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Record W4224903927 · doi:10.1088/1674-4527/ac6417

The First Photometric Study of AH Mic Contact Binary System

2022· article· en· W4224903927 on OpenAlexaff
Atila Poro, Mark G. Blackford, Selda Ranjbar Salehian, E. Jahangiri, M. Samiei Dastjerdi, M. Gozarandi, Reza Karimi, Tabassom Madayen, Elnaz Bakhshi, F. Hedayati

Bibliographic record

VenueResearch in Astronomy and Astrophysics · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsUniversity of Toronto
FundersEuropean Space AgencyNational Aeronautics and Space AdministrationNational Science Foundation
KeywordsLight curveContact binaryPhysicsAstrophysicsBinary systemMass ratioBinary numberEphemerisPhotometry (optics)Markov chain Monte CarloParallaxBinary starMonte Carlo methodStarsAstronomyStatisticsMathematics

Abstract

fetched live from OpenAlex

Abstract The first multi-color light curve analysis of the AH Mic binary system is presented. This system has very few past observations from the southern hemisphere. We extracted the minima times from the light curves based on the Markov Chain Monte Carlo (MCMC) approach and obtained a new ephemeris. To provide modern photometric light curve solutions, we used the Physics of Eclipsing Binaries (PHOEBE) software package and the MCMC approach. Light curve solutions yielded a system temperature ratio of 0.950, and we assumed a cold starspot for the hotter star based on the O’Connell effect. This analysis reveals that AH Mic is a W-subtype W UMa contact system with a fill-out factor of 21.3% and a mass ratio of 2.32. The absolute physical parameters of the components are estimated by using the Gaia Early Data Release 3 (EDR3) parallax method to be M h ( M ⊙ ) = 0.702(26), M c ( M ⊙ ) = 1.629(104), R h ( R ⊙ ) = 0.852(21), R c ( R ⊙ ) = 1.240(28), L h ( L ⊙ ) = 0.618(3) and L c ( L ⊙ ) = 1.067(7). The orbital angular momentum of the AH Mic binary system was found to be 51.866(35). The components’ positions of this system are plotted in the Hertzsprung–Russell diagram.

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 score0.094
Threshold uncertainty score0.958

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.033
GPT teacher head0.292
Teacher spread0.259 · 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

Citations3
Published2022
Admission routes1
Has abstractyes

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