KPM: A Flexible and Data-Driven K-Process Model for Nucleosynthesis

TL;DR

This paper introduces KPM, a data-driven model with two main processes, to explain stellar element abundances, revealing bimodality and improving predictions over previous models, aiding understanding of galactic formation and nucleosynthesis.

Contribution

The paper presents KPM, a flexible, data-driven two-process model for stellar abundances, demonstrating its effectiveness and comparing it to prior models, with extensions to four processes for enhanced flexibility.

Findings

KPM with K=2 explains abundance bimodality in stars.

KPM outperforms previous models in predicting certain element abundances.

Adding four processes improves model flexibility without changing core conclusions.

Abstract

The element abundance pattern found in Milky Way disk stars is close to two-dimensional, dominated by production from one prompt process and one delayed process. This simplicity is remarkable, since the elements are produced by a multitude of nucleosynthesis mechanisms operating in stars with a wide range of progenitor masses. 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 fixes the relative contribution of the prompt and delayed process to two elements to break degeneracies and improve interpretability; we find that some of the nucleosynthetic implications are dependent upon these detailed choices. We find that moving to four processes adds flexibility and improves the model's ability to predict the stellar abundances, but doesn't qualitatively change the story. The results of KPM will help us to interpret and constrain the formation of the Galaxy disk, the relationship between abundances and ages, and the physics of nucleosynthesis.