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Record W4285490004 · doi:10.1117/12.2630490

NIRPS fiber-link design, performances and modal noise mitigation performances tested on sky

2022· article· en· W4285490004 on OpenAlexaff
F. Bouchy, Nicolas Blind, José Luis Rasilla, Frédérique Baron, René Doyon, Félix Gracia, G. Lo Curto, Lison Malo, F. Wildi

Bibliographic record

VenueGround-based and Airborne Instrumentation for Astronomy IX · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstronomy and Astrophysical Research
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsTilt (camera)SpectrographOpticsNoise (video)FiberTelescopeModalPhysicsAcousticsMaterials scienceComputer scienceEngineeringArtificial intelligence

Abstract

fetched live from OpenAlex

NIRPS (Near Infra-Red Planet Searcher) is an AO-assisted and fiber-fed high-resolution spectrograph operating in the YJH-bands at the ESO 3.6m telescope in La Silla Observatory, Chile. The optimal geometrical scrambling and the minimization of the modal noise, requested to reach 1 m s−1 precision in radial velocity, is obtained by combining octagonal fibers, a fiber stretcher, a double-scrambler, and a tip-tilt scanning of the 29-µm fiber core. We tested the performance of the fiber-link design on sky and evaluated the modal noise mitigation via near and far-field images taken at the fiber-link output. Without the inclusion of the stretcher and tip-tilt scanning, an extreme injection position at the edge of the fiber should induce an apparent change in radial velocity of ~20 m s−1 with respect to a well-centered injection. Observations with the entire instrument of fast-rotating hot stars show that the stretcher and tip-tilt scanning significantly reduce the modal noise from 1.6% to 0.7%. Optimizing the tip-tilt scanning pattern can further minimize the modal noise, thereby improving the precision in radial velocity.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.963
Threshold uncertainty score1.000

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 studies0.0010.000
Scholarly communication0.0000.001
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 head0.016
GPT teacher head0.258
Teacher spread0.242 · 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.

Study designOther design
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

Citations7
Published2022
Admission routes1
Has abstractyes

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