Ionized gas outflow signatures in SDSS-IV MaNGA active galactic nuclei
Bibliographic record
Abstract
ABSTRACT The prevalence of outflow and feedback signatures in active galactic nuclei (AGNs is a major unresolved question which large integral field unit (IFU) surveys now allow to address. In this paper, we present a kinematic analysis of the ionized gas in 2778 galaxies at z ∼ 0.05 observed by Sloan Digital Sky Survey-IV (SDSS-IV) Mapping Nearby Galaxies at Apache Point Observatory (MaNGA). Specifically, we measure the kinematics of the [O iii] λ5007 Å emission line in each spatial element and fit multiple Gaussian components to account for possible non-gravitational motions of gas. Comparing the kinematics of the ionized gas between 308 MaNGA-selected AGNs that have been previously identified through emission-line diagnostics and sources not classified as AGN, we find that while 25 per cent of MaNGA-selected AGN show [O iii] components with emission-line widths of >500 km s−1 in more than 10 per cent of their spaxels, only 7 per cent of MaNGA non-AGNs show a similar signature. Even the AGNs that do not show nuclear AGN photoionization signatures and that were only identified as AGN based on their larger scale photoionization signatures show similar kinematic characteristics. In addition to obscuration, another possibility is that outflow and mechanical feedback signatures are longer lived than the AGN itself. Our measurements demonstrate that high velocity gas is more prevalent in AGN compared to non-AGN and that outflow and feedback signatures in low-luminosity, low-redshift AGN may so far have been underestimated. We show that higher luminosity MaNGA-selected AGNs are able to drive larger scale outflows than lower luminosity AGN. But estimates of the kinetic coupling efficiencies are ≪1 per cent and suggest that the feedback signatures probed in this paper are unlikely to have a significant impact on the AGN host galaxies. However, continuous energy injection may still heat a fraction of the cool gas and delay or suppress star formation in individual galaxies even when the AGN is weak.
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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 | 0.001 |
| 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".