AVERAGE HEATING RATE OF HOT ATMOSPHERES IN DISTANT CLUSTERS BY RADIO ACTIVE GALACTIC NUCLEUS: EVIDENCE FOR CONTINUOUS ACTIVE GALACTIC NUCLEUS HEATING
Bibliographic record
Abstract
We examine atmospheric heating by radio active galactic nuclei (AGNs) in distant X-ray clusters by cross correlating clusters selected from the 400 Square Degree (400SD) X-ray Cluster survey with radio sources in the NRAO VLA Sky Survey. Roughly 30% of the clusters show radio emission above a flux threshold of 3 mJy within a projected radius of 250 kpc. The radio emission is presumably associated with the brightest cluster galaxy. The mechanical jet power for each radio source was determined using scaling relations between radio power and cavity (mechanical) power determined for nearby clusters, groups, and galaxies with hot atmospheres containing X-ray cavities. The average jet power of central radio AGNs is approximately 2 × 10 44 erg s −1 . We find no significant correlation between radio power, and hence mechanical jet power, and the X-ray luminosities of clusters in the redshift range 0.1–0.6. This implies that the mechanical heating rate per particle is higher in lower mass, lower X-ray luminosity clusters. The jet power averaged over the sample corresponds to an atmospheric heating of approximately 0.2 keV per particle within R 500 . Assuming the current AGN heating rate does not evolve but remains constant to redshifts of 2, the heating rate per particle would rise by a factor of two. We find that the energy injected from radio AGNs contribute substantially to the excess entropy in hot atmospheres needed to break self-similarity in cluster scaling relations. The detection frequency of radio AGNs is inconsistent with the presence of strong cooling flows in 400SD clusters, but does not exclude weak cooling flows. It is unclear whether central AGNs in 400SD clusters are maintained by feedback at the base of a cooling flow. Atmospheric heating by radio AGNs may retard the development of strong cooling flows at early epochs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".