Abstract

Abstract The near-infrared is populated by numerous emission lines radiated from the Earth’s atmosphere, and these emission lines are often several orders of magnitude brighter in intensity than the typical astrophysical science target. The subtraction of these emission lines, sky subtraction, can create large systematic errors in ground-based astronomical spectra effectively limiting the number of usable resolution elements. A more effective sky subtraction, and the reduction of the systematic errors due to the sky subtraction process, is a major hurdle which ground-based astronomy must overcome to increase the amount of usable spectrum, and to be able to observe fainter scientific targets. Large high-quality data sets such as the Sloan Digital Sky Survey (SDSS) in themselves present opportunities for a reduction of the systematic sky subtraction errors through self-calibration. The sky residual correction method of Wild & Hewett is one such self-calibration technique which uses principal component analysis to reduce the systematic sky residual errors present in SDSS spectra. We apply sky residual corrections to the SDSS, Baryon Oscillation Spectroscopic Survey, and Apache Point Observatory Galactic Evolution Experiment data sets to optimize the number of subtraction components, and to quantify the reduction of the systematic errors in the science spectra. Finally as a proof of concept we use the sky-residual-corrected SDSS luminous red galaxy spectra to search for gravitationally lensed emission line Galaxies.

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