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The diversity of strongly interacting Type IIn supernovae

2025· article· en· W6884513552 on OpenAlexfundno aff

Bibliographic record

VenueSpringer Link (Chiba Institute of Technology) · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGamma-ray bursts and supernovae
Canadian institutionsnot available
FundersEuropean Social FundPlanetary Science DivisionDeutsches Elektronen-SynchrotronInstituto de Astrofísica de CanariasMax-Planck-Institut für AstronomieInstituto Nacional de Astrofísica, Óptica y ElectrónicaEötvös Loránd TudományegyetemStockholms UniversitetHáskóli ÍslandsUniversitetet i OsloLos Alamos National LaboratoryEuropean Space AgencyJohns Hopkins UniversityMinistero dell’Istruzione, dell’Università e della RicercaQueen's UniversityEuropean CommissionMinisterio de Ciencia e InnovaciónAgencia Nacional de Investigación y DesarrolloTrinity College DublinGeneralitat de CatalunyaDurham UniversityIstituto Nazionale di AstrofisicaNational Science FoundationLiverpool John Moores UniversitySmithsonian InstitutionNational Natural Science Foundation of ChinaNational Key Research and Development Program of ChinaUniversidad Nacional Autónoma de MéxicoSpace Telescope Science InstituteCalifornia Institute of TechnologyInstitut National de Physique Nucléaire et de Physique des ParticulesScience and Technology Facilities CouncilTurun YliopistoAarhus UniversitetGordon and Betty Moore FoundationQueen's University BelfastNational Aeronautics and Space AdministrationNational Central UniversityAgencia Estatal de InvestigaciónScience Mission DirectorateJavna Agencija za Raziskovalno Dejavnost RS
KeywordsEjectaSupernovaLight curveKinetic energyLuminosityStarsNeutrinoParticle accelerationType (biology)

Abstract

fetched live from OpenAlex

Context. At late stages, massive stars experience strong mass-loss rates, losing their external layers and thus producing a dense H-rich circumstellar medium (CSM). After the explosion of a massive star, the collision and continued interaction of the supernova (SN) ejecta with the CSM power the SN light curve through the conversion of kinetic energy into radiation. When the interaction is strong, the light curve shows a broad peak and high luminosity that lasts for several months. For these SNe, the spectral evolution is also slower compared to non-interacting SNe. Notably, energetic shocks between the ejecta and the CSM create the ideal conditions for particle acceleration and the production of high-energy (HE) neutrinos above 1 TeV. Aims. We study four strongly interacting Type IIn SNe, 2021acya, 2021adxl, 2022qml, and 2022wed, in order to highlight their peculiar characteristics, derive the kinetic energy of their explosion and the characteristics of the CSM, infer clues on the possible progenitors and their environment, and relate them to the production of HE neutrinos. Methods. We analysed spectro-photometric data of a sample of interacting SNe to determine their common characteristics and derive the physical properties (radii and masses) of the CSM and the ejecta kinetic energies and compare them to HE neutrino production models. Results. The SNe analysed in this sample exploded in dwarf star-forming galaxies, and they are consistent with energetic explosions and strong interaction with the surrounding CSM. For SNe 2021acya and 2022wed, we find high CSM masses and mass-loss rates, linking them to very massive progenitors. For SN 2021adxl, the spectral analysis and less extreme CSM mass suggest a stripped-envelope massive star as a possible progenitor. SN 2022qml is marginally consistent with being a Type Ia thermonuclear explosion embedded in a dense CSM. The mass-loss rates for all the SNe are consistent with the expulsion of several solar masses of material during eruptive episodes in the last few decades before the explosion. Finally, we find that the SNe in our sample are marginally consistent with HE neutrino production.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.242
Teacher spread0.229 · 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".

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Citations0
Published2025
Admission routes1
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