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Record W2009775316 · doi:10.1364/oe.17.018957

Closed-loop control of magnetic fluid deformable mirrors

2009· article· en· W2009775316 on OpenAlex
Azhar Iqbal, Zhizheng Wu, Foued Ben Amara

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 · 2009
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdaptive optics and wavefront sensing
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDeformable mirrorAdaptive opticsWavefrontController (irrigation)Computer scienceOpticsControl theory (sociology)ActuatorControl systemPhysicsArtificial intelligenceControl (management)Engineering

Abstract

fetched live from OpenAlex

This paper presents the first-ever experimental evaluation of a closed-loop adaptive optics system based on a magnetic fluid deformable mirror (MFDM). MFDMs are a new type of wavefront correctors used in adaptive optics systems to compensate for complex optical aberrations. They have been found particularly suitable for ophthalmic imaging systems where they can be used to compensate for the aberrations in the eye that lead to blurry retinal images. However, their practical implementation in clinical devices requires effective methods to control the shape of their deformable surface. This paper presents one such control method which is based on an innovative technique used to linearize the response of the MFDM surface shape. The design of the controller is based on a DC-decoupled model of the multi-input multi-output system and on considering a decentralized PI controller. Experimental results showing the performance of the closed-loop system comprising the developed controller and a 19-channel prototype MFDM are presented.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.541
Threshold uncertainty score0.706

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 head0.012
GPT teacher head0.233
Teacher spread0.221 · 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