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Record W4398775097 · doi:10.1016/j.diamond.2024.111237

Making the diamond vortex phase masks for the METIS instrument

2024· article· en· W4398775097 on OpenAlexaboutno aff
Pontus Forsberg, Petri Karvinen, Samuel Ronayette, Markku Kuittinen, Olivier Absil, Lorenzo König, Christian Delacroix, Gilles Orban de Xivry, Jean-Christophe Barrière, É. Pantin, Mikael Karlsson

Bibliographic record

VenueDiamond and Related Materials · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdaptive optics and wavefront sensing
Canadian institutionsnot available
FundersEuropean Southern ObservatoryEuropean Commission
KeywordsDiamondMetisPhase (matter)VortexMaterials scienceNanotechnologyOpticsPhysicsComputer scienceMeteorologyComposite material

Abstract

fetched live from OpenAlex

Direct observation of exoplanets and proto-planetary disks with the METIS instrument at the Extremely Large Telescope will provide new insights into the processes of planet formation and exoplanet atmospheres. This will be possible thanks to a powerful vector vortex coronagraph that can suppress the starlight to reveal faint signals around it. Here we present the process of making the phase masks at the heart of the coronagraph. These annular groove phase masks consist of deep sub-wavelength gratings in diamond that are etched using inductively coupled oxygen plasma with a strong bias. The METIS instrument requires a wider bandwidth than such components have previously been demonstrated for, leading to a grating design with higher aspect ratio and more vertical walls. To achieve this, the etch mask used for diamond etching was changed from aluminium to silicon and the plasma power was increased. We also improved on our method for reducing the grating depth of finished components to fine-tune them. Together with improved optical testing, this allowed us to produce the best vortex phase masks so far demonstrated for the astronomical N-band.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.541
Threshold uncertainty score0.380

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.026
GPT teacher head0.290
Teacher spread0.264 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2024
Admission routes1
Has abstractyes

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