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

• Published in: Frontiers in Astronomy and Space Sciences
• Main Authors: Sun, Tianrui, Hu, Lei, Zhang, Songbo, Li, Xiaoyan, Meng, Kelai, Wu, Xuefeng, Wang, Lifan, Castro-Tirado, Alberto J.
• Other Authors: Ministerio de Ciencia e Innovación (España)
• Format: Article in Journal/Newspaper
• Language: English
• Published: Frontiers Media 2022
• Subjects: Data analysis; Astrometry; Instrumentation; Image processing; Photometric—(stars); Transient detection; Convolutional neural networks—CNN; Antarctic; The Antarctic; Tirado; Antarc*; Antarctica
• Online Access: http://hdl.handle.net/10261/286550; https://doi.org/10.3389/fspas.2022.897100; https://doi.org/10.13039/501100004837

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. 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. © 2022 Sun, Hu, Zhang, Li, Meng, Wu, Wang and Castro-Tirado. This work is partially supported by the National Natural Science Foundation of China (Grant Nos. 11725314 and 12041306), the Major Science and Technology Project of Qinghai Province (2019-ZJ-A10), the ACAMAR Postdoctoral Fellow, the China Postdoctoral Science Foundation (Grant No. 2020M681758) and the Natural Science Foundation of Jiangsu Province (grant No. BK20210998). TS and AC also acknowledge financial support from the State Agency for Research of the Spanish MCIU through the “ Center of Excellence Severo Ochoa” award to the Instituto de Astrofísica de Andalucía (SEV-2017-0709). TS acknowledges the China Scholarship ...