NIGHT: A compact, near-infrared, high-resolution spectrograph to survey helium in exoplanet systems
Bibliographic record
Abstract
ABSTRACT Among highly irradiated exoplanets, some have been found to undergo significant hydrodynamic expansion traced by atmospheric escape. To better understand these processes in the context of planetary evolution, we propose NIGHT (the Near-Infrared Gatherer of Helium Transits). NIGHT is a high-resolution spectrograph dedicated to surveying and temporally monitoring He i triplet absorption at 1083 nm in stellar and planetary atmospheres. In this paper, we outline our scientific objectives, requirements, and cost-efficient design. Our simulations, based on previous detections and modelling using the current exoplanet population, determine our requirements and survey targets. With a spectral resolution of 70 000 on a 2-m telescope, NIGHT can accurately resolve the helium triplet and detect 1 per cent peak absorption in 118 known exoplanets in a single transit. Additionally, it can search for 3σ temporal variations of 0.4 per cent in 66 exoplanets in-between two transits. These are conservative estimates considering the ongoing detections of transiting planets amenable to atmospheric characterization. We find that instrumental stability at 40 m s−1, less stringent than for radial velocity monitoring, is sufficient for transmission spectroscopy in He i. As such, NIGHT can utilize mostly off-the-shelf components, ensuring cost-efficiency. A fibre-fed system allows for flexibility as a visitor instrument on a variety of telescopes, making it ideal for follow-up observations after JWST or ground-based detections. Over a few years of surveying, NIGHT could offer detailed insights into the mechanisms shaping the hot Neptune desert and close-in planet population by significantly expanding the statistical sample of planets with known evaporating atmospheres. First light is expected in 2024.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".