Present optical and mechanical design status of NFIRAOS for TMT
Bibliographic record
Abstract
This paper describes the current optical and mechanical designs of NFIRAOS (Narrow Field InfraRed Adaptive Optics System, pronounced nefarious). The main subsystems are the science path optics, the laser guide star (LGS) wavefront sensors (WFSs), the visible natural guide star (NGS) truth WFSs, the IR acquisition camera, and a source and calibration unit. The science optics deliver a diffraction limited f/15 beam with a two arcminute field of view (FOV) to one of three instruments mounted to NFIRAOS. The LGS system relies on an asterism of five laser guide stars oriented in a 35 arcsecond radius pentagon with a sixth guide star at the center. The LGS optics are comprised of six separate optical trains that feed individual WFSs. Each optical train includes three zoom mechanisms catering to sodium layer height variations of 85-235 km. The visible WFS system includes an atmospheric dispersion corrector (ADC); the NGS WFS, used only for NGS mode; the moderate order radial (MOR) truth WFS, used for fast tracking of radially symmetric aberrations while in LGS mode; and the high-order low-bandwidth (HOL) truth WFS, used for sensing high-order LGS WFS offsets. The majority of NFIRAOS is cooled to -30 C to reduce background emissivity. Within the thermal enclosure are standard optical benches which are semi-kinematically mounted to a sub-structure, which is in turn connected via bipod flexures to the external NFIFAOS structure. This protects the optics benches from thermal distortion while maintaining alignment to instruments and TMT.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.004 |
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".