An ALMA Survey of the SCUBA-2 Cosmology Legacy Survey UKIDSS/UDS Field: Identifying Candidate z ∼ 4.5 [C II] Emitters
Bibliographic record
Abstract
Abstract We report the results of a search for serendipitous [C ii] 157.74 μm emitters at z ≃ 4.4–4.7 using the Atacama Large Millimeter/submillimeter Array (ALMA). The search exploits the AS2UDS continuum survey, which covers ∼50 arcmin2 of the sky toward 695 luminous (S 870 ≳ 1 mJy) submillimeter galaxies (SMGs), selected from the SCUBA-2 Cosmology Legacy Survey 0.96 deg2 Ultra Deep Survey (UDS) field. We detect 10 candidate line emitters, with an expected false detection rate of 10%. All of these line emitters correspond to 870 μm continuum-detected sources in AS2UDS. The emission lines in two emitters appear to be high-J CO, but the remainder have multi-wavelength properties consistent with [C ii] from z ≃ 4.5 galaxies. Using our sample, we place a lower limit of on the space density of luminous (L IR ≃ 1013 ) SMGs at z = 4.40–4.66, suggesting % of SMGs with mJy lie at 4 < z < 5. From stacking the high-resolution (∼0.″15 full-width half maximum) ALMA 870 μm imaging, we show that the [C ii] line emission is more extended than the continuum dust emission, with an average effective radius for the [C ii] of kpc, compared to r e = 1.0 ± 0.1 kpc for the continuum (rest-frame 160 μm). By fitting the far-infrared photometry for these galaxies from 100 to 870 μm, we show that SMGs at z ∼ 4.5 have a median dust temperature of T d = 55 ± 4 K. This is systematically warmer than 870 μm selected SMGs at z ≃ 2, which typically have temperatures around 35 K. These z ≃ 4.5 SMGs display a steeper trend in the luminosity-temperature plane than z ≤ 2 SMGs. We discuss the implications of this result in terms of the selection biases of high-redshift starbursts in far-infrared/submillimeter surveys.
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 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 | 0.001 |
| 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".