Stellar color regression: a spectroscopy based method for color calibration to a few mmag accuracy and the recalibration of Stripe 82

TL;DR

This paper introduces a spectroscopy-based Stellar Color Regression method that achieves millimagnitude accuracy in color calibration, improves existing calibrations, and reveals subtle systematic errors in SDSS Stripe 82 data.

Contribution

The paper presents a novel spectroscopy-based calibration method that is highly accurate, insensitive to certain systematic errors, and applicable to large imaging surveys.

Findings

Achieved 2-3 times improvement in color calibration accuracy.

Identified magnitude-dependent errors in SDSS z-band data.

Demonstrated the method's consistency with independent galaxy color tests.

Abstract

In this paper, we propose a spectroscopy based Stellar Color Regression (SCR) method to perform accurate color calibration for modern imaging surveys, taking advantage of millions of stellar spectra now available. The method is straightforward, insensitive to systematic errors in the spectroscopically determined stellar atmospheric parameters, applicable to regions that are effectively covered by spectroscopic surveys, and capable of delivering an accuracy of a few millimagnitudes for color calibration. As an illustration, we have applied the method to the SDSS Stripe 82 data (Ivezic et al; I07 hereafter). With a total number of 23,759 spectroscopically targeted stars, we have mapped out the small but strongly correlated color zero point errors present in the photometric catalog of Stripe 82, and improve the color calibration by a factor of 2 -- 3. Our study also reveals some small but significant magnitude dependence errors in z-band for some CCDs. Such errors are likely to be present in all the SDSS photometric data. Our results are compared with those from a completely independent test based on the intrinsic colors of red galaxies presented by I07. The comparison as well as other tests shows that the SCR method has achieved a color calibration internally consistent at a level of about 5 mmag in u-g, 3 mmag in g-r, and 2 mmag in r-i and i-z, respectively. Given the power of the SCR method, we discuss briefly the potential benefits by applying the method to existing, on-going, and up-coming imaging surveys.