Awesome SOSS: transmission spectroscopy of WASP-96b with NIRISS/SOSS
Bibliographic record
Abstract
ABSTRACT The future is now – after its long-awaited launch in 2021 December, JWST began science operations in 2022 July and is already revolutionizing exoplanet astronomy. The Early Release Observations (ERO) programme was designed to provide the first images and spectra from JWST, covering a multitude of science cases and using multiple modes of each on-board instrument. Here, we present transmission spectroscopy observations of the hot-Saturn WASP-96 b with the Single Object Slitless Spectroscopy (SOSS) mode of the Near Infrared Imager and Slitless Spectrograph, observed as part of the ERO programme. As the SOSS mode presents some unique data reduction challenges, we provide an in-depth walk-through of the major steps necessary for the reduction of SOSS data: including background subtraction, correction of 1/f noise, and treatment of the trace order overlap. We furthermore offer potential routes to correct for field star contamination, which can occur due to the SOSS mode’s slitless nature. By comparing our extracted transmission spectrum with grids of atmosphere models, we find an atmosphere metallicity between 1× and 5× solar, and a solar carbon-to-oxygen ratio. Moreover, our models indicate that no grey cloud deck is required to fit WASP-96 b’s transmission spectrum, but find evidence for a slope shortward of 0.9 μm, which could either be caused by enhanced Rayleigh scattering or the red wing of a pressure-broadened Na feature. Our work demonstrates the unique capabilities of the SOSS mode for exoplanet transmission spectroscopy and presents a step-by-step reduction guide for this new and exciting instrument.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".