Pipeline for the Antarctic Survey Telescope 3-3 in Yaoan, Yunnan

• Published in: Frontiers in Astronomy and Space Sciences
• Main Authors: Tianrui Sun, Lei Hu, Songbo Zhang, Xiaoyan Li, Kelai Meng, Xuefeng Wu, Lifan Wang, A. J. Castro-Tirado
• Format: Article in Journal/Newspaper
• Language: English
• Published: Frontiers Media S.A. 2022
• Subjects: data analysis—astrometry—instrumentation; image processing; photometric—(stars); transient detection; convolutional neural networks—CNN; Astronomy; QB1-991; Geophysics. Cosmic physics; QC801-809; Antarctic; The Antarctic; Antarc*; Antarctica
• Online Access: https://doi.org/10.3389/fspas.2022.897100; https://doaj.org/article/d186658962d9438e94179cbba76f5f34

AST3-3 is the third robotic facility of the Antarctic Survey Telescopes (AST3) for transient surveys to be deployed at Dome A, Antarctica. Due to the current pandemic, the telescope has been currently deployed at the Yaoan Observation Station in China, starting the commissioning observation and a transient survey. This article presented a fully automatic data processing system for AST3-3 observations. The transient detection pipeline uses state-of-the-art image subtraction techniques optimized for GPU devices. Image reduction and transient photometry are accelerated by concurrent task methods. Our Python-based system allows for transient detection from wide-field data in a real-time and accurate way. A ResNet-based rotational-invariant neural network was employed to classify the transient candidates. As a result, the system enables the auto-generation of transients and their light curves.