The Mini-SiTian Array: the mini-SiTian Realtime Image Processing pipeline (STRIP)
Fuente:
arXiv
Guardado en:
| Autores principales: | , , , , , , , , , , , , |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| _version_ | 1866910901748105216 |
|---|---|
| author | Gu, Hongrui Huang, Yang Sun, Yongkang Xiao, Kai Li, Zhirui Wang, Beichuan Fan, Zhou Zheng, Chuanjie Han, Henggeng Zou, Hu Li, Wenxiong Wu, Hong Liu, Jifeng |
| author_facet | Gu, Hongrui Huang, Yang Sun, Yongkang Xiao, Kai Li, Zhirui Wang, Beichuan Fan, Zhou Zheng, Chuanjie Han, Henggeng Zou, Hu Li, Wenxiong Wu, Hong Liu, Jifeng |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_01609 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | The Mini-SiTian Array: the mini-SiTian Realtime Image Processing pipeline (STRIP) Gu, Hongrui Huang, Yang Sun, Yongkang Xiao, Kai Li, Zhirui Wang, Beichuan Fan, Zhou Zheng, Chuanjie Han, Henggeng Zou, Hu Li, Wenxiong Wu, Hong Liu, Jifeng Instrumentation and Methods for Astrophysics 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. |
| title | The Mini-SiTian Array: the mini-SiTian Realtime Image Processing pipeline (STRIP) |
| topic | Instrumentation and Methods for Astrophysics |
| url | https://arxiv.org/abs/2504.01609 |