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Star formation quenching stages of active and non-active galaxies

2021· article· en· W3132122625 on OpenAlexafffund
V. Kalinova, Dario Colombo, S. F. Sánchez, Keiichi Kodaira, R. García-Benito, R. M. González Delgado, Erik Rosolowsky, E. A. D. Lacerda

Bibliographic record

VenueSpringer Link (Chiba Institute of Technology) · 2021
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaDeutsche Forschungsgemeinschaft
KeywordsPhysicsActive galactic nucleusAstrophysicsStar formationGalaxyAstronomyPeculiar galaxyDiscLuminous infrared galaxyQuenching (fluorescence)Elliptical galaxyLenticular galaxy

Abstract

fetched live from OpenAlex

The mechanisms that bring galaxies to strongly reduce their star formation activity (star-formation quenching) remain poorly understood. To better study galaxy evolution, we propose a classification based on maps of ionised hydrogen distribution traced by the kiloparsec-resolved, equivalent width of Hα maps, and the nuclear activity of the galaxies using information from the Baldwin-Philips-Terlevich diagnostic diagrams. Using these tools, we group a sample of 238 galaxies from the Calar Alto Legacy Integral Field spectroscopy Area survey in six quenching stages (QSs): (i) objects dominated by recent star formation; (ii) systems that present a quiescent-nuclear-ring structure in their centre; (iii) galaxies that are centrally quiescent; (iv) galaxies with no clear pattern in their ionisation gas distribution (mixed); (v) systems that posses only a few star-forming regions (nearly retired), or (vi) galaxies that are completely quiescent (fully retired). Regarding their nuclear activity, we further divide the galaxies into two groups: active systems that host a weak or strong active galactic nucleus (AGN) at their centre, and non-active objects. Galaxies grouped into quenching-stage classes occupy specific locations on the star-formation-rate versus stellar mass diagram. The ‘blue cloud’ is populated by the star-forming and the quiescent-nuclear-ring galaxies, the ‘green valley’ is populated by centrally quiescent and mixed systems, and the ‘red sequence’ by the nearly- and fully retired objects. Generally, galaxies that host a weak or strong AGN show properties comparable to those of their non-active counterparts at the same QSs, except for the AGN-hosting star-forming systems. The degree of star-formation quenching increases along the present emission-line pattern sequence from star-forming to fully retired. The proposed emission-line classes reinforce the ‘inside-out’ quenching scenario, which foresees that the suppression of star formation begins from the central regions of the galaxies.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.219
Threshold uncertainty score0.816

Codex and Gemma teacher scores by category

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

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 head0.008
GPT teacher head0.219
Teacher spread0.210 · 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

Citations25
Published2021
Admission routes2
Has abstractyes

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