Detection of Contact Binary Candidates Observed By TESS Using the Autoencoder Neural Network

• Published in: The Astronomical journal Vol. 167; no. 5; pp. 192 - 205
• Main Authors: Ding, Xu, Song, ZhiMing, Wang, ChuanJun, Ji, KaiFan
• Format: Journal Article
• Language: English
• Published: Madison The American Astronomical Society 01.05.2024; IOP Publishing
• Subjects: Binary stars; Contact binary stars; Eclipsing binary stars; Goodness of fit; Light; Light curve; Neural networks; Variable stars
• ISSN: 0004-6256; 1538-3881
• DOI: 10.3847/1538-3881/ad3048

A contact binary may be the progenitor of a red nova that eventually produces a merger event and have a cut-off period of around 0.2 days. Therefore, a large number of contact binaries is needed to search for the progenitor of red novae and to study the characteristics of short-period contact binaries. In this paper, we employ the Phoebe program to generate a large number of light curves based on the fundamental parameters of contact binaries. Using these light curves as samples, an autoencoder model is trained, which can reconstruct the light curves of contact binaries very well. When the error between the output light curve from the model and the input light curve is large, it may be due to other types of variable stars. The goodness of fit ( R 2 ) between the output light curve from the model and the input light curve is calculated. Based on the thresholds for global goodness of fit ( R 2 ), period, range magnitude, and local goodness of fit ( R 2 ), a total of 1322 target candidates were obtained.