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Record W4399663492 · doi:10.1117/12.3018397

ANDES, the high resolution spectrograph for the ELT: extending to the K-band

2024· article· en· W4399663492 on OpenAlexaffabout
Wolfgang Gäessler, H. Korhonen, Frédérique Baron, W. Brandner, P. Di Marcantonio, René Doyon, Monica Ebert, A. Kaminski, Laura Kreidberg, W. Laun, Michael Lehmitz, A. Marconi, P. Mollière, A. Quirrenbach, Ralf-Rainer Rohloff, W. Seifert, Julian Stuermer, Jonathan Saint-Antoine, Wenli Xu, Alessio Zanutta

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicParticle Accelerators and Free-Electron Lasers
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsSpectrographResolution (logic)Remote sensingHigh resolutionComputer scienceGeologyPhysicsAstronomyArtificial intelligence

Abstract

fetched live from OpenAlex

ANDES is a high resolution spectrograph for the ELT, with the goal of providing simultaneous spectra with R 100000 from 0.35 to 2.4 micrometer. The baseline of the instrument covers 0.4 - 1.8 micron. Here we present the study on the extension into the K-band (1.95 to 2.45 micron) with its scientific motivation and the technical solution. The spectrograph design is constrained by external limits, but a solution is found that enables key science cases in this wavelength range and closes the gap in ELT high resolution spectroscopy between the ANDES baseline and the METIS instrument. The spectrograph design is throughput-optimized and is fed by the diffraction-limited input from the ANDES SCAO system. We summarize the preliminary optical and cryo-mechanical design. But, as the available mass is one of the critical parameters, we also look into an alternative implementation of the spectrograph with carbon fiber.

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)0.002
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: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.002

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 head0.011
GPT teacher head0.234
Teacher spread0.223 · 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 designNot applicable
Domainnot available
GenreMethods

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
Published2024
Admission routes2
Has abstractyes

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