Infrared on-detector guide-windows in the era of extremely large telescopes
Bibliographic record
Abstract
Future Extremely Large Telescopes (ELTs) will require advances in Adaptive Optics (AO) systems to fully realize their potential. In addition to separate, dedicated wavefront sensors, it is recognized that wavefront sensing within the science focal plane itself will also be needed for many new instruments. One approach is to use On-Detector Guide Windows (ODGWs), whereby a small sub-window of a science detector is read-out continuously (~10s-100s of Hz) in parallel with slower reads of the full chip (>10 s). Guide star centroids from these windows can be used to correct for vibrations and flexure. Another potential use for these windows is to perform localized resets at high cadence to prevent saturation and to minimize persistence from bright sources. We have prototyped an ODGW system using a 5-μm cutoff Teledyne HAWAII-2RG infrared detector, and the new Astronomical Research Cameras Gen-4 controller. We describe our implementation of an ODGW mode, and science image artifacts that were observed.
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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".