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Record W4392501469 · doi:10.1088/1674-4527/ad30b2

BSN: Photometric Light Curve Analysis of Two Contact Binary Systems LS Del and V997 Cyg

2024· article· en· W4392501469 on OpenAlexaff
Atila Poro, Mehmet Tanrıver, Elham Sarvari, Shayan Zavvarei, Hossein Azarara, Sabrina Baudart, Asma Ababafi, Nazanin Kahali Poor, Fariba Zare, A. Bulut, Ahmet Keskin

Bibliographic record

VenueResearch in Astronomy and Astrophysics · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysical Phenomena and Observations
Canadian institutionsInstitute of Indigenous Peoples' Health
FundersErciyes ÜniversitesiEuropean Space AgencyNational Aeronautics and Space Administration
KeywordsPhysicsLight curveAstrophysicsContact binaryBinary numberBinary starAstronomyStars

Abstract

fetched live from OpenAlex

Abstract The light curve analyses and orbital period variations for two contact binary stars, LS Del and V997 Cyg, are presented in this work which was conducted in the frame of the Binary Systems of South and North project. Ground-based photometric observations were performed at two observatories in France. We used the Transiting Exoplanet Survey Satellite (TESS) data for extracting times of minima and light curve analysis of the target systems. The O − C diagram for both systems displays a parabolic trend. LS Del and V997 Cyg’s orbital periods are increasing at rates of dP / dt = 7.20 × 10 −08 days yr −1 and dP / dt = 2.54 × 10 −08 days yr −1 , respectively. Therefore, it can be concluded that mass is being transferred from the less massive star to the more massive component with a rate of dM / dt = –1.96 × 10 −7 M ⊙ yr −1 for the LS Del system, and dM / dt =–3.83 × 10 −7 M ⊙ yr −1 for V997 Cyg. The parameters of a third possible object in the system are also considered. The PHysics Of Eclipsing BinariEs Python code was used to analyze the light curves. The light curve solutions needed a cold starspot due to the asymmetry in the LS Del system’s light curve maxima. The mass ratio, fill-out factor, and star temperature all indicate that both systems are contact binary types in this investigation. Two methods were applied to estimate the absolute parameters of the systems: one method relied on the parallax of Gaia DR3, and the other used a P − M relationship. The positions of the systems are also depicted on the M − L , M − R , q − L ratio , and <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mi>log</mml:mi> <mml:msub> <mml:mrow> <mml:mi>M</mml:mi> </mml:mrow> <mml:mrow> <mml:mi>tot</mml:mi> </mml:mrow> </mml:msub> <mml:mo>−</mml:mo> <mml:msub> <mml:mrow> <mml:mi mathvariant="italic">logJ</mml:mi> </mml:mrow> <mml:mrow> <mml:mn>0</mml:mn> </mml:mrow> </mml:msub> </mml:math> diagrams. We recommend that further observations and investigations be done on the existence of a fourth body in this system.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.524
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.004
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.044
GPT teacher head0.344
Teacher spread0.300 · 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.

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

Citations4
Published2024
Admission routes1
Has abstractyes

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