Performance update of the combined GNAO+GIRMOS imaging system based on the newly-derived adaptive optics bench
Why this work is in the frame
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Bibliographic record
Abstract
The GNAO facility is an upcoming adaptive optics (AO) system for the Gemini North Telescope. It will deliver both wide and narrow field AO capabilities to its first light instrument GIRMOS. GIRMOS is a multi-object AO (MOAO) instrument that houses four near infrared (NIR) IFU spectrographs and a NIR imager similar to GSAOI at Gemini South. The required sensitivity of the combined system is largely driven by rapid transient follow-up AO-corrected Imaging and the required sensitivity is in part driven by the performance of the AO system. Up until recently, the estimated AO performance feeding the combined GNAO+GIRMOS imaging system was derived from models using limited information on what the actual parameters will eventually be. However, the AO system (currently called the AO Bench, or AOB) recently underwent a competitive bidding process to derive an AO design that met or exceeded our AO requirements. This work summarizes the update to the combined GNAO+GIRMOS imaging system performance based on the newly designed AOB parameters. We discuss the impact due to the changes in performance, specifically with respect to key science cases of the GNAO+GIRMOS imaging system compared to the previous models of the AO system. We also discuss the largest hurdles in terms of parameters that affect performance, such as telescope vibrations and detector quantum efficiency and our plans for mitigation.
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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) | 0.000 | 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 it