The regulation of star formation in cool-core clusters: imprints on the stellar populations of brightest cluster galaxies
Bibliographic record
Abstract
A fraction of brightest cluster galaxies (BCGs) shows bright emission in the UV and the blue part of the optical spectrum, which has been interpreted as evidence of recent star formation. Most of these results are based on the analysis of broadband photometric data. Here, we study the optical spectra of a sample of 19 BCGs hosted by X-ray luminous galaxy clusters at 0.15 < z < 0.3, a subset from the Canadian Cluster Comparison Project (CCCP) sample. We identify plausible star formation histories of the galaxies by fitting Simple Stellar Populations (SSPs) as well as composite populations, consisting of a young stellar component superimposed on an intermediate/old stellar component, to accurately constrain their star formation histories. We detect prominent young (~200 Myr) stellar populations in 4 of the 19 galaxies. Of the four, the BCG in Abell 1835 shows remarkable A-type stellar features indicating a relatively large population of young stars, which is extremely unusual even amongst star forming BCGs. We constrain the mass contribution of these young components to the total stellar mass to be typically between 1% to 3%, but rising to 7% in Abell 1835. We find that the four of the BCGs with strong evidence for recent star formation (and only these four galaxies) are found within a projected distance of 5 kpc of their host cluster's X-ray peak, and the diffuse, X-ray gas surrounding the BCGs exhibit a ratio of the radiative cooling-to-free-fall time ($t_{c}/t_{ff}$) of < 10. These are also some of the clusters with the lowest central entropy. Our results are consistent with the predictions of the precipitation-driven star formation and AGN feedback model, in which the radiatively cooling diffuse gas is subject to local thermal instabilities once the instability parameter $t_{c}/t_{ff}$ falls below ~10, leading to the condensation and precipitation of cold gas. [Abridged]
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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".