The Mini-SiTian Array: the mini-SiTian Realtime Image Processing pipeline (STRIP)

Abstract

This paper provides a comprehensive introduction to the Mini-SiTian Real-Time Image Processing pipeline (STRIP) and evaluates its operational performance. The STRIP pipeline is specifically designed for real-time alert triggering and light curve generation for transient sources. By applying the STRIP pipeline to both simulated and real observational data of the Mini-SiTian survey, it successfully identified various types of variable sources, including stellar flares, supernovae, variable stars, and asteroids, while meeting requirements of reduction speed within 5 minutes. For the real observational dataset, the pipeline detected 1 flare event, 127 variable stars, and 14 asteroids from three monitored sky regions. Additionally, two datasets were generated: one, a real-bogus training dataset comprising 218,818 training samples, and the other, a variable star light curve dataset with 421 instances. These datasets will be used to train machine learning algorithms, which are planned for future integration into STRIP.