Monte Carlo variations as a tool to assess nuclear physics uncertainties in nucleosynthesis studies

TL;DR

This paper introduces a Monte Carlo approach to quantify nuclear physics uncertainties in nucleosynthesis models, enabling detailed statistical analysis and identification of key reactions affecting isotopic abundances.

Contribution

The paper presents a novel Monte Carlo method that incorporates temperature-dependent uncertainties and reaction contributions on excited states for nucleosynthesis studies.

Findings

Quantifies uncertainties in isotopic abundances as probability distributions.

Identifies key nuclear reactions influencing nucleosynthesis outcomes.

Provides a systematic automated procedure for reaction importance ranking.

Abstract

The propagation of uncertainties in reaction cross sections and rates of neutron-, proton-, and $\alpha$-induced reactions into the final isotopic abundances obtained in nucleosynthesis models is an important issue in studies of nucleosynthesis and Galactic Chemical Evolution. We developed a Monte Carlo method to allow large-scale postprocessing studies of the impact of nuclear uncertainties on nucleosynthesis. Temperature-dependent rate uncertainties combining realistic experimental and theoretical uncertainties are used. The importance of contributions of cross sections of reactions on excited states of the nuclear targets, which have weights different from from the thermal Boltzmann population factors, is explained. From detailed statistical analyses of the Monte Carlo data uncertainties in the final abundances are derived as probability density distributions. Furthermore, based on rate and abundance correlations an automated procedure identifies the most important reactions in complex flow patterns from superposition of many zones or tracers. The method already has been applied to a number of nucleosynthesis processes.