Mechanical and optical studies for an extremely large telescope mid-infrared instrument
Bibliographic record
Abstract
Extremely Large Telescopes are considered worldwide as one of the highest priorities in ground-based astronomy, since they have the potential to vastly advance astrophysical knowledge. ESO is building its own Extremely Large optical and infrared Telescope, the ELT. This new telescope will have a 39m main mirror and will be the largest optical telescope in the world, able to work at the diffraction limit. METIS, one of the first light instruments of the ELT, has powerful imaging and spectrographic capabilities on the thermal wavelengths. It will allow the investigation of key properties of a wide range of celestial objects. METIS is an extremely complex instrument, weighing almost 11t, and requiring high positioning and steering precisions. Here I present the ELT’s METIS’ Warm Support Structure. It consists of a seven leg elevation platform, an hexapod capable of providing METIS with sub-millimetre and arcsecond positioning and steering resolutions, and an access platform where personnel can perform in-situ maintenance activities. The structure weighs less than 5 t and is capable of surviving earthquake conditions with accelerations up to 5g. The current design is supported by FEM simulations in ANSYS®, and was approved for Phase C. I also study the impact of the Talbot effect on the optics of METIS. This near-field effect reimages high frequencies of the phase into the amplitude, having the potential to harm the High contrast imaging (HCI) modes of the instrument. I analyse the phase errors resulting from the surface form errors of optical elements and conclude that they have an impact of less than 3% on the amplitude considering the current specifications. Finally, I develop a way of replicating the behaviour of a vortex coronagraph with raytracing software. I use this to assess the straylight caused by this kind of coronagraphs.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".