AN ALMA SURVEY OF SUBMILLIMETER GALAXIES IN THE EXTENDED CHANDRA DEEP FIELD-SOUTH: THE AGN FRACTION AND X-RAY PROPERTIES OF SUBMILLIMETER GALAXIES
Bibliographic record
Abstract
The large gas and dust reservoirs of submillimeter galaxies (SMGs) could potentially provide ample fuel to trigger an active galactic nucleus (AGN), but previous studies of the AGN fraction in SMGs have been controversial largely due to the inhomogeneity and limited angular resolution of the available submillimeter surveys. Here we set improved constraints on the AGN fraction and X-ray properties of the SMGs with Atacama Large Millimeter/submillimeter Array (ALMA) and Chandra observations in the Extended Chandra Deep Field-South (E-CDF-S). This study is the first among similar works to have unambiguously identified the X-ray counterparts of SMGs; this is accomplished using the fully submillimeter-identified, statistically reliable SMG catalog with 99 SMGs from the ALMA LABOCA E-CDF-S Submillimeter Survey. We found 10 X-ray sources associated with SMGs (median redshift z = 2.3), of which eight were identified as AGNs using several techniques that enable cross-checking. The other two X-ray detected SMGs have levels of X-ray emission that can be plausibly explained by their star formation activity. Six of the eight SMG-AGNs are moderately/highly absorbed, with N H > 10 23 cm −2 . An analysis of the AGN fraction, taking into account the spatial variation of X-ray sensitivity, yields an AGN fraction of for AGNs with rest-frame 0.5–8 keV absorption-corrected luminosity ⩾7.8 × 10 42 erg s −1 ; we provide estimated AGN fractions as a function of X-ray flux and luminosity. ALMA's high angular resolution also enables direct X-ray stacking at the precise positions of SMGs for the first time, and we found four potential SMG-AGNs in our stacking sample.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 | 0.000 |
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".