The Infrared Imaging Spectrograph (IRIS) for TMT: Volume Phase Holographic Grating Performance Testing and Discussion
Bibliographic record
Abstract
Maximizing the grating efficiency is a key goal for the first light instrument IRIS (Infrared Imaging Spectrograph) currently being designed to sample the diffraction limit of the TMT (Thirty Meter Telescope). Volume Phase Holographic (VPH) gratings have been shown to offer extremely high efficiencies that approach 100% for high line frequencies (i.e., 600 to 6000l/mm), which has been applicable for astronomical optical spectrographs. However, VPH gratings have been less exploited in the near-infrared, particularly for gratings that have lower line frequencies. Given their potential to offer high throughputs and low scattered light, VPH gratings are being explored for IRIS as a potential dispersing element in the spectrograph. Our team has procured near-infrared gratings from two separate vendors. We have two gratings with the specifications needed for IRIS current design: 1.51-1.82μm (H-band) to produce a spectral resolution of 4000 and 1.19-1.37μm (J-band) to produce a spectral resolution of 8000. The center wavelengths for each grating are 1.629μm and 1.27μm, and the groove densities are 177l/mm and 440l/mm for H-band R=4000 and J-band R=8000, respectively. We directly measure the efficiencies in the lab and find that the peak efficiencies of these two types of gratings are quite good with a peak efficiency of ~88% at the Bragg angle in both TM and TE modes at H-band, and 90.23% in TM mode, 79.91% in TE mode at J-band for the best vendor. We determine the drop in efficiency off the Bragg angle, with a 20-23% decrease in efficiency at H-band when 2.5° deviation from the Bragg angle, and 25%-28% decrease at J-band when 5° deviation from the Bragg angle.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".