The Accretion History of EX Lup: A Century of Bursts, Outbursts, and Quiescence
Bibliographic record
Abstract
Abstract EX Lup is the archetype for the class of young stars that undergoes repeated accretion outbursts of ∼5 mag at optical wavelengths that last for months. Despite extensive monitoring that dates back 130 yr, the accretion history of EX Lup remains mostly qualitative and has large uncertainties. We assess historical accretion rates of EX Lup by applying correlations between optical brightness and accretion, developed on multi-band magnitude photometry of the ∼2 mag optical burst in 2022. Two distinct classes of bursts occur: major outbursts (ΔV ∼ 5 mag) have year-long durations, are rare, reach accretion rates of M ̇ acc ∼ 10 − 7 M ⊙ yr−1 at peak, and have a total accreted mass of around 0.1 Earth mass. The characteristic bursts (ΔV ∼ 2 mag) have durations of ∼2–3 months, are more common, reach accretion rates of M ̇ acc ∼ 10 − 8 M ⊙ yr−1 at peak, and have a total accreted mass of around 10−3 Earth masses. The distribution of total accreted mass in the full set of bursts is poorly described by a power law, which suggests different driving causes behind the major outburst and characteristic bursts. The total mass accreted during two classes of bursts is around 2 times the masses accreted during quiescence. Our analysis of the light curves reveals a color-dependent time lag in the 2022 post-burst light curve, attributed to the presence of both hot and cool spots on the stellar surface.
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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 | 0.003 |
| 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 | 0.001 | 0.001 |
| 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".