OPTICAL PHASE CURVES OF<i>KEPLER</i>EXOPLANETS
Bibliographic record
Abstract
We conducted a comprehensive search for optical phase variations of all close-in ( a / R ⋆ < 10) planet candidates in 15 quarters of Kepler space telescope data. After correcting for systematics, we found eight systems that show secondary eclipses as well as phase variations. Of these, five (Kepler-5, Kepler-6, Kepler-8, KOI-64, and KOI-2133) are new and three (TrES-2, HAT-P-7, and KOI-13) have published phase curves, albeit with many fewer observations. We model the full phase curve of each planet candidate, including the primary and secondary transits, and derive their albedos, dayside and nightside temperatures, ellipsoidal variations, and Doppler beaming. We find that KOI-64 and KOI-2133 have nightside temperatures well above their equilibrium values (while KOI-2133 also has an albedo, >1), so we conclude that they are likely to be self-luminous objects rather than planets. The other six candidates have characteristics consistent with their being planets with low geometric albedos (<0.3). For TrES-2 and KOI-13, the Kepler bandpass appears to probe atmospheric layers hotter than the planet's equilibrium temperature. For KOI-13, we detect a never-before-seen third cosine harmonic with an amplitude of 6.7 ± 0.3 ppm and a phase shift of −1.1 ± 0.1 rad in the phase curve residual, possibly due to its spin-orbit misalignment. We report derived planetary parameters for all six planets, including masses from ellipsoidal variations and Doppler beaming, and compare our results to published values when available. Our results nearly double the number of Kepler exoplanets with measured phase curve variations, thus providing valuable constraints on the properties of hot Jupiters.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.000 |
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".