A new approach in data reduction: proper handling of random errors and image distortions

Abstract

Data reduction procedures are aimed to minimize the impact of data acquisition imperfections on the measurement of data properties with a scientific meaning for the astronomer. To achieve this purpose, appropriate arithmetic manipulations with data and calibration frames must be performed. Furthermore, a full understanding of all the possible measurements relies on a solid constraint of their associated errors. We discuss different strategies for obtaining realistic determinations of final random errors. In particular, we highlight the benefits of considering the data reduction process as the full characterization of the raw-data frames, but avoiding, as far as possible, the arithmetic manipulation of that data until the final measure and analysis of the image properties. This philosophy will be used in the pipeline data reduction for ELMER and EMIR.