Light-curve Instabilities of β Lyrae Observed by the BRITE Satellites
Bibliographic record
Abstract
Abstract Photometric instabilities of β Lyrae (β Lyr) were observed in 2016 by two red-filter BRITE satellites over more than 10 revolutions of the binary, with ∼100 minute sampling. Analysis of the time series shows that flares or fading events take place typically three to five times per binary orbit. The amplitudes of the disturbances (relative to the mean light curve, in units of the maximum out-of-eclipse light flux, f.u.) are characterized by a Gaussian distribution with σ = 0.0130 ± 0.0004 f.u. Most of the disturbances appear to be random, with a tendency to remain for one or a few orbital revolutions, sometimes changing from brightening to fading or the reverse. Phases just preceding the center of the deeper eclipse showed the most scatter while phases around the secondary eclipse were the quietest. This implies that the invisible companion is the most likely source of the instabilities. Wavelet transform analysis showed the domination of the variability scales at phase intervals 0.05–0.3 (0.65–4 days), with the shorter (longer) scales dominating in numbers (variability power) in this range. The series can be well described as a stochastic Gaussian process with the signal at short timescales showing a slightly stronger correlation than red noise. The signal decorrelation timescale, τ = (0.068 ± 0.018) in phase or (0.88 ± 0.23) days, appears to follow the same dependence on the accretor mass as that observed for active galactic nucleus and quasi-stellar object masses five to nine orders of magnitude larger than the β Lyr torus-hidden component.
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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 | 0.001 |
| 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".