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Aberration correction with a magnetic liquid active mirror

2008· article· en· W1982620586 on OpenAlexaff
E. F. Borra, Denis Brousseau, Marie-Aimée Cliche, Jocelyn Parent

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society · 2008
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdaptive optics and wavefront sensing
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsPhysicsComa (optics)OpticsTelescopeAstigmatismMagnetic fieldDeformable mirrorSpherical aberrationSecondary mirrorAberrations of the eyePrimary mirrorOptical aberrationAdaptive opticsWavefrontLens (geology)

Abstract

fetched live from OpenAlex

We investigate active magnetic liquid mirrors and their use for the correction of non-axisymmetrical aberrations (like third-order coma and astigmatism). We are mainly concerned with their application to the correction of the severe aberrations of a telescope observing at large angles from the optical axis of its primary mirror. We performed numerical simulations showing that it is possible to generate third- and fifth-order coma and astigmatism by applying electrical currents to simple networks of copper wires. These wire networks generate a magnetic field that can deform the surface of a magnetic liquid (ferrofluid) to a desired optical surface. We present the results from laboratory tests on a prototype mirror demonstrating third-order coma and astigmatism. We show that it is possible to correct non-axisymmetrical aberrations by using an active ferrofluidic mirror. This novel type of deformable mirror could be used to correct the aberrations present in many optical systems, particularly in zenith telescopes, like liquid mirror telescopes, rendering them far more versatile and powerful.

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)0.000
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.269
Threshold uncertainty score0.444

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 head0.009
GPT teacher head0.197
Teacher spread0.188 · 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

Citations9
Published2008
Admission routes1
Has abstractyes

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