The impact of global nuclear mass model uncertainties on $r$-process abundance predictions

TL;DR

This paper investigates how uncertainties in nuclear mass models affect r-process element abundance predictions, highlighting the need to reduce model errors below 100 keV for more reliable astrophysical predictions.

Contribution

It quantifies the impact of mass model uncertainties on r-process predictions using Monte Carlo simulations and emphasizes the importance of improving mass model accuracy.

Findings

Current mass models have large rms errors affecting predictions.

Reducing errors below 100 keV improves prediction robustness.

Current models cannot reliably reproduce observed abundance features.

Abstract

Rapid neutron capture or `$r$-process' nucleosynthesis may be responsible for half the production of heavy elements above iron on the periodic table. Masses are one of the most important nuclear physics ingredients that go into calculations of $r$-process nucleosynthesis as they enter into the calculations of reaction rates, decay rates, branching ratios and Q-values. We explore the impact of uncertainties in three nuclear mass models on $r$-process abundances by performing global monte carlo simulations. We show that root-mean-square (rms) errors of current mass models are large so that current $r$-process predictions are insufficient in predicting features found in solar residuals and in $r$-process enhanced metal poor stars. We conclude that the reduction of global rms errors below $100$ keV will allow for more robust $r$-process predictions.