The MOAO system of the IRMOS near-infrared multi-object spectrograph for TMT
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The near-Infrared Multi-Object Spectrograph (IRMOS) for TMT is one of the most powerful astronomical instruments ever envisioned. The combination of the collecting area of TMT, the unique image-sharpening capabilities of the Multi-Object Adaptive Optics (MOAO) system, and the multiplexing advantage of the multi-object integral-field spectra provided by the IRMOS back-end make it capable of addressing some of the leading scientific challenges of the coming decades. Here we present an overview of one potential IRMOS concept and then focus on the MOAO system. In particular we will describe our concept for the laser and natural guide star wavefront sensors, deformable mirrors and the calibration system of MOAO. For each of these design elements, we describe the key trade studies which help define each subsystem. From results of our studies, we assemble a MOAO ensquared energy budget. We find that 50% of the energy is ensquared within the 50 milli-arcsecond spatial pixel of the IRMOS integral field units for a wavelength of 1.65μm. Given the requirements placed on the MOAO system to achieve this performance, large ensquared energies can be achieved with even finer plate scales for wavelengths longer than 1.5μm.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 it