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Record W4387882078 · doi:10.1088/1538-3873/acf61c

The Adaptive Optics System for the Gemini Infrared Multi-Object Spectrograph: Performance Modeling

2023· article· en· W4387882078 on OpenAlexafffund
Uriel Conod, Kate Jackson, Paolo Turri, S. C. Chapman, Olivier Lardière, Masen Lamb, Carlos Correia, Gaetano Sivo, Suresh Sivanandam, Jean‐Pierre Véran

Bibliographic record

VenuePublications of the Astronomical Society of the Pacific · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdaptive optics and wavefront sensing
Canadian institutionsCanadian Institute for Theoretical AstrophysicsDalhousie UniversityUniversity of British ColumbiaHerzberg Institute of Astrophysics
FundersBritish Columbia Knowledge Development FundNational Research Council CanadaUniversity of TorontoNova Scotia Research Innovation Trust
KeywordsSpectrographAdaptive opticsTelescopeIntegral field spectrographZenithPhysicsOpticsField of viewSpectral resolutionPoint spread functionComputer scienceRemote sensingAstronomy

Abstract

fetched live from OpenAlex

Abstract The Gemini Infrared Multi-Object Spectrograph (GIRMOS) will be a near-infrared, multi-object, medium spectral resolution, integral field spectrograph (IFS) for Gemini North Telescope, designed to operate behind the future Gemini North Adaptive Optics system (GNAO). In addition to a first ground layer Adaptive Optics (AO) correction in closed loop carried out by GNAO, each of the four GIRMOS IFSs will independently perform additional multi-object AO correction in open loop, resulting in an improved image quality that is critical to achieve top level science requirements. We present the baseline parameters and simulated performance of GIRMOS obtained by modeling both the GNAO and GIRMOS AO systems. The image quality requirement for GIRMOS is that 57% of the energy of an unresolved point-spread function ensquared within a 0.1 × 0.1 arcsecond at 2.0 μ m. It was established that GIRMOS will be an order 16 × 16 adaptive optics (AO) system after examining the tradeoffs between performance, risks and costs. The ensquared energy requirement will be met in median atmospheric conditions at Maunakea at 30° from zenith.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.306
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.030
GPT teacher head0.241
Teacher spread0.210 · 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 designSimulation or modeling
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

Citations6
Published2023
Admission routes2
Has abstractyes

Explore more

Same venuePublications of the Astronomical Society of the PacificSame topicAdaptive optics and wavefront sensingFrench-language works237,207