A relationship between halo mass, cooling, active galactic nuclei heating and the co-evolution of massive black holes
Bibliographic record
Abstract
We derive X-ray mass, luminosity, and temperature profiles for 45 galaxy clusters to explore relationships between halo mass, AGN feedback, and central cooling time. We find that radio--mechanical feedback power (referred to here as "AGN power") in central cluster galaxies correlates with halo mass as P$_{\rm mech}$ $\propto$ M$^{1.55\pm0.26}$, but only in halos with central atmospheric cooling times shorter than 1 Gyr. The trend of AGN power with halo mass is consistent with the scaling expected from a self-regulating AGN feedback loop, as well as with galaxy and central black hole co-evolution along the $M_{\rm BH} - \sigma$ relation. AGN power in clusters with central atmospheric cooling times longer than $\sim 1$ Gyr typically lies two orders of magnitude below those with shorter central cooling times. Galaxies centred in clusters with long central cooling times nevertheless experience ongoing and occasionally powerful AGN outbursts. We further investigate the impact of feedback on cluster scaling relations. We find $L-T$, and $M-T$ relations in clusters with direct evidence of feedback which are steeper than self-similar, but not atypical compared to previous studies of the full cluster population. While the gas mass rises, the stellar mass remains nearly constant with rising total mass, consistent with earlier studies. This trend is found regardless of central cooling time, implying tight regulation of star formation in central galaxies as their halos grew, and long-term balance between AGN heating and atmospheric cooling. Our scaling relations are presented in forms that can be incorporated easily into galaxy evolution models.
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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 | 0.000 | 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".