Modeling of the Thirty-Meter-Telescope matched-filter-based LGS wavefront sensing
Bibliographic record
Abstract
The Adaptive Optics Laboratory of the University of Victoria has build a LGS SH-WFS test bench for the Thirty-Meter-Telescope project and its AO system, NFIRAOS. The UVic AOLab has recently shown the ability to track Na profile induced aberrations while correcting for turbulence aberrations. The UVic AOLab has started the second phase of development of its LGS SH-WFS test bench. This next step consists in adding the Truth WFSs into the current bench design and in modeling and implementing the algorithms which blends the data coming from the variousWFSs. This paper shows the various components of the control architecture of NFIRAOS LGS wavefront sensing process. A first simulation shows the stability of the proposed control architecture and demonstrates that the DM is kept away from reproducing the LGS aberrations.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".