The MACHO Project Large Magellanic Cloud Variable‐Star Inventory. IX. Frequency Analysis of the First‐Overtone RR Lyrae Stars and the Indication for Nonradial Pulsations
Bibliographic record
Abstract
More than 1300 variables classified provisionally as first-overtone RR Lyrae pulsators in the MACHO variable-star database of the Large Magellanic Cloud (LMC) have been subjected to standard frequency analysis. Based on the remnant power in the prewhitened spectra, we found 70% of the total population to be monoperiodic. The remaining 30% (411 stars) are classified as one of nine types according to their frequency spectra. Several types of RR Lyrae pulsational behavior are clearly identified here for the first time. Together with the earlier discovered double-mode (fundamental and first-overtone) variables, this study increased the number of known double-mode stars in the LMC to 181. During the total 6.5 yr time span of the data, 10% of the stars showed strong period changes. The size, and in general also the patterns of the period changes, exclude a simple evolutionary explanation. We also discovered two additional types of multifrequency pulsators with low occurrence rates of 2% for each. In the first type, there remains one closely spaced component after prewhitening by the main pulsation frequency. In the second type, the number of remnant components is two; they are also closely spaced, and are symmetric in their frequency spacing relative to the central component. This latter type of variables are associated with their relatives among the fundamental pulsators, known as Blazhko variables. Their high frequency (≈20%) among the fundamental-mode variables versus the low occurrence rate of their first-overtone counterparts makes it more difficult to explain the Blazhko phenomenon by any theory depending mainly on the role of aspect angle or magnetic field. None of the current theoretical models are able to explain the observed close frequency components without invoking nonradial pulsation components in these stars.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.005 |
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".