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Record W2982217689 · doi:10.1093/mnras/stz2903

Star formation at the edge of the Local Group: a rising star formation history in the isolated galaxy WLM

2019· article· en· W2982217689 on OpenAlexaff
Saundra Albers, Daniel R. Weisz, Andrew A. Cole, Andrew E. Dolphin, Evan D. Skillman, Benjamin F. Williams, Michael Boylan-Kolchin, James S. Bullock, Julianne J. Dalcanton, Philip F. Hopkins, Ryan Leaman, Alan W. McConnachie, Mark Vogelsberger, Andrew Wetzel

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsHerzberg Institute of Astrophysics
FundersNational Science Foundation of Sri LankaNational Aeronautics and Space Administration
KeywordsPhysicsAstrophysicsLocal GroupStar formationGalaxyDwarf galaxyAstronomyStellar massGlobular clusterGalaxy formation and evolutionReionizationAdvanced Camera for SurveysHaloRedshift

Abstract

fetched live from OpenAlex

ABSTRACT We present the star formation history (SFH) of the isolated (D ∼ 970 kpc) Local Group dwarf galaxy Wolf–Lundmark–Melotte (WLM) measured from colour–magnitude diagrams (CMDs) constructed from deep Hubble Space Telescope imaging. Our observations include a central ($0.5 \, r_h$) and outer field ($0.7 \, r_h$) that reach below the oldest main-sequence turn-off. WLM has no early dominant episode of star formation: 20 per cent of its stellar mass formed by ∼12.5 Gyr ago ($z$ ∼ 5). It also has an SFR that rises to the present with 50 per cent of the stellar mass within the most recent 5 Gyr ($z$ < 0.7). There is evidence of a strong age gradient: the mean age of the outer field is 5 Gyr older than the inner field despite being only 0.4 kpc apart. Some models suggest such steep gradients are associated with strong stellar feedback and dark-matter core creation. The SFHs of real isolated dwarf galaxies and those from the Feedback in Realistic Environment suite are in good agreement for M⋆($z$ = 0) ∼ 107–109M⊙, but in worse agreement at lower masses ($M_{\star }(z=0) \sim 10^5\!-\!10^7 \, \mathrm{M}_{\odot }$). These differences may be explainable by systematics in the models (e.g. reionization model) and/or observations (HST field placement). We suggest that a coordinated effort to get deep CMDs between HST/JWST (crowded central fields) and WFIRST (wide-area halo coverage) is the optimal path for measuring global SFHs of isolated dwarf 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 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)0.000
metaresearch head score (Gemma)0.000
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 score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.006
GPT teacher head0.179
Teacher spread0.172 · 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

Citations49
Published2019
Admission routes1
Has abstractyes

Explore more

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