Testing the Limits of AGN Feedback and the Onset of Thermal Instability in the Most Rapidly Star Forming Brightest Cluster Galaxies
Bibliographic record
Abstract
We present new, deep, narrow- and broad-band Hubble Space Telescope observations of seven of the most star-forming brightest cluster galaxies (BCGs). Continuum-subtracted [O II] maps reveal the detailed, complex structure of warm ($T \sim 10^4$ K) ionized gas filaments in these BCGs, allowing us to measure spatially-resolved star formation rates (SFRs) of ~60-600 Msun/yr. We compare the SFRs in these systems and others from the literature to their intracluster medium (ICM) cooling rates (dM/dt), measured from archival Chandra X-ray data, finding a best-fit relation of log(SFR) = (1.67+/-0.17) log(dM/dt) + (-3.25+/-0.38) with an intrinsic scatter of 0.39+/-0.09 dex. This steeper-than-unity slope implies an increasingly efficient conversion of hot ($T \sim 10^7$ K) gas into young stars with increasing dM/dt, or conversely a gradual decrease in the effectiveness of AGN feedback in the strongest cool cores. We also seek to understand the physical extent of these multiphase filaments that we observe in cluster cores. We show, for the first time, that the average extent of the multiphase gas is always smaller than the radii at which the cooling time reaches 1 Gyr, the tcool/tff profile flattens, and that X-ray cavities are observed. This implies a close connection between the multiphase filaments, the thermodynamics of the cooling core, and the dynamics of X-ray bubbles. Interestingly, we find a one-to-one correlation between the average extent of cool multiphase filaments and the radius at which the cooling time reaches 0.5 Gyr, which may be indicative of a universal condensation timescale in cluster cores.
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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 | 0.001 | 0.004 |
| 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 | 0.001 |
| 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".