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Expected performances of the Characterising Exoplanet Satellite (CHEOPS) II. The CHEOPS simulator

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 نشر من قبل David Futyan
 تاريخ النشر 2020
  مجال البحث فيزياء
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The CHaracterising ExOPlanet Satellite (CHEOPS) is a mission dedicated to the search for exoplanetary transits through high precision photometry of bright stars already known to host planets. The telescope will provide the unique capability of determining accurate radii for planets whose masses have already been measured from ground-based spectroscopic surveys. This will allow a first-order characterisation of the planets internal structure through the determination of the bulk density, providing direct insight into their composition. The CHEOPS simulator has been developed to perform detailed simulations of the data which is to be received from the CHEOPS satellite. It generates accurately simulated images that can be used to explore design options and to test the on-ground data processing, in particular, the pipeline producing the photometric time series. It is, thus, a critical tool for estimating the photometric performance expected in flight and to guide photometric analysis. It can be used to prepare observations, consolidate the noise budget, and asses the performance of CHEOPS in realistic astrophysical fields that are difficult to reproduce in the laboratory. Images generated by CHEOPSim take account of many detailed effects, including variations of the incident signal flux and backgrounds, and detailed modelling of the satellite orbit, pointing jitter and telescope optics, as well as the CCD response, noise and readout. The simulator results presented in this paper have been used in the context of validating the data reduction processing chain, in which image time series generated by CHEOPSim were used to generate light curves for simulated planetary transits across real and simulated targets. Independent analysts were successfully able to detect the planets and measure their radii to an accuracy within the science requirements of the mission.

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392 - Adrien Deline 2019
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