Off-axis point spread function reconstruction from a dual deformable mirror adaptive optics system
Bibliographic record
Abstract
In AO applications, PSF reconstruction is used in calibrating image analysis techniques for astrometry, and in the deconvolution of images to enhance their contrast. The partial correction provided by the AO system is due to the finite sampling of the wavefront sensor, the DM (limited number of freedoms on the DM, i.e., the number of actuators) and the finite bandwidth of the control system. Furthermore, the correction provided by an AO system degrades across the field of view, depending on the angular separation between the guide star and the target object (anisoplanatism). In this paper, an end to end numerical model of an off-axis dual DM AO system has been implemented to accommodate for the anisoplanatic errors that degrade the performance of AO systems at greater angular distances from the guide star. An improved off-axis PSF reconstruction methodology has been developed and numerically evaluated for the dual DM (Woofer/Tweeter) off-axis AO architecture.
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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 | 0.000 | 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 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".