The SPT-Chandra BCG Spectroscopic Survey. I. Evolution of the Entropy Threshold for ICM Cooling and AGN Feedback in Galaxy Clusters over the Last 10 Gyr
Bibliographic record
Abstract
Abstract We present a multiwavelength study of the brightest cluster galaxies (BCGs) in a sample of the 95 most massive galaxy clusters selected from the South Pole Telescope Sunyaev–Zeldovich (SZ) survey. Our sample spans a redshift range of 0.3 < z < 1.7, and is complete with optical spectroscopy from various ground-based observatories, as well as ground and space-based imaging from optical, X-ray, and radio wave bands. At z ∼ 0, previous studies have shown a strong correlation between the presence of a low-entropy cool core and the presence of both star formation and radio-loud active galactic nuclei in the central BCG. We show for the first time that the central entropy threshold for triggering star formation, which is universally seen in nearby systems, persists out to z ∼ 1, with only marginal (∼1σ) evidence for evolution in the threshold entropy value itself. In contrast, we do not find a similar high-z analog for an entropy threshold for feedback, but instead measure a strong evolution in the fraction of radio-loud BCGs in high-entropy cores, decreasing with increasing redshift. This could imply that the cooling-feedback loop was not as tight in the past, or that some other fuel source like mergers are fueling the radio sources more often with increasing redshift, making the radio luminosity an increasingly unreliable proxy for radio jet power. We also find that our SZ-based sample is missing a small (∼4%) population of the most luminous radio sources (ν L ν > 1042 erg s−1), likely due to radio contamination suppressing the SZ signal with which these clusters are detected.
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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 | 0.001 |
| 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".