Gaia eclipsing binary and multiple systems. Two-Gaussian models applied to OGLE-III eclipsing binary light curves in the Large Magellanic Cloud

@inproceedings{Mowlavi2017GaiaEB,
  title={Gaia eclipsing binary and multiple systems. Two-Gaussian models applied to OGLE-III eclipsing binary light curves in the Large Magellanic Cloud},
  author={N. Mowlavi and I. Lecoeur-Taibi and B. Holl and L. Rimoldini and F. Barblan and A. Pr{\vs}a and A. Kochoska and M. Suveges and L. Eyer and K. Nienartowicz and G. Jevardat and J. Charnas and L. Guy and M. Audard},
  year={2017}
}
The advent of large scale multi-epoch surveys raises the need for automated light curve (LC) processing. This is particularly true for eclipsing binaries (EBs), which form one of the most populated types of variable objects. The Gaia mission, launched at the end of 2013, is expected to detect of the order of few million EBs over a 5-year mission. We present an automated procedure to characterize EBs based on the geometric morphology of their LCs with two aims: first to study an ensemble of EBs… Expand
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Surveying the reach and maturity of machine learning and artificial intelligence in astronomy
  • C. Fluke, C. Jacobs
  • Computer Science, Physics
  • Wiley Interdiscip. Rev. Data Min. Knowl. Discov.
  • 2020
TLDR
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This study investigates the potential of a few machine-learning methods for the automated analysis of eclipsing binaries in the data of large surveys, and investigates the performance of principal component analysis (PCA), linear discriminant analysis (LDA), random forest classification and self-organizing maps. Expand
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