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Record W2087157906 · doi:10.1088/0004-6256/142/2/45

EVIDENCE FOR PRE-EXISTING DUST IN THE BRIGHT TYPE IIn SN 2010jl

2011· article· en· W2087157906 on OpenAlexaff
Jennifer E. Andrews, Geoffrey C. Clayton, R. Wesson, Ben Sugerman, M. J. Barlow, James L. Clem, Barbara Ercolano, J. Fabbri, J. S. Gallagher, A. U. Landolt, M. Meixner, Masaaki Otsuka, D. Riebel, D. L. Welch

Bibliographic record

VenueThe Astronomical Journal · 2011
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGamma-ray bursts and supernovae
Canadian institutionsMcMaster University
FundersScience and Technology Facilities Council
KeywordsAstrophysicsPhysicsTorusGalaxyFlux (metallurgy)SkyCircumstellar dustEvent (particle physics)Radiative transferCircumstellar diskAstronomyCosmic dustStarsOpticsGeometryMaterials science

Abstract

fetched live from OpenAlex

SN 2010jl was an extremely bright, Type IIn supernova (SN) which showed a significant infrared (IR) excess no later than 90 days after explosion. We have obtained Spitzer 3.6 and 4.5 μm and JHK observations of SN 2010jl ~90 days post-explosion. Little to no reddening in the host galaxy indicated that the circumstellar material lost from the progenitor must lie in a torus inclined out of the plane of the sky. The likely cause of the high mid-IR flux is the reprocessing of the initial flash of the SN by pre-existing circumstellar dust. Using a three-dimensional Monte Carlo radiative-transfer code, we have estimated that between 0.03 and 0.35 M ☉ of dust exists in a circumstellar torus around the SN located 6 × 1017 cm away from the SN and inclined between 60° and 80° to the plane of the sky. On day 90, we are only seeing the illumination of approximately 5% of this torus, and expect to see an elevated IR flux from this material up until day ~ 450. It is likely this dust was created in a luminous blue variable (LBV) like mass-loss event of more than 3 M ☉, which is large but consistent with other LBV progenitors such as η Carinae.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.042
Threshold uncertainty score0.798

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.113
GPT teacher head0.317
Teacher spread0.203 · 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 teacher head, 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

Citations78
Published2011
Admission routes1
Has abstractyes

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