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Record W4384807961 · doi:10.1093/mnras/stad2170

Helium as a signature of the double detonation in Type Ia supernovae

2023· article· en· W4384807961 on OpenAlexfundno aff
Christine E. Collins, Stuart Sim, Luke J. Shingles, Sabrina Gronow, F. K. Röpke, Rüdiger Pakmor, I. R. Seitenzahl, M. Kromer

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGamma-ray bursts and supernovae
Canadian institutionsnot available
FundersH2020 European Research CouncilOffice of International Science and EngineeringEuropean Cooperation in Science and TechnologyGauss Centre for SupercomputingKlaus Tschira StiftungDeutsche ForschungsgemeinschaftQueen's University BelfastScience and Technology Facilities CouncilQueen's UniversityEuropean CommissionDepartment for the EconomyNational Science Foundation
KeywordsPhysicsSupernovaSignature (topology)HeliumAstrophysicsDetonationType (biology)AstronomyExplosive materialAtomic physics

Abstract

fetched live from OpenAlex

ABSTRACT The double detonation is a widely discussed mechanism to explain Type Ia supernovae from explosions of sub-Chandrasekhar mass white dwarfs. In this scenario, a helium detonation is ignited in a surface helium shell on a carbon/oxygen white dwarf, which leads to a secondary carbon detonation. Explosion simulations predict high abundances of unburnt helium in the ejecta, however, radiative transfer simulations have not been able to fully address whether helium spectral features would form. This is because helium can not be sufficiently excited to form spectral features by thermal processes, but can be excited by collisions with non-thermal electrons, which most studies have neglected. We carry out a full non-local thermodynamic equilibrium radiative transfer simulation for an instance of a double detonation explosion model, and include a non-thermal treatment of fast electrons. We find a clear He i λ10830 feature which is strongest in the first few days after explosion and becomes weaker with time. Initially this feature is blended with the Mg ii λ10927 feature but over time separates to form a secondary feature to the blue wing of the Mg ii λ10927 feature. We compare our simulation to observations of iPTF13ebh, which showed a similar feature to the blue wing of the Mg ii λ10927 feature, previously identified as C i. Our simulation shows a good match to the evolution of this feature and we identify it as high velocity He i λ10830. This suggests that He i λ10830 could be a signature of the double detonation scenario.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.010
GPT teacher head0.230
Teacher spread0.220 · 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 designObservational
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

Citations13
Published2023
Admission routes1
Has abstractyes

Explore more

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