Constraining cold accretion on to supermassive black holes: molecular gas in the cores of eight brightest cluster galaxies revealed by joint CO and CN absorption
Bibliographic record
Abstract
Abstract To advance our understanding of the fuelling and feedback processes which power the Universe’s most massive black holes, we require a significant increase in our knowledge of the molecular gas which exists in their immediate surroundings. However, the behaviour of this gas is poorly understood due to the difficulties associated with observing it directly. We report on a survey of 18 brightest cluster galaxies lying in cool cores, from which we detect molecular gas in the core regions of eight via carbon monoxide (CO), cyanide (CN) and silicon monoxide (SiO) absorption lines. These absorption lines are produced by cold molecular gas clouds which lie along the line of sight to the bright continuum sources at the galaxy centres. As such, they can be used to determine many properties of the molecular gas which may go on to fuel supermassive black hole accretion and AGN feedback mechanisms. The absorption regions detected have velocities ranging from −45 to 283 km s−1 relative to the systemic velocity of the galaxy, and have a bias for motion towards the host supermassive black hole. We find that the CN N = 0 − 1 absorption lines are typically 10 times stronger than those of CO J = 0 − 1. This is due to the higher electric dipole moment of the CN molecule, which enhances its absorption strength. In terms of molecular number density CO remains the more prevalent molecule with a ratio of CO/CN ∼10, similar to that of nearby galaxies. Comparison of CO, CN, and H i observations for these systems shows many different combinations of these absorption lines being detected.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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".