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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 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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.507
Threshold uncertainty score0.219

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 head0.011
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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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
Published2024
Admission routes2
Has abstractyes

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