MétaCan
Menu
Back to cohort
Record W1823203199

Type IIn Supernova Detections in z ~ 2 Lyman Break Galaxies: Probing the IMF Directly

2011· book-chapter· en· W1823203199 on OpenAlexaboutno aff
Jeff Cooke, M. Sullivan, E. J. Barton, Richard S. Ellis, A. Gal‐Yam

Bibliographic record

VenueCaltechAUTHORS (California Institute of Technology) · 2011
Typebook-chapter
Languageen
FieldPhysics and Astronomy
TopicGamma-ray bursts and supernovae
Canadian institutionsnot available
FundersCentre National de la Recherche Scientifique
KeywordsPhysicsAstrophysicsGalaxySupernovaRedshiftAstronomyStellar populationStar formationPopulation
DOInot available

Abstract

fetched live from OpenAlex

Type IIn supernovae (SNe IIn) exhibit luminous ultraviolet continua during outburst and luminous, long-lived narrow ultraviolet and optical emission lines attributed to circumstellar interaction. These properties have enabled successful detections at z ~ 2 in archival imaging and continued investigations from late-time spectroscopy. Because SNe IIn are believed to have massive (≳50M_☉) progenitors, searches in the well-studied Lyman break galaxy (LBG) host population offer the prospect of testing the form of the high-redshift stellar initial mass function (IMF) in a high density star formation environment directly. I briefly discuss our z ~ 2 photometric detection method targeting LBGs in the Canada-France-Hawaii Telescope Legacy Survey (CFHTLS) and present data from the first 6 confirmed z ~ 2 SNe IIn pulled from 30 photometric SN candidates. A comparison of the color and magnitude distributions of the SN host galaxies to that of the full LBG sample finds that z ~ 2 SNe preferentially occur in bluer, fainter galaxies. I conclude with a discussion of an approach that uses the CFHTLS pilot sample to provide a first estimate of the form of the high-redshift IMF. Upcoming deep synoptic imaging surveys will greatly improve z ~ 2 SNe IIn statistics from ~10^5 expected detections and future large aperture space- and ground-based telescopes will have the sensitivities to extend this work to z ≳ 6.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.920
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
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 head0.020
GPT teacher head0.229
Teacher spread0.209 · 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.

Study designNot applicable
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

Citations0
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueCaltechAUTHORS (California Institute of Technology)Same topicGamma-ray bursts and supernovaeFrench-language works237,207