The METIS imager: final opto-mechanics design and manufacturing
Bibliographic record
Abstract
The Imager subsystem of METIS, the Mid-infrared ELT Imager and Spectrograph for the Extremely Large Telescope (ELT) in Chile, provides diffraction-limited imaging capabilities and medium-resolution spectroscopy over the full wavelength range 3 to 13 microns. This Imager has a collimator that feeds two cameras: LM bands and N band. A dichroic splits the bands into two camera optics and to the corresponding detectors. It also incorporates a precise pupil re-imaging optics for each channel, allowing the positioning of high contrast imaging masks for coronographic applications. The collimator and the two cameras are Three-Mirror Anastigmat systems (TMA). All mirrors' surfaces are freeform defined as Zernike surfaces directly polished onto bare aluminium. This optics permits diffraction-limited performance and allows diffraction-limited spectroscopy in the complete wavelength range as well as the required pupil performance. The Imager works at 40 Kelvin to provide detector-limited performance in both bands, while the fore optics of METIS operates at 70 Kelvin. Therefore, a kinematic mounting has been implemented to allow the temperature difference but at the same time keeps the optics aligned to the challenging accuracy required for high contrast imaging. We will present the optics design, the final opto-mechanics and their ongoing manufacturing at Fraunhofer Institute for Applied Optics and Precision Engineering (IOF).
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.011 |
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".