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Record W2727219479 · doi:10.3847/1538-3881/aa7dd8

Detection of Water Vapor in the Thermal Spectrum of the Non-transiting Hot Jupiter Upsilon Andromedae b

2017· article· en· W2727219479 on OpenAlexaff

Bibliographic record

VenueThe Astronomical Journal · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsPlanetWater vaporOrbital inclinationAtmosphere (unit)Hot JupiterOpacityRadial velocityFlux (metallurgy)Binary number

Abstract

fetched live from OpenAlex

Abstract The Upsilon Andromedae system was the first multi-planet system discovered orbiting a main-sequence star. We describe the detection of water vapor in the atmosphere of the innermost non-transiting gas giant ups And b by treating the star–planet system as a spectroscopic binary with high-resolution, ground-based spectroscopy. We resolve the signal of the planet’s motion and break the mass-inclination degeneracy for this non-transiting planet via deep combined flux observations of the star and the planet. In total, seven epochs of Keck NIRSPEC L band observations, three epochs of Keck NIRSPEC short-wavelength K band observations, and three epochs of Keck NIRSPEC long wavelength K band observations of the ups And system were obtained. We perform a multi-epoch cross-correlation of the full data set with an atmospheric model. We measure the radial projection of the Keplerian velocity ( K P = 55 ± 9 km s −1 ), true mass ( M J ), and orbital inclination ( i b 24° ± 4°), and determine that the planet’s opacity structure is dominated by water vapor at the probed wavelengths. Dynamical simulations of the planets in the ups And system with these orbital elements for ups And b show that stable, long-term (100 Myr) orbital configurations exist. These measurements will inform future studies of the stability and evolution of the ups And system, as well as the atmospheric structure and composition of the hot Jupiter.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.319

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.010
GPT teacher head0.214
Teacher spread0.205 · 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

Citations42
Published2017
Admission routes1
Has abstractyes

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