A MECHANISM FOR STIMULATING AGN FEEDBACK BY LIFTING GAS IN MASSIVE GALAXIES
Bibliographic record
Abstract
ABSTRACT Observation shows that nebular emission, molecular gas, and young stars in giant galaxies are associated with rising X-ray bubbles inflated by radio jets launched from nuclear black holes. We propose a model where molecular clouds condense from low-entropy gas caught in the updraft of rising X-ray bubbles. The low-entropy gas becomes thermally unstable when it is lifted to an altitude where its cooling time is shorter than the time required to fall to its equilibrium location in the galaxy, i.e., . The infall speed of a cloud is bounded by the lesser of its free-fall and terminal speeds, so that the infall time here can exceed the free-fall time by a significant factor. This mechanism is motivated by Atacama Large Millimeter Array observations revealing molecular clouds lying in the wakes of rising X-ray bubbles with velocities well below their free-fall speeds. Our mechanism would provide cold gas needed to fuel a feedback loop while stabilizing the atmosphere on larger scales. The observed cooling time threshold of —the clear-cut signature of thermal instability and the onset of nebular emission and star formation—may result from the limited ability of radio bubbles to lift low-entropy gas to altitudes where thermal instabilities can ensue. Outflowing molecular clouds are unlikely to escape, but instead return to the central galaxy in a circulating flow. We contrast our mechanism to precipitation models where the minimum value of triggers thermal instability, which we find to be inconsistent with observation.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".