A multiwavelength study of a sample of 70 ηm selected galaxies in the Cosmos field. I. Spectral energy distributions and luminosities
Bibliographic record
Abstract
We present a large robust sample of 1503 reliable and unconfused 70 μm selected sources from the multiwavelength data set of the Cosmic Evolution Survey. Using the Spitzer IRAC and MIPS photometry, we estimate the total infrared (IR) luminosity, L IR (8-1000 μm), by finding the best-fit template from several different template libraries. The long-wavelength 70 and 160 μm data allow us to obtain a reliable estimate of L IR, accurate to within 0.2 and 0.05 dex, respectively. The 70 μm data point enables a significant improvement over the luminosity estimates possible with only a 24 μm detection. The full sample spans a wide range in IR luminosity, L IR ≈ 108-1014 L sun, with a median luminosity of 1011.4 L sun. We identify a total of 687 luminous, 303 ultraluminous, and 31 hyperluminous infrared galaxies (LIRGs, ULIRGs, and HyLIRGs) over the redshift range 0.01 < z < 3.5 with a median redshift of 0.5. Presented here are the full spectral energy distributions (SEDs) for each of the sources compiled from the extensive multiwavelength data set from the ultraviolet (UV) to the far-infrared. A catalog of the general properties of the sample (including the photometry, redshifts, and L IR) is included with this paper. We find that the overall shape of the SED and trends with L IR (e.g., IR color temperatures and optical-IR ratios) are similar to what has been seen in studies of local objects; however, our large sample allows us to see the extreme spread in UV to near-infrared colors spanning nearly 3 orders of magnitude. In addition, using SED fits we find possible evidence for a subset of cooler ultraluminous objects than observed locally. However, until direct observations at longer wavelengths are obtained, the peak of emission and the dust temperature cannot be well constrained. We use these SEDs, along with the deep radio and X-ray coverage of the field, to identify a large sample of candidate active galactic nuclei (AGNs). We find that the fraction of AGNs increases strongly with L IR, as it does in the local universe, and that nearly 70% of ULIRGs and all HyLIRGs likely host a powerful AGN. 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.; and 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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".