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Record W1971912102 · doi:10.1117/12.892265

TMTracer: a modeling tool for the TMT alignment and phasing system

2011· article· en· W1971912102 on OpenAlexfundno aff
Piotr Piatrou

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2011
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdaptive optics and wavefront sensing
Canadian institutionsnot available
FundersNational Research Council CanadaOntario Ministry of Research and InnovationNatural Sciences and Engineering Research Council of CanadaNational Science CouncilResearch and Innovation FoundationGordon and Betty Moore FoundationNational Science Foundation
KeywordsAdaptive opticsWavefrontActive opticsSoftwareWavefront sensorPhaserComputer scienceDeformable mirrorTelescopeActuatorOpticsPhysicsArtificial intelligence

Abstract

fetched live from OpenAlex

The Alignment and Phasing System (APS) is one of the key parts of the Thirty Meter Telescope (TMT) active optics system, with the responsibility for evaluating and correcting the pre-adaptive optics wavefront delivered by the telescope. APS is a high complexity system comprising a multi-channel wavefront-sensing instrument that produces as many as 250,000 discrete measurements and control software that delivers commands to about 12,000 active optics system actuators. The APS software is designed to guide the instrument development and predict its performance via simulation and also ultimately to serve the physical instrument itself. The software is built around a modeling tool we have developed called TMTracer, which is tailored to the optical alignment of extremely large segmented telescopes. We will present the underlying philosophy of TMTracer, as well as its architecture and sample simulation results that demonstrate its capabilities.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.926
Threshold uncertainty score0.767

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.019
GPT teacher head0.223
Teacher spread0.204 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations5
Published2011
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