Markov Chain Monte Carlo Predictions of Neutron-rich Lanthanide Properties as a Probe of $r$-process Dynamics

TL;DR

This paper uses Markov Chain Monte Carlo methods to predict neutron-rich lanthanide nuclear masses, helping to understand the astrophysical r-process and its role in element formation, with predictions aligning well with experimental data.

Contribution

It introduces a statistical MCMC approach to explore nuclear mass predictions under different r-process conditions, providing new insights into peak formation mechanisms.

Findings

Mass solutions depend on outflow conditions and r-process path.

Predictions align with experimental neutron-rich mass measurements.

Extended equilibrium conditions yield the most consistent results.

Abstract

Lanthanide element signatures are key to understanding many astrophysical observables, from merger kilonova light curves to stellar and solar abundances. To learn about the lanthanide element synthesis that enriched our solar system, we apply the statistical method of Markov Chain Monte Carlo to examine the nuclear masses capable of forming the $r$-process rare-earth abundance peak. We describe the physical constraints we implement with this statistical approach and demonstrate the use of the parallel chains method to explore the multidimensional parameter space. We apply our procedure to three moderately neutron-rich astrophysical outflows with distinct types of $r$-process dynamics. We show that the mass solutions found are dependent on outflow conditions and are related to the $r$-process path. We describe in detail the mechanism behind peak formation in each case. We then compare our mass predictions for neutron-rich neodymium and samarium isotopes to the latest experimental data from the CPT at CARIBU. We find our mass predictions given outflows that undergo an extended (n,$\gamma$)$\rightleftarrows$($\gamma$,n) equilibrium to be those most compatible with both observational solar abundances and neutron-rich mass measurements.