Bibliographic record
Abstract
The gas-phase metallicity distribution has been analysed for the hot atmospheres of 29 galaxy clusters using Chandra X-ray Observatory observations. All host brightest cluster galaxies (BCGs) with X-ray cavity systems produced by radio AGN. We find high elemental abundances projected preferentially along the cavities of 16 clusters. The metal-rich plasma was apparently lifted out of the BCGs with the rising X-ray cavities (bubbles) to altitudes between twenty and several hundred kiloparsecs. A relationship between the maximum projected altitude of the uplifted gas (the ‘iron radius’) and jet power is found with the form |$R_{\rm Fe} \propto P_{\rm jet}^{0.45}$|. The estimated outflow rates are typically tens of solar masses per year but exceed 100 M⊙ yr− 1 in the most powerful AGN. The outflow rates are 10–20 per cent of the cooling rates, and thus alone are unable to offset a cooling inflow. Nevertheless, hot outflows effectively redistribute the cooling gas and may play a significant role at regulating star formation and AGN activity in BCGs and presumably in giant elliptical galaxies. The metallicity distribution overall can be complex, perhaps due to metal-rich gas returning in circulation flows or being blown around in the hot atmospheres. Roughly 15 per cent of the work done by the cavities is expended lifting the metal-enriched gas, implying their nuclear black holes have increased in mass by at least ∼107–109 M⊙. Finally, we show that hot outflows can account for the broad, gas-phase metallicity distribution compared to the stellar light profiles of BCGs, and we consider a possible connection between hot outflows and cold molecular gas flows discovered in recent Atacama Large Millimeter Array observations.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".