Variability of Luminous QSOs following thermal timescale in standard thin accretion disk models
Bibliographic record
Abstract
Abstract We study the dependence of the stochastic variability of QSOs on luminosity, wavelength and thermal timescale in their accretion disks. We use over 5,000 of the most luminous known QSOs with light curves of almost nightly cadence spanning >5 years of observations from the NASA/ATLAS project, which provides 2 billion magnitude pairs for a bootstrap analysis. The results depend on which timescales are included in the analysis: when we only consider timescales >6 months, we find a robust behaviour for the whole sample. This behaviour is consistent with an un-damped random walk on the thermal timescales predicted by thin-disk models. We find a variability amplitude of log(A/A0) ≈1/2×log(Δt/tth). On shorter timescales, we observe a suppression of the amplitude due to light travel-time filtering, which could be used to measure sizes of accretion disks.
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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 | 0.002 | 0.007 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".