Jet-mode Feedback in NGC 5972: Insights from Resolved MUSE, GMRT, and VLA Observations
Bibliographic record
Abstract
Abstract NGC 5972, a Voorwerp galaxy, features a helical-shaped extended emission-line region (EELR) with a radius >10 kpc and an S-shaped radio structure spanning about 470 kpc. We use the Very Large Telescope, Multi Unit Spectroscopic Explorer, Giant Metrewave Radio Telescope, and Very Large Array (VLA) to study the stellar and ionized gas kinematics and how the radio jet influences the gas in the galaxy. Our sensitive radio observations detect the southern jet for the first time, roughly coinciding with the southern EELR. The VLA images show a continuous inner jet connected to the outer east–west lobe, confirming the jet origin of the radio emission. Our kinematic analysis shows spatial correlations between the radio jet and the outflowing gas, supporting the jet-driven feedback mechanism. More interestingly, we observe enhanced velocity dispersion in the perpendicular direction along with a shell-like structure. Our Baldwin–Phillips–Telervich analysis shows that the [O III] emission overlapping with the radio jet is consistent with the shock+precursor model, whereas in the perpendicular region, a pure shock model fits well with the observations, indicating jet-induced shocks. Radio observations indicate episodic AGN activity characterized by surface brightness and spectral index discontinuities. Overall, based on our findings, we propose a jet-driven feedback mechanism as one of the key factors in the formation of the EELR in NGC 5972. Future high-resolution radio observations will be crucial to further investigate the origin of the EELR and quantify the extent to which the jet influences its formation and evolution.
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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 | 0.002 | 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 | 0.000 |
| 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".