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Record W4312171495 · doi:10.3847/1538-3881/aca1af

Deep Orbital Search for Additional Planets in the HR 8799 System

2022· article· en· W4312171495 on OpenAlexaff
William Thompson, Christian Marois, Clarissa R. Do Ó, Quinn Konopacky, Jean-Baptiste Ruffio, Jason Wang, Andrew Skemer, Robert J. De Rosa, Bruce Macintosh

Bibliographic record

VenueThe Astronomical Journal · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsHerzberg Institute of AstrophysicsUniversity of Victoria
Fundersnot available
KeywordsPlanetPhysicsOuter planetsPlanetary systemAstronomyAstrophysicsDirect imagingOptics

Abstract

fetched live from OpenAlex

Abstract The HR 8799 system hosts four massive planets orbiting 15 and 80 au. Studies of the system's orbital stability and its outer debris disk open the possibility of additional planets, both interior to and exterior to the known system. Reaching a sufficient sensitivity to search for interior planets is very challenging due to the combination of bright quasi-static speckle noise close to the stellar diffraction core and relatively fast orbital motion. In this work, we present a deep L -band imaging campaign using NIRC2 at Keck comprising 14 observing sequences. We further re-reduce archival data for a total of 16.75 hr, one of the largest uniform data sets of a single direct imaging target. Using a Bayesian modeling technique for detecting planets in images while compensating for plausible orbital motion, we then present deep limits on the existence of additional planets in the HR 8799 system. The final combination shows a tentative candidate, consistent with 4–7 M jup at 4–5 au, detected with an equivalent false-alarm probability better than 3 σ . This analysis technique is widely applicable to archival data and to new observations from upcoming missions that revisit targets at multiple epochs.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.034
Threshold uncertainty score0.998

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 science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.016
GPT teacher head0.229
Teacher spread0.213 · 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 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

Citations19
Published2022
Admission routes1
Has abstractyes

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