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Record W2909737439 · doi:10.3847/1538-3881/aafee2

Reference Star Differential Imaging of Close-in Companions and Circumstellar Disks with the NIRC2 Vortex Coronagraph at the W. M. Keck Observatory

2019· article· en· W2909737439 on OpenAlexaff
Garreth Ruane, Henry Ngo, Dimitri Mawet, Olivier Absil, Élodie Choquet, Therese Cook, Carlos Gómez González, Elsa Huby, Keith Matthews, Tiffany Meshkat, Maddalena Reggiani, Eugene Serabyn, Nicole L. Wallack, Jerry W. Xuan

Bibliographic record

VenueThe Astronomical Journal · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsHerzberg Institute of Astrophysics
Fundersnot available
KeywordsCoronagraphPhysicsObservatoryOpticsAstrophysicsPoint spread functionAstronomyExoplanetStars

Abstract

fetched live from OpenAlex

Abstract Reference star differential imaging (RDI) is a powerful strategy for high-contrast imaging. Using example observations taken with the vortex coronagraph mode of Keck/NIRC2 in L ′ band, we demonstrate that RDI provides improved sensitivity to point sources at small angular separations compared to angular differential imaging (ADI). Applying RDI to images of the low-mass stellar companions HIP 79124 C (192 mas separation, Δ L ′ = 4.01) and HIP 78233 B (141 mas separation, Δ L ′ = 4.78), the latter a first imaging detection, increases the significance of their detections by up to a factor of 5 with respect to ADI. We compare methods for reference frame selection and find that pre-selection of frames improves detection significance of point sources by up to a factor of 3. In addition, we use observations of the circumstellar disks around MWC 758 and 2MASS J16042165−2130284 to show that RDI allows for accurate mapping of scattered light distributions without self-subtraction artifacts.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.376

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 integrity0.0000.001
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 head0.214
Teacher spread0.202 · 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 designObservational
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

Citations74
Published2019
Admission routes1
Has abstractyes

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