Very Large Array observations of the mini-halo and AGN feedback in the Phoenix cluster
Bibliographic record
Abstract
Context. The relaxed cool-core Phoenix cluster (SPT-CL J2344-4243) features an extremely strong cooling flow, as well as a mini halo. Strong star formation in the brightest cluster galaxy indicates that active galactic nucleus (AGN) feedback has been unable to inhibit this cooling flow. Aims. We aim to study the strong cooling flow in the Phoenix cluster by determining the radio properties of the AGN and its lobes. In addition, we used spatially resolved radio observations to investigate the origin of the mini halo. Methods. We present new multifrequency Very Large Array 1–12 GHz observations of the Phoenix cluster, which resolve the AGN and its lobes in all four frequency bands as well as the mini-halo in the L and S bands. Results. Using our L-band observations, we measure the total flux density of the radio lobes at 1.5 GHz to be 7.6 ± 0.8 mJy, and the flux density of the mini halo to be 8.5 ± 0.9 mJy. Using high-resolution images in the L and X bands, we produced the first spectral index maps of the lobes from the AGN and find the spectral indices of the northern and southern lobes to be −1.35 ± 0.07 and −1.30 ± 0.12, respectively. Similarly, using L- and S-band data, we mapped the spectral index of the mini halo, and obtain an integrated spectral index of α = −0.95 ± 0.10. Conclusions. We find that the mini halo is most likely formed by turbulent re-acceleration powered by sloshing in the cool core due to a recent merger. In addition, we find that the feedback in the Phoenix cluster is consistent with the picture that stronger cooling flows are to be expected for massive clusters such as this one, as these may feature an underweight supermassive black hole due to their merging history. Strong time variability of the AGN on Myr timescales may help explain the disconnection between the radio and the X-ray properties of the system. Finally, a small amount of jet precession of the AGN likely contributes to the relatively low intracluster medium re-heating efficiency of the mechanical feedback.
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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 | 0.000 | 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".