<i>MOST</i> photometry of the enigmatic PMS pulsator HD 142666
Bibliographic record
Abstract
Context. Modeling of pre-main sequence (PMS) stars through asteroseismology of PMS p-mode pulsators has only recently become possible, and spacebased photometry is one of the important sources of data for these efforts. We present precise photometry of the pulsating Herbig Ae star HD 142666 obtained in two consecutive years with the MOST (Microvariability & Oscilations of STars) satellite.Aims. Previously, only a single pulsation period was known for HD 142666. The MOST photometry reveals that HD 142666 is multi-periodic. However, the unique identification of pulsation frequencies is complicated by the presence of irregular variability caused by the star's circumstellar dust disk. The two light curves obtained with MOST in 2006 and 2007 provided data of unprecedented quality to study the pulsations in HD 142666 and also to monitor the circumstellar variability.Methods. Frequency analysis was performed using the routine sigspec and the results from the 2006 and 2007 campaigns were then compared to each other with the software cinderella to identify frequencies common to both light curves. The correlated frequencies were then submitted to an asteroseismic analysis.Results. We attribute 12 frequencies to pulsation. Model fits to the three frequencies with the highest amplitudes lie well outside the uncertainty box for the star's position in the HR diagram based on published values. Some of the frequencies appear to be rotationally split modes.Conclusions. The models suggest that either (1) the published estimate of the luminosity of HD 142666, based on a relation between circumstellar disk radius and stellar luminosity, is too high and/or (2) additional physics such as mass accretion may be needed in our models to accurately fit both the observed frequencies and HD 142666's position in the HR diagram.
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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 | 0.000 |
| 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) | 0.004 | 0.001 |
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".