The SCUBA-2 Cosmology Legacy Survey: Multi-wavelength Properties of ALMA-identified Submillimeter Galaxies in UKIDSS UDS
Bibliographic record
Abstract
Abstract We present a multi-wavelength analysis of 52 submillimeter galaxies (SMGs), identified using ALMA 870 μ m continuum imaging in a pilot program to precisely locate bright SCUBA-2-selected submillimeter sources in the UKIDSS Ultra Deep Survey (UDS) field. Using the available deep (especially near-infrared) panoramic imaging of the UDS field at optical-to-radio wavelengths we characterize key properties of the SMG population. The median photometric redshift of the bright ALMA/SCUBA-2 UDS (AS2UDS) SMGs that are detected in a sufficient number of wavebands to derive a robust photometric redshift is z = 2.65 ± 0.13. However, similar to previous studies, 27% of the SMGs are too faint at optical-to-near-infrared wavelengths to derive a reliable photometric redshift. Assuming that these SMGs lie at z ≳ 3 raises the median redshift of the full sample to z = 2.9 ± 0.2. A subset of 23 unlensed, bright AS2UDS SMGs have sizes measured from resolved imaging of their rest-frame far-infrared emission. We show that the extent and luminosity of the far-infrared emission are consistent with the dust emission arising from regions that are, on average, optically thick at a wavelength of (1 σ dispersion of 55–90 μ m). Using the dust masses derived from our optically thick spectral energy distribution models, we determine that these galaxies have a median hydrogen column density of N H = 9.8 × 10 23 cm −2 , or a corresponding median V -band obscuration of A v = 540 mag, averaged along the line of sight to the source of their rest-frame ∼200 μ m emission. We discuss the implications of this extreme attenuation by dust for the multi-wavelength study of dusty starbursts and reddening-sensitive tracers of star formation.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".