Straylight analyses and mitigation strategies for the ELT METIS instrument
Bibliographic record
Abstract
The Mid-infrared ELT Imager and Spectrograph (METIS) is one of the three first-generation instruments on the Extremely Large Telescope (ELT). It will provide 20 instrument configurations for direct and high-contrast imaging, medium and high resolution spectroscopy in the wavelength range of 3 − 13μ. The straylight will affect the image contrast and objects recognition thus influencing the final instrument performance. For this reason it should be taken into account and accurately modeled at the design stage. In the present study we consider straylight from the following sources: surface roughness and defects of the optical surfaces, multiple reflections and diffraction, which will all influence the instrument performance. We estimate their influence using a bottom-up modelling approach at the system level and derive the requirements for some critical parameters. Using empirical and analytical models and performing non-sequential raytracing we demonstrate that the target straylight level can be reached in the current design with reasonable specifications on the optical components.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".