A Near-infrared Look at AGN Feedback in Bulgeless Galaxies
Bibliographic record
Abstract
Abstract While it is generally believed that supermassive black holes (SMBHs) lie in most galaxies with bulges, few SMBHs have been confirmed in bulgeless galaxies. Identifying such a population could provide important insights to the BH seed population and secular BH growth. To this end, we obtained near-infrared (NIR) spectroscopic observations of a sample of low-redshift bulgeless galaxies with mid-infrared colors suggestive of active galactic nuclei (AGNs). We find additional evidence of AGN activity (such as coronal lines and broad permitted lines) in 69% (9/13) of the sample, demonstrating that mid-infrared selection is a powerful tool to detect AGNs. More than half of the galaxies with confirmed AGN activity show fast outflows in [O iii] in the optical and/or [Si vi] in the NIR, with the latter generally having much faster velocities that are also correlated to their spatial extent. We are also able to obtain virial BH masses for some targets and find they fall within the scatter of other late-type galaxies in the M BH–M stellar relation. The fact that they lack a significant bulge component indicates that secular processes, likely independent of major mergers, grew these BHs to supermassive sizes. Finally, we analyze the rotational gas kinematics and find two notable exceptions: two AGN hosts with outflows that appear to be rotating faster than expected. There is an indication that these two galaxies have stellar masses significantly lower than expected from their dark matter halo masses. This, combined with the observed AGN activity and strong gas outflows, may be evidence of the effects of AGN 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 | 0.001 | 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) | 0.002 | 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".