A deep Chandra observation of the active galactic nucleus outburst and merger in Hickson compact group 62
Bibliographic record
Abstract
We report on an analysis of new Chandra data of the galaxy group HCG 62, well known for possessing cavities in its intragroup medium (IGM) that were inflated by the radio lobes of its central active galactic nucleus (AGN). With the new data, a factor of 3 deeper than previous Chandra data, we re-examine the energetics of the cavities and determine new constraints on their contents. We confirm that the ratio of radiative to mechanical power of the AGN outburst that created the cavities is less than 10− 4, among the lowest of any known cavity system, implying that the relativistic electrons in the lobes can supply only a tiny fraction of the pressure required to support the cavities. This finding implies additional pressure support in the lobes from heavy particles (e.g. protons) or thermal gas. Using spectral fits to emission in the cavities, we constrain any such volume-filling thermal gas to have a temperature kT ≳ 4.3 keV. For the first time, we detect X-ray emission from the central AGN, with a luminosity of |$L_{2\text{--}10\,{\rm keV}} = (1.1 \pm 0.4)\times 10^{39}$| erg s− 1 and properties typical of a low-luminosity AGN. Finally, we report evidence for a recent merger from the surface brightness, temperature and metallicity structure of the IGM.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".