Molecular flows in contemporary active galaxies and the efficacy of radio-mechanical feedback
Bibliographic record
Abstract
ABSTRACT Molecular gas flows are analysed in 14 cluster galaxies (BCGs) centred in cooling hot atmospheres. The BCGs contain $10^{9}\!-\!10^{11}~\rm M_\odot$ of molecular gas, much of which is being moved by radio jets and lobes. The molecular flows and radio jet powers are compared to molecular outflows in 45 active galaxies within z < 0.2. We seek to understand the relative efficacy of radio, quasar, and starburst feedback over a range of active galaxy types. Molecular flows powered by radio feedback in BCGs are ∼10–1000 times larger in extent compared to contemporary galaxies hosting quasar nuclei and starbursts. Radio feedback yields lower flow velocities but higher momenta compared to quasar nuclei, as the molecular gas flows in BCGs are usually ∼10–100 times more massive. The product of the molecular gas mass and lifting altitude divided by the AGN or starburst power – a parameter referred to as the lifting factor – exceeds starbursts and quasar nuclei by 2–3 orders of magnitude, respectively. When active, radio feedback is generally more effective at lifting gas in galaxies compared to quasars and starburst winds. The kinetic energy flux of molecular clouds generally lies below and often substantially below a few per cent of the driving power. We find tentatively that star formation is suppressed in BCGs relative to other active galaxies, perhaps because these systems rarely form molecular discs that are more impervious to feedback and are better able to promote star formation.
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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 | 0.001 |
| Scholarly communication | 0.001 | 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".