The Onset of Thermally Unstable Cooling from the Hot Atmospheres of Giant Galaxies in Clusters: Constraints on Feedback Models
Bibliographic record
Abstract
Abstract We present accurate mass and thermodynamic profiles for 57 galaxy clusters observed with the Chandra X-ray Observatory. We investigate the effects of local gravitational acceleration in central cluster galaxies, and explore the role of the local free-fall time ( ) in thermally unstable cooling. We find that the radially averaged cooling time ( ) is as effective an indicator of cold gas, traced through its nebular emission, as the ratio / . Therefore, primarily governs the onset of thermally unstable cooling in hot atmospheres. The location of the minimum / , a thermodynamic parameter that many simulations suggest is key in driving thermal instability, is unresolved in most systems. Consequently, selection effects bias the value and reduce the observed range in measured / minima. The entropy profiles of cool-core clusters are characterized by broken power laws down to our resolution limit, with no indication of isentropic cores. We show, for the first time, that mass isothermality and the entropy profile slope imply a floor in / profiles within central galaxies. No significant departures of / below 10 are found. This is inconsistent with models that assume thermally unstable cooling ensues from linear perturbations at or near this threshold. We find that the inner cooling times of cluster atmospheres are resilient to active galactic nucleus (AGN)-driven change, suggesting gentle coupling between radio jets and atmospheric gas. Our analysis is consistent with models in which nonlinear perturbations, perhaps seeded by AGN-driven uplift of partially cooled material, lead to cold gas condensation.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".