GaBoDS: The Garching‐Bonn Deep Survey

TLDR

The Garching Bonn Deep Survey (GaBoDS) provides about 20 square degrees of high‑quality WFI@MPG/ESO 2.2 m data, motivating the development of a homogeneous imaging pipeline. The paper presents and evaluates an image‑processing system for reducing optical data from multi‑chip cameras, detailing its algorithms and accuracy, and discusses observing strategies that affect data quality. The pipeline, optimized for weak gravitational lensing, removes instrumental signatures, aligns astrometry, calibrates photometry, and produces deep co‑added mosaics, and its modular design allows adaptation to other scientific applications. The system has been successfully ported to numerous optical instruments and its outputs have been employed in diverse scientific studies. © 2005 WILEY‑VCH Verlag GmbH & Co.

Abstract

Abstract We present our image processing system for the reduction of optical imaging data from multi‐chip cameras. In the framework of the Garching Bonn Deep Survey (GaBoDS; Schirmer et al. 2003) consisting of about 20 square degrees of high‐quality data from WFI@MPG/ESO 2.2m, our group developed an imaging pipeline for the homogeneous and efficient processing of this large data set. Having weak gravitational lensing as the main science driver, our algorithms are optimised to produce deep co‐added mosaics from individual exposures obtained from empty field observations. However, the modular design of our pipeline allows an easy adaption to different scientific applications. Our system has already been ported to a large variety of optical instruments and its products have been used in various scientific contexts. In this paper we give a thorough description of the algorithms used and a careful evaluation of the accuracies reached. This concerns the removal of the instrumental signature, the astrometric alignment, photometric calibration and the characterisation of final co‐added mosaics. In addition we give a more general overview on the image reduction process and comment on observing strategies where they have significant influence on the data quality. (© 2005 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)