A Large and Precise All-Sky Photometric Standard Star Dataset Across More Than 200 Passbands

TL;DR

This paper introduces the BEST database, the largest and most precise all-sky standard star dataset with over 200 million stars across 200+ bands, enabling mmag-level calibration for large surveys.

Contribution

The authors constructed the largest, most precise, and most comprehensive all-sky standard star dataset, significantly surpassing previous standards in size, accuracy, and spectral coverage.

Findings

Over 200 million stars cataloged as standards

Calibration of survey datasets to better than 10 mmag precision

Development of a complete sky distribution for the Pan-STARRS system

Abstract

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.