Pith. sign in

REVIEW 3 major objections 6 minor 93 references

Physics-driven Explosions of Stripped High-Mass Stars: Synthetic Light Curves and Spectra of Stripped-Envelope Supernovae with Broad Lightcurves

T0 review · 3 major / 6 minor · reviewed 2026-08-12 · deepseek-v4-flash

Pith's one-line read High-mass stripped-star explosions reveal that the standard rise-time formula overestimates ejecta mass by up to 2.6 times, while calibrated late-time tails stay within 20 percent in range.

desk verdict First public grid of physics-driven high-mass stripped-star explosions; the headline mass-bias factor is real but rides on an imposed nickel/mixing prescription, and the abstract overstates light-curve agreement. read the letter →

arxiv 2411.11000 v3 pith:OOIKPGKZ submitted 2024-11-17 astro-ph.HE astro-ph.SR

classification astro-ph.HEastro-ph.SR
keywords stripped-envelopesupernovaeWolf-Rayetprogenitorsradiativetransfersimulationssyntheticbolometriclightcurvesejectamassestimationheliumspectraldiagnosticsneutrino-drivenexplosionsnickel-56mixing
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

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

The reading

This paper uses radiative-transfer simulations to turn physics-driven neutrino explosions of six massive Wolf-Rayet stars into synthetic supernova light curves and spectra. It finds that the explosions with high ejecta masses (4–11 solar masses) produce light-curve shapes matching observed stripped-envelope supernovae with broad light curves, but their peak luminosities fall below the observed range. The paper then tests the analytic formulas observers use to infer ejecta mass from light curves: the standard rise-time formula overestimates the true ejecta mass by up to a factor of 2.6 for these high-mass explosions, while a calibratable late-time tail method stays within about 20% inside its calibrated range. It also finds that the near-infrared helium line at 1.083 microns appears even when only 0.02 solar masses of helium remains, so line presence cannot directly measure helium mass. Realistic helium features, the paper argues, require full radiative-transfer modeling for each explosion because line strength depends on nickel distribution, composition, and the radiation field.

What carries the argument

The machinery is a sequential pipeline: stellar evolution of solar-metallicity Wolf-Rayet stars, a turbulence-aided neutrino-driven explosion that supplies self-consistent energy and remnant mass, a one-dimensional radiation-hydrodynamics code that produces the bolometric light curves, and a Monte Carlo radiative-transfer code that synthesizes spectra. The test instruments are the analytic ejecta-mass estimators applied to the synthetic light curves, namely the rise-time formula, the raw late-time tail formula, and a late-time formula calibrated on lower-mass binary-stripped progenitors. Throughout, the fixed inputs of 0.07 solar masses of nickel-56 mixed out to 60 percent of the ejecta set the peak luminosity, rise time, and late-time tail, as well as the radiation field that drives helium line formation.

What would settle it

Compute the same six explosions with a nuclear-reaction network (or with nickel masses varied across the plausible range, e.g., 0.03 to 0.15 solar masses) and compare the resulting light curves with observed broad SESNe; if the models then match the observed peak luminosities, the claim that high-mass Wolf-Rayet progenitors are too faint falls. Alternatively, apply the rise-time and late-time formulas to a set of real SESNe with independent ejecta-mass measurements; if rise-time masses do not systematically exceed tail masses, the claimed 2.6-fold overestimate does not generalize.

Watch

Extended reading notes

Core claim

On its own terms, the paper claims that a self-consistent chain from stellar evolution to neutrino-driven explosion to radiative transfer shows that stripped high-mass Wolf-Rayet stars are viable progenitors of the broad-lightcurve subclass of stripped-envelope supernovae, but only for light-curve shape, not for peak brightness. The same chain exposes a systematic flaw in a widely used estimator: applying the standard rise-time formula to these models overestimates ejecta mass by 80% to 160% (up to a factor 2.6), because the assumed constant opacity and the rise-time measurement do not capture the physics of these extended, faint explosions. A late-time decay-tail estimator calibrated on lower-mass progenitors performs much better, with average uncertainties near 20%, provided the true ejecta mass lies inside its calibrated range; outside that range, as in the most massive model, it underestimates the ejecta mass by about 70%. Spectroscopically, the paper establishes that helium features are not a simple mass meter: the He I 1.083 micron line is saturated even at 0.02 solar masses of helium, and the optical helium lines are controlled by the radiation field, nickel distribution, and mixing rather than helium abundance alone.

Load-bearing premise

The whole comparison rests on the fixed assumption that every explosion produces 0.07 solar masses of nickel-56 mixed out to 60 percent of the ejecta, because the explosion and light-curve codes do not track nuclear burning; if the real nickel yield or mixing differs, the peak luminosities, rise times, tails, and helium-line strengths would all shift.

Editorial extensions

If this is right

  • If these models represent real high-mass stripped explosions, then published ejecta masses for broad-lightcurve SESNe derived from rise-time formulas are systematically too high, by as much as a factor of 2.6.
  • The calibrated late-time tail method can be trusted to roughly 20 percent only when the true ejecta mass is within its lower-mass calibration range; applying it to a ~10.85-solar-mass ejecta underestimates the mass by about 70 percent.
  • High-initial-mass Wolf-Rayet explosions produce broad, faint light curves, so they cannot by themselves explain the typical bright stripped-envelope supernovae; extra power sources (or lower-mass progenitors) are needed for the normal population.
  • A strong He I 1.083 micron line cannot be used to infer helium abundance, since even 0.02 solar masses of helium saturates the feature, so Type Ib/Ic classification by near-infrared helium alone is unreliable.
  • Optical helium-line strength is set by nickel distribution, composition, and radiation field, so each new hydrodynamic model requires its own radiative-transfer calculation before helium content can be interpreted.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • If the 2.6-fold rise-time bias is real, correcting observed samples of broad-lined SESNe with late-time methods could shift their inferred ejecta masses down, potentially reducing the apparent need for very massive progenitors.
  • Because the nickel mass is fixed, the 'too faint' peak luminosity is a conditional result: models with a self-consistent or larger nickel yield might land inside the observed luminosity range, which would make high-mass single-star progenitors more attractive.
  • The saturated near-infrared helium line implies that NIR classification alone cannot distinguish helium-poor from helium-rich events; pairing NIR spectra with optical helium lines and full radiative-transfer fits is a testable route to hidden-helium constraints.
  • The paper's comparison suggests a clean observational test: measure both rise-time and late-time ejecta masses for a sample of broad SESNe; if the rise-time values systematically exceed the tail values, the bias claimed here is present in real data.
Share X Bluesky LinkedIn Reddit HN

Signed reviews

No signed human review yet.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

3 major / 6 minor

Summary. The paper presents synthetic bolometric light curves and optical/NIR spectral time series for six stripped-envelope supernova models derived from solar-metallicity, non-rotating Wolf-Rayet progenitors with MZAMS = 45-120 Msun. The progenitors are evolved with KEPLER, exploded with the neutrino-driven STIR/FLASH framework, and post-processed with SNEC and TARDIS. The main results are: (1) the models are broad and faint compared to the typical SESN population, marginally resembling observed broad-LC SESNe; (2) the Wheeler et al. (2015) rise-time-based ejecta mass estimator overestimates the true ejecta mass by up to a factor 2.6, while the Haynie & Piro (2023) calibrated tail method is accurate to ~20% within its calibrated mass range but underestimates high-mass models; and (3) He I lines, especially 1.083 um, persist even with 0.02 Msun of helium, so He line strength is not a simple mass indicator. The authors provide public data on Zenodo and explicitly discuss the main caveats, including the fixed 56Ni mass/mixing and the approximate helium treatment.

Significance. The modeling pipeline is state-of-the-art and the paper provides a valuable public set of self-consistent explosion-to-spectra models for high-mass stripped progenitors. Its main strength is the direct test of widely used analytic ejecta-mass estimators against physics-driven explosion simulations, and the explicit, repeated acknowledgment of the fixed inputs (56Ni mass of 0.07 Msun, 60% mixing, SNEC opacity floor) and the recomb-NLTE helium approximation. If the headline overestimate factor (up to 2.6) is robust to variations in these inputs, the result would be an important caution for the SESN community. The helium-line persistence result, if confirmed with more detailed NLTE treatment, would support and extend Teffs et al. (2020) and Williamson et al. (2021). However, the quantitative claims are currently presented without a sensitivity analysis of the key imposed parameters, which limits the strength of the conclusions.

major comments (3)
  1. [Section 3.3, Figure 5] The central quantitative claim that the Wheeler et al. (2015) rise-time method overestimates ejecta mass by a factor up to 2.6 is not robust to the imposed 56Ni mixing and opacity floor. Section 3.2 and Figure 4 show that the rise time is shortened by tens of days when 56Ni is fully mixed, and Section 3.3 itself notes that the SNEC opacity floor was calibrated for SNe II and may be too high for SESNe. Since both the 0.07 Msun 56Ni mass and the 60% mixing mass cut are fixed inputs (Section 2.3, Table 1) rather than outputs of the explosion model, the 1.8-2.6x range in Figure 5 reflects one prescription. Please quantify the sensitivity of the inferred Mej ratios to (a) the mixing fraction (e.g., using the fully mixed cases already shown in Fig. 4) and (b) a lower opacity floor, or explicitly state that the claim is conditional on the fiducial prescription. This is load-bearing because the abstract and conclusion present the overestimate as a general property of high-initial-mass progenitors.
  2. [Abstract vs Section 3.2] The abstract states that the light curve shape 'is consistent with observed SESNe with broad light curves,' but Section 3.2 says the rise/decline rates 'marginally resemble' those of observed broad-LC SESNe. Because the comparison sample is the anchor for the astrophysical relevance of the models, the wording should be aligned. Either strengthen the quantitative comparison (e.g., show the distribution of t-1/2 and t+1/2 for the observed sample and the models, with uncertainties) or soften the abstract claim. As written, the overstatement could mislead readers about the degree of agreement.
  3. [Section 3.3, Table 3 and Figure 5] The abstract's claim that the Haynie & Piro (2023) method 'reduces uncertainties to an average of 20% within the calibrated ejecta mass range' is supported only by a visual inspection of Figure 5 for five models sharing the same 56Ni input. Please list the inferred masses and the individual ratios for the Mej < 5 Msun models, state the number of models used, and clarify whether the 20% is a mean or median absolute deviation. This is load-bearing because the conclusion encourages use of the H23 method.
minor comments (6)
  1. [Section 2.3] There are several typos in the text; for example, 'descrisd' should be 'described' and 'Hmma,rize' appears to be garbled for 'summarize'. Please proofread the manuscript.
  2. [Section 3.3] In Section 3.3, 'approxiamated' should be 'approximated'.
  3. [Section 2.4] In Section 2.4, 'Marto Carlo' should be 'Monte Carlo'.
  4. [Table 1] The footnote b gives MFallBack = 1.518 and 0.366 Msun, while the text in Section 3.3 gives 1.52 and 0.37 Msun; please make the precision consistent.
  5. [Figure 4] In Figure 4, the label 'MZAM S' is missing an underscore and should read 'MZAMS'.
  6. [Section 3.5 and Abstract] The He I 1.083 um persistence claim should be accompanied in the abstract or conclusion by the caveat that the recomb-NLTE approximation may overestimate NIR He lines; the paper already states this in Section 3.5, but the abstract and conclusion do not reflect it.

Circularity Check

0 steps flagged · score 0.0 of 10

No circularity found: the central claims are tested against externally published analytic formulas, and the fixed explosion inputs (56Ni mass/mixing, opacity settings) are explicitly disclosed as caveats rather than fitted targets.

full rationale

This manuscript is a forward-modeling study. Fixed progenitor and explosion inputs from Sukhbold et al. (2016) and Couch et al. (2020), together with an adopted 56Ni mass of 0.07 M_sun mixed to 60% of the ejecta, are evolved with SNEC and TARDIS, and the resulting synthetic observables are compared with external analytic ejecta-mass estimators (Wheeler et al. 2015; Haynie & Piro 2023). I find no step in the derivation chain where a prediction is equivalent to an input by definition. The rise-time-based mass overestimate is not fitted to the observed light curves; it follows from the simulated rise time and photospheric velocity inserted into an independently published formula with fixed constants. The sensitivity of the rise time to 56Ni mixing and to the SNEC opacity floor is explicitly documented in Sections 3.2 and 3.3, so the result is caveated rather than concealed. The Haynie & Piro (2023) tail method agrees within 20% only inside that paper's own 2-5 M_sun calibration range, and the manuscript states this limitation; no constant from that method is refit here. Self-citations to Couch et al. (2020) and Barker et al. (2022) supply predecessor simulation stages and methodology, but they are published, code-based prior work with stated assumptions and do not function as an unverified uniqueness theorem or as a fitted input renamed as a prediction. The helium-feature conclusions also depend on the stated 56Ni input, and that dependence is acknowledged in Sections 3.1 and 3.5. Overall, the paper's load-bearing comparisons are not circular; the main limitations are model-input sensitivities, which are openly discussed.

Assumptions & free parameters 3 free parameters · 6 assumptions · 0 invented entities

The paper introduces no new particles or forces. The central claims rest on fixed simulation inputs (56Ni mass and mixing, opacity floor), domain assumptions inherited from prior simulation frameworks, and approximations in the helium treatment. These are clearly stated in the text and do not reduce to fitting the target results.

free parameters (3)
  • 56Ni mass = 0.07 M_sun
    Fixed input for all models, adopted from Sukhbold et al. (2016) synthesis values, not derived from the explosion simulations. It sets the peak luminosity and late-time tail, directly affecting the ejecta mass comparison and He line strengths.
  • 56Ni mixing fraction = 60% of ejecta mass
    Chosen mixing degree for 56Ni in SNEC, kept fixed except in Fig. 4 where it is varied. It affects the rise time and the radiation field that drives He line formation.
  • SNEC opacity floor = 0.24 cm2/g (core), 0.01 cm2/g (envelope)
    Adopted from the Bersten et al. (2011) calibration for SNe II; the authors note it may be too high for SESNe, which contributes to the rise time and inferred ejecta mass.
assumptions (6)
  • domain assumption The turbulence-aided neutrino-driven explosion models of Couch et al. (2020) with alpha_Lambda=1.25 are representative of real SN explosions of these progenitors.
    The entire pipeline depends on the explosion energies and remnant masses from C20. The authors note the explosions are 1D and use a mixing-length prescription calibrated to 3D simulations.
  • domain assumption The asymptotic explosion energy can be estimated analytically from the STIR output because the simulations are terminated at 15,000 km before energy convergence.
    Section 2.2; the average energy difference between STIR output and estimated asymptotic value is 0.2x10^51 erg. This affects the light curve shape and ejecta mass.
  • domain assumption The inner shocked region can be approximated as pure helium for SNEC light curve calculations, and pure oxygen for TARDIS spectra.
    Section 2.3 and 2.4; justified by negligible effect on bolometric light curves (Barker et al. 2022), but it affects the spectra and He line strengths.
  • domain assumption The recomb-NLTE approximation for helium in TARDIS (Boyle et al. 2017) is valid for these SESNe models, assuming He II ground state dominates.
    Section 2.4 and 3.5; the authors note it may overestimate He line strengths, especially the 2.058 um line, and is being applied beyond its originally tested regime.
  • domain assumption The mass-loss prescription of Sukhbold et al. (2016) (Nieuwenhuijzen & de Jager 1990 plus Wellstein & Langer 1999) produces realistic WR progenitors for these masses.
    Section 3.1; the authors note this mass loss is stronger than common recent prescriptions, affecting the progenitor structure and He content.
  • domain assumption Spherical symmetry (1D) is sufficient for light curve and spectral formation in this context.
    All simulations are 1D; the authors mention mixing is approximated by boxcar smoothing and fixed Ni mixing.

how reviews work

0 comments
Cite this review

Pith. "Pith review of Physics-driven Explosions of Stripped High-Mass Stars: Synthetic Light Curves and Spectra of Stripped-Envelope Supernovae with Broad Lightcurves." pith.science (2026). https://pith.science/paper/OOIKPGKZ

@misc{pith2026241111000,
  author       = {Pith},
  title        = {Pith review of: Physics-driven Explosions of Stripped High-Mass Stars: Synthetic Light Curves and Spectra of Stripped-Envelope Supernovae with Broad Lightcurves},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/OOIKPGKZ}},
  note         = {Machine review of arXiv:2411.11000}
}
read the original abstract

Stripped-envelope supernovae (SESNe) represent a significant fraction of core-collapse supernovae, arising from massive stars that have shed their hydrogen and, in some cases, helium envelopes. The origins and explosion mechanisms of SESNe remain a topic of active investigation. In this work, we employ radiative-transfer simulations to model the light curves and spectra of a set of explosions of single, solar-metallicity, massive Wolf-Rayet (WR) stars with ejecta masses ranging from 4 to 11 Msun, that were computed from a turbulence-aided and neutrino-driven explosion mechanism. We analyze these synthetic observables to explore the impact of varying ejecta mass and helium content on observable features. We find that the light curve shape of these progenitors with high ejecta masses is consistent with observed SESNe with broad light curves but not the peak luminosities. The commonly used analytic formula based on rising bolometric light curves overestimates the ejecta mass of these high-initial-mass progenitor explosions by a factor up to 2.6. In contrast, the calibrated method by Haynie et al., which relies on late-time decay tails, reduces uncertainties to an average of 20% within the calibrated ejecta mass range.Spectroscopically, the He I 1.083 um line remains prominent even in models with as little as 0.02 Msun of helium. However, the strength of the optical He I lines is not directly proportional to the helium mass but instead depends on a complex interplay of factors such as 56Ni distribution, composition, and radiation field. Thus, producing realistic helium features requires detailed radiative transfer simulations for each new hydrodynamic model.

Figures

Figures reproduced from arXiv: 2411.11000 by the authors.

Figure 1
Figure 1. The numerical methods flow chart of the four sequential simulation stages. The grey arrows and corresponding texts indicate the simulation inputs. The utilized code and reference for each stage are marked below. Note that all simulations are performed in 1D. time of explosion relevant for determining SNe prop￾erties are not monotonic in MZAMS. The final radius (Rpre-SN), mass (Mpre-SN), and remaining helium mass (MH… view at source ↗
Figure 2
Figure 2. Composition and velocity profiles of the models in mass coordinates. The grey region on the left side of each subplot indicates the stir computation domain, where the snec input unmixed composition (marked with dotted lines) is replaced with pure He. The snec boxcar-smoothed composition is plotted with solid lines. For TARDIS input composition, the inner pure He is replaced with pure O before the smoothing process, … view at source ↗
Figure 4
Figure 4. The snec bolometric light curves of models with varying 56Ni mixing percentage (relative to the total ejecta mass in mass coordinate). The light curves of the same set of progenitors exploded in Sukhbold et al. (2016) are plotted for comparison, except the MZAMS = 45 M⊙ model, which did not explode in their work. The dotted black and grey lines are thermalized heating energy rates from radioactive decay of 56Ni = 0.… view at source ↗
Figures from the paper (4 more)
Figure 5
Figure 5. Figure 5: The ratio of the inferred ejecta mass from bolo￾metric light curves and the model ejecta mass from simula￾tion. The inferred ejecta masses are based on the analytical models summarized in Wheeler et al. (2015) and Haynie & Piro (2023). The error bars on the ejecta mass…
Figure 6
Figure 6. Figure 6: tardis spectral time series of MZAMS = 45, 60, 80, 120 M⊙ model. Spectra are color-coded with time relative to the explosion. The vertical dark gray lines mark the strong He lines in the restframe. absorption feature presenting around 1 µm that can be contributed by ot…
Figure 7
Figure 7. Figure 7: tardis spectral comparison at fixed phases relative to the explosion date (left column) or the bolometric light curve peak (right column). On the top row, the bolometric light curves are plotted for reference purposes with the corresponding time reference as the column…
Figure 8
Figure 8. Figure 8: tardis elemental deposition plot of MZAMS = 45 M⊙ (top panels) and 120 M⊙ (bottom panels) model at 20 (left panels) and 60 (right panels) days. The colored patches are the cumulated wavelength distribution of energy packets before (indicated with negative flux) and aft…

Discussion (0). Continue with ORCID to comment.

Reference graph

Works this paper leans on

93 extracted references · 3 canonical work pages

  1. [1]

    R., Khatami, D

    Afsariardchi, N., Drout, M. R., Khatami, D. K., et al. 2021, ApJ, 918, 89, doi: 10.3847/1538-4357/ac0aeb

  2. [2]

    2023, A&A, 675, A201, doi: 10.1051/0004-6361/202244751

    Agudo, I., Amati, L., An, T., et al. 2023, A&A, 675, A201, doi: 10.1051/0004-6361/202244751

  3. [3]

    Anderson, J. P. 2019, A&A, 628, A7, doi: 10.1051/0004-6361/201935027

  4. [4]

    Z., de Wit, S., et al

    Antoniadis, K., Bonanos, A. Z., de Wit, S., et al. 2024, A&A, 686, A88, doi: 10.1051/0004-6361/202449383

  5. [5]

    Arnett, W. D. 1982, ApJ, 253, 785, doi: 10.1086/159681 Astropy Collaboration, Robitaille, T. P., Tollerud, E. J., et al. 2013, A&A, 558, A33, doi: 10.1051/0004-6361/201322068 4 https://zenodo.org/records/14343229 5 https://www.astropy.org/ 6 https://pandas.pydata.org/ 7 https://scipy.org/ 8 https://stellarcollapse.org/SNEC.html 9 https://github.com/tardis...

  6. [6]

    L., Harris, C

    Barker, B. L., Harris, C. E., Warren, M. L., O’Connor, E. P., & Couch, S. M. 2022, ApJ, 934, 67, doi: 10.3847/1538-4357/ac77f3

  7. [7]

    C., & Sarazin, C

    Begelman, M. C., & Sarazin, C. L. 1986, ApJL, 302, L59, doi: 10.1086/184637

  8. [8]

    C., Benvenuto, O., & Hamuy, M

    Bersten, M. C., Benvenuto, O., & Hamuy, M. 2011, ApJ, 729, 61, doi: 10.1088/0004-637X/729/1/61

Show all 93 references
  1. [9]

    C., Benvenuto, O

    Bersten, M. C., Benvenuto, O. G., Nomoto, K., et al. 2012, ApJ, 757, 31, doi: 10.1088/0004-637X/757/1/31

  2. [10]

    A., Hachinger, S., & Kerzendorf, W

    Boyle, A., Sim, S. A., Hachinger, S., & Kerzendorf, W. 2017, A&A, 599, A46, doi: 10.1051/0004-6361/201629712

  3. [11]

    Y., Endeve, E., & Mezzacappa, A

    Cardall, C. Y., Endeve, E., & Mezzacappa, A. 2013, PhRvD, 87, 103004, doi: 10.1103/PhysRevD.87.103004

  4. [12]

    Clocchiatti, A., & Wheeler, J. C. 1997, ApJ, 491, 375, doi: 10.1086/304961 16 Lu et al

  5. [13]

    Conti, P. S. 1975, Memoires of the Societe Royale des Sciences de Liege, 9, 193

  6. [14]

    M., Warren, M

    Couch, S. M., Warren, M. L., & O’Connor, E. P. 2020, ApJ, 890, 127, doi: 10.3847/1538-4357/ab609e

  7. [15]

    2021, ApJ, 921, 143, doi: 10.3847/1538-4357/ac0dc5

    Curtis, S., Wolfe, N., Fr¨ ohlich, C., et al. 2021, ApJ, 921, 143, doi: 10.3847/1538-4357/ac0dc5

  8. [18]

    J., Woosley, S., et al

    Dessart, L., Hillier, D. J., Woosley, S., et al. 2015, MNRAS, 453, 2189, doi: 10.1093/mnras/stv1747 —. 2016, MNRAS, 458, 1618, doi: 10.1093/mnras/stw418

  9. [19]

    Heuvel, E. P. J. 2002, MNRAS, 331, 1027, doi: 10.1046/j.1365-8711.2002.05257.x

  10. [20]

    2013, ApJ, 772, 30, doi: 10.1088/0004-637X/772/1/30

    Dexter, J., & Kasen, D. 2013, ApJ, 772, 30, doi: 10.1088/0004-637X/772/1/30

  11. [21]

    R., Soderberg, A

    Drout, M. R., Soderberg, A. M., Gal-Yam, A., et al. 2011, ApJ, 741, 97, doi: 10.1088/0004-637X/741/2/97

  12. [22]

    B., Weide, K., et al

    Dubey, A., Reid, L. B., Weide, K., et al. 2009, arXiv e-prints, arXiv:0903.4875, doi: 10.48550/arXiv.0903.4875

  13. [23]

    J., Izzard, R

    Eldridge, J. J., Izzard, R. G., & Tout, C. A. 2008, MNRAS, 384, 1109, doi: 10.1111/j.1365-2966.2007.12738.x

  14. [24]

    M., & Woosley, S

    Ensman, L. M., & Woosley, S. E. 1988, ApJ, 333, 754, doi: 10.1086/166785

  15. [25]

    E., Sukhbold, T., & Janka, H

    Ertl, T., Woosley, S. E., Sukhbold, T., & Janka, H. T. 2020, ApJ, 890, 51, doi: 10.3847/1538-4357/ab6458

  16. [26]

    2019, Nature Astronomy, 3, 434, doi: 10.1038/s41550-019-0710-6

    Gal-Yam, A. 2019, Nature Astronomy, 3, 434, doi: 10.1038/s41550-019-0710-6

  17. [27]

    E., Petermann, I., et al

    Farmer, R., Fields, C. E., Petermann, I., et al. 2016, ApJS, 227, 22, doi: 10.3847/1538-4365/227/2/22

  18. [28]

    2023, ApJ, 948, 111, doi: 10.3847/1538-4357/acc315

    Justham, S. 2023, ApJ, 948, 111, doi: 10.3847/1538-4357/acc315

  19. [29]

    Filippenko, A. V. 1997, ARA&A, 35, 309, doi: 10.1146/annurev.astro.35.1.309

  20. [30]

    2000, ApJS, 131, 273, doi: 10.1086/317361

    Fryxell, B., Olson, K., Ricker, P., et al. 2000, ApJS, 131, 273, doi: 10.1086/317361

  21. [31]

    2017, Observational and Physical Classification of Supernovae, ed

    Gal-Yam, A. 2017, Observational and Physical Classification of Supernovae, ed. A. W. Alsabti & P. Murdin (Cham: Springer International Publishing), 195–237, doi: 10.1007/978-3-319-21846-5 35

  22. [32]

    A., Taubenberger, S., et al

    Hachinger, S., Mazzali, P. A., Taubenberger, S., et al. 2012, MNRAS, 422, 70, doi: 10.1111/j.1365-2966.2012.20464.x

  23. [33]

    P., Wheeler, J

    Harkness, R. P., Wheeler, J. C., Margon, B., et al. 1987, ApJ, 317, 355, doi: 10.1086/165283

  24. [34]

    Haynie, A., & Piro, A. L. 2023, ApJ, 956, 98, doi: 10.3847/1538-4357/acf844

  25. [35]

    Hillier, D. J. 1991, A&A, 247, 455

  26. [36]

    1993, A&A, 268, 570

    Hoeflich, P., Mueller, E., & Khokhlov, A. 1993, A&A, 268, 570

  27. [37]

    2023, A&A, 678, A87, doi: 10.1051/0004-6361/202245231

    Karamehmetoglu, E., Sollerman, J., Taddia, F., et al. 2023, A&A, 678, A87, doi: 10.1051/0004-6361/202245231

  28. [38]

    2024, tardis-sn/tardis: TARDIS v2024.08.04, release-2024.08.04, Zenodo, doi: 10.5281/zenodo.13207705

    Kerzendorf, W., Sim, S., Vogl, C., et al. 2024, tardis-sn/tardis: TARDIS v2024.08.04, release-2024.08.04, Zenodo, doi: 10.5281/zenodo.13207705

  29. [39]

    E., & Sim, S

    Kerzendorf, W. E., & Sim, S. A. 2014, MNRAS, 440, 387, doi: 10.1093/mnras/stu055

  30. [40]

    1992, ApJ, 390, 602, doi: 10.1086/171311

    Kozma, C., & Fransson, C. 1992, ApJ, 390, 602, doi: 10.1086/171311

  31. [41]

    A., Williamson, M., Jha, S

    Kwok, L. A., Williamson, M., Jha, S. W., et al. 2022, ApJ, 937, 40, doi: 10.3847/1538-4357/ac8989

  32. [42]

    2021, A&A, 656, A58, doi: 10.1051/0004-6361/202140506

    Laplace, E., Justham, S., Renzo, M., et al. 2021, A&A, 656, A58, doi: 10.1051/0004-6361/202140506

  33. [44]

    Lucy, L. B. 1991, ApJ, 383, 308, doi: 10.1086/170787

  34. [45]

    D., Bersier, D., James, P

    Lyman, J. D., Bersier, D., James, P. A., et al. 2016, MNRAS, 457, 328, doi: 10.1093/mnras/stv2983

  35. [46]

    Podsiadlowski, P., & Gilmore, G. F. 2004, Nature, 427, 129, doi: 10.1038/nature02161 McKinney Wes. 2010, in Proceedings of the 9th Python in Science Conference, ed. St´ efan van der Walt & Jarrod Millman, 56 – 61, doi: 10.25080/Majora-92bf1922-00a

  36. [47]

    Mezzacappa, A., & Bruenn, S. W. 1993, ApJ, 405, 669, doi: 10.1086/172395

  37. [48]

    P., & Arcavi, I

    Modjaz, M., Guti´ errez, C. P., & Arcavi, I. 2019, Nature Astronomy, 3, 717, doi: 10.1038/s41550-019-0856-2

  38. [49]

    S., et al

    Modjaz, M., Kewley, L., Bloom, J. S., et al. 2011, ApJL, 731, L4, doi: 10.1088/2041-8205/731/1/L4

  39. [50]

    L., Renzo, M., & Ott, C

    Morozova, V., Piro, A. L., Renzo, M., & Ott, C. D. 2016, ApJ, 829, 109, doi: 10.3847/0004-637X/829/2/109

  40. [51]

    L., Renzo, M., et al

    Morozova, V., Piro, A. L., Renzo, M., et al. 2015, ApJ, 814, 63, doi: 10.1088/0004-637X/814/1/63

  41. [52]

    L., & Valenti, S

    Morozova, V., Piro, A. L., & Valenti, S. 2018, ApJ, 858, 15, doi: 10.3847/1538-4357/aab9a6

  42. [53]

    Nakar, E., & Piro, A. L. 2014, ApJ, 788, 193, doi: 10.1088/0004-637X/788/2/193

  43. [54]

    1990, A&A, 231, 134

    Nieuwenhuijzen, H., & de Jager, C. 1990, A&A, 231, 134

  44. [55]

    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

  45. [56]

    Nugis, T., & Lamers, H. J. G. L. M. 2000, A&A, 360, 227 O’Connor, E. 2015, ApJS, 219, 24, doi: 10.1088/0067-0049/219/2/24 Synthetic observables of stripped high-mass star explosions 17 O’Connor, E. P., & Couch, S. M. 2018, ApJ, 854, 63, doi: 10.3847/1538-4357/aaa893

  46. [57]

    2017, ApJ, 840, 90, doi: 10.3847/1538-4357/aa6ea9

    Ouchi, R., & Maeda, K. 2017, ApJ, 840, 90, doi: 10.3847/1538-4357/aa6ea9

  47. [58]

    1983, ApJ, 267, 315, doi: 10.1086/160870 pandas development team, T

    Paczynski, B. 1983, ApJ, 267, 315, doi: 10.1086/160870 pandas development team, T. 2020, pandas-dev/pandas: Pandas, latest, Zenodo, doi: 10.5281/zenodo.3509134

  48. [59]

    A., & Eastman, R

    Pinto, P. A., & Eastman, R. G. 2000, ApJ, 530, 757, doi: 10.1086/308380

  49. [60]

    L., Haynie, A., & Yao, Y

    Piro, A. L., Haynie, A., & Yao, Y. 2021, ApJ, 909, 209, doi: 10.3847/1538-4357/abe2b1

  50. [61]

    C., & Hsu, J

    Podsiadlowski, P., Joss, P. C., & Hsu, J. J. L. 1992, ApJ, 391, 246, doi: 10.1086/171341

  51. [62]

    J., Ashall, C., James, P

    Prentice, S. J., Ashall, C., James, P. A., et al. 2019, MNRAS, 485, 1559, doi: 10.1093/mnras/sty3399

  52. [63]

    2024, Research Notes of the American Astronomical Society, 8, 152, doi: 10.3847/2515-5172/ad530e

    Cantiello, M. 2024, Research Notes of the American Astronomical Society, 8, 152, doi: 10.3847/2515-5172/ad530e

  53. [64]

    D., Shore, S

    Renzo, M., Ott, C. D., Shore, S. N., & de Mink, S. E. 2017, A&A, 603, A118, doi: 10.1051/0004-6361/201730698 Rodr ´ ıguez,´O., Maoz, D., & Nakar, E. 2023, ApJ, 955, 71, doi: 10.3847/1538-4357/ace2bd Rodr ´ ıguez,´O., Nakar, E., & Maoz, D. 2024, Nature, 628, 733, doi: 10.1038/s...

  54. [65]

    1988, Nature, 334, 508, doi: 10.1038/334508a0

    Saio, H., Nomoto, K., & Kato, M. 1988, Nature, 334, 508, doi: 10.1038/334508a0

  55. [66]

    E., de Koter, A., et al

    Sana, H., de Mink, S. E., de Koter, A., et al. 2012, Science, 337, 444, doi: 10.1126/science.1223344

  56. [67]

    2023, arXiv e-prints, arXiv:2301.03610, doi: 10.48550/arXiv.2301.03610

    Sawada, R., & Suwa, Y. 2023, arXiv e-prints, arXiv:2301.03610, doi: 10.48550/arXiv.2301.03610

  57. [68]

    Schneider, F. R. N., Podsiadlowski, P., & M¨ uller, B. 2021, A&A, 645, A5, doi: 10.1051/0004-6361/202039219

  58. [69]

    Y., Ashall, C., et al

    Shahbandeh, M., Hsiao, E. Y., Ashall, C., et al. 2022, ApJ, 925, 175, doi: 10.3847/1538-4357/ac4030

  59. [70]

    2011, Progress of Theoretical Physics, 125, 1255, doi: 10.1143/PTP.125.1255

    Shibata, M., Kiuchi, K., Sekiguchi, Y., & Suwa, Y. 2011, Progress of Theoretical Physics, 125, 1255, doi: 10.1143/PTP.125.1255

  60. [71]

    1990, ApJ, 360, 242, doi: 10.1086/169114

    Shigeyama, T., & Nomoto, K. 1990, ApJ, 360, 242, doi: 10.1086/169114

  61. [72]

    2017, PASP, 129, 054201, doi: 10.1088/1538-3873/aa54a6

    Shivvers, I., Modjaz, M., Zheng, W., et al. 2017, PASP, 129, 054201, doi: 10.1088/1538-3873/aa54a6

  62. [73]

    2014, ARA&A, 52, 487, doi: 10.1146/annurev-astro-081913-040025

    Smith, N. 2014, ARA&A, 52, 487, doi: 10.1146/annurev-astro-081913-040025

  63. [74]

    V., & Chornock, R

    Smith, N., Li, W., Filippenko, A. V., & Chornock, R. 2011, MNRAS, 412, 1522, doi: 10.1111/j.1365-2966.2011.17229.x

  64. [75]

    W., Hempel, M., & Fischer, T

    Steiner, A. W., Hempel, M., & Fischer, T. 2013, ApJ, 774, 17, doi: 10.1088/0004-637X/774/1/17

  65. [76]

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

  66. [77]

    R., & Crowther, P

    Sun, N.-C., Maund, J. R., & Crowther, P. A. 2023, MNRAS, 521, 2860, doi: 10.1093/mnras/stad690

  67. [78]

    2016, A&A, 592, A89, doi: 10.1051/0004-6361/201628703

    Taddia, F., Fremling, C., Sollerman, J., et al. 2016, A&A, 592, A89, doi: 10.1051/0004-6361/201628703

  68. [79]

    D., Bersten, M., et al

    Taddia, F., Stritzinger, M. D., Bersten, M., et al. 2018, A&A, 609, A136, doi: 10.1051/0004-6361/201730844

  69. [80]

    2019, A&A, 621, A71, doi: 10.1051/0004-6361/201834429

    Taddia, F., Sollerman, J., Fremling, C., et al. 2019, A&A, 621, A71, doi: 10.1051/0004-6361/201834429

  70. [81]

    Teffs, J., Ertl, T., Mazzali, P., Hachinger, S., & Janka, H. T. 2020, MNRAS, 499, 730, doi: 10.1093/mnras/staa2549

  71. [82]

    E., et al

    Virtanen, P., Gommers, R., Oliphant, T. E., et al. 2020, Nature Methods, 17, 261, doi: 10.1038/s41592-019-0686-2

  72. [83]

    A., Zimmerman, G

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

  73. [84]

    1999, A&A, 350, 148, doi: 10.48550/arXiv.astro-ph/9904256

    Wellstein, S., & Langer, N. 1999, A&A, 350, 148, doi: 10.48550/arXiv.astro-ph/9904256

  74. [85]

    C., Johnson, V., & Clocchiatti, A

    Wheeler, J. C., Johnson, V., & Clocchiatti, A. 2015, MNRAS, 450, 1295, doi: 10.1093/mnras/stv650

  75. [86]

    C., & Levreault, R

    Wheeler, J. C., & Levreault, R. 1985, ApJL, 294, L17, doi: 10.1086/184500

  76. [87]

    2021, ApJ, 908, 150, doi: 10.3847/1538-4357/abd244

    Williamson, M., Kerzendorf, W., & Modjaz, M. 2021, ApJ, 908, 150, doi: 10.3847/1538-4357/abd244

  77. [88]

    2023, ApJL, 944, L49, doi: 10.3847/2041-8213/acb549

    Williamson, M., Vogl, C., Modjaz, M., et al. 2023, ApJL, 944, L49, doi: 10.3847/2041-8213/acb549

  78. [89]

    E., Eastman, R

    Woosley, S. E., Eastman, R. G., Weaver, T. A., & Pinto, P. A. 1994, ApJ, 429, 300, doi: 10.1086/174319

  79. [90]

    E., & Heger, A

    Woosley, S. E., & Heger, A. 2007, PhR, 442, 269, doi: 10.1016/j.physrep.2007.02.009

  80. [91]

    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

  81. [92]

    E., Langer, N., & Weaver, T

    Woosley, S. E., Langer, N., & Weaver, T. A. 1993, ApJ, 411, 823, doi: 10.1086/172886

  82. [93]

    E., Sukhbold, T., & Kasen, D

    Woosley, S. E., Sukhbold, T., & Kasen, D. N. 2021, ApJ, 913, 145, doi: 10.3847/1538-4357/abf3be

  83. [94]

    2024, arXiv e-prints, arXiv:2409.04522, doi: 10.48550/arXiv.2409.04522

    Yesmin, N., Pellegrino, C., Modjaz, M., et al. 2024, arXiv e-prints, arXiv:2409.04522, doi: 10.48550/arXiv.2409.04522

  84. [95]

    2015, PASA, 32, e015, doi: 10.1017/pasa.2015.16

    Yoon, S.-C. 2015, PASA, 32, e015, doi: 10.1017/pasa.2015.16

  85. [96]

    C., Woosley, S

    Yoon, S. C., Woosley, S. E., & Langer, N. 2010, ApJ, 725, 940, doi: 10.1088/0004-637X/725/1/940

Pith tools

Reviewed August 12, 2026 · model on record in the stance chip above.