Zooming into local active galactic nuclei: The power of combining SDSS-IV MaNGA with higher resolution integral field unit observations
Bibliographic record
Abstract
Ionized gas outflows driven by active galactic nuclei (AGN) are ubiquitous in high-luminosity AGN with outflow speeds apparently correlated with the total bolometric luminosity of the AGN. This empirical relation and theoretical work suggest that in the range Lbol ∼ 1043−45 erg s−1 there must exist a threshold luminosity above which the AGN becomes powerful enough to launch winds that will be able to escape the galaxy potential. In this paper, we present pilot observations of two AGN in this transitional range that were taken with the Gemini North Multi-Object Spectrograph integral field unit (IFU). Both sources have also previously been observed within the Sloan Digital Sky Survey-IV (SDSS) Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey. While the MaNGA IFU maps probe the gas fields on galaxy-wide scales and show that some regions are dominated by AGN ionization, the new Gemini IFU data zoom into the centre with four times better spatial resolution. In the object with the lower Lbol we find evidence of a young or stalled biconical AGN-driven outflow where none was obvious at the MaNGA resolution. In the object with the higher Lbol we trace the large-scale biconical outflow into the nuclear region and connect the outflow from small to large scales. These observations suggest that AGN luminosity and galaxy potential are crucial in shaping wind launching and propagation in low-luminosity AGN. The transition from small and young outflows to galaxy-wide feedback can only be understood by combining large-scale IFU data that trace the galaxy velocity field with higher resolution, small-scale IFU maps.
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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 | 0.001 |
| 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".