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Record W2095378609 · doi:10.1117/12.692234

CGH null test design and fabrication for off-axis aspherical mirror tests

2006· article· en· W2095378609 on OpenAlexaff
Min Wang, Daniel Asselin, P. Topart, Jonny Gauvin, Philippe Berlioz, Bernd Harnisch

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2006
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdaptive optics and wavefront sensing
Canadian institutionsInstitut National d'Optique
Fundersnot available
KeywordsOpticsFabricationWavefrontNull (SQL)Materials scienceHolographyInterferometryComputer-generated holographyPhysicsComputer science

Abstract

fetched live from OpenAlex

A null-lens based on a Computer Generated Hologram (CGH) is designed to test the primary off-axis aspherical mirror of the GAIA space telescope. This custom-designed and fabricated CGH includes five zones (null CGH, alignment CGH, and beam-projection CGH) on the same substrate. The optical test configuration is simple and the designed five-zones CGHs can simultaneously provide the aberrated wavefront correction for null tests, CGH alignment with a commercial interferometer, pre-positioning of the mirror under test in a cryogenic chamber, and isolation of the diffraction orders in the test setup. Positioning of the five zones with respect to each other is extremely critical for the success of this custom-made CGH null testing. For this reason, the fringes of all five zones were manufactured on a single photolithographic mask. With INO's special micro-fabrication processes, including its photolithographic, etching, and coating technologies, this 4.5-inch in diameter CGH was successfully made. The RMS wavefront error is estimated at 7.33 nm for the fabricated null CGH.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.013
GPT teacher head0.227
Teacher spread0.214 · 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 designBench or experimental
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

Citations4
Published2006
Admission routes1
Has abstractyes

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Same venueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIESame topicAdaptive optics and wavefront sensingFrench-language works237,207