The Sloan Digital Sky Survey Reverberation Mapping Project: Investigation of Continuum Lag Dependence on Broad-line Contamination and Quasar Properties
Bibliographic record
Abstract
Abstract This work studies the relationship between accretion-disk size and quasar properties, using a sample of 95 quasars from the Sloan Digital Sky Survey Reverberation Mapping Project with measured lags between the g and i photometric bands. Our sample includes disk lags that are both longer and shorter than predicted by the Shakura and Sunyaev model, requiring explanations that satisfy both cases. Although our quasars each have one lag measurement, we explore the wavelength-dependent effects of diffuse broad-line region (BLR) contamination through our sample’s broad redshift range, 0.1 < z < 1.2. We do not find significant evidence of variable diffuse Fe ii and Balmer nebular emission in the rms spectra, nor from Anderson–Darling tests of quasars in redshift ranges with and without diffuse nebular emission falling in the observed-frame filters. Contrary to previous work, we do not detect a significant correlation between the measured continuum and BLR lags in our luminous quasar sample, similarly suggesting that our continuum lags are not dominated by diffuse nebular emission. Similar to other studies, we find that quasars with larger-than-expected continuum lags have lower 3000 Å luminosities, and we additionally find longer continuum lags with lower X-ray luminosities and black hole masses. Our lack of evidence for diffuse BLR contribution to the lags indicates that the anticorrelation between continuum lag and luminosity is not likely to be due to the Baldwin effect. Instead, these anticorrelations favor models in which the continuum lag increases in lower-luminosity active galactic nuclei, including scenarios featuring magnetic coupling between the accretion disk and X-ray corona, and/or ripples or rims in the disk.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".