High accuracy, absolute, cryogenic refractive index measurements of infrared lens materials for JWST NIRCam using CHARMS
Bibliographic record
Abstract
The refractive optical design of the James Webb Space Telescope (JWST) Near Infrared Camera (NIRCam) uses three infrared materials in its lenses: LiF, BaF2, and ZnSe. In order to provide the instrument's optical designers with accurate, heretofore unavailable data for absolute refractive index based on actual cryogenic measurements, two prismatic samples of each material were measured using the cryogenic, high accuracy, refraction measuring system (CHARMS) at NASA's Goddard Space Flight Center (GSFC), densely covering the temperature range from 15 to 320 K and wavelength range from 0.4 to 5.6 microns. Data reduction methods are discussed and graphical and tabulated data for absolute refractive index, dispersion, and thermo-optic coefficient for these three materials are presented for selected wavelengths and temperatures along with estimates of index uncertainty. Coefficients for temperature-dependent Sellmeier fits of measured index are also presented with an example of their usage to predict absolute index at any wavelength or temperature within the applicable range of those parameters.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.001 | 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 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".