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Record W4399670254 · doi:10.1117/12.3019440

Adaptive optics telemetry tools for REVOLT: a deep dive into telemetry

2024· article· en· W4399670254 on OpenAlexaff
Maaike van Kooten, Kate Jackson, Jennifer Dunn, Edward L. Chapin, Eric Steinbring, Jean‐Pierre Véran, Olivier Lardière, Dan Kerley, Tarun Kumar, David R. Andersen, Mojtaba Taheri

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdaptive optics and wavefront sensing
Canadian institutionsUniversity of VictoriaHerzberg Institute of Astrophysics
Fundersnot available
KeywordsTelemetryComputer scienceAdaptive opticsRemote sensingTelecommunicationsElectrical engineeringEngineeringGeologyOpticsPhysics

Abstract

fetched live from OpenAlex

REVOLT (Research, Experiment and Validation of Adaptive Optics with a Legacy Telescope) is an adaptive optics (AO) system on the 1.2-m telescope at the Herzberg Astronomy and Astrophysics Research Centre which is intended to demonstrate various AO developments, technologies, and algorithms. This AO system is a platform to test the Herzberg Extensible Adaptive optics Real-time Toolkit (HEART) where new AO control features can be exercised on-sky ahead of deployment on a facility class instrument. In this paper, we present various analysis of the telemetry produced by HEART and its various wavefront-sensing arms that enable both open- and closed-loop operation including a closed-loop Shack-Hartmann wavefront sensor, a closed-loop pyramid wavefront sensor, and an open-loop Shack-Hartmann. Employing REVOLT’s single-conjugate AO configuration, we look at extracting the Fried parameter and other atmospheric parameters from the telemetry and compare the results to an in-situ Ring Image Next Generation Scintillation Sensor (RINGSS) atmospheric seeing monitor and optical turbulence profiler. Finally, we discuss the AO system’s rejection-transfer function and overall system’s performance.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.832
Threshold uncertainty score0.959

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 head0.023
GPT teacher head0.275
Teacher spread0.252 · 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 designTheoretical or conceptual
Domainnot available
GenreMethods

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
Published2024
Admission routes1
Has abstractyes

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