2022 journal article

Solar data uncertainty impacts on MCMC methods for r-process nucleosynthesis


By: N. Vassh*, G. McLaughlin, M. Mumpower & R. Surman

author keywords: nucleosynthesis; solar abundances; r-process; heavy elements; Markov Chain Monte Carlo (MCMC); uncertainty quantification (UQ)
Source: Web Of Science
Added: January 17, 2023

In recent work, we developed a Markov Chain Monte Carlo (MCMC) procedure to predict the ground state masses capable of forming the observed Solar r -process rare-earth abundance peak. By applying this method to nucleosynthesis calculations which make use of distinct astrophysical conditions and comparing our results to the latest precision mass measurements, we are able to shed light on the conditions/masses capable of producing a rare-earth peak which matches Solar data. Here we examine how our mass predictions change when using a few different sets of r -process Solar abundance residuals that have been reported in the literature. We explore how the differing error estimates of these Solar evaluations propagate through the Markov Chain Monte Carlo to our mass predictions. We find that Solar data which reports the rare-earth peak to have its highest abundance at mass number A = 162 can require distinctly different mass predictions from data with the peak centered at A = 164. Nevertheless, we find that two important general conclusions from past work, regarding the inconsistency of ‘cold’ astrophysical outflows with current mass measurements and the need for local stability at N = 104 in ‘hot’ scenarios, remain robust in the face of differing Solar data evaluations. Additionally, we show that the masses our procedure finds capable of producing a peak at A < 164 are not in line with the latest precision mass measurements.