PUSH CCSN to explosions in spherical symmetry. III.

DOI

In a previously presented proof-of-principle study, we established a parameterized spherically symmetric explosion method (PUSH) that can reproduce many features of core-collapse supernovae (CCSNe) for a wide range of pre-explosion models. The method is based on the neutrino-driven mechanism and follows collapse, bounce, and explosion. There are two crucial aspects of our model for nucleosynthesis predictions. First, the mass cut and explosion energy emerge simultaneously from the simulation (determining, for each stellar model, the amount of Fe-group ejecta). Second, the interactions between neutrinos and matter are included consistently (setting the electron fraction of the innermost ejecta). In the present paper, we use the successful explosion models from Paper II (Ebinger+, 2019, J/ApJ/870/1) that include two sets of pre-explosion models at solar metallicity, with combined masses between 10.8 and 120M_{sun}_. We perform systematic nucleosynthesis studies and predict detailed isotopic yields. The resulting ^56^Ni ejecta are in overall agreement with observationally derived values from normal CCSNe. The Fe-group yields are also in agreement with derived abundances for metal-poor star HD84937. We also present a comparison of our results with observational trends in alpha element to iron ratios.

Identifier
DOI http://doi.org/10.26093/cds/vizier.18700002
Source https://dc.g-vo.org/rr/q/lp/custom/CDS.VizieR/J/ApJ/870/2
Related Identifier https://cdsarc.cds.unistra.fr/viz-bin/cat/J/ApJ/870/2
Related Identifier http://vizier.cds.unistra.fr/viz-bin/VizieR-2?-source=J/ApJ/870/2
Metadata Access http://dc.g-vo.org/rr/q/pmh/pubreg.xml?verb=GetRecord&metadataPrefix=oai_b2find&identifier=ivo://CDS.VizieR/J/ApJ/870/2
Provenance
Creator Curtis S.; Ebinger K.; Frohlich C.; Hempel M.; Perego A.; Liebendorfer M.,Thielemann F.-K.
Publisher CDS
Publication Year 2020
Rights https://cds.unistra.fr/vizier-org/licences_vizier.html
OpenAccess true
Contact CDS support team <cds-question(at)unistra.fr>
Representation
Resource Type Dataset; AstroObjects
Discipline Astrophysics and Astronomy; Interdisciplinary Astronomy; Natural Sciences; Observational Astronomy; Physics; Stellar Astronomy