The ELT/METIS annular groove phase masks
Bibliographic record
Abstract
High-contrast imaging instruments use coronagraphs for studying stellar environments by suppressing the intense glare of stars. The Annular Groove Phase Mask (AGPM), a vector vortex coronagraph, has proven to be a valuable tool, offering high-contrast performance at small angular separations. The Mid-infrared ELT Imager and Spectrograph (METIS) project will incorporate multiple AGPMs designed to operate at various wavelengths within the LMN spectral bands. Recently, the METIS project has entered the Manufacture, Assembly, Integration, and Test (MAIT) phase. During MAIT, the AGPMs, referred to as Vortex Phase Masks (VPMs) in the framework of METIS, are subject to an iterative process of manufacturing and testing. In the event of performance discrepancies, a component undergoes a minor re-etching process and is subsequently re-tested until it meets the specified requirements. In this work, we evaluate the performance of the METIS VPMs on two distinct coronagraphic test benches. On one hand, the Vortex Optical Demonstrator for Coronagraphic Applications (VODCA) at the University of Liège, featuring a supercontinuum laser source and a FLIR infrared camera, is employed to assess the METIS L- and M-band VPMs. On the other hand, the performance of the METIS N-band VPMs is assessed using a cryogenic testbed at CEA Paris-Saclay. This second testbed is equipped with a series of lasers spanning the 8 to 12.5μm range, ensuring high wavefront quality with a single-mode output. We present the outcome of our extensive manufacturing and testing campaigns and reveal the measured coronagraphic performance results for all METIS VPMs.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".