ELISa: A new tool for fast modelling of eclipsing binaries

Čokina, M.; Fedurco, M.; Parimucha, Š.

doi:10.1051/0004-6361/202039171

Cited by 12 publications

(4 citation statements)

References 21 publications

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“…As it is difficult to obtain a sufficient number of data set objects by annotating observational data of eclipsing binaries, we used the software ELISa (Fedurco et al, 2020;Čokina et al, 2021) (created by the co-authors of our paper), which is available online 1 .…”

Section: Synthetic Data Generator For Light Curves -Elisamentioning

confidence: 99%

Automatic classification of eclipsing binary stars using deep learning methods

Čokina,

Maslej-Krešňáková,

Butka

et al. 2021

Preprint

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In the last couple of decades, tremendous progress has been achieved in developing robotic telescopes and, as a result, sky surveys (both terrestrial and space) have become the source of a substantial amount of new observational data. These data contain a lot of information about binary stars, hidden in their light curves. With the huge amount of astronomical data gathered, it is not reasonable to expect all the data to be manually processed and analyzed. Therefore, in this paper, we focus on the automatic classification of eclipsing binary stars using deep learning methods. Our classifier provides a tool for the categorization of light curves of binary stars into two classes: detached and over-contact. We used the ELISa software to obtain synthetic data, which we then used for the training of the classifier. For evaluation purposes, we collected 100 light curves of observed binary stars, in order to evaluate a number of classifiers. We evaluated semi-detached eclipsing binary stars as detached.The best-performing classifier combines bidirectional Long Short-Term Memory (LSTM) and a one-dimensional convolutional neural network, which achieved 98% accuracy on the evaluation set. Omitting semi-detached eclipsing binary stars, we could obtain 100% accuracy in classification.

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Section: Synthetic Data Generator For Light Curves -Elisamentioning

confidence: 99%

Automatic classification of eclipsing binary stars using deep learning methods

Čokina,

Maslej-Krešňáková,

Butka

et al. 2021

Preprint

Self Cite

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show abstract

“…Eclipsing binary stars are systems, where the components are mutually obscured for the observer during their motion around a common centre of mass. It is a very important group of variable stars with specific and wellrecognized light-curves, where their shapes depend on the physical properties of the components and geometrical configuration (Hilditch 2001;Prša 2019;Čokina et al 2021).…”

Section: Introductionmentioning

confidence: 99%

Photomeric analysis of eclipsing binaries: VY UMI, RU UMI AND GSC 04364-00648

Kudak¹,

Parimucha²,

Perig³

et al. 2023

Preprint

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We present the photometric analysis of BVR and TESS light curves of three eclipsing binaries (RU UMi and purely studied VY UMi, GSC 04364-00648), together with their period changes considering archival data and new minima times from our and TESS observations. For the first time we detected wave-like variations with low-amplitude in O − C residua of RU UMi, which can be interpreted as a consequence of the light-time effect caused by the 3rd invisible component with period 7370 days. Period increase with rate 2.56(9)×10 −7 d/yr −1 detected in the VY UMi system corresponds to mass transfer from the secondary to the primary component. For GSC 04364-00648 binary system we find some quadratic changes on the O − C diagram, which corresponds to a period decrease with a high rate of −2.26(5) × 10 −5 d/yr −1 . We cannot assumptions about their nature, mainly due to short time of observation and uneven coverage of O − C diagram. We also determined the absolute parameter of their components using the photometric solution and GAIA distances.

show abstract

“…Eclipsing binary stars are systems where the components are mutually obscured for the observer during their motion around a common centre of mass. It is a very important group of variable stars with specific and well-recognized light-curves, whose shapes depend on the physical properties of the components and their geometrical configuration (Hilditch 2001;Prša 2018;Čokina et al 2021).…”

Section: Introductionmentioning

confidence: 99%

Photometric Analysis of Eclipsing Binaries: Vy Umi, Ru Umi and GSC 04364-00648

Kudak

Parimucha

Perig

et al. 2023

RMxAA

View full text Add to dashboard Cite

We present the photometric analysis of BVR and TESS light curves of three eclipsing binaries, together with their period changes considering archival data and new minima times from our and TESS observations. For the first time we detected wave-like variations with low-amplitude in O − C residua of RU UMi, which can be interpreted as a consequence of the light-time effect caused by the 3rd component with period 7370 days. The period increase detected in the VY UMi system corresponds to mass transfer from the secondary to the primary component. For the GSC 04364-00648 binary system we find quadratic changes on the O − C diagram, which correspond to a period decrease. We cannot make assumptions about their nature, mainly due to short time of observation and uneven coverage of O − C diagram. We also determined the absolute parameter of their components using the photometric solution and GAIA distances.

show abstract

ELISa: A new tool for fast modelling of eclipsing binaries

Cited by 12 publications

References 21 publications

Automatic classification of eclipsing binary stars using deep learning methods

Automatic classification of eclipsing binary stars using deep learning methods

Photomeric analysis of eclipsing binaries: VY UMI, RU UMI AND GSC 04364-00648

Photometric Analysis of Eclipsing Binaries: Vy Umi, Ru Umi and GSC 04364-00648

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