High-resolution exploration of transiting sub-Neptunes’ atmospheres with NIRPS
Bibliographic record
Abstract
Atmospheric characterization of smaller exoplanets has entered a new era with the capabilities of JWST and the latest high-resolution spectrographs such as NIRPS, in combination with HARPS on the ESO 3.6m at La Silla, which has started operations on April 1st, 2023. By the start of the EGU General Assembly 2024, the NIRPS consortium has scheduled 25 transits of more than 10 sub-Neptunes (< 3 REarth) not named TRAPPIST-1, and many more to come during the 725 total nights of NIRPS Guaranteed Time Observations (GTO).In this talk, we present an early overview of the high-resolution transmission spectroscopy analysis of those targets, looking for a wide range of atomic and molecular species both in infrared and in the visible, and compare those results with the latest JWST findings for those targets. We show that NIRPS observations lead to some of the most precise transmission spectra in the metastable helium region ever produced, strongly constraining this element's presence or lack thereof in the upper atmosphere of exoplanets.
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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 | 0.000 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".