Stellar Interpretation of Meteoritic Data and PLotting for Everyone (SIMPLE): Isotope Mixing Lines for Six Sets of Core-collapse Supernova Models

Abstract Bulk meteorites and their inclusions exhibit, for many chemical elements, isotopic variability produced by nucleosynthetic events in stars and supernovae before the formation of the Sun. While the exact astrophysical origins of these variations are still a matter of debate, their identification provides insights into the environment of the Sun’s birth and the formation of the solar system. Here, we present a new Python tool called Stellar Interpretation of Meteoritic Data and Plotting for Everyone (SIMPLE) designed to compare the isotopic composition of the ejecta from core-collapse supernovae (CCSNe) with meteoritic data. In the present version, the SIMPLE toolkit includes a dataset of 18 CCSN models from six different published sets, with initial masses of 15, 20, and 25 M ⊙ and solar metallicity. SIMPLE is designed to easily extract the isotopic abundances predicted by each CCSN model for any elements and postprocess them into the format needed to compare to the meteoritic data, therefore facilitating their interpretation. As an example of how to use SIMPLE, we analyze the composition of the Ni isotopes in the 18 models and confirm that bulk meteorite Ni anomalies are compatible with material from the innermost Si-rich region of CCSN ejecta. Designed as a collaborative platform, SIMPLE is open source and welcomes community contributions to enhance its development and dissemination for stellar nucleosynthesis and meteoritic studies. Future enhancements include the addition of more model predictions and the inclusion of mixing between different layers of supernova ejecta.

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Publication Details

Journal
The Astrophysical Journal
Published
2026-08-14
DOI
https://doi.org/10.3847/1538-4357/ae7327
Primary Topic
Astro and Planetary Science
Type
article
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article

Stellar Interpretation of Meteoritic Data and PLotting for Everyone (SIMPLE): Isotope Mixing Lines for Six Sets of Core-collapse Supernova Models

Mattias Ek, A. Chieffi, Chris Fryer, Gábor Balázs et al.
The Astrophysical Journal
Astro and Planetary Science
article

Stellar Interpretation of Meteoritic Data and PLotting for Everyone (SIMPLE): Isotope Mixing Lines for Six Sets of Core-collapse Supernova Models

Mattias Ek, A. Chieffi, Chris Fryer, Gábor Balázs, Maria Lugaro, Lorenzo Roberti, Falk Herwig, R. Trappitsch, Thomas V Lawson, James M. Ball, Borbála Cseh, Marco Limongi, Marco Pignatari, Andre Sieverding, Maria Schönbächler, Thomas Rauscher, Georgy V. Makhatadze, Chiara Incollingo
article en

Abstract

Abstract Bulk meteorites and their inclusions exhibit, for many chemical elements, isotopic variability produced by nucleosynthetic events in stars and supernovae before the formation of the Sun. While the exact astrophysical origins of these variations are still a matter of debate, their identification provides insights into the environment of the Sun’s birth and the formation of the solar system. Here, we present a new Python tool called Stellar Interpretation of Meteoritic Data and Plotting for Everyone (SIMPLE) designed to compare the isotopic composition of the ejecta from core-collapse supernovae (CCSNe) with meteoritic data. In the present version, the SIMPLE toolkit includes a dataset of 18 CCSN models from six different published sets, with initial masses of 15, 20, and 25 M ⊙ and solar metallicity. SIMPLE is designed to easily extract the isotopic abundances predicted by each CCSN model for any elements and postprocess them into the format needed to compare to the meteoritic data, therefore facilitating their interpretation. As an example of how to use SIMPLE, we analyze the composition of the Ni isotopes in the 18 models and confirm that bulk meteorite Ni anomalies are compatible with material from the innermost Si-rich region of CCSN ejecta. Designed as a collaborative platform, SIMPLE is open source and welcomes community contributions to enhance its development and dissemination for stellar nucleosynthesis and meteoritic studies. Future enhancements include the addition of more model predictions and the inclusion of mixing between different layers of supernova ejecta.

The Astrophysical JournalVol. 1007(2)
Eötvös Loránd University (HU), University of Copenhagen (DK), Lawrence Livermore National Laboratory (US), Los Alamos National Laboratory (US), University of Hertfordshire (GB), Kavli Institute for the Physics and Mathematics of the Universe (JP), University of Basel (CH), University of Hull (GB), Université Paris Cité (FR), University of Victoria (CA), Australian Regenerative Medicine Institute (AU), Konkoly Observatory (HU), Institute for Space Astrophysics and Planetology (IT), Osservatorio Astronomico di Palermo (IT), Institute of Geochemistry (CN), Momentum Research (US), Centralsjukhuset Kristianstad (SE), Istituto Nazionale di Fisica Nucleare, Sezione di Perugia (IT), University of Bayreuth (DE), Monash University (AU), National Institute for Astrophysics (IT)
Openalex Percentile: Top 86%
Astro and Planetary Science
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