The Near Infrared Imager and Slitless Spectrograph for the James Webb Space Telescope. III. Single Object Slitless Spectroscopy
Bibliographic record
Abstract
Abstract The Near Infrared Imager and Slitless Spectrograph instrument (NIRISS) is the Canadian Space Agency contribution to the suite of four science instruments of the James Webb Space Telescope. As one of the three NIRISS observing modes, the Single Object Slitless Spectroscopy (SOSS) mode is tailor-made to undertake time-series observations of exoplanets to perform transit spectroscopy. The SOSS permits observing point sources between 0.6 and 2.8 μ m at a resolving power of 650 at 1.25 μ m using a slitless cross-dispersing grism while its defocussing cylindrical lens enables observing targets as bright as J = 6.7 by spreading light across 23 pixels along the cross-dispersion axis. This paper officially presents the design of the SOSS mode, its operation, characterization, and its performance, from ground-based testing and flight-based commissioning. On-sky measurements demonstrate a peak photon conversion efficiency of 55% at 1.2 μ m. The first time series on the A-type star BD+60°1753 achieves a flux stability close to the photon-noise limit, so far tested to a level of 20 parts per million on a 40 minute timescale after simply subtracting a long-term trend. Uncorrected 1/ f noise residuals underneath the spectral traces add an extra source of noise equivalent to doubling the readout noise. Preliminary analysis of an HAT-P-14b transit time series indicates that it is difficult to remove all of the noise in pixels with partially saturated ramps. Overall, the SOSS delivers performance at the level required to tackle key exoplanetary science programs such as detecting secondary atmospheres on terrestrial planets and measuring abundances of several chemical species in gas giants.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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 teacher head, 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".