Tunable filter imager for JWST: etalon opto-mechanical design and test results
Bibliographic record
Abstract
The Tunable Filter Imager of the James Webb Space Telescope will be based on blocking filters and a tunable Fabry- Perot etalon with an average resolution of about 100. It will operate in two wavelength bands from 1.6 μm to 2.5 μm and from 3.1 μm to 4.9 μm at a cryogenic temperature of about 35K. It will respectively be used to study the First Light and re-ionization of the universe by surveying Lyman-alpha sources and to provide an in-depth study of proto-planetary systems as well as giant planets of nearby stars. The Tunable Filter Imager (TFI) is designed to image a sky field of view of 2.2' by 2.2' (magnified to 4.6 deg. x 4.6 deg. at the etalon). Its tunable etalon has an aperture of 56 mm. It operates at low orders 1 and 3 for the two wavelength bands which reduces the number of blocking filters to a number of eight. The etalon gap tuning between 2.5 μm and 5.5 μm is provided by piezoelectric actuators and will be servo controlled by using capacitive displacement sensors. In this paper, we present the etalon's opto-mechanical design that allows us to achieve the stringent requirements in terms of resolution over a wide infrared wavelength band, and operation at low gap at cryogenic temperature. Cryogenic test results will be shared as well.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".