A<i>CHANDRA</i>STUDY OF THE LARGE-SCALE SHOCK AND COOL FILAMENTS IN HYDRA A: EVIDENCE FOR SUBSTANTIAL GAS DREDGE-UP BY THE CENTRAL OUTBURST
Bibliographic record
Abstract
We present the results of a Chandra study of the Hydra A galaxy cluster, where a powerful active galactic nucleus (AGN) outburst created a large-scale cocoon shock. We investigated possible azimuthal variations in shock strength and shape, finding indications for a weak shock with a Mach number in the range ∼1.2–1.3. We measured the temperature change across the shock front. However, the detection of a temperature rise in the regions immediately inside of the front is complicated by the underlying temperature profile of the cluster atmosphere. We measured the global temperature profile of the cluster up to 700 kpc, which represents the farthest measurement obtained with Chandra for this cluster. A "plateau" in the temperature profile in the range ∼70–150 kpc indicates the presence of cool gas, which is likely the result of uplift of material by the AGN outburst. After masking the cool filaments visible in the hardness ratio map, the plateau disappears and the temperature profile recovers a typical shape with a peak around 190 kpc, just inside the shock front. However, it is unlikely that such a temperature feature is produced by the shock as it is consistent with the general shape of the temperature profiles observed for relaxed galaxy clusters. We studied the spectral properties of the cool filaments finding evidence that ∼10 11 M ☉ of low-entropy material has been dredged up by the rising lobes from the central 30 kpc to the observed current position of 75–150 kpc. The energy required to lift the cool gas is ≳ 2.2 × 10 60 erg, which is comparable to the work required to inflate the cavities and is ∼25% of the total energy of the large-scale shock. Our results show that the AGN feedback in Hydra A is acting not only by directly heating the gas, but also by removing a substantial amount of potential fuel for the supermassive black hole.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 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".