An ALMA Spectroscopic Survey of the Brightest Submillimeter Galaxies in the SCUBA-2-COSMOS Field (AS2COSPEC): Physical Properties of z = 2–5 Ultra- and Hyperluminous Infrared Galaxies
Bibliographic record
Abstract
Abstract We report the physical properties of the 18 brightest (S 870 μm = 12.4–19.2 mJy) and not strongly lensed 870 μm–selected dusty star-forming galaxies (DSFGs), also known as submillimeter galaxies (SMGs), in the COSMOS field. This sample is part of an ALMA band 3 spectroscopic survey (AS2COSPEC), and spectroscopic redshifts are measured in 17 of them at z = 2–5. We perform spectral energy distribution analyses and deduce a median total infrared luminosity of L IR = (1.3 ± 0.1) × 1013 L ⊙, infrared-based star formation rate (SFR) of SFRIR = 1390 ± 150 M ⊙ yr−1, stellar mass of M * = (1.4 ± 0.6) × 1011 M ⊙, dust mass of M dust = (3.7 ± 0.5) × 109 M ⊙, and molecular gas mass of M gas = (α CO/0.8)(1.2 ± 0.1) × 1011 M ⊙, suggesting that they are one of the most massive, ISM-enriched, and actively star-forming systems at z = 2–5. In addition, compared to less massive and less active galaxies at similar epochs, SMGs have comparable gas fractions; however, they have a much shorter depletion time, possibly caused by more active dynamical interactions. We determine a median dust emissivity index of β = 2.1 ± 0.1 for our sample, and by combining our results with those from other DSFG samples, we find no correlation of β with redshift or infrared luminosity, indicating similar dust grain compositions across cosmic time for infrared luminous galaxies. We also find that AS2COSPEC SMGs have one of the highest dust-to-stellar mass ratios, with a median of 0.02 ± 0.01, significantly higher than model predictions, possibly due to too-strong active galactic nucleus feedback implemented in the model. Finally, our complete and uniform survey enables us to put constraints on the most massive end of the dust and molecular gas mass functions.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".