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Record W3103859819 · doi:10.3847/1538-3881/aba1eb

Characterization of the Atmosphere of Super-Earth 55 Cancri e Using High-resolution Ground-based Spectroscopy

2020· article· en· W3103859819 on OpenAlexafffund
Abhinav Jindal, Ernst de Mooij, Ray Jayawardhana, Emily Deibert, Matteo Brogi, Zafar Rustamkulov, Jonathan J. Fortney, Callie E. Hood, Caroline Morley

Bibliographic record

VenueThe Astronomical Journal · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsCanadian Institute for Theoretical AstrophysicsUniversity of Toronto
FundersScience and Technology Facilities CouncilNatural Sciences and Engineering Research Council of Canada
KeywordsPhysicsAtmosphere (unit)PlanetRADIUSWater vaporAstrophysicsSuper-EarthPlanetary systemMeteorology

Abstract

fetched live from OpenAlex

Abstract The nearby super-Earth 55 Cnc e orbits a bright ( V = 5.95 mag) star with a period of ∼18 hr and a mass of ∼8 M ⊕ . Its atmosphere may be water-rich and have a large-scale height; though, attempts to characterize it have yielded ambiguous results. Here we present a sensitive search for water and TiO in its atmosphere at high spectral resolution using the Gemini North telescope and the GRACES spectrograph. We combine observations with previous observations from Subaru and CFHT, improving the constraints on the presence of water vapor. We adopt parametric models with an updated planet radius based on recent measurements, and use a cross-correlation technique to maximize sensitivity. Our results are consistent with atmospheres that are cloudy or contain minimal amounts of water and TiO. Using these parametric models, we rule out a water-rich atmosphere (VMR 0.1%) with a mean molecular weight of 15 g mol −1 at a 3 σ confidence level, improving on the previous limit by a significant margin. For TiO, we rule out a mean molecular weight of 5 g mol −1 with a 3 σ confidence level for a VMR greater than 10 −8 ; for a VMR of greater than 10 −7 , the limit rises to a mean molecular weight of 10 g mol −1 . We can rule out low mean-molecular-weight chemical equilibrium models both including and excluding TiO/VO at very high confidence levels (>10 σ ). Overall, our results are consistent with an atmosphere with a high mean molecular weight and/or clouds, or no atmosphere.

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 score0.017
Threshold uncertainty score0.345

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 head0.015
GPT teacher head0.212
Teacher spread0.197 · 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
Published2020
Admission routes2
Has abstractyes

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