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The colours of satellite galaxies in groups and clusters

2008· article· en· W1919617765 on OpenAlexfundno aff
Andreea S. Font, R. G. Bower, Ian G. McCarthy, Andrew Benson, Carlos S. Frenk, John Helly, C. G. Lacey, C. M. Baugh, Shaun Cole

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society · 2008
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsnot available
FundersScience and Technology Facilities CouncilNatural Sciences and Engineering Research Council of CanadaDurham UniversityGordon and Betty Moore Foundation
KeywordsPhysicsSatellite galaxyAstrophysicsGalaxySatelliteGalaxy groupSupernovaHaloGalaxy clusterGalaxy groups and clustersRam pressureGalaxy formation and evolutionAstronomyStar formation

Abstract

fetched live from OpenAlex

Current models of galaxy formation predict satellite galaxies in groups and clusters that are redder than observed. We investigate the effect on the colours of satellite galaxies produced by the ram-pressure stripping of their hot-gaseous atmospheres as the satellites orbit within their parent halo. We incorporate a model of the stripping process based on detailed hydrodynamic simulations within the Durham semi-analytic model of galaxy formation. The simulations show that the environment in groups and clusters is less aggressive than previously assumed. The main uncertainty in the model is the treatment of gas expelled by supernovae. With reasonable assumptions for the stripping of this material, we find that satellite galaxies are able to retain a significant fraction of their hot gas for several Gyr, thereby replenishing their reservoirs of cold, star-forming gas and remaining blue for a relatively long period of time. A bimodal distribution of galaxy colours, similar to that observed in Sloan Digital Sky Survey data, is established and the colours of the satellite galaxies are in good agreement with the data. In addition, our model naturally accounts for the observed dependence of satellite colours on environment, from small groups to high-mass clusters.

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 score0.020
Threshold uncertainty score0.377

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 studies0.0000.001
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 head0.006
GPT teacher head0.185
Teacher spread0.179 · 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

Citations315
Published2008
Admission routes1
Has abstractyes

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Same venueMonthly Notices of the Royal Astronomical SocietySame topicGalaxies: Formation, Evolution, PhenomenaFrench-language works237,207