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Record W4392234764 · doi:10.1093/mnras/stae600

Quenching-driven equatorial depletion and limb asymmetries in hot Jupiter atmospheres: WASP-96b example

2024· article· en· W4392234764 on OpenAlexaff
Maria Zamyatina, Duncan Christie, Éric Hébrard, Nathan J. Mayne, Michael Radica, Jake Taylor, Harry Baskett, Ben Moore, Craig Lils, Denis E. Sergeev, Eva-Maria Ahrer, James Manners, K. Koháry, Adina D. Feinstein

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstro and Planetary Science
Canadian institutionsUniversité de Montréal
FundersUniversity of LeicesterLeverhulme TrustScience and Technology Facilities CouncilMet OfficeUK Research and Innovation
KeywordsPhysicsHot JupiterJupiter (rocket family)AstrobiologyPlanetAstrophysicsAstronomyQuenching (fluorescence)ExoplanetOptics

Abstract

fetched live from OpenAlex

ABSTRACT Transport-induced quenching in hot Jupiter atmospheres is a process that determines the boundary between the part of the atmosphere at chemical equilibrium and the part of the atmosphere at thermochemical (but not photothermochemical) disequilibrium. The location of this boundary, the quench level, depends on the interplay between the dynamical and chemical time-scales in the atmosphere, with quenching occurring when these time-scales are equal. We explore the sensitivity of the quench level position to an increase in the planet’s atmospheric metallicity using aerosol-free 3D general circulation model simulations of a hot Jupiter WASP-96b. We find that the temperature increase at pressures of ∼104–107 Pa that occurs when metallicity is increased could shift the position of the quench level to pressures dominated by the jet, and cause an equatorial depletion of CH4, NH3, and HCN. We discuss how such a depletion affects the planet’s transmission spectrum, and how the analysis of the evening–morning limb asymmetries, especially within ∼3–5 μm, could help distinguish atmospheres of different metallicities that are at chemical equilibrium from those with the upper layers at thermochemical disequilibrium.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.275
Threshold uncertainty score0.731

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 head0.009
GPT teacher head0.202
Teacher spread0.193 · 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

Citations16
Published2024
Admission routes1
Has abstractyes

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