Subpixel pupil tracking on METIS for ELT
Bibliographic record
Abstract
The METIS instrument for ELT will use a pyramid wavefront sensor(WFS)for natural guide star based adaptive optics, instead of the more traditional Shack-Hartmann WFS. The pyramid produces four pupil images, one on each quadrant of the resulting WFS image. One of the dynamic problems that METIS will encounter is a lateral drift on these four exit pupils of the telescope instrument. This drift will occur over time and needs to be corrected for by shifting the Pupil Stabilization Mirror. We aim to create a Pupil Position Control (PPC) algorithm specifically calibrated for the ELT. The lateral shift would need to be measured and corrected for on a subpixel level. The goal is to measure the lateral shift, on both axes, to within 1/10th of a pixel (with regards to the pupil images on the WFS). The observed pupil image in METIS has unique characteristics that can both benefit and hamperattemptsto calculate thecenter. Traditional methods such ascenterof gravity algorithms are too easily skewed by reflectivity differences or missing segments. Our approach is to build a series of sequential matched filters and correlate these to the pupil image to determine the level of lateral shift. The PPC algorithm was evaluated for all stages of handover; open-loop prior to handover, closed-loop with 50 modes during handover andfullclosed-loop after handover.Through a series of simulations and unit testswe show that the PPC algorithm canachieve the desired accuracy, while still offering a level of invariance to rotation, warping, missing segments and luminosity differences in the pupil image.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".