6 papers
The Phenomenological Classification of TESS Eclipsing Binaries
Shi-Qi Liu, Kai Li, Xiao-Dian Chen +1
Eclipsing binaries are crucial astrophysical laboratories for studying stellar parameters and evolutionary processes. In this study, we constructed a machine-learning-based model f…
Photometric Analysis of 30 Contact Binaries in M31
Xiang Gao, Kai Li, Li-Heng Wang +3
M31, as the largest galaxy in the Local Group, is of significant importance for the study of stellar formation and evolution. Based on the data of 5,859 targets observed in M31 by…
A neural network model for quickly solving multiple-band light curves of contact binaries
Kai Li, Li-Heng Wang, Xiang Gao
The advent of large-scale photometric surveys has led to the discovery of over a million contact binary systems. Conventional light curve analysis methods are no longer adequate fo…
BSN-III: The First Multiband Photometric Study on the Eight Total Eclipse Contact Binary Stars
Atila Poro, Kai Li, Raul Michel +6
This study continues our in-depth investigation of total-eclipse W Ursae Majoris-type contact binaries by analyzing eight new systems, complementing our previous work. Multiband $B…
Using machine learning method for variable star classification using the TESS Sectors 1-57 data
Li-Heng Wang, Kai Li, Xiang Gao +2
The Transiting Exoplanet Survey Satellite (TESS) is a wide-field all-sky survey mission designed to detect Earth-sized exoplanets. After over four years photometric surveys, data f…
Physical parameters of 12201 ASAS-SN contact binaries determined by the Neural Network
Kai Li, Li-Heng Wang
In the era of astronomical big data, more than one million contact binaries have been discovered. Traditional approaches of light curve analysis are inadequate for investigating su…