OBSERVATIONS OF DOPPLER BOOSTING IN KEPLER LIGHT CURVES
Bibliographic record
Abstract
Among the initial results from Kepler were two striking light curves, for KOI 74 and KOI 81, in which the relative depths of the primary and secondary eclipses showed that the more compact, less luminous object was hotter than its stellar host. That result became particularly intriguing because a substellar mass had been derived for the secondary in KOI 74, which would make the high temperature challenging to explain; in KOI 81, the mass range for the companion was also reported to be consistent with a substellar object. We re-analyze the Kepler data and demonstrate that both companions are likely to be white dwarfs. We also find that the photometric data for KOI 74 show a modulation in brightness as the more luminous star orbits, due to Doppler boosting. The magnitude of the effect is sufficiently large that we can use it to infer a radial velocity amplitude accurate to 1 km s -1 . As far as we are aware, this is the first time a radial-velocity curve has been measured photometrically. Combining our velocity amplitude with the inclination and primary mass derived from the eclipses and primary spectral type, we infer a secondary mass of 0.22 ± 0.03 M ☉ . We use our estimates to consider the likely evolutionary paths and mass-transfer episodes of these binary systems.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 | 0.001 |
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".