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<i>Herschel</i>-SPIRE, far-infrared properties of millimetre-bright and -faint radio galaxies

2010· article· en· W2165206441 on OpenAlexaff

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society Letters · 2010
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsUniversity of British ColumbiaUniversity of Lethbridge
FundersScience and Technology Facilities Council
KeywordsGalaxySpire (mollusc)RedshiftLuminous infrared galaxyExtrapolationPhotometry (optics)Spectral energy distributionStar formation

Abstract

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Abstract We present the first study of the far-infrared (FIR) properties of high-redshift, radio-selected ultraluminous infrared galaxies (ULIRGs) using deep observations obtained with the Spectral and Photometric Imaging Receiver (SPIRE) from the Herschel Multi-tiered Extragalactic Survey (HerMES). These galaxies span a large range of 850-μm fluxes from submillimetre-luminous ∼10 mJy sources (SCUBA galaxies) to ∼1.5 mJy from stacked SCUBA non-detections, thus likely representing a complete distribution of ULIRG spectral energy distributions (SEDs). From Keck spectroscopic surveys in the Lockman-North field we identified a sample of 31 submillimetre galaxies (SMGs) and 37 submillimetre-faint, optically faint radio galaxies (OFRGs), all with radio-inferred IR luminosities >1012 L⊙. These galaxies were cross-identified with SPIRE 250-, 350- and 500-μm catalogues based on fluxes extracted at 24-μm positions in the SWIRE survey, yielding a sample of more than half of the galaxies well detected in at least two of the SPIRE bandpasses. By fitting greybody dust models to the SPIRE photometry together with SCUBA 850-μm measurements (for OFRGs, only 850- upper limits), we infer dust temperatures and FIR luminosities. The OFRGs detected by SPIRE have median 〈Td〉= 41 ± 5 K and the SMGs have 〈Td〉= 34 ± 5 K, both in reasonable agreement with previous (pre-Herschel) estimates, reaffirming that the local FIR/radio correlation holds (at least for this subset of high-z ULIRGs) at high redshift (we measure 〈qIR〉= 2.43 ± 0.21 using SIR derived from greybody fit coupled with a power-law extrapolation to the 24 μm). Our observations first confirm that a substantial fraction of OFRGs exhibits large infrared luminosities corresponding to SFRs of ∼400 M⊙ yr−1. The SPIRE observations secondly confirm the higher dust temperatures for these OFRGs than similarly selected SMGs, consistent with early predictions of the submillimetre-faint radio populations. Our observations also clearly confirm the large infrared luminosities of most SMGs selected with S850 μm > 5 mJy and radio and strong 24-μm detections, corresponding to SFRs of ∼700 M⊙ yr−1.

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 score0.002
Threshold uncertainty score0.005

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)0.0020.001

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 head0.005
GPT teacher head0.170
Teacher spread0.165 · 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

Citations61
Published2010
Admission routes1
Has abstractyes

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