The single laser adaptive optics system for the METIS
Bibliographic record
Abstract
METIS, the Mid-IR instrument for the ELT will be operating an internal Single Conjugate Adaptive Optics System (SCAO), which will be the work horse AO system and mainly serve the science cases targeting exoplanets and disks around bright stars. In order to extend the sky coverage and brightness range of targets requiring AO correction to fainter stars, a Single Laser Adaptive Optics (SLAO) system is proposed. Although SLAO systems are currently in operation on 8-10 meter class (and smaller) telescopes, extending SLAO systems to the ELT increases the challenges associated with the cone effect and the spot elongation significantly. But since METIS will be operated at L-band, the requirements on required AO correction are fortunately reduced (with respect to other ELT instruments), making a SLAO system an attractive low-cost option for METIS. The METIS SLAO system will operate using an on-axis Laser Guide Star (LGS) and re-use the internal SCAO WFS for field stabilization and low-order correction (truth sensing), further reducing cost and complexity. In this paper we will present the current state of the design of the METIS SLAO system, and will address the challenges, like the impact of the cone effect, spot elongation and design constraints on the system. We will show that this system will likely provide a >60% SR in L-band over >50% of the sky, providing an attractive addition to the METIS SCAO system.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.046 | 0.023 |
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".