THE Fe II EMISSION IN ACTIVE GALACTIC NUCLEI: EXCITATION MECHANISMS AND LOCATION OF THE EMITTING REGION
Bibliographic record
Abstract
ABSTRACT We present a study of Fe ii emission in the near-infrared region (NIR) for 25 active galactic nuclei (AGNs) to obtain information about the excitation mechanisms that power it and the location where it is formed. We employ an NIR Fe ii template derived in the literature and find that it successfully reproduces the observed Fe ii spectrum. The Fe ii bump at 9200 Å detected in all objects studied confirms that Lyα fluorescence is always present in AGNs. The correlation found between the flux of the 9200 Å bump, the 1 μm lines, and the optical Fe ii implies that Lyα fluorescence plays an important role in Fe ii production. We determined that at least 18% of the optical Fe ii is due to this process, while collisional excitation dominates the production of the observed Fe ii. The line profiles of Fe ii λ10502, O i λ11287, Ca ii λ8664, and Paβ were compared to gather information about the most likely location where they are emitted. We found that Fe ii, O i and Ca ii have similar widths and are, on average, 30% narrower than Paβ. Assuming that the clouds emitting the lines are virialized, we show that the Fe ii is emitted in a region twice as far from the central source than Paβ. The distance, though, strongly varies: from 8.5 light-days for NGC 4051 to 198.2 light-days for Mrk 509. Our results reinforce the importance of the Fe ii in the NIR to constrain critical parameters that drive its physics and the underlying AGN kinematics, as well as more accurate models aimed at reproducing this complex emission.
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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 | 0.000 | 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) | 0.000 | 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".