The hardware control system for WEAVE at the William Herschel Telescope
Bibliographic record
Abstract
When an alt-azimuth telescope is tracking at a specific field, it is necessary to use a de-rotator system to compensate the Earth’s rotation of the field of view. In order, to keep the telescope tracking the field of view selected, the instrument will need to a rotation system for compensating it [1]. The new WEAVE [2] two degrees field of view requires a new field de-rotator on the top-end of the telescope. The rotator system has been designed with a direct drive motor which eliminates the need for mechanical transmission elements such as gearboxes, speed reducers, and worm gear drives. This design is a huge advantage for the system performance and lifetime because it eliminates undesirable characteristics such as long-time drift, elasticity, and backlash. The hardware control system has been developed with a Rockwell servo-drive and controller. The rotator has to be controlled by the high-level software which is also responsible for the telescope control. This paper summarizes the model developed for simulating and the software which will be used to accept the rotator system. A performance study is also carried out to test the CIP (Common Industrial Protocol) for communications between the high-level software and the rotator hardware.
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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 | 0.001 | 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) | 0.017 | 0.007 |
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".