The Sloan Digital Sky Survey Reverberation Mapping Project: How Broad Emission Line Widths Change When Luminosity Changes
Bibliographic record
Abstract
Abstract Quasar broad emission lines are largely powered by photoionization from the accretion continuum. Increased central luminosity will enhance line emissivity in more distant clouds, leading to increased average distance of the broad-line-emitting clouds and decreased averaged line width, which is known as the “breathing” broad-line region. However, different lines breathe differently, and some high-ionization lines, such as C iv, can even show “anti-breathing” where the line broadens when luminosity increases. Using multi-year photometric and spectroscopic monitoring data from the Sloan Digital Sky Survey Reverberation Mapping project, we quantify the breathing effect ( ) of broad Hα, Hβ, Mg ii, C iv, and C iii] for statistical quasar samples over z ≈ 0.1–2.5. We find that Hβ displays the most consistent normal breathing expected from the virial relation (α ∼ −0.25), Mg ii and Hα on average show no breathing (α ∼ 0), and C iv (and similarly C iii] and Si iv) mostly shows anti-breathing (α > 0). The anti-breathing of C iv can be well understood by the presence of a non-varying core component in addition to a reverberating broad-base component, which is consistent with earlier findings. The deviation from canonical breathing introduces extra scatter (a luminosity-dependent bias) in single-epoch virial BH mass estimates due to intrinsic quasar variability, which underlies the long-argued caveats of C iv single-epoch masses. Using the line dispersion instead of FWHM leads to fewer, albeit still substantial, deviations from canonical breathing in most cases. Our results strengthen the need for reverberation mapping to provide reliable quasar BH masses and to quantify the level of variability-induced bias in single-epoch BH masses based on various lines.
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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 | 0.002 |
| 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 | 0.001 | 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".