Validation and Improvement of the Pan-STARRS Photometric Calibration with the Stellar Color Regression Method

As one of the best ground-based photometric dataset, Pan-STARRS1 (PS1) has been widely used as reference to calibrate other surveys. In this work, we present an independent validation and re-calibration PS1 photometry using spectroscopic data from LAMOST DR7 corrected Gaia EDR3 with Stellar Color Regression (SCR) method. Using per band typically a total 1.5 million LAMOST-PS1-Gaia stars standards, show that calibration precisions in $grizy$ filters are around $4\sim 5$ mmag when averaged over $20'$ regions. However, significant large- small-scale spatial variation magnitude offset, up 1 cent, probably caused by errors PS1, found for all filters. The different un-correlated, slightly larger $g$ $y$ We also detect moderate magnitude-dependent (0.005, 0.005, 0.004, 0.003 mag 14 -- 17 range filters, respectively) comparing catalogs. likely systematic uncertainties PSF magnitudes. provide two-dimensional maps correct such offsets footprint at resolutions $160'$. results demonstrate power SCR method improving precision wide-field surveys combined spectroscopy photometry.