Manufacturing requirements and challenges of the fully integrated monolithic aluminium cryogenic tip-tilt mirror for the METIS instrument
Bibliographic record
Abstract
The chopper is a cryogenic tip-tilt mechanism in the Common Fore Optics (CFO) of METIS, the mid-infrared imager and spectrograph for ESO’s Extremely Large Telescope (ELT). In this paper we delve into the milling process of the mirror of the chopper mechanism, denominated as CM5. This highly accurate mirror is fully integrated into a tip-tilt mechanism and operates to reduce the background noise by shifting between the target object and the background, this happens with a frequency of 5Hz. We will primarily focus on the challenges encountered during the mirror-mechanism fabrication. Notably, the tip/tilt mechanism in the chopper requires precision levels that surpass the accuracy of the 5-axis milling machine that is used. The general accuracy of the used machine on a multi sided part is typically 20 to 30 microns, and is dominated by thermal drift of the machine itself. This significantly increases the manufacturing complexity, therefore a specialized production methodology was devised to ensure the achievement of the micron-level tolerances. In the next paragraphs we will describe how the critical tolerances of down to 5 microns in the mechanism features have been achieved. The use of a so-called Golden Sample provides a known and stable reference during manufacturing, allowing to bypass the drift and static errors of the machine. The usage of CMM measurements proves that the developed production method delivers excellent results overcoming the limitations of the machine accuracy. This monolithic aluminium cryogenic mirror has been produced through in-house CNC programming, milling, and thermal ageing followed by thermal cycling, Single point diamond turning (SPDT) and Wire Electrical Discharging Machining (Wire EDM) by external suppliers. After SPDT of the optical surface, the surface is polished to optical quality and finally a gold coating layer is applied to increase the reflectivity in the desired wavelength.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".