Pith. sign in

REVIEW 3 major objections 5 minor 54 references

Mesoscale Turbulence in Type Ia Supernova Deflagrations: Buoyancy-Driven Fuel Heating and Prospects for Delayed-Detonations

T0 review · 3 major / 5 minor · reviewed 2026-08-07 · deepseek-v4-flash

Pith's one-line read In simulated Type Ia supernova flames, buoyancy compresses and heats nearby fuel, cutting its ignition time by two to more than five orders of magnitude.

desk verdict A serious flame-in-a-box study with a plausible but not yet established claim about buoyancy preconditioning fuel for DDT; worth refereeing, but the headline number rests on a 4-8 cell layer with no convergence check. read the letter →

arxiv 2505.18482 v1 pith:X7PGDZGJ submitted 2025-05-24 astro-ph.SR physics.data-an

classification astro-ph.SRphysics.data-an
keywords TypeIasupernovaedeflagration-to-detonationtransitionRayleigh-Taylorinstabilityturbulentthermonuclearcombustionwhitedwarfflamesfuelignitiontimeadiabaticheatingadaptivemeshrefinement
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 claims that in three-dimensional simulations of Rayleigh-Taylor-unstable thermonuclear flames under Type Ia supernova conditions, the flame's buoyant motion adiabatically compresses and heats the fuel immediately ahead of the front, shortening the fuel's carbon ignition time by roughly two orders of magnitude at low density and by more than five at high density, for fuel densities from about $5\times10^6$ to $6\times10^7$ g cm$^{-3}$. The authors interpret this heating as a new energy source inside fuel that penetrates the turbulent flame brush and as the kind of preconditioning the Zel'dovich deflagration-to-detonation transition requires. This matters because delayed-detonation models are a leading explanation for a major class of Type Ia supernovae, yet no simulation has demonstrated the transition self-consistently under realistic conditions. The paper also reports that flame-brush turbulence is strongly intermittent and that velocity fluctuations on detonation-relevant scales (about 60 to 200 km/s near the 8 km scale) lie far below earlier estimates near 1000 km/s, a difference that favors some proposed DDT mechanisms over others.

What carries the argument

The mechanism carrying the argument is adiabatic compression of fuel by buoyancy-driven flame motion, diagnosed through the carbon ignition time as a function of the flame progress variable and a flame-surface orientation factor $n_{f,g}=\nabla\phi\cdot\mathbf{g}/(\|\nabla\phi\|\|\mathbf{g}\|)$. Joint probability distributions of ignition time against this orientation factor show the shortest ignition times where $n_{f,g}\approx+1$, at the tops of rising flame bubbles, and longer times in sinking spikes; this correlation is the signature that ties the ignition-time reduction to buoyancy rather than to the flame's thermal structure alone. The numerical machinery is a thickened-flame advection-diffusion-reaction model with adaptive mesh refinement at an effective resolution of 62.5 m, evolved to a quasi-steady state and analyzed in a frame co-moving with the turbulent post-flame region.

What would settle it

Repeat the highest-density (HID) model at twice the effective resolution ($\approx$31 m) or with a thinner flame profile: if the more-than-five-order-of-magnitude reduction in fuel ignition times does not persist, the buoyant heating is a numerical artifact of the thickened flame's diffusive precursor rather than a physical effect. A complementary check is to enable fuel-restricted self-heating in the same model and determine whether the predicted early ignition actually occurs ahead of the flame front.

Watch

Extended reading notes

Core claim

The paper's central finding is that fuel in the turbulent post-flame region of a Rayleigh-Taylor-driven deflagration is not inert: as the flame front approaches a fuel parcel, the flame's thermal expansion and buoyant acceleration compress the fuel adiabatically, and this compression is strongest where the flame surface's normal is aligned with gravity, namely at the tops of rising Rayleigh-Taylor bubbles. Using a flame progress variable to tag distance from the front, the authors measure carbon ignition times in the compressed fuel layers and find reductions of about two orders of magnitude in the lowest-density model, three in the intermediate model, and more than five in the highest-density model, with the ignition-time distribution broadened into a tail of strongly preheated parcels. They argue that such heated layers, up to several hundred meters wide, are plausible sites for the Zel'dovich mechanism, especially in cusps where rising bubbles collide and in Rayleigh-Taylor spikes that resemble the fuel channels in which their earlier spectrally-driven turbulence models produced detonations. The paper is explicit, however, that pure Rayleigh-Taylor forcing alone did not reproduce that earlier preconditioning, and that demonstrating an actual transition will require higher-resolution simulations with fuel self-heating included.

Load-bearing premise

The load-bearing premise is that the simulations' 62.5-meter effective resolution, refinement criteria, and prescribed subgrid flame speed faithfully capture the physical compressive heating of fuel by the flame, rather than an artifact of the artificially thickened flame; the paper reports no resolution-convergence study to confirm this.

Editorial extensions

If this is right

  • If the buoyant heating is physical, fuel ahead of the flame in Type Ia deflagrations can ignite far sooner than cold-fuel burn rates imply, so burning should begin ahead of the front and possibly in isolated pockets inside the warm fuel layer.
  • The preconditioning required by the Zel'dovich DDT mechanism can develop in buoyancy-driven flame brushes at fuel densities of roughly $5\times10^6$ to $6\times10^7$ g cm$^{-3}$, most plausibly in fuel at bubble tops and in cusps and spikes that resemble the fuel channels of the earlier spectrally-driven models.
  • Turbulent velocity fluctuations on detonation-relevant scales are about 60 to 200 km/s, far below the roughly 1000 km/s assumed by distributed-burning DDT models, so mechanisms requiring high turbulence intensity on 10 km scales are disfavored while low-fluctuation ZDDT models are consistent with the data.
  • Under the turbulence-induced DDT picture, the most likely transition density shifts above the earlier estimate of $3\times10^7$ g cm$^{-3}$, because the measured intensities are higher than assumed at the high-density end and lower at the low-density end.
  • Next-generation Rayleigh-Taylor deflagration simulations must include fuel-restricted nuclear self-heating, since the heated fuel layers may release energy before the front arrives and feed back into the flow.

Reading between the lines

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

  • The trend in the paper's own numbers — ignition-time reduction growing from about two to more than five orders of magnitude as density increases — implies that if a delayed detonation occurs through this channel, it should be most favored at the high-density end of the DDT window, possibly above the canonical $2\times10^7$ g cm$^{-3}$.
  • A natural next calculation, which the paper notes would be comparatively cheap, is to switch on fuel self-heating in the highest-density model and watch whether preheated fuel actually ignites ahead of the front; if it does, the ignition-time reductions correspond to real precursor burning rather than to a diagnostic artifact.
  • Because no resolution-convergence study is reported, the stronger heating seen at higher density could in principle be amplified by the thickened flame's wider diffusive precursor; repeating the highest-density model at about 31 m resolution would test whether the more-than-five-order reduction survives.
  • If buoyant preheating operates in real explosions, carbon would burn at lower density than standard deflagration models assume, which would shift the nucleosynthetic yields and the early light curve of delayed-detonation models; this is an observational consequence the paper does not address.
Share X Bluesky LinkedIn Reddit HN

Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

3 major / 5 minor

Summary. The paper presents three-dimensional AMR simulations of Rayleigh-Taylor-unstable thermonuclear deflagrations in a flame-in-a-box setup, at three fuel densities spanning approximately 5e6 to 6e7 g/cm^3, using a thickened-flame ADR model with a subgrid flame speed based on the RTI growth rate. The authors analyze a co-moving 'turbulent post-flame' (TPF) region and report that fuel near the flame front is adiabatically compressed by buoyancy, reducing carbon ignition times by about two to more than five orders of magnitude (Section 3.4, Figs. 9-11), with stronger reduction at higher density. They also characterize turbulence spectra, intermittency, velocity statistics, and flame fractal dimension, and compare their results with previous SN Ia DDT studies.

Significance. If the central heating claim is correct, it identifies a new fuel-preconditioning mechanism relevant to the Zel'dovich DDT scenario in SNe Ia, with quantitative estimates at densities where DDT is thought to occur. The paper is careful in several respects: ignition times are computed with an external formula (Dursi & Timmes 2006) rather than fitted to the result, PDFs are time-averaged over several eddy turnovers, and limitations (no self-heating, need for better resolution) are explicitly acknowledged in Section 5. However, because the claim depends on resolving a thin fuel layer with a thickened-flame model and no resolution-convergence study is reported, the present evidence is suggestive rather than definitive.

major comments (3)
  1. [Section 3.4 / Figs. 9-10] The central claim that fuel ignition times are reduced by two to five orders of magnitude rests on resolving the thermodynamic state in fuel layers that the authors themselves state are only up to several hundred meters wide (Abstract; Section 5). With the effective mesh resolution Delta_x = 62.5 m (Section 2), this layer spans only about 4-8 cells, and the compensated spectrum in Fig. 6 shows a flat inertial-range segment only for k approximately 4-12, i.e., scales of 3-8 km. No resolution-convergence study is reported; all quoted statistics come from a single finest resolution. Because the carbon ignition time is exponentially sensitive to temperature, a modest numerical error in the preheated layer could account for the entire quoted reduction. I request at least a systematic comparison of the ignition-time PDFs at 256-cell and 512-cell lateral resolution, and ideally a higher-resolution run for one density, such as the HID model.
  2. [Section 2 / Section 3.4] The ADR thickened-flame model intentionally adds diffusion to the progress variables (Model B of Zhiglo 2009), and the paper explicitly states that a diffusive precursor relates the progress variable to physical distance from the flame front (Section 3.4). The AMR refinement criteria (phi in [0.01,0.99] and delta p/p > 1e-3) do not specifically refine the pure-fuel region phi <= 1e-5 where the heating is diagnosed. The anti-correlation with negative divergence shown in Fig. 9 is suggestive, but a numerical diffusive precursor with its associated artificial compression could produce qualitatively similar signatures. The authors should demonstrate that the elevated temperature ahead of the front follows an adiabatic compression relation tied to the resolved velocity field, and that the result is insensitive to the flame-model diffusion parameters.
  3. [Section 4.1 / Section 5] The manuscript presents ignition-time reductions computed post hoc from the simulated temperature and density fields while explicitly omitting fuel self-heating (conclusions iii and x). Since the claim is that ignition times are reduced to values comparable to or shorter than advection times, the absence of self-heating feedback is potentially load-bearing: if the shortest-ignition-time parcels actually ignite during the simulation, the flame structure and the very statistics being measured would change. The authors appropriately call for 'better resolved numerical simulations with self-consistent fuel state', but as it stands the paper's conclusion (ii), that adiabatic heating 'may result in fuel burning ahead of the flame front', is a projection rather than a demonstrated outcome of the simulations.
minor comments (5)
  1. [Section 3.3 / Fig. 6] The caption of Fig. 6 describes the flat region as 'k approximately 8 +/- 4', while the text says the inertial subrange starts at k approximately 4; please clarify which wavenumber range is used for the inertial-range estimate.
  2. [Table 4] The header of Table 4 appears to contain duplicated superscript labels ('b' and 'b' for v8 and vRMS), which is likely a typesetting error; the column labels should be corrected to match the text.
  3. [Section 3.1] The TPF region is defined using a super-Gaussian fit with exponent p=10 and a fixed 32 km cube (Eq. 1); please report the sensitivity of the main ignition-time PDFs to these somewhat ad hoc choices, or justify the values with a convergence test over the TPF selection parameters.
  4. [Section 3.4 / footnote 3] The paper notes that the Dursi & Timmes (2006) formula produces numerical artifacts for nearly exhausted carbon at phi=0.99; please state explicitly whether the very short ignition-time tail in Fig. 10 contains any such artifact cells and whether excluding them changes the quoted reductions.
  5. [Section 4.2.1 / Fig. 12] The comparison with Ropke (2007) in Fig. 12 says the original parameter values were 'adjusted to scale up theoretical distributions to approximately match our data'; please specify exactly which parameters were changed and why, so the comparison is reproducible.

Circularity Check

0 steps flagged · score 0.0 of 10

No circularity: the ignition-time reduction is a post-processing diagnostic from an external nuclear formula applied to simulated fields, not a fitted or self-defined output.

full rationale

The paper's central claim—that buoyancy-driven compression near RT-unstable flame fronts shortens fuel ignition times by 2-5 orders of magnitude—is derived from simulated density and temperature fields processed through the external carbon ignition-time formula of Dursi & Timmes (2006). No parameter is fitted to the reported shortening: the initial fuel temperature is chosen a priori to give a burning timescale near 330 ms, and the subgrid flame speed is prescribed from the RTI growth rate rather than tuned to the ignition-time outcome. The self-citations to Brooker et al. (2021) are motivational and comparative, and the paper explicitly reports that the present RTI-driven models do not reproduce the preconditioning found in those spectrally driven models (conclusion iii), so the argument is not forced by the prior work. The resolution and thickened-flame concerns raised in the skeptical view are legitimate correctness risks, but they concern numerical fidelity rather than logical circularity: nothing in the derivation defines the result in terms of its own conclusion or renames an input as a prediction. Hence no specific circular step can be exhibited, and the appropriate score is 0.

Assumptions & free parameters 3 free parameters · 5 assumptions · 0 invented entities

The central claim rests on a series of modeling choices inherited from prior literature (thickened flame, ADR, Helmholtz EOS) and on an analysis construct (TPF region). No new physical entities are introduced. The main free parameters are the subgrid flame speed and the adjusted initial fuel temperature; neither is fitted to the claimed ignition-time reduction, which limits circularity burden but does not remove the need to validate the flame model against resolved flame simulations.

free parameters (3)
  • Subgrid-scale flame speed vf,SGS = LOD 0.420, MED 0.425, HID 0.330 km/s
    Prescribed from the RTI growth rate and Atwood number as a constant in the thickened ADR flame model (Section 2, Table 1). Chosen a priori, not fitted to the ignition-time result.
  • Initial fuel temperature = LOD 1.5e9 K, MED 1.3e9 K, HID 1.2e9 K
    Adjusted so that the unburned fuel burning timescale is slightly longer than 300 ms (Section 2, Table 1). A hand-set input that affects the baseline ignition time from which reductions are measured.
  • Super-Gaussian exponent p = 10
    Chosen for fitting the flame brush position with Eq. (1) to define the TPF region; an analysis parameter that influences which cells are included in the statistics.
assumptions (5)
  • standard math Conservation equations plus the Helmholtz equation of state describe the stellar plasma in this regime.
    Used in Section 2 to integrate the flow; standard hydrodynamics and equation of state from cited literature.
  • domain assumption The thickened ADR flame model with prescribed vf,SGS reproduces the leading-order behavior of a carbon deflagration on unresolved scales.
    Section 2 invokes Colin et al. (2000) thickening and the Khokhlov ADR scheme to replace the physical flame, a modeling approximation inherited from prior work.
  • domain assumption Initial conditions extracted from a 2D centrally ignited pure-deflagration explosion model are representative of DDT-relevant conditions in a Chandrasekhar-mass white dwarf.
    Section 2 takes density, gravity, and composition from the Plewa (2007) and Wong and Schwab (2019) explosion model at the target densities.
  • domain assumption The Dursi and Timmes (2006) ignition-time formula is valid for the fuel states produced in the simulations.
    All ignition-time reductions in Section 3.4 are computed with this formula; its applicability to the modeled thermonuclear regime is assumed.
  • ad hoc to paper The TPF region, defined by a super-Gaussian fit with p=10 and a 32 km cube, captures the region most relevant to DDT preconditioning.
    Equation (1) and Section 3.1 define the analysis region; the central ignition-time statistics are computed only inside this region.

how reviews work

0 comments
Cite this review

Pith. "Pith review of Mesoscale Turbulence in Type Ia Supernova Deflagrations: Buoyancy-Driven Fuel Heating and Prospects for Delayed-Detonations." pith.science (2026). https://pith.science/paper/X7PGDZGJ

@misc{pith2026250518482,
  author       = {Pith},
  title        = {Pith review of: Mesoscale Turbulence in Type Ia Supernova Deflagrations: Buoyancy-Driven Fuel Heating and Prospects for Delayed-Detonations},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/X7PGDZGJ}},
  note         = {Machine review of arXiv:2505.18482}
}
abstract

The aim of this work is to characterize the thermodynamic state of fuel mixed into the turbulent flame brush in the context of the Zel'dovich deflagration-to-detonation transition (ZDDT) mechanism of Type Ia supernovae (SNe Ia). We perform a series of three-dimensional computer simulations of thermonuclear deflagrations subject to the Rayleigh-Taylor instability (RTI) for conditions found in model explosions of centrally ignited realistic, Chandrasekhar mass white dwarf progenitors. These conditions correspond to explosion times when the flame reaches low density progenitor regions where DDT is expected to occur. The flame database is constructed using a thickened flame model. High numerical resolution is achieved with the help of the adaptive mesh refinement (AMR) approach allowing, for the first time, to resolve mesoscale buoyancy-driven flame turbulence. The system is evolved to a quasi-steady state, and flow properties in the turbulent region, where turbulence is most isotropic, is analyzed in a co-moving frame of reference. We find evidence for strong buoyancy-driven adiabatic heating of fuel layers adjacent to the flame front. The heating results in a dramatic reduction of fuel ignition times by between $\approx$2 and more than about 5 orders of magnitude. The heating increases with the RTI forcing. The observed shortening of fuel burning timescales suggests a new source of energy is important inside fuel penetrating the flame brush. These regions are up to several hundred meters wide. On the basis of the previous results of turbulent combustion in SNe Ia, preconditioning required by the ZDDT mechanism can occur there.

Figures

Figures reproduced from arXiv: 2505.18482 by the authors.

Figure 1
Figure 1. The Reynolds stress tensor components are shown in a reference frame co-moving with the TPF region for all analyzed time slices for the LOD (top panel), MED (middle panel), and HID (bottom panel) models. The laterally-averaged radial (aligned with direction of gravity), Rxx, and the sum of the lateral, Ryy + Rzz, Reynolds stress tensor components are shown in the left and right columns, respectively. For clarity of … view at source ↗
Figure 2
Figure 2. Flooded-contour plot of the fuel mass fraction, Xfuel, defined in terms of the flame progress variable value, in the TPF region as a function of time for the LOD (left panel), MED (middle panel), and HID (right panel) model. The flooded-contours shaded from darkest gray to lightest gray correspond to maximum values of the flame progress variable of 1 × 10−5 , 1 × 10−3 , 0.01, 0.1, 0.3, and 0.999. Note that the horiz… view at source ↗
Figure 3
Figure 3. Model flame morphology and select flow structures inside the TPF region. The low density (LOD), medium density (MED), and high density (HID) model data at the final simulated times are shown in the left, middle, and right columns of panels, respectively. The top row shows an iso-volume of the flame progress variable between 0.4 and 0.6 colored by the x-component of the vorticity, while the bottom row shows the iso-v… view at source ↗
Figures from the paper (7 more)
Figure 4
Figure 4. Figure 4: Time evolution of the main turbulent flame properties. Evolution of the flame surface area increase factor, Sˆ f , and the turbulent flame speed, vf , are shown with solid and dashed lines, respectively, for LOD (thin lines), MED (medium lines), and HID (thick lines). …
Figure 5
Figure 5. Figure 5: Time evolution of the fractal dimension of the RT-unstable ther￾monuclear flame models, Df , in the TPF region. Fractal dimension was ob￾tained for the iso-contour value of the flame progress variable, ϕ = 0.5. The results indicate that the flame surface fractal dimens…
Figure 8
Figure 8. Figure 8: Evolution of the compressibility of TPF turbulence as a function of time shown in units of eddy turnover time, τeddy. The amount of compress￾ibility in the LOD, MED, and HID models is depicted with solid, dashed, and dotted lines, respectively. See text for discussion.…
Figure 9
Figure 9. Figure 9: Scatter plot rendering of the individual mesh cells in the TPF region in (a) LOD, (b) MED, and (c) HID flame models at a single time slice. The mesh cell distribution is shown in terms of flame progress variable in log10-scale along x-axis, velocity divergence along y-…
Figure 10
Figure 10. Figure 10: Time-averaged PDFs of ignition time for the material in the TPF region constrained in terms of the flame progress variable for the LOD (left panel), MED (middle panel), and HID (right panel) model. Each time-averaged PDF is shown as a dashed line, and the associated g…
Figure 11
Figure 11. Figure 11: Pseudo-color map of time-averaged joint PDFs of ignition time for the fuel layer adjacent to the flame front, shown in log10-scale, and the normalized gravitational acceleration projected in the direction normal to the flame surface, nf,g. The projected acceleration i…
Figure 12
Figure 12. Figure 12: Time-averaged PDFs of turbulent velocity fluctuations for the material in the TPF region for the LOD (left panel), MED (middle panel), and HID (right panel) model. Time-averaged velocity PDFs marginalized in terms of the flame progress variable are plotted with dark g…

Discussion (0). Continue with ORCID to comment.

Reference graph

Works this paper leans on

54 extracted references · 33 canonical work pages

  1. [1]

    J., Bell J

    Aspden A. J., Bell J. B., Day M. S., Woosley S. E., Zingale M., 2008, @doi [ ] 10.1086/592726 , https://ui.adsabs.harvard.edu/abs/2008ApJ...689.1173A 689, 1173

  2. [2]

    J., Bell J

    Aspden A. J., Bell J. B., Woosley S. E., 2010, @doi [ ] 10.1088/0004-637X/710/2/1654 , https://ui.adsabs.harvard.edu/abs/2010ApJ...710.1654A 710, 1654

  3. [3]

    B., Day M

    Bell J. B., Day M. S., Rendleman C. A., Woosley S. E., Zingale M., 2004, @doi [ ] 10.1086/420841 , https://ui.adsabs.harvard.edu/abs/2004ApJ...608..883B 608, 883

  4. [4]

    Fluid Mech.] 10.1017/jfm.2024.700 , 1004, A12

    Bentkamp L., Wilczek M., 2025, @doi [J. Fluid Mech.] 10.1017/jfm.2024.700 , 1004, A12

  5. [5]

    Q., Toschi F., 2010, @doi [J

    Benzi R., Biferale L., Fisher R., Lamb D. Q., Toschi F., 2010, @doi [J. Fluid Mech.] 10.1017/S002211201000056X , https://ui.adsabs.harvard.edu/abs/2010JFM...653..221B 653, 221

  6. [6]

    Boldyrev S., Nordlund A ., Padoan P., 2002, @doi [ ] 10.1086/340758 , https://doi.org/10.48550/arXiv.astro-ph/0111345 573, 678

  7. [7]

    Brooker E., Plewa T., Fenn D., 2021, @doi [ ] 10.1093/mnrasl/slaa141 , https://ui.adsabs.harvard.edu/abs/2021MNRAS.501L..23B 501, L23

  8. [8]

    C., et al., 2007, @doi [ ] 10.1086/510709 , https://ui.adsabs.harvard.edu/abs/2007ApJ...656..313C 656, 313

    Calder A. C., et al., 2007, @doi [ ] 10.1086/510709 , https://ui.adsabs.harvard.edu/abs/2007ApJ...656..313C 656, 313

Show all 54 references
  1. [9]

    W., Childs H., Hansen C., eds, , High Performance Visualization--Enabling Extreme-Scale Scientific Insight

    Childs H., et al., 2012, in Bethel E. W., Childs H., Hansen C., eds, , High Performance Visualization--Enabling Extreme-Scale Scientific Insight. CRC Press/Francis--Taylor Group, Boca Raton, p. 357

  2. [10]

    C., R \"o pke F

    Ciaraldi-Schoolmann F., Schmidt W., Niemeyer J. C., R \"o pke F. K., Hillebrandt W., 2009, @doi [ ] 10.1088/0004-637X/696/2/1491 , https://ui.adsabs.harvard.edu/abs/2009ApJ...696.1491C 696, 1491

  3. [11]

    R., R \"o pke F

    Ciaraldi-Schoolmann F., Seitenzahl I. R., R \"o pke F. K., 2013, @doi [ ] 10.1051/0004-6361/201321480 , https://ui.adsabs.harvard.edu/abs/2013A&A...559A.117C 559, A117

  4. [12]

    Fluids] 10.1063/1.870436 , https://ui.adsabs.harvard.edu/abs/2000PhFl...12.1843C 12, 1843

    Colin O., Ducros F., Veynante D., Poinsot T., 2000, @doi [Phys. Fluids] 10.1063/1.870436 , https://ui.adsabs.harvard.edu/abs/2000PhFl...12.1843C 12, 1843

  5. [13]

    J., Timmes F

    Dursi L. J., Timmes F. X., 2006, @doi [ ] 10.1086/500638 , https://ui.adsabs.harvard.edu/abs/2006ApJ...641.1071D 641, 1071

  6. [14]

    Fenn D., Plewa T., 2017, @doi [ ] 10.1093/mnras/stx524 , 468, 1361

  7. [15]

    Fryxell B., et al., 2000, , 131, 273

  8. [16]

    V., Kagan L., Sivashinsky G., 2021, @doi [ ] 10.1103/PhysRevE.103.033106 , https://ui.adsabs.harvard.edu/abs/2021PhRvE.103c3106G 103, 033106

    Gordon P. V., Kagan L., Sivashinsky G., 2021, @doi [ ] 10.1103/PhysRevE.103.033106 , https://ui.adsabs.harvard.edu/abs/2021PhRvE.103c3106G 103, 033106

  9. [17]

    P., 2019, @doi [ ] 10.1093/mnras/stz2080 , https://ui.adsabs.harvard.edu/abs/2019MNRAS.489...36H 489, 36

    Hicks E. P., 2019, @doi [ ] 10.1093/mnras/stz2080 , https://ui.adsabs.harvard.edu/abs/2019MNRAS.489...36H 489, 36

  10. [18]

    M., Wheeler J

    H\"oflich P., Khokhlov A. M., Wheeler J. C., 1995, @doi [ ] 10.1086/175656 , https://ui.adsabs.harvard.edu/abs/1995ApJ...444..831H 444, 831

  11. [19]

    M., 1991a, , https://ui.adsabs.harvard.edu/abs/1991A&A...245..114K 245, 114

    Khokhlov A. M., 1991a, , https://ui.adsabs.harvard.edu/abs/1991A&A...245..114K 245, 114

  12. [20]

    M., 1991b, , https://ui.adsabs.harvard.edu/abs/1991A&A...246..383K 246, 383

    Khokhlov A. M., 1991b, , https://ui.adsabs.harvard.edu/abs/1991A&A...246..383K 246, 383

  13. [21]

    Khokhlov A., 1993, @doi [ ] 10.1086/187141 , https://ui.adsabs.harvard.edu/abs/1993ApJ...419L..77K 419, L77

  14. [22]

    M., 1995, @doi [ ] 10.1086/176091 , https://ui.adsabs.harvard.edu/abs/1995ApJ...449..695K 449, 695

    Khokhlov A. M., 1995, @doi [ ] 10.1086/176091 , https://ui.adsabs.harvard.edu/abs/1995ApJ...449..695K 449, 695

  15. [23]

    M., Oran E

    Khokhlov A. M., Oran E. S., Wheeler J. C., 1997, @doi [ ] 10.1086/303815 , https://ui.adsabs.harvard.edu/abs/1997ApJ...478..678K 478, 678

  16. [24]

    N., 1941, in Dokl

    Kolmogorov A. N., 1941, in Dokl. Akad. Nauk SSSR. pp 301--305

  17. [25]

    D., Lifshitz E

    Landau L. D., Lifshitz E. M., 1987, Fluid Mechanics. Butterworth-Heinemann, http://www.worldcat.org/isbn/0750627670

  18. [26]

    E., 2009, @doi [J

    Lee D., Deane A. E., 2009, @doi [J. Comput. Phys.] 10.1016/j.jcp.2008.08.026 , https://ui.adsabs.harvard.edu/abs/2009JCoPh.228..952L 228, 952

  19. [27]

    M., Hillebrandt W., Woosley S

    Lisewski A. M., Hillebrandt W., Woosley S. E., 2000, @doi [ ] 10.1086/309158 , https://ui.adsabs.harvard.edu/abs/2000ApJ...538..831L 538, 831

  20. [28]

    Livne E., Arnett D., 1993, @doi [ ] 10.1086/187044 , https://ui.adsabs.harvard.edu/abs/1993ApJ...415L.107L 415, L107

  21. [29]

    Fluids] 10.1063/1.2166455 , 18, 015103

    Mouri H., Takaoka M., Hori A., Kawashima Y., 2006, @doi [Phys. Fluids] 10.1063/1.2166455 , 18, 015103

  22. [30]

    C., Woosley S

    Niemeyer J. C., Woosley S. E., 1997, @doi [ ] 10.1086/303544 , https://ui.adsabs.harvard.edu/abs/1997ApJ...475..740N 475, 740

  23. [31]

    S., Gamezo V

    Oran E. S., Gamezo V. N., 2007, @doi [Combust. Flame] https://doi.org/10.1016/j.combustflame.2006.07.010 , 148, 4

  24. [32]

    C., Scalo J., 2008, @doi [ ] 10.1086/588575 , https://ui.adsabs.harvard.edu/abs/2008ApJ...681..470P 681, 470

    Pan L., Wheeler J. C., Scalo J., 2008, @doi [ ] 10.1086/588575 , https://ui.adsabs.harvard.edu/abs/2008ApJ...681..470P 681, 470

  25. [33]

    Plewa T., 2007, @doi [ ] 10.1086/511412 , https://ui.adsabs.harvard.edu/abs/2007ApJ...657..942P 657, 942

  26. [34]

    Y., Chambers J., Ahmed K., Gamezo V

    Poludnenko A. Y., Chambers J., Ahmed K., Gamezo V. N., Taylor B. D., 2019, @doi [ ] 10.1126/science.aau7365 , 366, eaau7365

  27. [35]

    M., 1993, @doi [Nucl

    Polyakov A. M., 1993, @doi [Nucl. Phys. B] 10.1016/0550-3213(93)90656-A , https://ui.adsabs.harvard.edu/abs/1993NuPhB.396..367P 396, 367

  28. [36]

    K., 2007, @doi [ ] 10.1086/520830 , https://ui.adsabs.harvard.edu/abs/2007ApJ...668.1103R 668, 1103

    R \"o pke F. K., 2007, @doi [ ] 10.1086/520830 , https://ui.adsabs.harvard.edu/abs/2007ApJ...668.1103R 668, 1103

  29. [37]

    C., R \"o pke F

    Schmidt W., Ciaraldi-Schoolmann F., Niemeyer J. C., R \"o pke F. K., Hillebrandt W., 2010, @doi [ ] 10.1088/0004-637X/710/2/1683 , https://ui.adsabs.harvard.edu/abs/2010ApJ...710.1683S 710, 1683

  30. [38]

    She Z.-S., Leveque E., 1994, @doi [ ] 10.1103/PhysRevLett.72.336 , https://ui.adsabs.harvard.edu/abs/1994PhRvL..72..336S 72, 336

  31. [39]

    L., 1985, @doi [Phys

    Takabe H., Mima K., Montierth L., Morse R. L., 1985, @doi [Phys. Fluids] 10.1063/1.865099 , https://ui.adsabs.harvard.edu/abs/1985PhFl...28.3676T 28, 3676

  32. [40]

    X., Swesty F

    Timmes F. X., Swesty F. D., 2000, @doi [ ] 10.1086/313304 , https://ui.adsabs.harvard.edu/abs/2000ApJS..126..501T 126, 501

  33. [41]

    X., Hoffman R

    Timmes F. X., Hoffman R. D., Woosley S. E., 2000, @doi [ ] 10.1086/313407 , https://ui.adsabs.harvard.edu/abs/2000ApJS..129..377T 129, 377

  34. [42]

    K., 2018, Physics of Buoyant Flows

    Verma M. K., 2018, Physics of Buoyant Flows. World Scientific, @doi 10.1142/10928 , https://doi.org/10.1142/10928

  35. [43]

    Methods] 10.1038/s41592-019-0686-2 , https://rdcu.be/b08Wh 17, 261

    Virtanen P., et al., 2020, @doi [Nat. Methods] 10.1038/s41592-019-0686-2 , https://rdcu.be/b08Wh 17, 261

  36. [44]

    Wong T. L. S., Schwab J., 2019, @doi [ ] 10.3847/1538-4357/ab1b49 , https://ui.adsabs.harvard.edu/abs/2019ApJ...878..100W 878, 100

  37. [45]

    E., 2007, @doi [ ] 10.1086/520835 , https://ui.adsabs.harvard.edu/abs/2007ApJ...668.1109W 668, 1109

    Woosley S. E., 2007, @doi [ ] 10.1086/520835 , https://ui.adsabs.harvard.edu/abs/2007ApJ...668.1109W 668, 1109

  38. [46]

    E., Kerstein A

    Woosley S. E., Kerstein A. R., Sankaran V., Aspden A. J., R \"o pke F. K., 2009, @doi [ ] 10.1088/0004-637X/704/1/255 , https://ui.adsabs.harvard.edu/abs/2009ApJ...704..255W 704, 255

  39. [47]

    E., Kerstein A

    Woosley S. E., Kerstein A. R., Aspden A. J., 2011, @doi [ ] 10.1088/0004-637X/734/1/37 , https://ui.adsabs.harvard.edu/abs/2011ApJ...734...37W 734, 37

  40. [48]

    Yakhot V., 1998, @doi [ ] 10.1103/PhysRevE.57.1737 , https://ui.adsabs.harvard.edu/abs/1998PhRvE..57.1737Y 57, 1737

  41. [49]

    B., Librovich V

    Zel'dovich Y. B., Librovich V. B., Makhviladze G. M., Sivashinskil G. I., 1970, @doi [J. Appl. Mech. Tech. Phys.] 10.1007/BF00908106 , 11, 264

  42. [50]

    Zhang J., Messer O. E. B., Khokhlov A. M., Plewa T., 2007, @doi [ ] 10.1086/510145 , https://ui.adsabs.harvard.edu/abs/2007ApJ...656..347Z 656, 347

  43. [51]

    V., 2007, @doi [ ] 10.1086/511525 , https://ui.adsabs.harvard.edu/abs/2007ApJS..169..386Z 169, 386

    Zhiglo A. V., 2007, @doi [ ] 10.1086/511525 , https://ui.adsabs.harvard.edu/abs/2007ApJS..169..386Z 169, 386

  44. [52]

    V., 2009, Phd dissertation, University of Chicago, Chicago, IL, @doi 10.48550/arXiv.0906.0393

    Zhiglo A. V., 2009, Phd dissertation, University of Chicago, Chicago, IL, @doi 10.48550/arXiv.0906.0393

  45. [53]

    E., Rendleman C

    Zingale M., Woosley S. E., Rendleman C. A., Day M. S., Bell J. B., 2005, @doi [ ] 10.1086/433164 , 632, 1021

  46. [54]

    write newline

    " write newline "" before.all 'output.state := FUNCTION fin.entry write newline FUNCTION new.block output.state before.all = 'skip after.block 'output.state := if FUNCTION new.sentence output.state after.block = 'skip output.state before.all = 'skip after.sentence 'output.stat...

Pith tools

Reviewed August 7, 2026 · model on record in the stance chip above.