TESTING SCALING RELATIONS FOR SOLAR-LIKE OSCILLATIONS FROM THE MAIN SEQUENCE TO RED GIANTS USING<i>KEPLER</i>DATA
Bibliographic record
Abstract
We have analyzed solar-like oscillations in ∼1700 stars observed by the Kepler Mission, spanning from the main sequence to the red clump. Using evolutionary models, we test asteroseismic scaling relations for the frequency of maximum power (ν max ), the large frequency separation (Δν), and oscillation amplitudes. We show that the difference of the Δν–ν max relation for unevolved and evolved stars can be explained by different distributions in effective temperature and stellar mass, in agreement with what is expected from scaling relations. For oscillation amplitudes, we show that neither ( L / M ) s scaling nor the revised scaling relation by Kjeldsen & Bedding is accurate for red-giant stars, and demonstrate that a revised scaling relation with a separate luminosity-mass dependence can be used to calculate amplitudes from the main sequence to red giants to a precision of ∼25%. The residuals show an offset particularly for unevolved stars, suggesting that an additional physical dependency is necessary to fully reproduce the observed amplitudes. We investigate correlations between amplitudes and stellar activity, and find evidence that the effect of amplitude suppression is most pronounced for subgiant stars. Finally, we test the location of the cool edge of the instability strip in the Hertzsprung–Russell diagram using solar-like oscillations and find the detections in the hottest stars compatible with a domain of hybrid stochastically excited and opacity driven pulsation.
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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 | 0.004 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".