Adaptive optics designs for an infrared multi-object spectrograph on TMT
Bibliographic record
Abstract
The Thirty Meter Telescope (TMT), the next generation giant segmented mirror telescope, will have unprecedented astronomical science capability. Since science productivity is greatly enhanced through the use of adaptive optics, the TMT science team has decided that adaptive optics should be implanted on all the IR instruments. We present the results of a feasibility study for the adaptive optics systems on the infrared multi-object spectrograph, IRMOS and report on the design concepts and architectural options. The IRMOS instrument is intended to produce integral field spectra of up to 20 objects distributed over a 5 arcminute field of regard. The IRMOS adaptive optics design is unique in that it will use multiple laser guidestars to reconstruct the atmospheric volume tomographically, then apply AO correction for each science direction independently. Such a scheme is made technically feasible and cost effective through the use of micro-electromechanical system (MEMS) deformable mirrors.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".