Cool-core Clusters: The Role of BCG, Star Formation, and AGN-driven Turbulence
Bibliographic record
Abstract
Abstract Recent observations of cool cluster cores that include the BCG gravity claim that the observed threshold in min(t cool/t ff) (cooling time to free-fall time ratio) lies at a somewhat higher value, close to 10–30, compared with the threshold seen in numerical simulations. There are only a few clusters in which this ratio falls much below 10. In this paper, we compare 3D hydrodynamic simulations of feedback active galactic nuclei (AGNs) jets interacting with the intracluster medium, with and without a BCG potential. We find that, for a fixed feedback efficiency, the presence of a BCG does not significantly affect the temperature, but increases (decreases) the core density (entropy) on average. Most importantly, min(t cool/t ff) is only affected slightly by the inclusion of the BCG gravity. Also notable is that the lowest value of min(t cool/t ff) in the NFW+BCG runs is about twice as large as in the NFW runs. We also look at the role of depletion of cold gas due to star formation, and show that it only affects the rotationally dominant component, while the radially dominant component remains largely unaffected. Stellar gas depletion also increases the repetition rate of AGN jets. The distribution of metals due to AGN jets in our simulations is predominantly along the jet direction, and the equatorial spread of metals is less compared with the observations. We also show that the turbulence in cool-core clusters is weak, which is consistent with recent Hitomi results on the Perseus cluster.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".