KPM: A Flexible and Data-driven K-process Model for Nucleosynthesis
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...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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IOP Publishing
2024-01-01
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| Series: | The Astronomical Journal |
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| Online Access: | https://doi.org/10.3847/1538-3881/ad19c7 |
| _version_ | 1797320633090048000 |
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| author | Emily J. Griffith David W. Hogg Julianne J. Dalcanton Sten Hasselquist Bridget Ratcliffe Melissa Ness David H. Weinberg |
| author_facet | Emily J. Griffith David W. Hogg Julianne J. Dalcanton Sten Hasselquist Bridget Ratcliffe Melissa Ness David H. Weinberg |
| author_sort | Emily J. Griffith |
| collection | DOAJ |
| description | 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 Data Release 17 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 has previously been possible. We compare to prior work by Weinberg et al., finding that KPM produces similar results, but that KPM better predicts stellar abundances, especially for the elements C+N and Mn and for stars at supersolar metallicities. The model fixes the relative contribution of the prompt and delayed processes 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 does not 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. |
| first_indexed | 2024-03-08T04:45:49Z |
| format | Article |
| id | doaj.art-7484b8e022b440d491632bb3e82be226 |
| institution | Directory Open Access Journal |
| issn | 1538-3881 |
| language | English |
| last_indexed | 2024-03-08T04:45:49Z |
| publishDate | 2024-01-01 |
| publisher | IOP Publishing |
| record_format | Article |
| series | The Astronomical Journal |
| spelling | doaj.art-7484b8e022b440d491632bb3e82be2262024-02-08T09:59:05ZengIOP PublishingThe Astronomical Journal1538-38812024-01-0116739810.3847/1538-3881/ad19c7KPM: A Flexible and Data-driven K-process Model for NucleosynthesisEmily J. Griffith0https://orcid.org/0000-0001-9345-9977David W. Hogg1https://orcid.org/0000-0003-2866-9403Julianne J. Dalcanton2Sten Hasselquist3https://orcid.org/0000-0001-5388-0994Bridget Ratcliffe4https://orcid.org/0000-0003-1124-7378Melissa Ness5https://orcid.org/0000-0001-5082-6693David H. Weinberg6https://orcid.org/0000-0001-7775-7261Center for Astrophysics and Space Astronomy, Department of Astrophysical and Planetary Sciences, University of Colorado , 389 UCB, Boulder, CO 80309-0389, USA ; Emily.Griffith-1@colorado.eduCenter for Cosmology and Particle Physics, Department of Physics, New York University , 726 Broadway, New York, NY 10003, USA; Max-Planck-Institut für Astronomie , Königstuhl 17, D-69117 Heidelberg, Germany; Center for Computational Astrophysics, Flatiron Institute , 162 Fifth Avenue, New York, NY 10010, USACenter for Computational Astrophysics, Flatiron Institute , 162 Fifth Avenue, New York, NY 10010, USA; Department of Astronomy, Box 351580, University of Washington , Seattle, WA 98195, USASpace Telescope Science Institute , 3700 San Martin Drive, Baltimore, MD 21218, USALeibniz-Institut für Astrophysik Potsdam (AIP) , An der Sternwarte 16, D-14482 Potsdam, GermanyCenter for Computational Astrophysics, Flatiron Institute , 162 Fifth Avenue, New York, NY 10010, USA; Department of Astronomy, Columbia University , Pupin Physics Laboratories, New York, NY 10027, USAThe Department of Astronomy and Center of Cosmology and AstroParticle Physics, The Ohio State University , Columbus, OH 43210, USAThe 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 Data Release 17 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 has previously been possible. We compare to prior work by Weinberg et al., finding that KPM produces similar results, but that KPM better predicts stellar abundances, especially for the elements C+N and Mn and for stars at supersolar metallicities. The model fixes the relative contribution of the prompt and delayed processes 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 does not 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.https://doi.org/10.3847/1538-3881/ad19c7Stellar abundancesNucleosynthesisGalaxy chemical evolutionCore-collapse supernovaeType Ia supernovae |
| spellingShingle | Emily J. Griffith David W. Hogg Julianne J. Dalcanton Sten Hasselquist Bridget Ratcliffe Melissa Ness David H. Weinberg KPM: A Flexible and Data-driven K-process Model for Nucleosynthesis The Astronomical Journal Stellar abundances Nucleosynthesis Galaxy chemical evolution Core-collapse supernovae Type Ia supernovae |
| title | KPM: A Flexible and Data-driven K-process Model for Nucleosynthesis |
| title_full | KPM: A Flexible and Data-driven K-process Model for Nucleosynthesis |
| title_fullStr | KPM: A Flexible and Data-driven K-process Model for Nucleosynthesis |
| title_full_unstemmed | KPM: A Flexible and Data-driven K-process Model for Nucleosynthesis |
| title_short | KPM: A Flexible and Data-driven K-process Model for Nucleosynthesis |
| title_sort | kpm a flexible and data driven k process model for nucleosynthesis |
| topic | Stellar abundances Nucleosynthesis Galaxy chemical evolution Core-collapse supernovae Type Ia supernovae |
| url | https://doi.org/10.3847/1538-3881/ad19c7 |
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