The Near-Infrared Spectrograph (NIRSpec) on the James Webb Space Telescope
Bibliographic record
Abstract
We provide an overview of the capabilities and performance of the Near-Infrared Spectrograph (NIRSpec) on the James Webb Space Telescope when used in its multi-object spectroscopy (MOS) mode employing a novel Micro Shutter Array (MSA) slit device. The MSA consists of four separate 98″ × 91″ quadrants each containing 365 × 171 individually addressable shutters whose open areas on the sky measure 0.20″ × 0.46″ on a 0.27″ × 0.53″ pitch. This is the first time that a configurable multi-object spectrograph has been available on a space mission. The levels of multiplexing achievable with NIRSpec MOS mode are quantified and we show that NIRSpec will be able to observe typically fifty to two hundred objects simultaneously with the pattern of close to a quarter of a million shutters provided by the MSA. This pattern is fixed and regular, and we identify the specific constraints that it yields for NIRSpec observation planning. In particular, the roll angle at which a given NIRSpec MSA observation will be executed will, in most cases, not be known before the observation is actually scheduled. As a consequence, NIRSpec users planning MOS mode observations cannot at the proposal stage know precisely which subset of their intended targets will be observable, and will therefore need to intentionally oversize their submitted target catalogues accordingly. We also present the data processing and calibration steps planned for the NIRSpec MOS data. The significant variation in size of the mostly diffraction-limited instrument point spread function over the large wavelength range of 0.6–5.3 µm covered by the instrument, combined with the fact that most targets observed with the MSA cannot be expected to be perfectly centred within their respective slits, makes the spectrophotometric and wavelength calibration of the obtained spectra particularly complex. This is reflected by the inclusion of specific steps such as the wavelength zero-point correction nd the relative path loss correction in the NIRSpec data processing and calibration flow. The processing of spectra of morphologically extended targets will require additional attention and development. These challenges notwithstanding, the sensitivity and multiplexing capabilities anticipated of NIRSpec in MOS mode are unprecedented, and should enable significant progress to be made in addressing a wide range of outstanding astrophysical problems.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".