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Record W2498327851 · doi:10.1117/12.2232952

The Infrared Imaging Spectrograph (IRIS) for TMT: the ADC optical design

2016· article· en· W2498327851 on OpenAlexfundno aff

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2016
Typearticle
Languageen
FieldEngineering
TopicAdvanced optical system design
Canadian institutionsnot available
FundersOntario Ministry of Research and InnovationBritish Columbia Knowledge Development FundNatural Sciences and Engineering Research Council of CanadaNational Astronomical Observatory of JapanAssociation of Canadian Universities for Research in AstronomyNational Institutes of Natural SciencesCalifornia Institute of TechnologyGordon and Betty Moore FoundationNational Science Foundation
KeywordsSpectrographIRIS (biosensor)ResidualPupilPassbandInfraredDisplacement (psychology)Adaptive optics

Abstract

fetched live from OpenAlex

We present the current optical design for the IRIS Atmospheric Dispersion Corrector (ADC). The ADC is designed for residual dispersions less than ~1 mas across a given passband at elevations of 25 degrees. Since the last report, the area of the IRIS Imager has increased by a factor of four, and the pupil size has increased from 75 to 90mm, both of which contribute to challenges with the design. Several considerations have led to the current design: residual dispersion, amount of introduced distortion, glass transmission, glass availability, and pupil displacement. In particular, it was found that there are significant distortions that appear (two different components) that can lead to image blur over long exposures. Also, pupil displacement increases the wave front error at the imager focus. We discuss these considerations, discuss the compromises, and present the final design choice and expected performance.

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)0.001
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.010
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.005

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 head0.222
Teacher spread0.211 · 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 designSimulation or modeling
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

Citations10
Published2016
Admission routes1
Has abstractyes

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Same venueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIESame topicAdvanced optical system designFrench-language works237,207