Speaker
Description
The element abundance pattern seen in Milky Way disk stars is close to two-dimensional, dominated by production from one prompt process and one delayed process. We fit the abundances of 14 elements for 48,659 red-giant stars from APOGEE DR17 using a flexible, data-driven K-process model---dubbed KPM. In our fiducial model, with K=2, each abundance in each star is described as the sum of a prompt and a delayed process contribution.
We find that KPM with K=2 is able to explain the abundances well, recover the observed abundance bimodality, and detect the bimodality over a greater range in metallicity than previously has been possible. We compare to prior work by Weinberg et al. (2022), finding that KPM produces similar results, but that KPM better predicts stellar abundances, especially for elements C+N and Mn and for stars at super-solar metallicities.The model makes assumptions, including especially that it fixes some parameters to break degeneracies and improve interpretability; we find that some of the nucleosynthetic implications are dependent upon these detailed parameter choices. We add a third and fourth process (to make K=4), finding that the additional processes give the model more freedom and improve the model's ability to predict the stellar abundances, as expected, but they don't qualitatively change the story.
