Does absorption against AGN reveal supermassive black hole accretion?
Bibliographic record
Abstract
ABSTRACT Galaxies often contain large reservoirs of molecular gas that shape their evolution. This can be through cooling of the gas – which leads to star formation, or accretion on to the central supermassive black hole – which fuels active galactic nucleus (AGN) activity and produces powerful feedback. Molecular gas has been detected in early-type galaxies on scales of just a few tens to hundreds of solar masses by searching for absorption against their compact radio cores. Using this technique, ALMA has found absorption in several brightest cluster galaxies, some of which show molecular gas moving towards their galaxy’s core at hundreds of km s−1. In this paper, we constrain the location of this absorbing gas by comparing each galaxy’s molecular emission and absorption. In four galaxies, the absorption properties are consistent with chance alignments between the continuum and a fraction of the molecular clouds visible in emission. In four others, the properties of the absorption are inconsistent with this scenario. In these systems, the absorption is likely produced by a separate population of molecular clouds in close proximity to the galaxy core and with high inward velocities and velocity dispersions. We thus deduce the existence of two types of absorber, caused by chance alignments between the radio core and: (i) a fraction of the molecular clouds visible in emission, and (ii) molecular clouds close to the AGN, in the process of accretion. We also present the first ALMA observations of molecular emission in S555, Abell 2390, RXC J1350.3+0940, and RXC J1603.6+1553 – with the latter three having $M_{\rm {mol}} \gt 10^{10}\, \rm {M}_{\odot }$.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".