Speaker
Description
Fingerprints of the properties of exotic nuclei on nucleosynthesis observables have been used for decades to frame our picture of how the heaviest elements are produced. The abundance of elements in our Sun and metal-poor stars hints at multiple neutron capture nucleosynthesis processes, the slow (s), intermediate (i) and rapid (r) neutron capture processes. Not only are the site(s) of the r and i processes under active study, but open questions remain regarding how much each of these contributed to the overall enrichment of stars such as our Sun. In particular, the r process synthesizes exotic and unstable nuclei that have yet to be probed in terrestrial experiments, implying r-process studies must consider nuclear physics uncertainties in the interpretation of observables. To move towards a systematic and modern approach, we explore applications of machine learning to decipher metal-poor star abundance patterns and highlight recent results. MeV gamma rays are also an exciting opportunity to pin down the element production of r-process events and hunt for nearby remnants. I will present recent work demonstrating the utility of MeV gamma rays from r-process nuclei (e.g. Rh-106 and Tl-208) that could be used to indicate whether an event reached the heaviest r-process isotopes (A>130) or solely produced a weak r process (A<130). I will also discuss the opportunity to refine our understanding of observables through future measurements at radioactive isotope beam facilities and show how recently reported nuclear masses from cutting-edge ab initio nuclear theory impact our picture for the abundance of key elements (e.g. gold) in neutron star mergers. Novel, interdisciplinary work at the intersection of observation, experiment, theory, and computational science are key to carving out the new ideas and tools needed to tease out the big picture of heavy element origins.