Phase Offsets and the Energy Budgets of Hot Jupiters
Bibliographic record
Abstract
Abstract Thermal phase curves of short-period planets on circular orbits provide joint constraints on the fraction of incoming energy that is reflected (Bond albedo) and the fraction of absorbed energy radiated by the night hemisphere (heat recirculation efficiency). Many empirical studies of hot Jupiters have implicitly assumed that the dayside is the hottest hemisphere and the nightside is the coldest hemisphere. For a given eclipse depth and phase amplitude, an orbital lag between a planet’s peak brightness and its eclipse—a phase offset—implies that planet’s nightside emits greater flux. To quantify how phase offsets impact the energy budgets of short-period planets, we compile all infrared observations of the nine planets with multi-band eclipse depths and phase curves. Accounting for phase offsets shifts planets to lower Bond albedo and greater day–night heat transport, usually by ≲1σ. For WASP-12b, the published phase variations have been analyzed in two different ways, and the inferred energy budget depends sensitively on which analysis one adopts. Our fiducial scenario supports a Bond albedo of , significantly higher than the published optical geometric albedo, and a recirculation efficiency of , following the trend of larger day–night temperature contrast with greater stellar irradiation. If instead we adopt the alternative analysis, then WASP-12b has a Bond albedo consistent with zero and a much higher recirculation efficiency. To definitively determine the energy budget of WASP-12b, new observational analyses will be necessary.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".