Untangling the complex nature of AGN variability in Fairall 9
Bibliographic record
Abstract
ABSTRACT The accretion flow in active galactic nuclei (AGN) is not well understood, motivating intensive monitoring campaigns of multiwavelength variability to probe its structure. One of the best of these is the 3 yr optical/UV/X-ray approximately daily monitoring campaign on Fairall 9, a fairly typical moderate accretion rate AGN. The UV light curve shows a clear increase over $\sim 50$ d between years 1 and 2, strongly coherent with the X-ray light curve rise. This changes the average spectral energy distribution (SED) such that the disc component is stronger while the X-ray spectrum steepens, so that the total X-ray power remains roughly constant. Outside of this global change, we apply a Fourier-resolved analysis to test stochastic models where intrinsic fluctuations in the UV disc propagate down into the hard X-ray emission region via both changing the seed photon flux for Compton scattering (short light travel time-scale) and changing the electron density (longer propagation time-scale). Unlike these models, the hard X-rays are not particularly well correlated with the UV, and also have the wrong sign in that the hard X-rays marginally lead the UV fluctuations. We show that this is instead consistent with uncorrelated stochastic fluctuations in both the UV (slow) and X-ray (fast), which are linked together only weakly via light travel time. These variability properties, as well as the changes in the SED, have implications for our understanding of AGN structure and physics, as well as future monitoring campaigns.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".