An UBVRI calibration method based on Pan-STARRS photometric survey

Abstract

The Landolt’s standard stars catalog is the most widely utilized for CCD astronomy in the UBVRI broad band photometry system. The Panoramic Survey Telescope and Rapid Response System (Pan-STARRS) is one of the usage of the newly grizy photometric system. In this work, the main objective of this paper is to calibrate observations in the U, B, V, R, and I bands by utilizing data in the g, r, and i bands from the literature. First, the machine learning based method XGBoost is employed to train a model for selecting objects with linear relations between the two catalogs. Then, the color transformation method is utilized to convert objects with gri magnitudes of Pan-STARRS1 (PS1) catalog to the UBVRI system, and a set of transformation coefficients is presented. A photometric calibration system is developed and the color based calibration method is implemented in the system. The typical calibration errors of standard field GD279 from instrumental magnitudes to those of standard UBVRI system are derived as 0.173mag, 0.053mag, 0.024mag, 0.019mag, 0.020mag, respectively. Furthermore, the light curve comparison of SN 2017hpa of a large number of observations from different nights suggests that this method can be qualified for various astrometric observations.