SPACE TELESCOPE AND OPTICAL REVERBERATION MAPPING PROJECT. II.<i>SWIFT</i>AND<i>HST</i>REVERBERATION MAPPING OF THE ACCRETION DISK OF NGC 5548
Bibliographic record
Abstract
Recent intensive Swift monitoring of the Seyfert 1 galaxy NGC 5548 yielded 282 usable epochs over 125 days across six UV/optical bands and the X-rays. This is the densest extended active galactic nucleus (AGN) UV/optical continuum sampling ever obtained, with a mean sampling rate <0.5 day. Approximately daily Hubble Space Telescope UV sampling was also obtained. The UV/optical light curves show strong correlations ( ) and the clearest measurement to date of interband lags. These lags are well-fit by a wavelength dependence, with a normalization that indicates an unexpectedly large disk radius of lt-day at 1367 Å, assuming a simple face-on model. The U band shows a marginally larger lag than expected from the fit and surrounding bands, which could be due to Balmer continuum emission from the broad-line region as suggested by Korista and Goad. The UV/X-ray correlation is weaker ( ) and less consistent over time. This indicates that while Swift is beginning to measure UV/optical lags in general agreement with accretion disk theory (although the derived size is larger than predicted), the relationship with X-ray variability is less well understood. Combining this accretion disk size estimate with those from quasar microlensing studies suggests that AGN disk sizes scale approximately linearly with central black hole mass over a wide range of masses.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".