K-DRIFT Preparation: Experimental Verification of an Observation Strategy for Accurate Dark-Sky Flats

Abstract

Despite its scientific importance, the low-surface-brightness universe has yet to be fully explored due to various systematic uncertainties that affect the achievable surface-brightness limit. Reducing these uncertainties requires very accurate data processing. The dark-sky flat is a widely used calibration frame for accurate flat-field correction, generated by combining the sky background from science images. However, the night sky will likely contain complex local fluctuations, thus may still lead to photometric errors in data calibrated with dark-sky flats. To address this concern, we conduct mock observations with semi-realistic sky simulation data and evaluate observation strategies to mitigate the impact of the fluctuating sky background. Our experiments consider two representative sky conditions (clear and dirty) and perform intensive comparative analysis on two observation methods (offset and rolling). Our findings suggest that the rolling dithering method, which incorporates the operation of camera rotation into conventional dithering, can provide more accurate dark-sky flats. Finally, we discuss the broader implications of this method through additional experiments examining several factors that may affect the imaging quality of observational data.