Flattened pyramid wavefront sensor demonstration with a regular pyramid
Bibliographic record
Abstract
Wavefront sensors (WFS) are key components for Adaptive Optics (AO) systems to deliver diffraction-limited images with current ground-based telescopes and future Extremely Large Telescopes. A new WFS concept, the Flattened Pyramid WFS (FPWFS), seems very promising in theory [1], with performances exceeding the “conventional” Pyramid WFS [2, 3], which was already superior to the Shack-Hartmann WFS. This new WFS has never been tested in a lab because the fabrication of a glass pyramid with a very shallow apex angle is technologically challenging. However, there is a simple way to mimic a “Flattened” Pyramid WFS with a regular double-pyramid, originally designed for NFIRAOS [4]. A lens can be arranged in order to overlap the four pupils on the detector. This paper describes the optical setup of the Flattened Pyramid WFS test bed built in the NRC-HAA AO lab, as well as the algorithms used to reconstruct the wavefront, and compares its performance with a conventional Pyramid WFS.
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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 | 0.000 | 0.000 |
| 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) | 0.001 | 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 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".