Innovations within the Altair real-time wavefront reconstructor
Bibliographic record
Abstract
The Gemini North adaptive optics system Altair utilises five cooperative CPU's to perform all the associated real-time tasks. One, the reconstructor (RTC), manages all of the highest speed hard real-time duties. As well as the core, computationally intensive, wavefront reconstruction, this processor implements a number of algorithms providing control system support services. These include: the quad-cell centroid gain estimation, determination and subtraction of invisible modes on the deformable mirror, and the blending of tip, tilt and focus from the on instrument wavefront sensors (which exist on all facility Gemini instruments). These associated support tasks are critically important to ensure that the system always runs with an optimal bandwidth and produce stable images with no artefacts such as a waffle pattern or residual non-common path errors. We present the original algorithm that we have developed for the centroid gain estimate and discuss how it is efficiently and conveniently implemented on the hard real-time processor.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".