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Record W6992932281

A multiwavelength study of a sample of 70 mm selected galaxies in the COSMOS Field. II. The role of mergers in galaxy evolution

2010· article· en· W6992932281 on OpenAlexaboutno aff

Bibliographic record

VenueMax Planck Institute for Plasma Physics · 2010
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsnot available
Fundersnot available
KeywordsGalaxyRedshiftLuminosityPopulationLuminous infrared galaxyGalaxy mergerInfrared
DOInot available

Abstract

fetched live from OpenAlex

We analyze the morphological properties of a large sample of 1503 70 μm selected galaxies in the COSMOS field spanning the redshift range 0.01 < z < 3.5 with a median redshift of 0.5 and an infrared luminosity range of 108 < L IR(8 - 1000 μm)< 1014 L sun with a median luminosity of 1011.4 L sun. In general, these galaxies are massive, with a stellar mass range of 1010-1012 M sun, and luminous, with -25 < M K < -20. We find a strong correlation between the fraction of major mergers and L IR, with the fraction at the highest luminosity (L IR > 1012 L sun) being up to ~50%. We also find that the fraction of spirals drops dramatically with L IR. Minor mergers likely play a role in boosting the infrared luminosity for sources with low luminosities (L IR < 1011.5 L sun). The precise fraction of mergers in any given L IR bin varies by redshift due to sources at z > 1 being difficult to classify and subject to the effects of bandpass shifting; therefore, these numbers can only be considered lower limits. At z < 1, where the morphological classifications are most robust, major mergers clearly dominate the ULIRG population (~50%-80%) and are important for the LIRG population (~25%-40%). At z > 1, the fraction of major mergers is lower, but is at least 30%-40% for ULIRGs. In a comparison of our visual classifications with several automated classification techniques we find general agreement; however, the fraction of identified mergers is underestimated due to automated classification methods being sensitive to only certain timescales of a major merger. Although the general morphological trends agree with what has been observed for local (U)LIRGs, the fraction of major mergers is slightly lower than seen locally. This is in part due to the difficulty of identifying merger signatures at high redshift. The distribution of the U - V color of the galaxies in our sample peaks in the green valley (langU - Vrang = 1.1) with a large spread at bluer and redder colors and with the major mergers peaking more strongly in the green valley than the rest of the morphological classes. We argue that, given the number of major gas-rich mergers observed and the relatively short timescale that they would be observable in the (U)LIRG phase, it is plausible for the observed red sequence of massive ellipticals (<1012 M sun) to have been formed entirely by gas-rich major mergers. Based on observations with the NASA/ESA Hubble Space Telescope, obtained at the Space Telescope Science Institute, which is operated by AURA Inc, under NASA contract NAS 5-26555; also based on data collected at the Subaru Telescope, which is operated by the National Astronomical Observatory of Japan; the XMM-Newton, an ESA science mission with instruments and contributions directly funded by ESA Member States and NASA; the European Southern Observatory under Large Program 175.A-0839, Chile; the National Radio Astronomy Observatory which is a facility of the National Science Foundation operated under cooperative agreement by Associated Universities, Inc; the Canada-France-Hawaii Telescope with MegaPrime/MegaCam operated as a joint project by the CFHT Corporation, CEA/DAPNIA, the National Research Council of Canada, the Canadian Astronomy Data Centre, the Centre National de la Recherche Scientifique de France, TERAPIX and the University of Hawaii.

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 score0.019
Threshold uncertainty score0.818

Codex and Gemma teacher scores by category

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

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 head0.217
Teacher spread0.209 · 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

Citations0
Published2010
Admission routes1
Has abstractyes

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