreover, we point out that a large deviation of the confidence interval for the energy in shell-model calculations from the corresponding experimental data can be used as an indicator of some exotic property, e.g. alpha clustering, etc. Other possible applications and impacts are also discussed.