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Record W4408348981 · doi:10.1093/mnras/staf261

Non-LTE radiative transfer simulations: improved agreement of the double detonation with normal Type Ia supernovae

2025· article· en· W4408348981 on OpenAlexaff
Christine E. Collins, Luke J. Shingles, Stuart Sim, F. P. Callan, Sabrina Gronow, W. Hillebrandt, M. Kromer, Rüdiger Pakmor, F. K. Röpke

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGamma-ray bursts and supernovae
Canadian institutionsTrinity College
FundersH2020 European Research CouncilGauss Centre for SupercomputingKlaus Tschira StiftungScience and Technology Facilities CouncilEuropean CommissionDepartment for the EconomyHorizon 2020 Framework ProgrammeDeutsche ForschungsgemeinschaftUK Research and InnovationDurham UniversityDepartment for Business, Energy and Industrial Strategy, UK Government
KeywordsPhysicsSupernovaRadiative transferAstrophysicsDetonationType (biology)Explosive materialOptics

Abstract

fetched live from OpenAlex

ABSTRACT The double detonation is a widely discussed explosion mechanism for Type Ia supernovae, whereby a helium shell detonation ignites a secondary detonation in the carbon/oxygen core of a white dwarf. Even for modern models that invoke relatively small He shell masses, many previous studies have found that the products of the helium shell detonation lead to discrepancies with normal Type Ia supernovae, such as strong Ti ii absorption features, extremely red light curves, and too large a variation with viewing direction. It has been suggested that non-local thermodynamic equilibrium (non-LTE) effects may help reduce these discrepancies between observations. Here we carry out full non-LTE radiative transfer simulations for a recent double detonation model with a relatively small helium mass of 0.05 ${\rm M}_{\odot}$. We construct 1D models representative of directions in a 3D explosion model to give an indication of viewing angle dependence, and show that at early times up to around maximum light, this gives a reasonable approximation of the different directions in the 3D model. This approximation breaks down once the ejecta start to become optically thin. The full non-LTE treatment leads to improved agreement between the models and observations. The light curves become less red, due to reduced absorption by the helium shell detonation products, since these species are more highly ionized. Additionally, the expected variation with observer direction is reduced. The full non-LTE treatment shows promising improvements and reduces the discrepancies between the double detonation models and observations of normal Type Ia supernovae.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.218
Teacher spread0.211 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2025
Admission routes1
Has abstractyes

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