Calibration and test procedures for the NFIRAOS deformable mirror prototypes
Bibliographic record
Abstract
A test setup and detailed plan for safe characterization of prototype deformable mirrors (DMs) for the Thirty Meter Telescope’ s Narrow Field Infrared Adaptive Optics System (NFIRAOS) are presented. The DM size and performance requirements for NFIRAOS are such that prototypes must be built and tested before commissioning the final deliverables in order to mitigate risk. There are two prototypes under test; the actuators have been constructed with the pitch, size and stroke range specified for the full scale DMs, and on the order of 15% of the total number of actuators required by DM0, the ground-conjugated DM. The diameters of the active areas of the prototypes are approximately 35% of the full DM0 diameter. The performance in terms of stroke, linearity, hysteresis and overall controllability must meet requirements at room temperature and at -30 degrees Celsius. NRC HAA has implemented a test setup to characterize the performance of the DM prototypes in this thermal environment. A testing procedure has also been developed to verify the technology up to its limits, while protecting from damage. A primary risk of damage comes from excessive inter-actuator stroke which must be carefully controlled, particularly in the case of non-linear and hysteretic actuators. A detailed calibration procedure and actuator protection scheme has been developed.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".