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Record W4403861214 · doi:10.1051/0004-6361/202449923

Photometry and kinematics of dwarf galaxies from the Apertif H I survey

2024· article· en· W4403861214 on OpenAlexfundno aff
Barbara Šiljeg, Elizabeth A. K. Adams, Filippo Fraternali, K.M. Hess, Tom Oosterloo, A. Marasco, B. Adebahr, Helga Dénes, Julián Garrido, D. M. Lucero, Pavel E. Mancera Piña, Vanessa A. Moss, Manuel Parra-Royón, Anastasia A. Ponomareva, S. Sánchez–Expósito, J. M. van der Hulst

Bibliographic record

VenueAstronomy and Astrophysics · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstronomy and Astrophysical Research
Canadian institutionsnot available
FundersPlanetary Science DivisionEuropean Regional Development FundScience and Technology Facilities CouncilJet Propulsion LaboratorySmithsonian Astrophysical ObservatoryMax-Planck-Institut für AstronomieNederlandse Organisatie voor Wetenschappelijk OnderzoekQueen's UniversityInstituto de Astrofísica de AndalucíaAgencia Estatal de InvestigaciónScience Mission DirectorateEuropean CommissionASTRONMinisterio de Ciencia e InnovaciónSpace Telescope Science InstituteMinisterio de Ciencia, Innovación y UniversidadesQueen's University BelfastNational Central UniversityNational Aeronautics and Space AdministrationEötvös Loránd TudományegyetemCalifornia Institute of TechnologyJohns Hopkins UniversityDurham UniversitySmithsonian InstitutionJunta de AndalucíaNational Science Foundation
KeywordsPhysicsAstrophysicsPhotometry (optics)Dwarf galaxyKinematicsAstronomyGalaxyDwarf spheroidal galaxyStarsInteracting galaxyClassical mechanics

Abstract

fetched live from OpenAlex

Context. Understanding the dwarf galaxy population in low density environments (in the field) is crucial for testing the current Λ Cold Dark Matter cosmological model. The increase in diversity toward low-mass galaxies is seen as an increase in the scatter of scaling relations, such as the stellar mass–size and the baryonic Tully-Fisher relation (BTFR), and is also demonstrated by recent in-depth studies of an extreme sub-class of dwarf galaxies with low surface brightnesses but large physical sizes called ultra-diffuse galaxies (UDGs). Aims. We aim to select dwarf galaxies independent of their stellar content and to make a detailed study of their gas and stellar properties. We selected galaxies from the APERture Tile In Focus (Apertif) H I survey and applied a constraint on their i -band absolute magnitude in order to exclude high-mass systems. The sample consists of 24 galaxies, 22 of which are resolved in H I by at least three beams, and they span H I mass ranges of 8.6 ≲ log( M H I / M ⊙ ) ≲ 9.7 and a stellar mass range of 8.0 ≲ log( M ⋆ / M ⊙ )≲9.7 (with only three galaxies having log ( M ⋆ / M ⊙ ) > 9). Methods. We determined the geometrical parameters of the H I and stellar disks, built kinematic models from the H I data using 3D Barolo, and extracted surface brightness profiles in the g -, r -, and i -bands from the Pan-STARRS 1 photometric survey. We used these measurements to place our galaxies on the stellar mass–size relation and the BTFR, and we compared them with other samples from the literature. Results. We find that at a fixed stellar mass, our H I -selected dwarfs have larger optical effective radii than isolated optically selected dwarfs from the literature, and we found misalignments between the optical and H I morphologies for some of our sample. For most of our galaxies, we used the H I morphology to determine their kinematics, and we stress that deep optical observations are needed to trace the underlying stellar disks. Standard dwarfs in our sample follow the same BTFR of high-mass galaxies, whereas UDGs are slightly offset toward lower rotational velocities, in qualitative agreement with results from previous studies. Finally, our sample features a fraction (25%) of dwarf galaxies in pairs that is significantly larger with respect to previous estimates based on optical spectroscopic data.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.813
Threshold uncertainty score0.894

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 communication0.0000.000
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 head0.017
GPT teacher head0.263
Teacher spread0.246 · 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

Citations7
Published2024
Admission routes1
Has abstractyes

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