Performance of a complementary metal-oxide-semiconductor sensor for laser guide star wavefront sensing
Bibliographic record
Abstract
The adaptive optics systems of future Extremely Large Telescopes (ELTs) will be assisted with laser guide stars (LGS) which will be created in the sodium layer at a height of ≈90 km above the telescopes. In a Shack–Hartmann wavefront sensor, the long elongation of LGS spots on the sub-pupils far apart from the laser beam axis constraints the design of the wavefront sensor (WFS) which must be able to fully sample the elongated spots without undersampling the non-elongated spots. To fulfill these requirements, a newly released large complementary metal oxide semiconductor sensor with 1100 × 1600 pixels and 9 μm pixel pitch could be employed. Here, we report on the characterization of such a sensor in terms of noise and linearity, and we evaluate its performance for wavefront sensing based on the spot centroid variations. We then illustrate how this new detector can be integrated into a full LGS WFS for both the European Southern Observatory’s ELT and the Thirty Meter Telescope.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".