2025MNRAS.536.2135J

We provide yields from 189 neutrino-driven core-collapse supernova (CCSN) simulations covering zero-age main sequence masses between 11 and $75\ \mathrm{M}_\odot$ and three different metallicities. Our CCSN simulations have two main advantages compared to previous methods used for applications in Galactic chemical evolution (GCE). First, the mass cut between remnant and ejecta evolves naturally. Secondly, the neutrino luminosities and thus the electron fraction are not modified. Both are key to obtain an accurate nucleosynthesis. We follow the composition with an in situ nuclear reaction network including the 16 most abundant isotopes and use the yields as input in a GCE model of the Milky Way. We adopt a GCE that takes into account infall of gas as well as nucleosynthesis from a large variety of stellar sources. The GCE model is calibrated to reproduce the main features of the solar vicinity. For the CCSN models, we use different calibrations and propagate the uncertainty. We find a big impact of the CCSN yields on our GCE predictions. We compare the abundance ratios of C, O, Ne, Mg, Si, S, Ar, Ca, Ti, and Cr with respect to Fe to an observational data set as homogeneous as possible. From this, we conclude that at least half of the massive stars have to explode to match the observed abundance ratios. If the explosions are too energetic, the high amount of iron will suppress the abundance ratios. With this, we demonstrate how GCE models can be used to constrain the evolution and death of massive stars.