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arxiv: 2604.09906 · v1 · submitted 2026-04-10 · 🌌 astro-ph.SR · astro-ph.HE

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Impacts of Multidimensional Progenitor Perturbations on Core-Collapse Supernova Explosions

Chien-Hui Chen , Eric J. Lentz , W. Raphael Hix , J. Austin Harris , Chloe Keeling Sandoval , Stephen W. Bruenn
Authors on Pith no claims yet

Pith reviewed 2026-05-10 16:34 UTC · model grok-4.3

classification 🌌 astro-ph.SR astro-ph.HE
keywords core-collapse supernovaeprogenitor perturbationstwo-dimensional simulationsshock revivalneutrino-driven convectionstanding accretion shock instabilityturbulent energystochasticity
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The pith

Simulations of 15-solar-mass stars show that differences in pre-collapse progenitor structure and composition do not alter the timing or development of core-collapse supernova explosions.

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

This paper runs seven two-dimensional simulations of 15-solar-mass stars using different pre-collapse progenitor models that include one- and two-dimensional stellar evolution effects. It finds that shock revival times and explosion development remain similar across these varied initial conditions and structures. The authors conclude that any turbulent energy from the multi-dimensional progenitor is overwhelmed by turbulence generated in the post-shock region through shock deformation and the standing accretion shock instability, which saturates before neutrino-driven convection becomes dominant. Stochastic variations in the simulations exceed any effects from these initial perturbations. This suggests the explosion mechanism is robust to differences in how the star evolved before collapse.

Core claim

Contrary to results reported by other groups, we observe similar shock revival times and explosion development in our simulations despite differences in initial compositions and structures. We find no discernible impact from turbulent energy introduced by the multi-D structures in the progenitor as the models evolve from the stalled shock to explosion. We attribute this to the turbulence generated in the post-shock region by shock deformation and standing accretion shock instability reaching a saturation level before the neutrino-driven convection dominates the post-shock dynamics. An examination of model stochasticity shows that any prior expected impacts on explosive outcome due to convect

What carries the argument

Comparison of 2D CHIMERA neutrino radiation hydrodynamics simulations of 15 solar mass progenitors with varying 1D and 2D pre-collapse structures, tracking shock dynamics, diagnostic energy, neutrino heating, accretion, explosion geometry, nuclear abundances, and turbulent convection to isolate the role of initial multi-dimensional perturbations.

If this is right

  • Shock revival times and explosion development proceed similarly across progenitors with and without multi-dimensional structures from pre-collapse evolution.
  • Turbulent energy supplied by the progenitor becomes irrelevant once post-shock motions from shock deformation and SASI reach saturation.
  • Effects from convection-related perturbations in the progenitor lie below the level of numerical stochasticity in these models.
  • Explosion outcomes remain insensitive to differences in initial compositions and structures introduced by different stellar evolution environments.

Where Pith is reading between the lines

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

  • If post-shock saturation always precedes neutrino-driven convection, then full 3D modeling of pre-collapse convection may not be required to predict 2D explosion outcomes.
  • The same progenitors run in three dimensions could test whether SASI behaves differently and allows progenitor perturbations to matter.
  • Neighboring studies reporting impacts from multi-D progenitors may need to verify that those effects survive changes in numerical resolution or neutrino transport.
  • The result implies that variability in supernova models is more often set by neutrino heating details or grid resolution than by stellar-evolution perturbations.

Load-bearing premise

That turbulence generated in the post-shock region by shock deformation and standing accretion shock instability reaches a saturation level before neutrino-driven convection dominates, rendering any progenitor-supplied turbulent energy irrelevant to the explosion outcome.

What would settle it

A simulation in which progenitor turbulence is strong enough to measurably shift shock revival time or change explosion development before post-shock SASI turbulence saturates.

Figures

Figures reproduced from arXiv: 2604.09906 by Chien-Hui Chen, Chloe Keeling Sandoval, Eric J. Lentz, J. Austin Harris, Stephen W. Bruenn, W. Raphael Hix.

Figure 1
Figure 1. Figure 1: Mean atomic mass, A¯, of G15-SiSB-M3 at the on￾set of collapse. The silicon-burning shell ranges from about 1500–2500 km and perturbations can be seen within it, the convective oxygen-burning shell is the aqua region, and the non-convective oxygen shell is the blue region at the edge. 3 we detail simulation results and differences caused by the density structure changes induced by multi-D pre￾collapse evol… view at source ↗
Figure 2
Figure 2. Figure 2: Angle-averaged density profiles of models from different pre-collapse progenitors (a) in the collapsing phase when the central density reaches 1.5 × 1010 g cm−3 , and (b) at 60 ms post-bounce. Vertical dashed lines indicate mass coordinates of 1.27, 1.34, 1.48, and 1.52 M⊙. perturbations. For brevity, the models are labeled, M1, M2, etc. in plots. 3. SIMULATION RESULTS 3.1. Initial Conditions and Density S… view at source ↗
Figure 3
Figure 3. Figure 3: Initial nuclear abundances of G15-SiSB-M1 (solid line), G15-SiSB-M2 (dotted line), and G15-SiSB-M3 (dashed line) as a function of (a) enclosed mass and of (b) radius from the center of the core to a radius of 10000 km at the onset of collapse. combination of these differences with differences due to weaker silicon burning in the 1.3–1.5 M⊙ shell for G15- SiSB-M2 discussed above, results in the edge of the … view at source ↗
Figure 4
Figure 4. Figure 4: Nuclear abundances at core bounce of G15-SiSB-M1 (solid line), G15-SiSB-M2 (dotted line), and G15-SiSB-M3 (dashed line) as a function (a) of enclosed mass and (b) of radius from the center of the core to a radius of 10000 km. 3.2. Shock Development [PITH_FULL_IMAGE:figures/full_fig_p008_4.png] view at source ↗
Figure 6
Figure 6. Figure 6: Left two panels, (a) and (c): mean shock radius; Right two panels, (b) and (d): mass enclosed by shock Msh. Upper panels, (a) and (b): cover first 300 ms after bounce; Lower panels, (c) and (d): full simulation. Radius of 200 km and 400 km in panel (a), Fe-core edge at 1.3 M⊙ and Si/O interface at 1.5 M⊙ in panel (b), and the top of convective O-shell at 1.7 M⊙ in panel (d) are marked with gray dash-dot li… view at source ↗
Figure 7
Figure 7. Figure 7: illustrates that the timescale ratio τadv/τheat of all our models exceeds unity between tpb = 85– 105 ms, with G15-SiSB-M1 being the latest reaching this criterion. Despite the oscillation of τadv/τheat, the overall trend of τadv/τheat stays increasing for all six models, indicating the success of explosions. However, the time when τadv/τheat reaches the critical value is ap￾proximately 100 ms before actua… view at source ↗
Figure 9
Figure 9. Figure 9: shows ηheat significantly increases as the neutrino-driven convection develops, stably grows, peaks with Q˙ ν around the onset of explosion (tpb = 150– 250 ms) and gradually drops as the explosion matures. 3.4. Accretion Stream Accretion onto the PNS contributes to the neutrino luminosity and thus the neutrino heating. We can ob￾serve the trend of neutrino heating ( [PITH_FULL_IMAGE:figures/full_fig_p011_9.png] view at source ↗
Figure 8
Figure 8. Figure 8: Neutrino heating rate in the gain region (a) smoothed over a 10 ms interval and (b) unsmoothed in the first 300 ms post-bounce. the neutrino energy deposition rate in the heating layer to the electron flavor neutrino luminosity at the gain surface (S. W. Bruenn et al. 2016, 2023), ηheat = Q˙ ν Lνe + Lν¯e . (1) [PITH_FULL_IMAGE:figures/full_fig_p011_8.png] view at source ↗
Figure 10
Figure 10. Figure 10: Panel (a): Neutrino luminosity on a linear scale. Panel (b): Net accretion rate through 100 km radius (solid lines) and inward mass accretion rate through the gain sur￾face (dashed lines). Panels (a) and (b) are smoothed over a 10 ms interval. Panel (c): Cumulative net mass accretion through 100 km radius (solid lines) and PNS mass increase (dotted lines), relative to 200 ms after bounce. sured at 100 km.… view at source ↗
Figure 11
Figure 11. Figure 11: Growth of diagnostic energy E + (solid lines) and overburden-corrected diagnostic energy E + ov (dashed lines). The gap between the solid line and the dashed line gives the overburden binding energy of each model. other equatorial accretion stream reaches the PNS near its equator at tpb = 436 ms. With the polar stream still active, adding the second stream enhances the total ac￾cretion. The timing of thes… view at source ↗
Figure 12
Figure 12. Figure 12: Diagnostic energy E + (cyan lines) and components for all six models G15-SiSB-M1 to G15-SiSB-M6 in panels left-to-right, top-to-bottom. Red dashed lines represent the thermal energy component, green dashed lines the kinetic energy component, and purple dashed lines the ‘negative’ gravitational potential energy component [PITH_FULL_IMAGE:figures/full_fig_p014_12.png] view at source ↗
Figure 13
Figure 13. Figure 13: shows the dipole deformation of the shock, which is measured as mean shock z-coordinate position normalized by mean shock radius, ⟨Z⟩/⟨R⟩. Factors that affect the dipole include bulk fluid motions like progenitor asymmetries, prompt convection in the PNS, SASI, and neutrino-driven convection. G15-SiSB-M2, G15-SiSB-M3 and G15-SiSB-M4 show obvious deforma￾tion of the shock immediately after bounce. In contr… view at source ↗
Figure 14
Figure 14. Figure 14: (b) shows that between 20–50 ms after bounce, though small, there is a growth of the lateral TKE Ek,θ,ϕ in the gain region for G15-SiSB-M1, G15- SiSB-M5, and G15-SiSB-M6. The early timing of this increase in lateral TKE makes it most likely due to the SASI instead of neutrino-driven convection. The lateral TKE of the ‘quiet’ models remain low, below 0.001 B, during the prompt convection phase and then dec… view at source ↗
Figure 15
Figure 15. Figure 15: Entropy pseudocolor plot to radius 5000 km at 600 ms after bounce for (a) G15-SiSB-M1 to (f) G15-SiSB-M6 on the same 5–35 kB baryon−1 scale. Explosion is sufficiently mature and explosion morphology is mostly determined at this time. its smaller E+ is likely a result of the more spherical shock morphology of G15-SiSB-M1, which inhibits the formation of a sustained, unidirectional accretion stream onto the… view at source ↗
Figure 16
Figure 16. Figure 16: Ejecta (unbound materials with vr > 0) masses for select nuclei for the first second after bounce. The sequence (a)–(f) follows a left-to-right, top-to-bottom arrangement, from G15-SiSB-M1 to G15-SiSB-M6 [PITH_FULL_IMAGE:figures/full_fig_p020_16.png] view at source ↗
Figure 17
Figure 17. Figure 17: Iron nuclei abundances in the ejecta (un￾bound materials with vr > 0). These nuclei are pro￾duced through complete explosive silicon burning. (a) com￾pares G15-SiSB-M1 and G15-SiSB-M3, and (b) compares G15-SiSB-M5 and G15-SiSB-M6. unchanged within its intrinsically turbulent silicon shell (1.3–1.5 M⊙) at a value close to 1015 erg g−1 . It is amplified about ten times in its outer iron core, from ∼ 1013 er… view at source ↗
Figure 19
Figure 19. Figure 19: (b) shows, in the cavity by tpb = 75 ms (dashed lines), the lateral turbulent kinetic energies of G15-SiSB￾M5 and G15-SiSB-M6 has been amplified by the shock deformation to the level of 1016 erg g−1 , only 10 times smaller than the saturation energy level that G15-SiSB￾M3 achieves early. This energy increase introduced by shock deformation proves the existence of SASI in our models. Between 75–100 ms post… view at source ↗
Figure 20
Figure 20. Figure 20: Lateral TKE for (a) G15-SiSB-M2 in the col￾lapsing phase; (b) G15-SiSB-M2 and G15-SiSB-M3 at the same times as in [PITH_FULL_IMAGE:figures/full_fig_p024_20.png] view at source ↗
Figure 21
Figure 21. Figure 21: Pre-shock density perturbation evaluated at radius 500 km by (a) normalized density fluctuations and (b) multipoles. No data are shown after the maximum shock reaches 500 km for each model. Lines for ℓ = 2 and ℓ = 3 modes are smoothed the data over 2 ms interval for clarity. ⟨ρ⟩ = ρ0 is the spherical average density at the analyzed radius. means more kinetic energy from the infalling matter is preserved a… view at source ↗
Figure 22
Figure 22. Figure 22: Mass and central density of PNS between 0–1000 ms after bounce for all models. to examine the impact of stochastic variation on our re￾sults. 5.1. M2b To isolate the role of stochasticity, we take one of our models, G15-SiSB-M2, and re-evolve it from core bounce to 600 ms as G15-SiSB-M2b. For this model, in addition to the standard numerical sources of variation (parallel summation order, recompiled execu… view at source ↗
Figure 23
Figure 23. Figure 23: Comparison of (a) mass accretion rates and (b) diagnostic energies of G15-SiSB-M2 and G15-SiSB-M2b for the first 600 ms after core bounce. (a) is smoothed over a 10 ms interval as [PITH_FULL_IMAGE:figures/full_fig_p026_23.png] view at source ↗
Figure 24
Figure 24. Figure 24: Dipole deformation of the shock, ⟨Z⟩/⟨R⟩, (a); and entropy pseudocolor plot at (b) 100 ms and (c) 200 ms after bounce. ence on the overall explosion geometry. Combining with the nature of 2D axis-symmetric simulation, the position where the equatorial downflows reaches the PNS forces the ejecta at the oppose direction. The changes in down￾flow orientation and stronger plumes are recoverable in the post-bo… view at source ↗
Figure 25
Figure 25. Figure 25: Pseudocolor plots of entropy for G15-SiSB-M2 and G15-SiSB-M2b at (a) 300 ms, (b) 400 ms, and (c) ≈340 ms (zoomed to show minor lobes) after bounce. 5.2. M5 vs M6 Aside from the comparison between G15-SiSB-M2 and G15-SiSB-M2b, we use another pair of models, G15- SiSB-M5 and G15-SiSB-M6, to show how stochastic￾ity affects simulation outcomes. These two models have nearly identical initial conditions, differ… view at source ↗
Figure 26
Figure 26. Figure 26: E + decomposition plot for (a) G15-SiSB-M2 and (b) G15-SiSB-M2b as in [PITH_FULL_IMAGE:figures/full_fig_p029_26.png] view at source ↗
Figure 27
Figure 27. Figure 27: Comparison of G15-SiSB-M2 and G15-SiSB-M2b (a) mean shock radii, (b) shock enclosed mass, Msh, (c) shock dipole deformation, and (d) PNS properties for tpb = 0–600 ms. are characteristic of Chimera models, without exam￾ples of marginal, or failed, explosions as in some of the progenitors and codes used in prior perturbation sensi￾tivity studies. Chimera models rarely evidence signif￾icant recession of the… view at source ↗
read the original abstract

Numerical studies of core-collapse supernovae have demonstrated the importance of non-radial motions in pre-collapse progenitors on the explosion outcome. We use the CHIMERA neutrino radiation hydrodynamics code running seven two-dimensional simulations of 15 solar mass progenitors with different progenitor structures introduced by different one and two-dimensional pre-collapse stellar evolution environments to examine the impacts of stellar structure and non-spherical motion in the pre-collapse progenitor on the development of explosions in 2D core-collapse supernova simulations. We compare the explosion evolution of these models in terms of shock dynamics, diagnostic energy, neutrino heating, accretion, explosion geometry, nuclear abundances, and turbulent convection. We also analyze how stochasticity impacts our simulations. Contrary to results reported by other groups examining the impacts of multi-dimensional progenitors, we observe similar shock revival times and explosion development in our simulations despite differences in initial compositions and structures. We find no discernible impact from turbulent energy introduced by the multi-D structures in the progenitor as the models evolve from the stalled shock to explosion. We attribute this to the turbulence generated in the post-shock region by shock deformation and standing accretion shock instability to a saturation level before the neutrino-driven convection dominates the post-shock dynamics. An examination of model stochasticity shows that any prior expected impacts on explosive outcome due to convection-related perturbations lie below the detectable threshold of numerical variation.

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 / 0 minor

Summary. The manuscript reports results from seven 2D CHIMERA neutrino radiation hydrodynamics simulations of 15 solar mass core-collapse supernovae. Progenitors are initialized with structures and perturbations drawn from both 1D and 2D pre-collapse stellar evolution calculations. The authors compare shock revival times, diagnostic energies, neutrino heating, accretion rates, explosion geometry, nuclear abundances, and turbulent convection across the set. They report similar revival times and explosion development despite initial differences, conclude that progenitor-supplied turbulent energy has no discernible effect once the stalled shock phase begins, and attribute this to saturation of post-shock turbulence by shock deformation and SASI before neutrino-driven convection dominates. A stochasticity analysis is presented to argue that any convection-related effects fall below numerical variation thresholds.

Significance. If the central observational result of similar revival times holds after the requested diagnostics are supplied, the work would indicate that, at least in 2D, post-shock hydrodynamic processes rapidly erase memory of pre-collapse multi-dimensional structure. This would stand in contrast to reports from other groups and would underscore the importance of quantifying stochasticity and resolution convergence in the field. The use of an ensemble of seven models with explicit stochasticity analysis is a constructive step toward placing bounds on variability.

major comments (2)
  1. [Abstract] Abstract: the attribution that 'turbulence generated in the post-shock region by shock deformation and standing accretion shock instability [reaches] a saturation level before the neutrino-driven convection dominates' is load-bearing for the claim of no discernible progenitor impact, yet the manuscript supplies no supporting quantitative evidence such as time series of turbulent kinetic energy decomposed by source (progenitor vs. gain-region generation), velocity power spectra at key epochs, or direct comparison of fluctuation amplitudes traceable to the initial multi-D structures.
  2. [Abstract] Abstract and stochasticity analysis: the statement that 'any prior expected impacts on explosive outcome due to convection-related perturbations lie below the detectable threshold of numerical variation' is not accompanied by resolution studies, quantitative error bars on shock revival times or diagnostic energies, or explicit criteria for data exclusion. Without these, the assertion that progenitor effects are negligible relative to numerical noise cannot be evaluated.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for the constructive and detailed report. The comments highlight areas where additional quantitative support would strengthen the manuscript. We address each point below and indicate revisions to be incorporated in the revised version.

read point-by-point responses

  1. Referee: [Abstract] Abstract: the attribution that 'turbulence generated in the post-shock region by shock deformation and standing accretion shock instability [reaches] a saturation level before the neutrino-driven convection dominates' is load-bearing for the claim of no discernible progenitor impact, yet the manuscript supplies no supporting quantitative evidence such as time series of turbulent kinetic energy decomposed by source (progenitor vs. gain-region generation), velocity power spectra at key epochs, or direct comparison of fluctuation amplitudes traceable to the initial multi-D structures.

    Authors: We agree that the manuscript would benefit from explicit quantitative diagnostics supporting the attribution of turbulence saturation. While the similar shock revival times, diagnostic energies, and post-shock flow properties across the seven models with differing initial perturbations provide indirect evidence that post-shock processes dominate, we will add time series of turbulent kinetic energy in the gain region (with decomposition where feasible from the available data) and velocity power spectra at representative epochs (e.g., at shock stall and near revival) for selected models. These additions will allow direct comparison of fluctuation amplitudes and their evolution independent of the initial progenitor structure. revision: yes

  2. Referee: [Abstract] Abstract and stochasticity analysis: the statement that 'any prior expected impacts on explosive outcome due to convection-related perturbations lie below the detectable threshold of numerical variation' is not accompanied by resolution studies, quantitative error bars on shock revival times or diagnostic energies, or explicit criteria for data exclusion. Without these, the assertion that progenitor effects are negligible relative to numerical noise cannot be evaluated.

    Authors: The stochasticity analysis in the manuscript uses the spread across the seven-member ensemble to quantify variation in revival times, diagnostic energies, and other quantities, with all models included and no data exclusion applied. We will add explicit error bars derived from the standard deviation of these quantities across the ensemble and state the inclusion criterion (all seven simulations are retained). While dedicated resolution convergence studies were not performed for this specific progenitor set, we will expand the discussion to place the observed ensemble variation in the context of prior CHIMERA resolution tests reported in the literature. This will clarify that the progenitor-induced differences fall within the quantified numerical variation. revision: partial

Circularity Check

0 steps flagged

No circularity: direct numerical comparison of distinct initial conditions

full rationale

The paper reports results from seven 2D CHIMERA simulations initialized with different 15 solar-mass progenitor structures and compositions. The central claims of similar shock revival times, explosion development, and no discernible impact from progenitor-supplied turbulent energy are presented as direct outcomes of evolving those distinct initial conditions to the stalled-shock and explosion phases. No equations, fitted parameters, or derivations are shown that reduce the reported outcomes to self-referential definitions or inputs called predictions. The post-hoc attribution to post-shock turbulence reaching saturation before neutrino-driven convection dominates is an interpretive statement, not a load-bearing step that constructs the main results by construction. No self-citation chains, uniqueness theorems, or ansatzes imported from prior work are invoked to force the conclusions. The study is therefore self-contained as a comparative simulation exercise.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

The central claim rests on the validity of the CHIMERA neutrino radiation hydrodynamics code and on the assumption that 2D post-shock dynamics are representative; no free parameters or invented entities are introduced in the abstract.

axioms (1)
  • domain assumption The CHIMERA code accurately captures neutrino-driven convection and standing accretion shock instability in 2D.
    Invoked implicitly when attributing the lack of progenitor impact to post-shock turbulence saturation.

pith-pipeline@v0.9.0 · 5566 in / 1433 out tokens · 36479 ms · 2026-05-10T16:34:19.488794+00:00 · methodology

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Reference graph

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