论文标题
使用出色的颜色回归方法验证和改进Pan-Stars光度校准
Validation and Improvement of the Pan-STARRS Photometric Calibration with the Stellar Color Regression Method
论文作者
论文摘要
作为最好的地面光度数据集之一,Pan-Starrs1(PS1)已被广泛用作校准其他调查的参考。在这项工作中,我们使用来自Lamost DR7的光谱数据和来自校正的GAIA EDR3的光度数据对PS1光度法进行了独立的验证和重新校准,并使用了恒星色彩回归(SCR)方法。使用每个频段通常总共有150万个Lamost-PS1-GAIA明星作为标准,我们表明,当平均$ 20'$ $ 20'的$ 20'$ 4 $ 5 $ mmag $ 4 \ sim中的PS1光度校准精度约为$ 4 \ sim。但是,对于所有$ grizy $滤波器,发现了大量偏移量的显着大小和小规模的空间变化,可能是由PS1中的校准误差引起的。不同过滤器中的校准错误是无关的,对于$ g $和$ y $的过滤器而言略大。我们还检测到中等幅度依赖性误差(分别为$ grizy $过滤器的14-17幅度范围内的0.005、0.005、0.005、0.004、0.004、0.003 mag在14-17幅度范围内),通过与Gaia EDR3和其他目录相比,在PS1光度法中。这些错误可能是由PSF幅度中的系统不确定性引起的。我们提供二维图,以在不同的空间分辨率从20'$到$ 160'$的不同空间分辨率的Lamost足迹中纠正这种级别的偏移。结果证明了SCR方法与杆光谱和GAIA光度法结合使用时SCR方法在提高宽场调查的校准精度方面的功能。
As one of the best ground-based photometric dataset, Pan-STARRS1 (PS1) has been widely used as the reference to calibrate other surveys. In this work, we present an independent validation and re-calibration of the PS1 photometry using spectroscopic data from the LAMOST DR7 and photometric data from the corrected Gaia EDR3 with the Stellar Color Regression (SCR) method. Using per band typically a total of 1.5 million LAMOST-PS1-Gaia stars as standards, we show that the PS1 photometric calibration precisions in the $grizy$ filters are around $4\sim 5$ mmag when averaged over $20'$ regions. However, significant large- and small-scale spatial variation of magnitude offset, up to over 1 per cent, probably caused by the calibration errors in the PS1, are found for all the $grizy$ filters. The calibration errors in different filters are un-correlated, and are slightly larger for the $g$ and $y$ filters. We also detect moderate magnitude-dependent errors (0.005, 0.005, 0.005, 0.004, 0.003 mag per magnitude in the 14 -- 17 magnitude range for the $grizy$ filters, respectively) in the PS1 photometry by comparing with the Gaia EDR3 and other catalogs. The errors are likely caused by the systematic uncertainties in the PSF magnitudes. We provide two-dimensional maps to correct for such magnitude offsets in the LAMOST footprint at different spatial resolutions from $20'$ to $160'$. The results demonstrate the power of the SCR method in improving the calibration precision of wide-field surveys when combined with the LAMOST spectroscopy and Gaia photometry.