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Record W7052497119

The single laser adaptive optics system for the METIS

2019· article· en· W7052497119 on OpenAlexaboutno aff

Bibliographic record

VenueResearch Repository (Delft University of Technology) · 2019
Typearticle
Languageen
FieldEngineering
TopicPlasma Diagnostics and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsNucleofectionProteogenomicsFusible alloyDysgeusiaLiquationDiafiltration
DOInot available

Abstract

fetched live from OpenAlex

METIS, the Mid-IR instrument for the ELT will be operating an internal Single Conjugate Adaptive Optics System (SCAO), which will be the work horse AO system and mainly serve the science cases targeting exoplanets and disks around bright stars. In order to extend the sky coverage and brightness range of targets requiring AO correction to fainter stars, a Single Laser Adaptive Optics (SLAO) system is proposed. Although SLAO systems are currently in operation on 8-10 meter class (and smaller) telescopes, extending SLAO systems to the ELT increases the challenges associated with the cone effect and the spot elongation significantly. But since METIS will be operated at L-band, the requirements on required AO correction are fortunately reduced (with respect to other ELT instruments), making a SLAO system an attractive low-cost option for METIS. The METIS SLAO system will operate using an on-axis Laser Guide Star (LGS) and re-use the internal SCAO WFS for field stabilization and low-order correction (truth sensing), further reducing cost and complexity. In this paper we will present the current state of the design of the METIS SLAO system, and will address the challenges, like the impact of the cone effect, spot elongation and design constraints on the system. We will show that this system will likely provide a >60% SR in L-band over >50% of the sky, providing an attractive addition to the METIS SCAO system.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.046
Threshold uncertainty score0.153

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0460.023

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 head0.020
GPT teacher head0.223
Teacher spread0.203 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations0
Published2019
Admission routes1
Has abstractyes

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