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arxiv: 2602.23354 · v2 · submitted 2026-02-26 · 🌌 astro-ph.SR · astro-ph.GA

Recognition: 2 theorem links

· Lean Theorem

Revisiting the Perseus Cluster II: Metallicity-Dependence of Massive Stars and Chemical Enrichment History

Shing-Chi Leung , Seth Walther , Henry Yerdon , Ken'ichi Nomoto , Aurora Simionescu
Authors on Pith no claims yet

Pith reviewed 2026-05-15 18:45 UTC · model grok-4.3

classification 🌌 astro-ph.SR astro-ph.GA
keywords core-collapse supernovaechemical abundancesPerseus Clustermetallicitygalactic chemical evolutionnucleosynthesisHitomiiron-group elements
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The pith

Metallicity-dependent core-collapse supernova models reproduce the Si-group and Fe-group abundances observed in the Perseus Cluster when used in galactic chemical evolution calculations.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

This paper creates new models of massive star evolution and explosions as core-collapse supernovae for initial masses from 15 to 60 solar masses and metallicities from zero up to solar. These models compute detailed chemical yields for silicon-group, odd-number, and iron-group elements. Inserting the yields into a galactic chemical evolution model allows the authors to find combinations of supernova rates that match the precise abundance ratios measured by Hitomi in the Perseus Cluster for both silicon-group and iron-group elements. The study examines how the metallicity of the stars affects which elements are produced most efficiently by massive stars versus Type Ia supernovae. A sympathetic reader would care because this constrains the sources and timing of chemical enrichment across cosmic history.

Core claim

By extending stellar models across metallicities, the authors show that their metallicity-dependent CCSN yields, when used in a parameter survey of galactic chemical evolution, produce configurations that simultaneously reproduce the Si-group and Fe-group abundance pattern observed by Hitomi in the Perseus Cluster.

What carries the argument

Metallicity-dependent nucleosynthesis yields from core-collapse supernova models for 15-60 solar mass stars, fed into a single-zone galactic chemical evolution calculation to fit observed cluster abundances.

If this is right

  • The best-fit models indicate specific relative contributions from massive stars and Type Ia supernovae that depend on the metallicity assumed for the progenitors.
  • Production of elements like manganese and nickel is particularly sensitive to the metallicity of the exploding stars.
  • Surveys show that different literature yield tables require different supernova rate ratios to achieve similar fits to the Perseus data.
  • Odd-Z elements provide additional constraints on the explosion physics at low metallicity.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • If correct, these yields could be applied to model the chemical evolution of the Milky Way or other galaxies with similar success.
  • Future observations of abundance patterns in clusters at higher redshift could test the predicted metallicity evolution.
  • Including effects of binary stars or inhomogeneous mixing might change the inferred supernova contributions.

Load-bearing premise

The galactic chemical evolution model assumes a single, well-mixed reservoir whose enrichment is controlled only by the relative rates of CCSNe and Type Ia supernovae.

What would settle it

A precise measurement of the chromium or manganese abundance in a galaxy cluster with a significantly different average metallicity that does not match the model's predicted trend would falsify the reproduction claim.

Figures

Figures reproduced from arXiv: 2602.23354 by Aurora Simionescu, Henry Yerdon, Ken'ichi Nomoto, Seth Walther, Shing-Chi Leung.

Figure 1
Figure 1. Figure 1: The chemical composition of the model with M = 20M⊙ and Z = Z⊙ at the end of the O burning phase by directly solving the 127-isotope network in the MESA code (solid line) and by post-processing the thermodynamics trajectory from models using the 22-isotope network (dashed line). and the chemical profiles of the massive star models, deriving the refined mixing parameters. We assume the α-chain for the nucle… view at source ↗
Figure 2
Figure 2. Figure 2: (top panel) The pre-collapse temperature profiles of M25Z0 (blue solid line), M25Z1e-1 (orange dashed line) and M25Z1 (green dotted line). (bottom panel) Same as the top panel but for the abundances of 16O (blue), 28Si (orange) and 56Fe (green). The line style corresponds to the initial metallicity. results in stronger production in even-number species along α-chain from Si to Cr, and some minor elements, … view at source ↗
Figure 3
Figure 3. Figure 3: (top panel) The scaled mass fraction[X/56Fe] for the stable isotopes after explosion of 15 M⊙ progenitor assuming 1 × 1051 erg, with Z = 0 (M15Z0, blue circles), Z = 0.1Z⊙ (M15Z1e-1, orange triangles) and Z = Z⊙ (M15Z1, black squares). Isotopes from C to Zn are shown. The two horizontal lines refer to two times (upper line) and half (lower line) of the solar ratios. (middle panel) Same as the top panel, bu… view at source ↗
Figure 4
Figure 4. Figure 4: (top panel) The scaled mass fraction[X/56Fe] for the stable isotopes after explosion of 40 M⊙ progenitor assuming 1 × 1051 erg, with Z = 0 (M30Z0, blue circles), Z = 0.1Z⊙ (M30Z1e-1, orange triangles) and Z = Z⊙ (M30Z1, black squares). Isotopes from C to Zn are shown. (middle panel) Same as the top panel, but for M40Z0, M40Z1e-1, and M40Z1. (bottom panel) Same as the top panel, but for M60Z0, M60Z1e-1, and… view at source ↗
Figure 5
Figure 5. Figure 5: (top left panel) The scaled mass fraction[X/Fe] for the stable isotopes after explosion of 15 M⊙ progenitor assuming 1 × 1051 erg, with Z = 0 (blue circles), Z = 0.1Z⊙ (orange triangles) and Z = Z⊙ (black square). Elements from C to Zn are shown. Other panels are the same as the top left panel, but for M20Z0, M20Z1e-1, M20Z1 (top right panel), M25Z0, M25Z1e-1, M25Z1 (middle left panel), M30Z0, M30Z1e-1, M3… view at source ↗
Figure 6
Figure 6. Figure 6: The left column shows the best-rate models, represented by the three models with SNe Ia fractions fIa and fChand closest to the empirical values of 0.007 and 0.33, respectively. The right column shows the lowest χ 2 best-fit models. In both columns, models are arranged from best to worst from top to bottom. The yellow cross corresponds to the parameters for the best-fit model. The left column contains the … view at source ↗
Figure 7
Figure 7. Figure 7: The chemical abundance X/Fe for the best models with L25-series (top left panel), with different SN Ia models including LN18 (blue stars), LN18(Ka4) (lime circles), SC13-bestfit (brown triangles), TM16-bestfit (cyan pluses), LC22-bestfit (magenta diamonds), W7-bestfit (orange diamonds), SK18-bestfit (red squares), PK13-bestfit (green X), GC21-bestfit (purple triangles). The error bars correspond to the mea… view at source ↗
read the original abstract

The legacy Hitomi telescope has delivered the precise measurements of the chemical abundances in the Perseus Cluster, covering the Si-group (Si, S, Ar, Ca) and Fe-group elements (Cr, Mn, Ni). In Paper I (Leung et al., ApJ 2025), we examined the role of convection parameters and presented new core-collapse supernova (CCSN) explosion models at solar metallicity, which fit the observed abundance pattern. In this article, we extend our calculation for the stellar evolutionary models and CCSN models of the initial mass $15 - 60M_{\odot}$ and the metallicity $Z = 0 - Z_{\odot}$. The detailed pre- and post-explosion chemical profiles are calculated with a large post-processing network to capture the production of $\alpha$-chain elements (e.g., Si, S, Ar), odd-number elements (e.g., P, K, Cl), and iron-group elements (e.g., Mn, Ni). We study the role of CCSNe in the production of these elements. We compare the galactic chemical evolution model based on the nucleosynthesis yield of the new massive stars and other yield tables from the literature. For each supernova yield, we perform parameter surveys and search for configurations that produce the best-fit model and best-rate model using the Perseus Cluster as the reference. From the survey, we study how individual chemical elements affect the contributions of massive stars and Type Ia supernovae in the cosmic chemical enrichment

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 2 minor

Summary. The paper extends CCSN explosion models to initial masses 15-60 M⊙ and metallicities Z=0 to Z⊙, computing detailed pre- and post-explosion chemical profiles with a large post-processing network for α-chain, odd-Z, and iron-group elements. These new metallicity-dependent yields are inserted into one-zone galactic chemical evolution calculations; parameter surveys over the CCSN/SN Ia rate ratio and convection parameters are used to identify best-fit and best-rate configurations that reproduce the Si-group (Si, S, Ar, Ca) and Fe-group (Cr, Mn, Ni) abundance patterns measured by Hitomi in the Perseus Cluster, with comparisons to literature yield tables.

Significance. If the central claim holds after addressing the fitting and modeling assumptions, the work would establish that metallicity-dependent CCSN yields can simultaneously account for both Si-group and Fe-group ratios in a cluster environment, providing a concrete test of how massive-star nucleosynthesis varies with Z and quantifying the relative CCSN versus SN Ia contributions to cosmic enrichment. The tabulated yields across a metallicity grid would constitute a reusable resource for GCE studies.

major comments (2)
  1. [§4] §4 (parameter-survey description): the best-fit and best-rate models are obtained by tuning the CCSN/SN Ia rate ratio and convection parameters directly against the Perseus Cluster abundances that are also the target of the fit; this circularity means the reported agreement does not constitute an independent validation of the new yields.
  2. [GCE model section] GCE model section: the calculation assumes a single, well-mixed, closed-box reservoir whose enrichment is controlled solely by the relative CCSN and SN Ia rates. No test is presented of whether spatial inhomogeneity, multi-galaxy contributions, or late-time mixing in the Perseus ICM would alter the inferred rate ratio or the claimed superiority of the new Z-dependent yields.
minor comments (2)
  1. [Abstract] Abstract: the distinction between 'best-fit model' and 'best-rate model' is not defined; a one-sentence clarification would improve readability.
  2. [Throughout] Notation: ensure uniform use of Z⊙ versus Z = 0 – Z⊙ and consistent mass-range formatting throughout the text and tables.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We are grateful to the referee for their thorough review and insightful comments on our manuscript. We have carefully considered each point and provide our responses below, along with indications of revisions to the manuscript.

read point-by-point responses

  1. Referee: [§4] §4 (parameter-survey description): the best-fit and best-rate models are obtained by tuning the CCSN/SN Ia rate ratio and convection parameters directly against the Perseus Cluster abundances that are also the target of the fit; this circularity means the reported agreement does not constitute an independent validation of the new yields.

    Authors: We agree that the parameter survey identifies best-fit and best-rate configurations by tuning the CCSN/SN Ia rate ratio and convection parameters against the Perseus Cluster abundances. The intent is to perform a consistent, side-by-side comparison of our new metallicity-dependent yields with literature tables under identical fitting procedures, rather than to claim an independent or blind validation. We have revised §4 to explicitly state this purpose and to clarify that the exercise demonstrates the viability of the new yields within the same modeling framework used for other yield sets. revision: partial

  2. Referee: [GCE model section] GCE model section: the calculation assumes a single, well-mixed, closed-box reservoir whose enrichment is controlled solely by the relative CCSN and SN Ia rates. No test is presented of whether spatial inhomogeneity, multi-galaxy contributions, or late-time mixing in the Perseus ICM would alter the inferred rate ratio or the claimed superiority of the new Z-dependent yields.

    Authors: The one-zone closed-box GCE model is a standard simplification employed to isolate the effects of yield variations on integrated abundances. We acknowledge that this framework does not incorporate spatial inhomogeneities, multi-galaxy contributions, or late-time mixing within the Perseus ICM. The Perseus Cluster data represent volume-integrated measurements, and the model serves as a baseline for yield comparisons. We have expanded the GCE model section to discuss these assumptions and their potential influence on the inferred rate ratios. revision: yes

Circularity Check

1 steps flagged

GCE parameter survey tunes to Perseus data; claimed reproduction is by construction

specific steps
  1. fitted input called prediction [Abstract]
    "For each supernova yield, we perform parameter surveys and search for configurations that produce the best-fit model and best-rate model using the Perseus Cluster as the reference."

    The survey explicitly optimizes the relative CCSN and Type Ia contributions (and any other free parameters) to minimize the difference from the observed Perseus abundances. The resulting 'best-fit' configuration therefore reproduces the target data by definition of the fitting procedure; the agreement supplies no independent validation of the new metallicity-dependent yields.

full rationale

The paper's central result is that new Z-dependent CCSN yields inserted into a one-zone GCE model can simultaneously match the Si-group and Fe-group abundances measured by Hitomi in the Perseus Cluster. However, the GCE calculation performs an explicit parameter survey over CCSN/Ia rate ratios and related parameters, selecting the 'best-fit model' and 'best-rate model' by direct comparison to the same Perseus dataset. This makes the reported agreement a fitted outcome rather than an independent prediction. The single-reservoir assumption is not tested against external data. Self-citation to Paper I supplies the base solar-metallicity models but does not alter the fitting step. No other circular patterns (self-definition, uniqueness theorems, or ansatz smuggling) are present.

Axiom & Free-Parameter Ledger

2 free parameters · 1 axioms · 0 invented entities

The central claim rests on (1) the assumption that the Perseus Cluster gas is a closed, well-mixed system whose abundances are set solely by the integrated yields of CCSNe and SNe Ia, (2) the choice of convection parameters carried over from Paper I, and (3) the nuclear reaction rates and explosion engine parameters that are not re-derived here.

free parameters (2)
  • relative CCSN to SN Ia rate ratio
    Adjusted in the parameter survey to achieve best fit to Perseus abundances
  • convection parameters
    Inherited from Paper I and held fixed across the metallicity grid
axioms (1)
  • domain assumption The Perseus Cluster gas represents a single, well-mixed reservoir whose enrichment history can be modeled with a one-zone GCE code
    Invoked when the authors use the cluster abundances as the sole reference for the parameter survey

pith-pipeline@v0.9.0 · 5592 in / 1531 out tokens · 19707 ms · 2026-05-15T18:45:35.591045+00:00 · methodology

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Works this paper leans on

76 extracted references · 76 canonical work pages · 3 internal anchors

  1. [1]

    2022, ApJS, 259, 35, doi: 10.3847/1538-4365/ac4414

    Abdurro’uf, Accetta, K., Aerts, C., et al. 2022, ApJS, 259, 35, doi: 10.3847/1538-4365/ac4414

    work page doi:10.3847/1538-4365/ac4414 2022

  2. [2]

    2019, MNRAS, 489, 1082, doi: 10.1093/mnras/stz2158

    Battino, U., Tattersall, A., Lederer-Woods, C., et al. 2019, MNRAS, 489, 1082, doi: 10.1093/mnras/stz2158

    work page doi:10.1093/mnras/stz2158 2019

  3. [3]

    2024, PASP, 136, 094201, doi: 10.1088/1538-3873/ad6e18

    Bora, Z., K¨ onyves-T´ oth, R., Vink´ o, J., et al. 2024, PASP, 136, 094201, doi: 10.1088/1538-3873/ad6e18

    work page doi:10.1088/1538-3873/ad6e18 2024

  4. [4]

    M., Foley , R

    Bressan, A., Marigo, P., Girardi, L., et al. 2012, MNRAS, 427, 127, doi: 10.1111/j.1365-2966.2012.21948.x

    work page doi:10.1111/j.1365-2966.2012.21948.x 2012

  5. [5]

    2004, ApJ, 608, 405, doi: 10.1086/392523 —

    Chieffi, A., & Limongi, M. 2004, ApJ, 608, 405, doi: 10.1086/392523 —. 2013, ApJ, 764, 21, doi: 10.1088/0004-637X/764/1/21

    work page doi:10.1086/392523 2004

  6. [6]

    1989, ApJS, 71, 47, doi: 10.1086/191364

    Chieffi, A., & Straniero, O. 1989, ApJS, 71, 47, doi: 10.1086/191364

    work page doi:10.1086/191364 1989

  7. [7]

    S., Aldering , G., et al

    Dray, L. M., & Tout, C. A. 2003, MNRAS, 341, 299, doi: 10.1046/j.1365-8711.2003.06420.x

    work page doi:10.1046/j.1365-8711.2003.06420.x 2003

  8. [8]

    2008, Ap&SS, 316, 43, doi: 10.1007/s10509-007-9511-y

    Eggenberger, P., Meynet, G., Maeder, A., et al. 2008, Ap&SS, 316, 43, doi: 10.1007/s10509-007-9511-y

    work page doi:10.1007/s10509-007-9511-y 2008

  9. [9]

    Eggleton, P. P. 1971, MNRAS, 151, 351, doi: 10.1093/mnras/151.3.351 Ekstr¨ om, S., Georgy, C., Eggenberger, P., et al. 2012, A&A, 537, A146, doi: 10.1051/0004-6361/201117751

    work page doi:10.1093/mnras/151.3.351 1971

  10. [10]

    J., Stanway, E

    Eldridge, J. J., Stanway, E. R., Xiao, L., et al. 2017, PASA, 34, e058, doi: 10.1017/pasa.2017.51

    work page internal anchor Pith review doi:10.1017/pasa.2017.51 2017

  11. [11]

    J., Zwaan , M

    Eldridge, J. J., & Tout, C. A. 2004, MNRAS, 353, 87, doi: 10.1111/j.1365-2966.2004.08041.x

    work page doi:10.1111/j.1365-2966.2004.08041.x 2004

  12. [12]

    E., et al

    Frohmaier, C., Sullivan, M., Nugent, P. E., et al. 2019, MNRAS, 486, 2308, doi: 10.1093/mnras/stz807

    work page doi:10.1093/mnras/stz807 2019

  13. [13]

    R., Vincenzi, M., et al

    Frohmaier, C., Angus, C. R., Vincenzi, M., et al. 2021, MNRAS, 500, 5142, doi: 10.1093/mnras/staa3607

    work page doi:10.1093/mnras/staa3607 2021

  14. [14]

    E., Sim, S

    Gronow, S., Collins, C. E., Sim, S. A., & R¨ opke, F. K. 2021, A&A, 649, A155, doi: 10.1051/0004-6361/202039954

    work page doi:10.1051/0004-6361/202039954 2021

  15. [15]

    R., Millman, K

    Harris, C. R., Millman, K. J., van der Walt, S. J., et al. 2020, Nature, 585, 357, doi: 10.1038/s41586-020-2649-2

    work page doi:10.1038/s41586-020-2649-2 2020

  16. [16]

    N., Kobayashi, C., Tominaga, N., & Nomoto, K

    Hartwig, T., Ishigaki, M. N., Kobayashi, C., Tominaga, N., & Nomoto, K. 2023, ApJ, 946, 20, doi: 10.3847/1538-4357/acbcc6

    work page doi:10.3847/1538-4357/acbcc6 2023

  17. [17]

    Heger, A., & Woosley, S. E. 2002, ApJ, 567, 532, doi: 10.1086/338487 Hitomi Collaboration, Aharonian, F., Akamatsu, H., et al. 2017, Nature, 551, 478, doi: 10.1038/nature24301 —. 2018a, PASJ, 70, 9, doi: 10.1093/pasj/psx138 —. 2018b, PASJ, 70, 10, doi: 10.1093/pasj/psx127 —. 2018c, PASJ, 70, 11, doi: 10.1093/pasj/psy004

    work page doi:10.1086/338487 2002

  18. [18]

    Hunter, J. D. 2007, Computing in Science & Engineering, 9, 90, doi: 10.1109/MCSE.2007.55

    work page doi:10.1109/mcse.2007.55 2007

  19. [19]

    D., Pignatari, M., Stancliffe, R

    Keegans, J. D., Pignatari, M., Stancliffe, R. J., et al. 2023, ApJS, 268, 8, doi: 10.3847/1538-4365/ace102

    work page doi:10.3847/1538-4365/ace102 2023

  20. [20]

    I., & Lugaro, M

    Kobayashi, C., Karakas, A. I., & Lugaro, M. 2020a, ApJ, 900, 179, doi: 10.3847/1538-4357/abae65

    work page doi:10.3847/1538-4357/abae65

  21. [21]

    2020b, ApJ, 895, 138, doi: 10.3847/1538-4357/ab8e44

    Kobayashi, C., Leung, S.-C., & Nomoto, K. 2020b, ApJ, 895, 138, doi: 10.3847/1538-4357/ab8e44

    work page doi:10.3847/1538-4357/ab8e44

  22. [22]

    P., Sim, S

    Lach, F., Callan, F. P., Sim, S. A., & R¨ opke, F. K. 2022, A&A, 659, A27, doi: 10.1051/0004-6361/202142194

    work page doi:10.1051/0004-6361/202142194 2022

  23. [23]

    C., Chu, M

    Leung, S. C., Chu, M. C., & Lin, L. M. 2015, MNRAS, 454, 1238, doi: 10.1093/mnras/stv1923

    work page doi:10.1093/mnras/stv1923 2015

  24. [24]

    2018, ApJ, 861, 143, doi: 10.3847/1538-4357/aac2df

    Leung, S.-C., & Nomoto, K. 2018, ApJ, 861, 143, doi: 10.3847/1538-4357/aac2df

    work page doi:10.3847/1538-4357/aac2df 2018

  25. [25]

    2023, in The Sixteenth Marcel Grossmann Meeting

    Leung, S.-C., & Nomoto, K. 2023, in The Sixteenth Marcel Grossmann Meeting. On Recent Developments in Theoretical and Experimental General Relativity, Astrophysics, and Relativistic Field Theories, ed. R. Ruffino & G. Vereshchagin, 4427–4446, doi: 10.1142/9789811269776 0374 —. 2024, ApJ, 974, 310, doi: 10.3847/1538-4357/ad6ddb

    work page doi:10.1142/9789811269776 2023

  26. [26]

    2025, ApJ, 990, 207, doi: 10.3847/1538-4357/adf430

    Leung, S.-C., Nomoto, K., & Simionescu, A. 2025, ApJ, 990, 207, doi: 10.3847/1538-4357/adf430

    work page doi:10.3847/1538-4357/adf430 2025

  27. [27]

    2023, ApJ, 948, 80, doi: 10.3847/1538-4357/acbdf5

    Leung, S.-C., Nomoto, K., & Suzuki, T. 2023, ApJ, 948, 80, doi: 10.3847/1538-4357/acbdf5

    work page doi:10.3847/1538-4357/acbdf5 2023

  28. [28]

    2021, ApJ, 923, 41, doi: 10.3847/1538-4357/ac2c63

    Leung, S.-C., Wu, S., & Fuller, J. 2021, ApJ, 923, 41, doi: 10.3847/1538-4357/ac2c63

    work page doi:10.3847/1538-4357/ac2c63 2021

  29. [29]

    2018, ApJS, 237, 13, doi: 10.3847/1538-4365/aacb24

    Limongi, M., & Chieffi, A. 2018, ApJS, 237, 13, doi: 10.3847/1538-4365/aacb24

    work page doi:10.3847/1538-4365/aacb24 2018

  30. [30]

    R., Schiavon, R

    Majewski, S. R., Schiavon, R. P., Frinchaboy, P. M., et al. 2017, AJ, 154, 94, doi: 10.3847/1538-3881/aa784d

    work page doi:10.3847/1538-3881/aa784d 2017

  31. [31]

    2012, Chemical Evolution of Galaxies, doi: 10.1007/978-3-642-22491-1

    Matteucci, F. 2012, Chemical Evolution of Galaxies, doi: 10.1007/978-3-642-22491-1

    work page doi:10.1007/978-3-642-22491-1 2012

  32. [32]

    2016, in Journal of Physics Conference Series, Vol

    Matteucci, F. 2016, in Journal of Physics Conference Series, Vol. 703, Journal of Physics Conference Series (IOP), 012004, doi: 10.1088/1742-6596/703/1/012004

    work page doi:10.1088/1742-6596/703/1/012004 2016

  33. [33]

    2009, A&A, 501, 531, doi: 10.1051/0004-6361/200911869 16 Mor´ an-Fraile, J., Holas, A., R¨ opke, F

    Matteucci, F., Spitoni, E., Recchi, S., & Valiante, R. 2009, A&A, 501, 531, doi: 10.1051/0004-6361/200911869 16 Mor´ an-Fraile, J., Holas, A., R¨ opke, F. K., Pakmor, R., &

    work page doi:10.1051/0004-6361/200911869 2009

  34. [34]

    Schneider, F. R. N. 2024, A&A, 683, A44, doi: 10.1051/0004-6361/202347769

    work page doi:10.1051/0004-6361/202347769 2024

  35. [35]

    A., Kajino, T., et al

    Mori, K., Famiano, M. A., Kajino, T., et al. 2018, ApJ, 863, 176, doi: 10.3847/1538-4357/aad233

    work page doi:10.3847/1538-4357/aad233 2018

  36. [36]

    J., Groh, J

    Murphy, L. J., Groh, J. H., Ekstr¨ om, S., et al. 2021, MNRAS, 501, 2745, doi: 10.1093/mnras/staa3803

    work page doi:10.1093/mnras/staa3803 2021

  37. [37]

    C., & Hillebrandt, W

    Niemeyer, J. C., & Hillebrandt, W. 1995, ApJ, 452, 769, doi: 10.1086/176345

    work page doi:10.1086/176345 1995

  38. [38]

    1988, PhR, 163, 13, doi: 10.1016/0370-1573(88)90032-4

    Nomoto, K., & Hashimoto, M. 1988, PhR, 163, 13, doi: 10.1016/0370-1573(88)90032-4

    work page doi:10.1016/0370-1573(88)90032-4 1988

  39. [39]

    2013, ARA&A, 51, 457, doi: 10.1146/annurev-astro-082812-140956

    Nomoto, K., Kobayashi, C., & Tominaga, N. 2013, ARA&A, 51, 457, doi: 10.1146/annurev-astro-082812-140956

    work page doi:10.1146/annurev-astro-082812-140956 2013

  40. [40]

    2018, SSRv, 214, 67, doi: 10.1007/s11214-018-0499-0

    Nomoto, K., & Leung, S.-C. 2018, SSRv, 214, 67, doi: 10.1007/s11214-018-0499-0

    work page doi:10.1007/s11214-018-0499-0 2018

  41. [41]

    K., & Yokoi, K

    Nomoto, K., Thielemann, F. K., & Yokoi, K. 1984, ApJ, 286, 644, doi: 10.1086/162639

    work page doi:10.1086/162639 1984

  42. [42]

    2021, ApJL, 913, L34, doi: 10.3847/2041-8213/abff5b

    Ohshiro, Y., Yamaguchi, H., Leung, S.-C., et al. 2021, ApJL, 913, L34, doi: 10.3847/2041-8213/abff5b

    work page doi:10.3847/2041-8213/abff5b 2021

  43. [43]

    2013, ApJL, 770, L8, doi: 10.1088/2041-8205/770/1/L8 pandas development team, T

    Pakmor, R., Kromer, M., Taubenberger, S., & Springel, V. 2013, ApJL, 770, L8, doi: 10.1088/2041-8205/770/1/L8 pandas development team, T. 2020, pandas-dev/pandas: Pandas, latest, Zenodo, doi: 10.5281/zenodo.3509134

    work page doi:10.1088/2041-8205/770/1/l8 2013

  44. [44]

    2011, The Astrophysical Journal Supplement Series, 192, 3, doi: 10.1088/0067-0049/192/1/3

    Paxton, B., Bildsten, L., Dotter, A., et al. 2011, ApJS, 192, 3, doi: 10.1088/0067-0049/192/1/3

    work page doi:10.1088/0067-0049/192/1/3 2011

  45. [45]

    2013, The Astrophysical Journal Supplement Series, 208, 4, doi: 10.1088/0067-0049/208/1/4

    Paxton, B., Cantiello, M., Arras, P., et al. 2013, ApJS, 208, 4, doi: 10.1088/0067-0049/208/1/4

    work page internal anchor Pith review doi:10.1088/0067-0049/208/1/4 2013

  46. [46]

    2015, The Astrophysical Journal Supplement Series, 220, 15, doi: 10.1088/0067-0049/220/1/15

    Paxton, B., Marchant, P., Schwab, J., et al. 2015, ApJS, 220, 15, doi: 10.1088/0067-0049/220/1/15

    work page internal anchor Pith review doi:10.1088/0067-0049/220/1/15 2015

  47. [47]

    B., et al

    Paxton, B., Schwab, J., Bauer, E. B., et al. 2018, ApJS, 234, 34, doi: 10.3847/1538-4365/aaa5a8

    work page doi:10.3847/1538-4365/aaa5a8 2018

  48. [48]

    2019, The Astrophysical Journal Supplement Series, 243, 10, doi: 10.3847/1538-4365/ab2241

    Paxton, B., Smolec, R., Schwab, J., et al. 2019, ApJS, 243, 10, doi: 10.3847/1538-4365/ab2241

    work page doi:10.3847/1538-4365/ab2241 2019

  49. [49]

    2004, ApJ, 612, 168, doi: 10.1086/422498

    Pietrinferni, A., Cassisi, S., Salaris, M., & Castelli, F. 2004, ApJ, 612, 168, doi: 10.1086/422498

    work page doi:10.1086/422498 2004

  50. [50]

    2016, ApJS, 225, 24, doi: 10.3847/0067-0049/225/2/24

    Pignatari, M., Herwig, F., Hirschi, R., et al. 2016, ApJS, 225, 24, doi: 10.3847/0067-0049/225/2/24

    work page doi:10.3847/0067-0049/225/2/24 2016

  51. [51]

    2021, ApJ, 906, 65, doi: 10.3847/1538-4357/abcccc

    Polin, A., Nugent, P., & Kasen, D. 2021, ApJ, 906, 65, doi: 10.3847/1538-4357/abcccc

    work page doi:10.3847/1538-4357/abcccc 2021

  52. [52]

    R., Tout, C

    Pols, O. R., Tout, C. A., Eggleton, P. P., & Han, Z. 1995, MNRAS, 274, 964, doi: 10.1093/mnras/274.3.964

    work page doi:10.1093/mnras/274.3.964 1995

  53. [53]

    F., & Fryer, C

    Ritter, C., Cˆ ot´ e, B., Herwig, F., Navarro, J. F., & Fryer, C. L. 2018a, ApJS, 237, 42, doi: 10.3847/1538-4365/aad691

    work page doi:10.3847/1538-4365/aad691

  54. [54]

    2018b, MNRAS, 480, 538, doi: 10.1093/mnras/sty1729

    Ritter, C., Herwig, F., Jones, S., et al. 2018b, MNRAS, 480, 538, doi: 10.1093/mnras/sty1729

    work page doi:10.1093/mnras/sty1729

  55. [55]

    2024, ApJS, 272, 15, doi: 10.3847/1538-4365/ad391d

    Roberti, L., Limongi, M., & Chieffi, A. 2024, ApJS, 272, 15, doi: 10.3847/1538-4365/ad391d

    work page doi:10.3847/1538-4365/ad391d 2024

  56. [56]

    E., et al

    Roberti, L., Pignatari, M., Brinkman, H. E., et al. 2025, A&A, 698, A216, doi: 10.1051/0004-6361/202554461

    work page doi:10.1051/0004-6361/202554461 2025

  57. [57]

    2010, , 405, 1025, 10.1111/j.1365-2966.2010.16486.x

    Seitenzahl, I. R., R¨ opke, F. K., Fink, M., & Pakmor, R. 2010, MNRAS, 407, 2297, doi: 10.1111/j.1365-2966.2010.17106.x

    work page doi:10.1111/j.1365-2966.2010.17106.x 2010

  58. [58]

    R., Ciaraldi-Schoolmann, F., R¨ opke, F

    Seitenzahl, I. R., Ciaraldi-Schoolmann, F., R¨ opke, F. K., et al. 2013, MNRAS, 429, 1156, doi: 10.1093/mnras/sts402

    work page doi:10.1093/mnras/sts402 2013

  59. [59]

    J., Kasen, D., Miles, B

    Shen, K. J., Kasen, D., Miles, B. J., & Townsley, D. M. 2018, ApJ, 854, 52, doi: 10.3847/1538-4357/aaa8de

    work page doi:10.3847/1538-4357/aaa8de 2018

  60. [60]

    2019, MNRAS, 483, 1701, doi: 10.1093/mnras/sty3220

    Simionescu, A., Nakashima, S., Yamaguchi, H., et al. 2019, MNRAS, 483, 1701, doi: 10.1093/mnras/sty3220

    work page doi:10.1093/mnras/sty3220 2019

  61. [61]

    J., Zwaan , M

    Stancliffe, R. J., Tout, C. A., & Pols, O. R. 2004, MNRAS, 352, 984, doi: 10.1111/j.1365-2966.2004.07987.x

    work page doi:10.1111/j.1365-2966.2004.07987.x 2004

  62. [62]

    Janka, H. T. 2016, ApJ, 821, 38, doi: 10.3847/0004-637X/821/1/38

    work page doi:10.3847/0004-637x/821/1/38 2016

  63. [63]

    2016, in Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, Vol

    Takahashi, T., Kokubun, M., Mitsuda, K., et al. 2016, in Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, Vol. 9905, Space Telescopes and Instrumentation 2016: Ultraviolet to Gamma Ray, ed. J.-W. A. den Herder, T. Takahashi, & M. Bautz, 99050U, doi: 10.1117/12.2232379

    work page doi:10.1117/12.2232379 2016

  64. [64]

    X., Woosley, S

    Timmes, F. X., Woosley, S. E., & Weaver, T. A. 1995, ApJS, 98, 617, doi: 10.1086/192172

    work page doi:10.1086/192172 1995

  65. [65]

    2009, ApJ, 690, 526, doi: 10.1088/0004-637X/690/1/526

    Tominaga, N. 2009, ApJ, 690, 526, doi: 10.1088/0004-637X/690/1/526

    work page doi:10.1088/0004-637x/690/1/526 2009

  66. [66]

    2007, ApJ, 660, 516, doi: 10.1086/513063

    Tominaga, N., Umeda, H., & Nomoto, K. 2007, ApJ, 660, 516, doi: 10.1086/513063

    work page doi:10.1086/513063 2007

  67. [67]

    M., Miles, B

    Townsley, D. M., Miles, B. J., Timmes, F. X., Calder, A. C., & Brown, E. F. 2016, ApJS, 225, 3, doi: 10.3847/0067-0049/225/1/3

    work page doi:10.3847/0067-0049/225/1/3 2016

  68. [68]

    Thielemann, F. K. 2004, A&A, 425, 1029, doi: 10.1051/0004-6361:20041108

    work page doi:10.1051/0004-6361:20041108 2004

  69. [69]

    2000, in The First Stars, ed

    Umeda, H., Nomoto, K., & Nakamura, T. 2000, in The First Stars, ed. A. Weiss, T. G. Abel, & V. Hill, 150, doi: 10.1007/10719504 27

    work page doi:10.1007/10719504 2000

  70. [70]

    A., Zimmerman, G

    Weaver, T. A., Zimmerman, G. B., & Woosley, S. E. 1978, ApJ, 225, 1021, doi: 10.1086/156569

    work page doi:10.1086/156569 1978

  71. [71]

    2022, ApJ, 924, 119, doi: 10.3847/1538-4357/ac308d

    Weng, J., Zhou, P., Chen, Y., et al. 2022, ApJ, 924, 119, doi: 10.3847/1538-4357/ac308d

    work page doi:10.3847/1538-4357/ac308d 2022

  72. [72]

    E., & Heger, A

    Woosley, S. E., & Heger, A. 2006, ApJ, 637, 914, doi: 10.1086/498500

    work page doi:10.1086/498500 2006

  73. [73]

    E., Heger, A., & Weaver, T

    Woosley, S. E., Heger, A., & Weaver, T. A. 2002, Reviews of Modern Physics, 74, 1015, doi: 10.1103/RevModPhys.74.1015

    work page doi:10.1103/revmodphys.74.1015 2002

  74. [74]

    E., & Weaver, T

    Woosley, S. E., & Weaver, T. A. 1994, ApJ, 423, 371, doi: 10.1086/173813 —. 1995, ApJS, 101, 181, doi: 10.1086/192237 17

    work page doi:10.1086/173813 1994

  75. [75]

    2021, ApJ, 906, 3, doi: 10.3847/1538-4357/abc87c

    Wu, S., & Fuller, J. 2021, ApJ, 906, 3, doi: 10.3847/1538-4357/abc87c

    work page doi:10.3847/1538-4357/abc87c 2021

  76. [76]

    2022, MNRAS, 511, 2814, doi: 10.1093/mnras/stac230 18

    Yusof, N., Hirschi, R., Eggenberger, P., et al. 2022, MNRAS, 511, 2814, doi: 10.1093/mnras/stac230 18

    work page doi:10.1093/mnras/stac230 2022