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Record W4289772963 · doi:10.1051/0004-6361/201832584

The Lyman Alpha Reference Sample

2018· article· en· W4289772963 on OpenAlexaboutno aff
Genoveva Micheva, Göran Östlin, Erik Zackrisson, Matthew Hayes, Jens Melinder, L. Guaita, John M. Cannon, Joanna S. Bridge, D. Kunth, Andreas Sandberg

Bibliographic record

VenueAstronomy and Astrophysics · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsnot available
FundersCentre National de la Recherche ScientifiqueJet Propulsion LaboratoryCentre National d’Etudes SpatialesInstitut national des sciences de l'UniversVetenskapsrådetNational Aeronautics and Space AdministrationKorea Astronomy and Space Science InstituteSwedish National Space AgencyKnut och Alice Wallenbergs StiftelseSpace Telescope Science InstituteCalifornia Institute of TechnologyAcademia Sinica
KeywordsAstrophysicsPhysicsGalaxyAstronomyPhotometry (optics)RedshiftSurface brightnessElliptical galaxyPopulationStars

Abstract

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Context. The Lyman α Reference Sample (LARS) of 14 star-forming galaxies offers a wealth of insight into the workings of these local analogs to high-redshift star-forming galaxies. The sample has been well-studied in terms of Lyα and other emission line properties, such as H I mass, gas kinematics, and morphology. Aims. We analyze deep surface photometry of the LARS sample in UBIK broadband imaging obtained at the Nordic Optical Telescope and the Canada-France-Hawaii Telescope, and juxtaposition their derived properties with a sample of local high-redshift galaxy analogs, namely, with blue compact galaxies (BCGs). Methods. We construct radial surface brightness and color profiles with both elliptical and isophotal integration, as well as RGB images, deep contours, color maps, a burst fraction estimate, and a radial mass-to-light ratio profile for each LARS galaxy. Standard morphological parameters like asymmetry, clumpiness, the Gini and M20 coefficients are also obtained and analyzed, as well as isophotal asymmetry profiles for each galaxy. In this context, we compare the LARS sample to the properties of the BCG sample and highlight the differences. Results. Several of these diagnostics indicate that the LARS galaxies have highly disturbed morphologies even at the level of the faintest outer isophotes, with no hint at a regular underlying population, as found in many BCG sample galaxies. The ground-based photometry reaches isophotes down to ~28 mag arcsec−2, while the space-based data reach only ~26 mag arcsec−2. The ground-based observations therefore reveal previously unexplored isophotes of the LARS galaxies. The burst fraction estimate suggests a spatially more extended burst region in LARS than in the BCGs. Comparison to stellar evolutionary models in color–color diagrams reveals complex behavior of the radial color profiles, often inconsistent with a single stellar population of any age and metallicity, but instead suggesting a mixture of at least two stellar populations with a typical young mass fraction in the range 0.1–1%. Conclusions. The galaxies in the LARS sample appear to be in earlier stages of a merger event compared to the BCGs. Standard morphological diagnostics like asymmetry, clumpiness, Gini and M20 coefficients cannot separate the two samples, although an isophotal asymmetry profile successfully captures the average difference in morphology. These morphological diagnostics do not show any correlation with the equivalent width or the escape fraction of Lyman Alpha.

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)0.002
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 score0.010
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0100.005

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 head0.211
Teacher spread0.201 · 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

Citations7
Published2018
Admission routes1
Has abstractyes

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