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Record W3011594691 · doi:10.3847/1538-3881/ababad

Systematic Phase Curve Study of Known Transiting Systems from Year One of the TESS Mission

2020· article· en· W3011594691 on OpenAlexaff

Bibliographic record

VenueThe Astronomical Journal · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsLight curveBrightnessEphemerisExoplanetEclipseDoppler effectAmplitudeTransit (satellite)Hot Jupiter

Abstract

fetched live from OpenAlex

Abstract We present a systematic phase curve analysis of known transiting systems observed by the Transiting Exoplanet Survey Satellite (TESS) during year one of the primary mission. Using theoretical predictions for the amplitude of the planetary longitudinal atmospheric brightness modulation, stellar ellipsoidal distortion and Doppler boosting, as well as brightness considerations to select targets with likely detectable signals, we applied a uniform data processing and light-curve modeling framework to fit the full-orbit phase curves of 22 transiting systems with planet-mass or brown dwarf companions, including previously published systems. Statistically significant secondary eclipse depths and/or atmospheric brightness modulation amplitudes were measured for HIP 65A, WASP-18, WASP-19, WASP-72, WASP-100, WASP-111, WASP-121, and WASP-122/KELT-14. For WASP-100b, we found marginal evidence that the brightest region of the atmosphere is shifted eastward away from the substellar point. We detected significant ellipsoidal distortion signals in the light curves of HIP 65A, TOI-503, WASP-18, and WASP-30, with HIP 65A, TOI-503 and WASP-18 also exhibiting Doppler boosting. The measured amplitudes of these signals agree with the predictions of theoretical models. Combining the optical secondary eclipse depths with previously published Spitzer 3.6 and 4.5 μ m measurements, we derived dayside brightness temperatures and visible-light geometric albedos for a subset of the analyzed systems. We also calculated updated transit ephemerides combining the transit timings from the TESS light curves with previous literature values.

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 score0.235
Threshold uncertainty score0.271

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 head0.028
GPT teacher head0.248
Teacher spread0.220 · 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

Citations68
Published2020
Admission routes1
Has abstractyes

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