Revisiting Emission-line Measurement Methods for Narrow-line Active Galactic Nuclei
Bibliographic record
Abstract
Abstract Measuring broad emission-line widths in active galactic nuclei (AGN) is not straightforward owing to the complex nature of flux variability in these systems. Line width measurements become especially challenging when the signal-to-noise ratio is low, profiles are narrower, or spectral resolution is low. We conducted an extensive correlation analysis between emission-line measurements from the optical spectra of Markarian 142 (Mrk 142; a narrow-line Seyfert galaxy) taken with the Gemini North Telescope (Gemini) at a spectral resolution of 185.6 ± 10.2 km s−1 and the Lijiang Telescope (LJT) at 695.2 ± 3.9 km s−1 to investigate the disparities in the measured broad-line widths from both telescopes’ data. Due to its narrow broad-line profiles, which were severely affected by instrumental broadening in the lower-resolution LJT spectra, Mrk 142 posed a challenge. We discovered that allowing the narrow-line flux of permitted lines having broad and narrow components to vary during spectral fitting caused a leak in the narrow-line flux to the broad component, resulting in broader broad-line widths in the LJT spectra. Fixing the narrow-line flux ratios constrained the flux leak and yielded the Hβ broad-line widths from LJT spectra ∼54% closer to the Gemini Hβ widths than with flexible narrow-line ratios. The availability of spectra at different resolutions presented this unique opportunity to inspect how spectral resolution affected emission-line profiles in our data and adopt a unique method to accurately measure broad-line widths. Reconsidering line measurement methods while studying diverse AGN populations is critical for the success of future reverberation-mapping studies. Based on the technique used in this work, we offer recommendations for measuring line widths in narrow-line AGN.
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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 | 0.008 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".