Phemenological Modelling of a Group of Eclipsing Binary Stars
Ivan L. Andronov, Mariia G. Tkachenko, Lidia L. Chinarova

TL;DR
This paper introduces the NAV phenomenological modeling method for eclipsing binary stars, demonstrating its effectiveness over traditional Fourier series approaches in fitting light curves with fewer parameters.
Contribution
The paper presents a novel NAV algorithm that models eclipsing binary star light curves efficiently using limited parameters, improving over traditional Fourier series methods.
Findings
NAV method requires fewer parameters for accurate modeling.
NAV outperforms Fourier polynomial fits in light curve analysis.
Application to real stars shows improved fit quality.
Abstract
Phenomenological modeling of variable stars allows determination of a set of the parameters, which are needed for classification in the "General Catalogue of Variable Stars" and similar catalogs. We apply a recent method NAV ("New Algol Variable") to eclipsing binary stars of different types. Although all periodic functions may be represented as Fourier series with an infinite number of coefficients, this is impossible for a finite number of the observations. Thus one may use a restricted Fourier series, i.e. a trigonometric polynomial (TP) of order s either for fitting the light curve, or to make a periodogram analysis. However, the number of parameters needed drastically increases with decreasing width of minimum. In the NAV algorithm, the special shape of minimum is used, so the number of parameters is limited to 10 (if the period and initial epoch are fixed) or 12 (not fixed). We…
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Taxonomy
TopicsStellar, planetary, and galactic studies · Astronomy and Astrophysical Research · Astrophysics and Star Formation Studies
