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Record W2011756660 · doi:10.1364/oe.16.005527

A laser guide star wavefront sensor bench demonstrator for TMT

2008· article· en· W2011756660 on OpenAlex
Olivier Lardière, Rodolphe Conan, Colin Bradley, Kate Jackson, Glen Herriot

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueOptics Express · 2008
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdaptive optics and wavefront sensing
Canadian institutionsHerzberg Institute of AstrophysicsUniversity of British ColumbiaUniversity of Victoria
Fundersnot available
KeywordsLaser guide starAdaptive opticsWavefront sensorWavefrontOpticsTelescopeGuide starPhysicsDeformable mirrorLaser

Abstract

fetched live from OpenAlex

Sodium laser guide stars (LGSs) allow, in theory, Adaptive Optics (AO) systems to reach a full sky coverage, but they have their own limitations. The artificial star is elongated due to the sodium layer thickness, and the temporal and spatial variability of the sodium atom density induces changing errors on wavefront measurements, especially with Extremely Large Telescopes (ELTs) for which the LGS elongation is larger. In the framework of the Thirty-Meter-Telescope project (TMT), the AO-Lab of the University of Victoria (UVic) has built an LGS-simulator test bed in order to assess the performance of new centroiding algorithms for LGS Shack-Hartmann wavefront sensors (SH-WFS). The design of the LGS-bench is presented, as well as laboratory SH-WFS images featuring 29x29 radially elongated spots, simulated for a 30-m pupil. The errors induced by the LGS variations, such as focus and spherical aberrations, are characterized and discussed. This bench is not limited to SH-WFS and can serve as an LGS-simulator test bed to any other LGS-AO projects for which sodium layer fluctuations are an issue.

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.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.304
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 studies0.0000.000
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 head0.022
GPT teacher head0.249
Teacher spread0.227 · 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