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Record W3199275390 · doi:10.1051/0004-6361/202140695

Stellar structures, molecular gas, and star formation across the PHANGS sample of nearby galaxies

2021· article· en· W3199275390 on OpenAlexafffund
Miguel Querejeta, Eva Schinnerer, Sharon E. Meidt, Jiayi Sun, Adam K. Leroy, Éric Emsellem, Ralf S. Klessen, J. C. Muñoz-Mateos, H. Salo, E. Laurikainen, Ivana Bešlić, Guillermo A. Blanc, Mélanie Chevance, Daniel A. Dale, Cosima Eibensteiner, Christopher M. Faesi, Axel García-Rodríguez, Simon C. O. Glover, Kathryn Grasha, Jonathan D. Henshaw, Cinthya N. Herrera, Annie Hughes, Kathryn Kreckel, J. M. Diederik Kruijssen, Daizhong Liu, E. J. Murphy, Hsi-An Pan, J. Pety, Alessandro Razza, Erik Rosolowsky, Toshiki Saito, Andreas Schruba, A. Usero, Elizabeth J. Watkins, Thomas G. Williams

Bibliographic record

VenueAstronomy and Astrophysics · 2021
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsUniversity of Alberta
FundersInstitut National de Physique Nucléaire et de Physique des ParticulesNational Institutes of Natural SciencesNatural Sciences and Engineering Research Council of CanadaNational Astronomical Observatory of JapanMinisterio de Ciencia e InnovaciónCentre National de la Recherche ScientifiqueDeutsche ForschungsgemeinschaftCalifornia Institute of TechnologyEuropean CommissionJet Propulsion LaboratoryCentre National d’Etudes SpatialesAssociated UniversitiesMinisterio de Ciencia, Innovación y UniversidadesKorea Astronomy and Space Science InstituteNational Aeronautics and Space AdministrationAcademy of FinlandAgencia Estatal de InvestigaciónNational Radio Astronomy ObservatoryNational Science Foundation
KeywordsStar formationPhysicsAstrophysicsSpiral galaxyGalaxyAstronomy

Abstract

fetched live from OpenAlex

We identify stellar structures in the PHANGS sample of 74 nearby galaxies and construct morphological masks of sub-galactic environments based on Spitzer 3.6 μ m images. At the simplest level, we distinguish five environments: centres, bars, spiral arms, interarm regions, and discs without strong spirals. Slightly more sophisticated masks include rings and lenses, which are publicly released but not explicitly used in this paper. We examine trends with environment in the molecular gas content, star formation rate, and depletion time using PHANGS–ALMA CO(2–1) intensity maps and tracers of star formation. The interarm regions and discs without strong spirals clearly dominate in area, whereas molecular gas and star formation are quite evenly distributed among the five basic environments. We reproduce the molecular Kennicutt–Schmidt relation with a slope compatible with unity within the uncertainties and without significant slope differences among environments. In contrast to what has been suggested by early studies, we find that bars are not always deserts devoid of gas and star formation, but instead they show large diversity. Similarly, spiral arms do not account for most of the gas and star formation in disc galaxies, and they do not have shorter depletion times than the interarm regions. Spiral arms accumulate gas and star formation, without systematically boosting the star formation efficiency. Centres harbour remarkably high surface densities and on average shorter depletion times than other environments. Centres of barred galaxies show higher surface densities and wider distributions compared to the outer disc; yet, depletion times are similar to unbarred galaxies, suggesting highly intermittent periods of star formation when bars episodically drive gas inflow, without enhancing the central star formation efficiency permanently. In conclusion, we provide quantitative evidence that stellar structures in galaxies strongly affect the organisation of molecular gas and star formation, but their impact on star formation efficiency is more subtle.

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 score0.055
Threshold uncertainty score0.757

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 head0.005
GPT teacher head0.202
Teacher spread0.196 · 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

Citations141
Published2021
Admission routes2
Has abstractyes

Explore more

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