NEAR-INFRARED THERMAL EMISSION DETECTIONS OF A NUMBER OF HOT JUPITERS AND THE SYSTEMATICS OF GROUND-BASED NEAR-INFRARED PHOTOMETRY
Bibliographic record
Abstract
We present detections of the near-infrared thermal emission of three hot Jupiters and one brown dwarf using the Wide-field Infrared Camera (WIRCam) on the Canada–France–Hawaii Telescope (CFHT). These include Ks -band secondary eclipse detections of the hot Jupiters WASP-3b and Qatar-1b and the brown dwarf KELT-1b. We also report Y -band, K CONT -band, and two new and one reanalyzed Ks -band detections of the thermal emission of the hot Jupiter WASP-12b. We present a new reduction pipeline for CFHT/WIRCam data, which is optimized for high precision photometry. We also describe novel techniques for constraining systematic errors in ground-based near-infrared photometry, so as to return reliable secondary eclipse depths and uncertainties. We discuss the noise properties of our ground-based photometry for wavelengths spanning the near-infrared (the YJHK bands), for faint and bright stars, and for the same object on several occasions. For the hot Jupiters WASP-3b and WASP-12b we demonstrate the repeatability of our eclipse depth measurements in the Ks band; we therefore place stringent limits on the systematics of ground-based, near-infrared photometry, and also rule out violent weather changes in the deep, high pressure atmospheres of these two hot Jupiters at the epochs of our observations.
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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 | 0.001 | 0.004 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".