Enhanced star formation in narrow-line Seyfert 1 active galactic nuclei revealed by<i>Spitzer</i>
Bibliographic record
Abstract
We present new low-resolution Spitzer mid-infrared spectroscopy of a sample of 20 ROSAT-selected local narrow-line Seyfert 1 galaxies (NLS1s). We detect strong active galactic nucleus (AGN) continuum in all and clear polycyclic aromatic hydrocarbon (PAH) emission in 70 per cent of the sources. The 6.2 μm PAH luminosity spans three orders of magnitude, from ∼1039 to ∼1042 erg s−1, providing strong evidence for intense ongoing star formation in the circumnuclear regions of these sources. Using the Infrared Spectrograph/Spitzer archive, we gathered a large number of additional NLS1s and their broad-line counterparts (BLS1s) and constructed NLS1 and BLS1 subsamples to compare them in various ways. The comparison shows a clear separation according to full width at half-maximum (Hβ) [FWHM(Hβ)] such that objects with narrower broad Hβ lines are the strongest PAH emitters. We test this division in various ways trying to remove biases due to luminosity and aperture size. Specifically, we find that star formation activity around NLS1 AGN is larger than around BLS1 of the same AGN luminosity. The above result seems to hold over the entire range of distance and luminosity. Moreover, the star formation rate is higher in low black hole mass and high L/LEdd systems indicating that black hole growth and star formation are occurring simultaneously.
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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 | 0.001 | 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".