A<i>CHANDRA</i>X-RAY ANALYSIS OF ABELL 1664: COOLING, FEEDBACK, AND STAR FORMATION IN THE CENTRAL CLUSTER GALAXY
Bibliographic record
Abstract
The brightest cluster galaxy (BCG) in the Abell 1664 cluster is unusually blue and is forming stars at a rate of ∼ 23 M ☉ yr −1 . The BCG is located within 5 kpc of the X-ray peak, where the cooling time of 3.5 × 10 8 yr and entropy of 10.4 keV cm 2 are consistent with other star-forming BCGs in cooling flow clusters. The center of A1664 has an elongated, "barlike" X-ray structure whose mass is comparable to the mass of molecular hydrogen, ∼10 10 M ☉ in the BCG. We show that this gas is unlikely to have been stripped from interloping galaxies. The cooling rate in this region is roughly consistent with the star formation rate, suggesting that the hot gas is condensing onto the BCG. We use the scaling relations of Bîrzan et al. to show that the active galactic nucleus (AGN) is underpowered compared to the central X-ray cooling luminosity by roughly a factor of three. We suggest that A1664 is experiencing rapid cooling and star formation during a low state of an AGN feedback cycle that regulates the rates of cooling and star formation. Modeling the emission as a single-temperature plasma, we find that the metallicity peaks 100 kpc from the X-ray center, resulting in a central metallicity dip. However, a multi-temperature cooling flow model improves the fit to the X-ray emission and is able to recover the expected, centrally peaked metallicity profile.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".