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Record W2030094391 · doi:10.1088/0004-637x/716/1/556

ULTRAVIOLET+INFRARED STAR FORMATION RATES: HICKSON COMPACT GROUPS WITH<i>SWIFT</i>AND<i>SPITZER</i>

2010· article· en· W2030094391 on OpenAlexaff
P. Tzanavaris, A. E. Hornschemeier, S. C. Gallagher, Kelsey E. Johnson, C. Gronwall, S. Immler, Amy E. Reines, E. A. Hoversten, J. C. Charlton

Bibliographic record

VenueThe Astrophysical Journal · 2010
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsWestern University
Fundersnot available
KeywordsAstrophysicsPhysicsGalaxyStar formationPhotometry (optics)BimodalityAstronomyStars

Abstract

fetched live from OpenAlex

We present Swift UVOT ultraviolet (UV; 1600–3000 Å) data with complete three-band UV photometry for a sample of 41 galaxies in 11 nearby (<4500 km s −1 ) Hickson Compact Groups (HCGs) of galaxies. We use UVOT uvw2 -band (2000 Å) photometry to estimate the dust-unobscured component, SFR UV , of the total star formation rate, SFR TOTAL . We use Spitzer MIPS 24 μm photometry to estimate SFR IR , the component of SFR TOTAL that suffers dust extinction in the UV and is re-emitted in the IR. By combining the two components, we obtain SFR TOTAL estimates for all HCG galaxies. We obtain total stellar mass, M * , estimates by means of Two Micron All Sky Survey K s -band luminosities, and use them to calculate specific star formation rates, SSFR ≡ SFR TOTAL / M * . SSFR values show a clear and significant bimodality, with a gap between low (≲3.2 × 10 −11 yr −1 ) and high-SSFR (≳1.2 × 10 −10 yr −1 ) systems. We compare this bimodality to the previously discovered bimodality in α IRAC , the MIR activity index from a power-law fit to the Spitzer IRAC 4.5–8 μm data for these galaxies. We find that all galaxies with α IRAC ⩽ 0 ( >0) are in the high- (low-) SSFR locus, as expected if high levels of star-forming activity power MIR emission from polycyclic aromatic hydrocarbon molecules and a hot dust continuum. Consistent with this finding, all elliptical/S0 galaxies are in the low-SSFR locus, while 22 out of 24 spirals/irregulars are in the high-SSFR locus, with two borderline cases. We further divide our sample into three subsamples (I, II, and III) according to decreasing H i richness of the parent galaxy group to which a galaxy belongs. Consistent with the SSFR and α IRAC bimodality, 12 out of 15 type I (11 out of 12 type III) galaxies are in the high- (low-) SSFR locus, while type II galaxies span almost the full range of SSFR values. We use the Spitzer Infrared Nearby Galaxy Survey (SINGS) to construct a comparison subsample of galaxies that (1) match HCG galaxies in J -band total galaxy luminosity and (2) are not strongly interacting and largely isolated. This selection eliminates mostly low-luminosity dwarfs and galaxies with some degree of peculiarity, providing a substantially improved, quiescent control sample. Unlike HCG galaxies, galaxies in the comparison SINGS subsample are continuously distributed both in SSFR and α IRAC , although they show ranges in SFR TOTAL values, morphologies and stellar masses similar to those for HCG systems. We test the SSFR bimodality against a number of uncertainties, and find that these can only lead to its further enhancement. Excluding galaxies belonging to HCGs with three giant galaxies (triplets) leaves both the SSFR and the α IRAC bimodality completely unaffected. We interpret these results as further evidence that an environment characterized by high galaxy number densities and low galaxy velocity dispersions, such as the one found in compact groups, plays a key role in accelerating galaxy evolution by enhancing star formation processes in galaxies and favoring a fast transition to quiescence.

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)0.001
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 score0.006
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0020.000

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 head0.205
Teacher spread0.199 · 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

Citations62
Published2010
Admission routes1
Has abstractyes

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