On the Observational Difference between the Accretion Disk–Corona Connections among Super- and Sub-Eddington Accreting Active Galactic Nuclei
Bibliographic record
Abstract
Abstract We present a systematic X-ray and multiwavelength study of a sample of 47 active galactic nuclei (AGNs) with reverberation mapping measurements. This sample includes 21 super-Eddington accreting AGNs and 26 sub-Eddington accreting AGNs. Using high-state observations with simultaneous X-ray and UV/optical measurements, we investigate whether super-Eddington accreting AGNs exhibit different accretion disk–corona connections compared to sub-Eddington accreting AGNs. We find tight correlations between the X-ray-to-UV/optical spectral slope parameter (α OX) and the monochromatic luminosity at 2500 Å (L 2500Å) for both the super- and sub-Eddington subsamples. The best-fit α OX–L 2500Å relations are consistent overall, indicating that super-Eddington accreting AGNs are not particularly X-ray weak in general compared to sub-Eddington accreting AGNs. We find dependences of α OX on both the Eddington ratio (L Bol/L Edd) and black hole mass (M BH) parameters for our full sample. A multivariate linear regression analysis yields , with a scatter similar to that of the α OX–L 2500Å relation. The hard (rest-frame >2 keV) X-ray photon index (Γ) is strongly correlated with L Bol/L Edd for the full sample and the super-Eddington subsample, but these two parameters are not significantly correlated for the sub-Eddington subsample. A fraction of super-Eddington accreting AGNs show strong X-ray variability, probably due to small-scale gas absorption, and we highlight the importance of employing high-state (intrinsic) X-ray radiation to study the accretion disk–corona connections in AGNs.
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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 | 0.001 |
| 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 | 0.000 | 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".