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

Marco Pignatari, Mattias Ek, Georgy V. Makhatadze, Gábor G. Bálazs, Lorenzo Roberti, James M. Ball, Borbála Cseh, Alessandro Chieffi, Chris Fryer, Falk Herwig, Chiara Incollingo, Thomas Lawson, Marco Limongi, Thomas Rauscher, Maria Schönbächler, Andre Sieverding, Reto Trappitsch, Maria Lugaro

TL;DR

The paper addresses how meteoritic isotope anomalies can be traced to nucleosynthetic ejecta from core-collapse supernovae. It introduces SIMPLE, a Python toolkit that ingests 18 CCSN models from 6 model sets, converts mass fractions to molar abundances, internally normalizes to each model’s initial composition, and computes dilution and $\varepsilon$-scale comparisons with meteoritic data. The Ni isotopes are presented as a case study, showing that bulk meteorite Ni anomalies are compatible with material from the innermost Si-rich CCSN ejecta and highlighting the impact of zone-specific nucleosynthesis and model differences. The work demonstrates the value of a community-driven, extensible framework for cross-model comparisons and outlines future enhancements including more model grids and layer mixing.

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 on the environment of the Sun's birth and the formation of the Solar System. Here we present a new Python tool called SIMPLE (Stellar Interpretation of Meteoritic Data and Plotting for Everyone) 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 6 different published sets, with initial masses of 15, 20, and 25 M$_{\odot}$ and solar metallicity. SIMPLE is designed to easily extract the isotopic abundances predicted by each CCSN model for any elements and post-process 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 addition of more model predictions and inclusion of mixing between different layers of supernova ejecta.

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

TL;DR

The paper addresses how meteoritic isotope anomalies can be traced to nucleosynthetic ejecta from core-collapse supernovae. It introduces SIMPLE, a Python toolkit that ingests 18 CCSN models from 6 model sets, converts mass fractions to molar abundances, internally normalizes to each model’s initial composition, and computes dilution and -scale comparisons with meteoritic data. The Ni isotopes are presented as a case study, showing that bulk meteorite Ni anomalies are compatible with material from the innermost Si-rich CCSN ejecta and highlighting the impact of zone-specific nucleosynthesis and model differences. The work demonstrates the value of a community-driven, extensible framework for cross-model comparisons and outlines future enhancements including more model grids and layer mixing.

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 on the environment of the Sun's birth and the formation of the Solar System. Here we present a new Python tool called SIMPLE (Stellar Interpretation of Meteoritic Data and Plotting for Everyone) 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 6 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 post-process 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 addition of more model predictions and inclusion of mixing between different layers of supernova ejecta.
Paper Structure (13 sections, 4 equations, 4 figures, 2 tables)

This paper contains 13 sections, 4 equations, 4 figures, 2 tables.

Figures (4)

  • Figure 1: Abundance profiles (in mass fraction [mass]) of all the stable Ni isotopes (different colors, as indicated in the legend box) as a function of the mass coordinate of the ejecta for the 20 M$_\odot$ CCSN models of the 6 sets described in Section \ref{['sec:models']}. Each set is indicated in the label box of each panel. Each model is separated into the different zone characterized by the most abundant burning products according to the classification of meyer95. Radiogenic production contributing to each isotope (according to Table \ref{['tab:Nitable']}) is included in each abundance. No abundances reported in the database for the gray area at the lowest mass coordinates, given that this area is not part of the ejecta but of the remnant, compact object. The stellar surface is also not shown, as the composition remains constant in the H-rich region. Note that in Si18 and La22 the explosion is only followed up to a peak temperature of $\sim 1.5$ GK, therefore these models only include the zones up to the He/N. In all the other cases the envelope of the star is included in the simulation dominion and also the H zone is provided.
  • Figure 2: The predicted slope of $\varepsilon^{64}$Ni$_{(81)}$ versus $\varepsilon^{62}$Ni$_{(81)}$ internally normalized to $^{58}$Ni/$^{61}$Ni, as indicated by the last digit of their masses in the subscript bracket (81) of the y-axis label, and where the asterisks indicate that all the radioactive isotopes are decayed into their corresponding stable daughter, calculated from the abundances shown in Figure \ref{['fig:Nispaghetti20']}. The slope reported by steele12 of 3.003$\pm$0.166 from bulk meteoritic data is indicated for comparison as the horizontal orange line, with the shaded region representing the uncertainty.
  • Figure 3: Mass fraction [mass] of $^{60}$Ni as a function of the mass coordinate of the ejecta for the 20 M$_\odot$ model of Ri18, with the different ejecta layers also indicated. The $^{60}$Ni abundance is calculated by progressively adding the abundances of the four radioactive isotopes listed in Table \ref{['tab:Nitable']}. In the label box, "$^{60}$Ni" corresponds to no radiogenic contributions, "$^{60}$Ni* +" to the addition of $^{60}$Cu, "$^{60}$Ni* + +" also of $^{60}$Zn, and "$^{60}$Ni* + + +" also of $^{60}$Co. $^{60}$Ni* includes all the previous isotopes plus $^{60}$Fe, therefore corresponding to the same line plotted in Figure \ref{['fig:Nispaghetti20']}. Note that the red, blue and green lines overlap, which means that only $^{60}$Co and $^{60}$Fe would contribute to the abundance of $^{60}$Ni in this model.
  • Figure 4: Summary of all the predicted slope of $\varepsilon^{64}$Ni$_{(81)}$ versus $\varepsilon^{62}$Ni$_{(81)}$, internally normalized to $^{58}$Ni/$^{61}$Ni, as indicated by the last digit of their masses in the subscript bracket (81) of the y-axis label, and where the asterisks indicate that all the radioactive isotopes in each of the different zones of the 6 sets considered, color-coded as indicated in the legend box. The small dots represent each local slope at a given mass coordinate, the large circles represent two different averages: weighted over the total mass included in each mass layer (filled circles), weighted over both the total mass and the total amount of Ni (in mass fraction) in each mass layer (empty circles), and as the previous but only including layers with Ni amounts varying within the 20th and the 80th percentile of the Ni distribution within the considered zone (i.e., with a statistical z-score lower than 1.25 - empty striped circles).