On the Optimal Choice of Nucleosynthetic Yields, Initial Mass Function, and Number of SNe Ia for Chemical Evolution Modeling

To fully harvest the rich library of stellar elemental abundance data available, we require reliable models that facilitate our interpretation of them. Galactic chemical evolution (GCE) models are one such set, a key part of which are the selection of chemical yields from different nucleosynthetic enrichment channels, predominantly asymptotic giant branch stars, Type Ia supernovae (SNe Ia), and core-collapse supernovae (CC-SNe). Here we present a scoring system for yield tables based on their ability to reproduce protosolar abundances within a simple parameterization of the GCE modeling software Chempy, which marginalizes over galactic parameters describing simple stellar populations (SSPs) and interstellar medium physics. Two statistical scoring methods are presented, based on Bayesian evidence and leave-one-out cross-validation, and are applied to five CC-SN tables, for (a) all mutually available elements and (b) a subset of the nine most abundant elements. We find that the yields of Prantzos et al. (P18, including stellar rotation) and Chieffi & Limongi (C04) best reproduce protosolar abundances for the two cases, respectively. The inferred best-fit SSP parameters for case (b) are for the initial mass function high-mass slope and for the SN Ia normalization, which are broadly consistent across tested yield tables. Additionally, we demonstrate how Chempy can be used to dramatically improve elemental abundance predictions of hydrodynamical simulations by plugging tailored best-fit SSP parameters into a Milky Way analog from Gutcke & Springel. Our code, including a comprehensive tutorial, is freely available and can additionally provide SSP enrichment tables for any combination of parameters and yield tables.