Volume 635, March 2020
|Number of page(s)||14|
|Section||Numerical methods and codes|
|Published online||02 March 2020|
Expected performances of the Characterising Exoplanet Satellite (CHEOPS)
III. Data reduction pipeline: architecture and simulated performances
Aix Marseille Univ., CNRS, LAM, Laboratoire d’Astrophysique de Marseille, Marseille, France
2 Division Technique INSU, BP 330, 83507 La Seyne Cedex, France
3 Instituto de Astrofísica e Ciencias do Espaço, Universidade do Porto, CAUP, Rua das Estrelas, 4150-762 Porto, Portugal
4 University of Bern, Physikalisches Institut, Gesellschaftstrasse 6, 3012 Bern, Switzerland
Accepted: 16 September 2019
The CHaracterizing ExOPlanet Satellite (CHEOPS) is set to be launched in December 2019 and will detect and characterize small size exoplanets via ultra high precision photometry during transits. CHEOPS is designed as a follow-up telescope and therefore it will monitor a single target at a time. The scientific users will retrieve science-ready light curves of the target that will be automatically generated by the CHEOPS data reduction pipeline of the Science Operations Centre. This paper describes how the pipeline processes the series of raw images and, in particular, how it handles the specificities of CHEOPS data, such as the rotating field of view, the extended irregular point spread function, and the data temporal gaps in the context of the strict photometric requirements of the mission. The current status and performance of the main processing stages of the pipeline, that is the calibration, correction, and photometry, are presented to allow the users to understand how the science-ready data have been derived. Finally, the general performance of the pipeline is illustrated via the processing of representative scientific cases generated by the mission simulator.
Key words: methods: data analysis / techniques: image processing / techniques: photometric / space vehicles: instruments / methods: observational / planetary systems
© S. Hoyer et al. 2020
Open Access article, published by EDP Sciences, under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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