A DISTANT MIRROR: SOLAR OSCILLATIONS OBSERVED ON NEPTUNE BY THE KEPLER K2 MISSION
Bibliographic record
Abstract
ABSTRACT Starting in 2014 December, Kepler K 2 observed Neptune continuously for 49 days at a 1 minute cadence. The goals consisted of studying its atmospheric dynamics, detecting its global acoustic oscillations, and those of the Sun, which we report on here. We present the first indirect detection of solar oscillations in intensity measurements. Beyond the remarkable technical performance, it indicates how Kepler would see a star like the Sun. The result from the global asteroseismic approach, which consists of measuring the oscillation frequency at maximum amplitude ν max and the mean frequency separation between mode overtones Δν, is surprising as the ν max measured from Neptune photometry is larger than the accepted value. Compared to the usual reference ν max,⊙ = 3100 μHz, the asteroseismic scaling relations therefore make the solar mass and radius appear larger by 13.8 ± 5.8% and 4.3 ± 1.9%, respectively. The higher ν max is caused by a combination of the value of ν max,⊙, being larger at the time of observations than the usual reference from SOHO/VIRGO/SPM data (3160 ± 10 μHz), and the noise level of the K 2 time series, being 10 times larger than VIRGO’s. The peak-bagging method provides more consistent results: despite a low signal-to-noise ratio (S/N), we model 10 overtones for degrees ℓ = 0, 1, 2. We compare the K 2 data with simultaneous SOHO/VIRGO/SPM photometry and BiSON velocity measurements. The individual frequencies, widths, and amplitudes mostly match those from VIRGO and BiSON within 1σ, except for the few peaks with the lowest S/N.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".