MétaCan
Menu
Back to cohort
Record W3112500460 · doi:10.1117/12.2561585

MAORY RTC, a status update

2020· article· en· W3112500460 on OpenAlexaff
Andrea Baruffolo, Italo Foppiani, Guido Agapito, Cédric Plantet, Lorenzo Busoni, Giuseppe Cosentino, Ivano Baronchelli, Carmelo Arcidiacono, Philippe Feautrier, P. Ciliegi, Simone Esposito, Roberto Ragazzoni, Roberto Biasi, Mauro Manetti, Jean‐Pierre Véran, Daniel A. Kerley, Malcom Smith, Jennifer Dunn

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdaptive optics and wavefront sensing
Canadian institutionsHerzberg Institute of Astrophysics
Fundersnot available
KeywordsStrehl ratioAdaptive opticsTelescopeTroubleshootingComputer scienceSkyDeformable mirrorAerospace engineeringSystems engineeringPhysicsOpticsEngineeringMeteorologyOperating system

Abstract

fetched live from OpenAlex

The Multi Conjugate Adaptive Optics RelaY (MAORY) for the ESO Extremely Large Telescope (ELT) is an Adaptive Optics module offering Multi-Conjugate (MCAO) and Single-Conjugate (SCAO) compensation modes. In MCAO, it relies on the use of a constellation of Laser Guide Stars (LGS) and up to three Natural Guide Stars (NGS) for atmospheric turbulence sensing, and multiple deformable mirrors for correction, providing uniform, high Strehl and high sky coverage. MAORY will be installed at the Nasmyth focus of the E-ELT and will feed the MICADO first-light diffraction limited imager and a future second instrument. MAORY is being built by a Consortium composed by INAF in Italy, IPAG in France and the School of Physics at the National University of Ireland Galway. In this paper we report about the status of the design of the MAORY Real Time Computer, which is the component in charge of implementing the main AO control loops, as well as of auxiliary computations to keep the loops operating optimally, and of telemetry data collection for postprocessing, monitoring, testing and troubleshooting. We will start by discussing the evolution of requirements towards MAORY RTC, with an emphasis on the main driving ones. Then, we will describe how the analysis of requirements has led to the derivation of the main design parameters. Finally, we will illustrate possible RTC designs satisfying user requirements, while also complying with standards set forth by ESO.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.858
Threshold uncertainty score0.999

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)0.0010.000

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 head0.017
GPT teacher head0.228
Teacher spread0.210 · 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.

Study designNot applicable
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

Citations1
Published2020
Admission routes1
Has abstractyes

Explore more

Same topicAdaptive optics and wavefront sensingFrench-language works237,207