Euclid is an ESA mission due to launch in 2021 and aim at mapping the geometry of the dark Universe in the optical/near-infrared domain, investigating the distance-redshift relationship and the evolution of cosmic structure out to redshifts 2. It will use mainly two cosmological probes: the Weak Gravitational Lensing and the Baryon Acoustic Oscillations. Euclid will map the entire extragalactic sky with two instruments, VIS (VISible imager) and NISP (Near-Infrared Spectro-Photometer), providing a huge amount of data: 850 Gbit per day of raw data, 1 Pbit per year of higher processed data. The Science Operations Centre (SOC), located at the European Space Astronomy Centre (ESAC), Villanueva de la Cañada, Spain, is responsible for implementing the survey strategy, its operation and monitoring its performance. It is also responsible to develop and run the Quick Look Analysis (QLA) software, the system in charge of pre-assessing - within 48 hours of data reception - the quality of the data in order to react as soon as possible in case of instrumental problems (mis-configurations, abnormal data, etc.). The system is based on a pass/fail structure given a set of quality flags and raising alerts accordingly.It consists of two main parts:the QLA Processing Framework (QPF), developed in Qtk/C++, provides the processing framework to execute system functionalities, a human-machine interface (HMI) to control all its tasks, access to a local and Euclid archives, interaction with VO-Space and an alerting system via email the QLA Diagnostic Tools (QDT), developed in Python, implements different algorithms and diagnostic functions to check the quality of all the data: VIS, NISP but also house-keeping and Attitude and Orbit Control System (AOCS) product. QLA will analyse all level 1 data: this is uncompressed, reordered raw data with tagged metadata associated. All the checks will be executed automatically due to the large amount of data. QLA shall be capable to: Check the correctness of instrument commanding sequence Assess the science data content against e.g. anomalies, mainly at pixel and instrumental level. However, QLA will not asses data quality from the scientific point of view Implement quick feed-back on survey execution and image quality Version 2.0 was released in the first quarter of 2018: it includes most of the envisaged checks for VIS and AOCS; the code for NISP is under development in collaboration with NASA/IPAC and currently includes the backbone architecture and a couple of diagnostics.
42nd COSPAR Scientific Assembly
- Pub Date:
- July 2018