2023MNRAS.525.4596D

The TESS Survey has released a large number of high-precision light curves of contact binaries. However, using the Phoebe program and Markov chain Monte Carlo (MCMC) algorithm to obtain the posterior distribution of contact binary parameters is a time-consuming process. In order to obtain the contact binary parameters from the TESS survey, we build neural network (NN) models and combine them with the MCMC algorithm to obtain the contact binary parameters and parameter errors quickly. NN model is used in place of the physical model, which can generate a light curve with a precision of less than a millimagnitude. The NN model is capable of generating light curves at a speed that is four orders of magnitude faster than Phoebe running on the same computing platform. In this study, we have determined the parameters of 318 contact binary systems exhibiting relatively symmetric light curves. Subsequently, a statistical analysis was conducted on the derived parameters of these 318 targets. The coefficient of determination (R²) for 318 contact binaries between the light curves generated by Phoebe using these parameters obtained by the NN model and MCMC as inputs and the original light curves is greater than 0.99. Additionally, the distribution and correlation of the parameters for these 318 contact binary systems have been presented.