ROBO-AO Kepler Asteroseismic Survey. II. Do Stellar Companions Inhibit Stellar Oscillations?
Bibliographic record
Abstract
Abstract The Kepler Space Telescope observed over 15,000 stars for asteroseismic studies. Of these, 75% of dwarfs (and 8% of giants) were found to show anomalous behavior, such as suppressed oscillations (low amplitude) or no oscillations at all. The lack of solar-like oscillations may be a consequence of multiplicity, due to physical interactions with spectroscopic companions or due to the dilution of oscillation amplitudes from “wide” (AO detected; visual) or spectroscopic companions introducing contaminating flux. We present a search for stellar companions to 327 of the Kepler asteroseismic sample, which were expected to display solar-like oscillations. We used direct imaging with Robo-AO, which can resolve secondary sources at ∼0.″15, and followed up detected companions with Keck AO. Directly imaged companion systems with both separations of ≤0.″5 and amplitude dilutions >10% all have anomalous primaries, suggesting these oscillation signals are diluted by a sufficient amount of excess flux. We also used the high-resolution spectrometer ESPaDOnS at the Canada–France–Hawai’i Telescope to search for spectroscopic binaries. We find tentative evidence for a higher fraction of spectroscopic binaries with high radial velocity scatter in anomalous systems, which would be consistent with previous results suggesting that oscillations are suppressed by tidal interactions in close eclipsing binaries.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".