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Record W4293524788 · doi:10.1117/12.2630415

Performance of the FAST self coherent camera at the NEW-EARTH lab and a simplified SCC measurement algorithm

2022· article· en· W4293524788 on OpenAlexaff
William Thompson, Christian Marois, Garima Singh, Olivier Lardière, Benjamin L. Gerard, Qiang Fu, Wolfgang Heidrich

Bibliographic record

VenueAdaptive Optics Systems VIII · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdaptive optics and wavefront sensing
Canadian institutionsHerzberg Institute of AstrophysicsUniversity of Victoria
Fundersnot available
KeywordsExoplanetWavefrontSpeckle patternPhysicsCoronagraphAdaptive opticsUpgradeWavefront sensorOpticsPlanetCardinal pointComputer scienceAstronomy

Abstract

fetched live from OpenAlex

In order to detect low mass and mature planets inwards of approximately 5 AU, future direct imaging instruments will require precision wavefront control that operates at relatively high speed. The self-coherent camera (SCC) is a promising technique for measuring the wavefront from science images at the focal plane. We present here results from NRC’s NEW-EARTH lab testing of the Fast Atmospheric SCC Technique, a variant of the SCC and its integration with a Lyot-stop Low-Order Wavefront Sensor. We demonstrate correction of quasi-static speckles in a half dark hole reaching raw 1&sigma; contrasts on the order of 5 &times; 10<sup>−7</sup> at 10 &lambda;/D. We also present a simplified process for extracting measurements and/or DM commands from SCC images using a single matrixvector multiply. This testing and development are important steps on the way to the upcoming Subaru Pathfinder Instrument for Detection of Exoplanets and Removal of Speckles and the Gemini Planet Imager’s CAL2 upgrade.

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 score0.584
Threshold uncertainty score0.730

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.017
GPT teacher head0.205
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

Citations4
Published2022
Admission routes1
Has abstractyes

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