Characteristics of solar-like oscillations in red giants observed in the CoRoT exoplanet field
Bibliographic record
Abstract
<i>Context. <i/>Observations during the first long run (~150 days) in the exo-planet field of CoRoT increase the number of G-K giant stars for which solar-like oscillations are observed by a factor of 100. This opens the possibility to study the characteristics of their oscillations in a statistical sense.<i>Aims. <i/>We aim to understand the statistical distribution of the frequencies of maximum oscillation power () in red giants and to search for a possible correlation between and the large separation ().<i>Methods. <i/>Red giants with detectable solar-like oscillations are identified using both semi-automatic and manual procedures. For these stars, we determine as the centre of a Gaussian fit to the oscillation power excess. For the determination of , we use the autocorrelation of the Fourier spectra, the comb response function and the power spectrum of the power spectrum.<i>Results. <i/>The resulting distribution shows a pronounced peak between 20-40 <i>μ<i/>Hz. For about half of the stars we obtain with at least two methods. The correlation between and follows the same scaling relation as inferred for solar-like stars.<i>Conclusions. <i/>The shape of the distribution can partly be explained by granulation at low frequencies and by white noise at high frequencies, but the population density of the observed stars turns out to be also an important factor. From the fact that the correlation between and for red giants follows the same scaling relation as obtained for sun-like stars, we conclude that the sound travel time over the pressure scale height of the atmosphere scales with the sound travel time through the whole star irrespective of evolution. The fraction of stars for which we determine does not correlate with in the investigated frequency range, which confirms theoretical predictions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".