A Large and Precise All-Sky Photometric Standard Star Dataset Across More Than 200 Passbands
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arXiv
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| Auteurs principaux: | , , , , , , , , , , , , , , |
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| Format: | Preprint |
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2026
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| _version_ | 1866914242862514176 |
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| author | Xiao, Kai Huang, Yang Yuan, Haibo Huang, Bowen Fan, Dongwei Beers, Timothy C. Li, Zhirui Han, Henggeng Zhang, Qiqian Wang, Tao Ma, Mingyang Wang, Yuanchang Xu, Shuai Yang, Lin Liu, Jifeng |
| author_facet | Xiao, Kai Huang, Yang Yuan, Haibo Huang, Bowen Fan, Dongwei Beers, Timothy C. Li, Zhirui Han, Henggeng Zhang, Qiqian Wang, Tao Ma, Mingyang Wang, Yuanchang Xu, Shuai Yang, Lin Liu, Jifeng |
| contents | High-precision photometric standard stars play a key role in enabling accurate photometric calibration and advancing various fields of astronomy. However, due to limitations in calibration methods and the limited availability and underuse of high-precision reference data, existing photometric standard stars may suffer from insufficient numbers, systematic errors exceeding 10 milli-magnitude (mmag), limited photometric band coverage, or incomplete sky coverage, among other issues. To overcome these limitations, we have constructed the largest (over 200 million stars, 1000 times the widely recognized Landolt standards in the same magnitude range), most precise (better than 10 mmag), and most comprehensive (over 200 bands, nearly 40 times the coverage of traditional standards) all-sky standard stars. Based on standards, we have calibrated multiple survey datasets to mmag precision, and subsequently developed a complete sky distribution of stars for the Pan-STARRS system. This database, the BEst STars Database (BEST), is expected to pave the way for achieving mmag-level - or even higher - photometric precision in large-scale surveys, and to play a central role in shaping a high-precision astronomical measurement framework. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_05486 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | A Large and Precise All-Sky Photometric Standard Star Dataset Across More Than 200 Passbands Xiao, Kai Huang, Yang Yuan, Haibo Huang, Bowen Fan, Dongwei Beers, Timothy C. Li, Zhirui Han, Henggeng Zhang, Qiqian Wang, Tao Ma, Mingyang Wang, Yuanchang Xu, Shuai Yang, Lin Liu, Jifeng Instrumentation and Methods for Astrophysics Solar and Stellar Astrophysics High-precision photometric standard stars play a key role in enabling accurate photometric calibration and advancing various fields of astronomy. However, due to limitations in calibration methods and the limited availability and underuse of high-precision reference data, existing photometric standard stars may suffer from insufficient numbers, systematic errors exceeding 10 milli-magnitude (mmag), limited photometric band coverage, or incomplete sky coverage, among other issues. To overcome these limitations, we have constructed the largest (over 200 million stars, 1000 times the widely recognized Landolt standards in the same magnitude range), most precise (better than 10 mmag), and most comprehensive (over 200 bands, nearly 40 times the coverage of traditional standards) all-sky standard stars. Based on standards, we have calibrated multiple survey datasets to mmag precision, and subsequently developed a complete sky distribution of stars for the Pan-STARRS system. This database, the BEst STars Database (BEST), is expected to pave the way for achieving mmag-level - or even higher - photometric precision in large-scale surveys, and to play a central role in shaping a high-precision astronomical measurement framework. |
| title | A Large and Precise All-Sky Photometric Standard Star Dataset Across More Than 200 Passbands |
| topic | Instrumentation and Methods for Astrophysics Solar and Stellar Astrophysics |
| url | https://arxiv.org/abs/2601.05486 |