The Euclid Data Processing Challenges

Dubath, P.; Apostolakos, N.; Bonchi, Andrea; Belikov, A. N.; Brescia, M.; Cavuoti, S.; Capak, P.; Coupon, J.; Dabin, C.; Degaudenzi, H.; Desai, S.; Dubath, F.; Fontana, A.; Fotopoulou, S.; Frailis, M.; Galametz, A.; Hoar, J.; Holliman, Mark; Hoyle, B.; Hudelot, P.; Ilbert, O.; Kuemmel, M.; Melchior, M.; Mellier, Y.; Mohr, J. J.; Morisset, N.; Paltani, S.; Pelló, R.; Pilo, S.; Polenta, G.; Poncet, M.; Saglia, R.; Salvato, M.; Sauvage, M.; Schefer, Marc; Serrano, S.; Soldati, Marco; Tramacere, A.; Williams, O. R.; Zacchei, A.

doi:10.1017/s1743921317001521

Cited by 7 publications

(5 citation statements)

References 8 publications

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“…The Agile based software development is progressing along with Information Technology (IT) and Science Challenges (SCs) [7]. The IT challenges exercise the infrastructure elements to ensure that the SGS system can support an SC.…”

Section: Science Ground Segmentmentioning

confidence: 99%

Euclid mission status after mission critical design

Laureijs

Racca

Mellier

et al. 2020

Space Telescopes and Instrumentation 2020: Optical, Infrared, and Millimeter Wave

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Euclid, an ESA mission designed to characterise dark energy and dark matter, passed its Mission Critical Design Review in November 2018. It was demonstrated that the project is ready to start integration and test of the main systems, and that it has the ability to fulfil its top-level mission requirements. In addition, based on the performances at M-CDR, the scientific community has verified that the science requirements can be achieved for the Weak Lensing and Galaxy Clustering dark energy probes, namely a dark energy Figure of Merit of 400 and a 2% accuracy in the growth factor exponent gamma. We present the status of the main elements of the Euclid mission in the light of the demanding high optical performance which is the essential design driver is the to meet the scientific requirements. We include the space segment comprising of a service module and payload module hosting the telescope and its two scientific instruments, and the ground segment, which encompasses the operational and science ground segment. The elements for the scientific success of the mission for a timely release of the data are shortly presented: the processing and calibration of the data, and the design of the sky survey. Euclid is presently on schedule for a launch in September 2022.

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Section: Science Ground Segmentmentioning

confidence: 99%

Euclid mission status after mission critical design

Laureijs

Racca

Mellier

et al. 2020

Space Telescopes and Instrumentation 2020: Optical, Infrared, and Millimeter Wave

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“…The data reduction for actual Euclid images is handled by Euclid OU-VIS (Organizational Unit VIS) with more advanced pipelines than were used in this work. The OU-VIS reduction pipeline includes bias subtraction, flat fielding, CR removal, and CTI corrections, as well as astrometric and photometric calibrations with the Gaia (Gaia Collaboration et al 2016) catalog (Dubath et al 2016).…”

Section: Simulated Euclid Images and Preprocessingmentioning

confidence: 99%

Euclid: Identification of asteroid streaks in simulated images using StreakDet software

Pöntinen

Granvik

Nucita

et al. 2020

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Context. The ESA Euclid space telescope could observe up to 150 000 asteroids as a side product of its primary cosmological mission. Asteroids appear as trailed sources, that is streaks, in the images. Owing to the survey area of 15 000 square degrees and the number of sources, automated methods have to be used to find them. Euclid is equipped with a visible camera, VIS (VISual imager), and a near-infrared camera, NISP (Near-Infrared Spectrometer and Photometer), with three filters. Aims. We aim to develop a pipeline to detect fast-moving objects in Euclid images, with both high completeness and high purity. Methods. We tested the StreakDet software to find asteroids from simulated Euclid images. We optimized the parameters of StreakDet to maximize completeness, and developed a post-processing algorithm to improve the purity of the sample of detected sources by removing false-positive detections. Results. StreakDet finds 96.9% of the synthetic asteroid streaks with apparent magnitudes brighter than 23rd magnitude and streak lengths longer than 15 pixels (10 arcsec h−1), but this comes at the cost of finding a high number of false positives. The number of false positives can be radically reduced with multi-streak analysis, which utilizes all four dithers obtained by Euclid. Conclusions. StreakDet is a good tool for identifying asteroids in Euclid images, but there is still room for improvement, in particular, for finding short (less than 13 pixels, corresponding to 8 arcsec h−1) and/or faint streaks (fainter than the apparent magnitude of 23).

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“…Focusing on the latter problem, an interesting approach, to robustly map the empirical distribution of galaxies in a multidimensional colour space, has been presented in [38] under the form of unsupervised clustering (via Self Organizing Maps) of the spectroscopic objects in the COSMOS survey [39]. In order to prepare the ground for the future Euclid surveys [40], the photometry was reduced to the Euclid photometric system, and all galaxies in the COSMOS master catalogue were clustered (in a completely data driven approach) to find similar objects. In this way, they found that (cf.…”

Section: Biases In the Parameter Spacementioning

confidence: 99%

Data Deluge in Astrophysics: Photometric Redshifts as a Template Use Case

Brescia

Cavuoti

Amaro

et al. 2018

Communications in Computer and Information Science

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Astronomy has entered the big data era and Machine Learning based methods have found widespread use in a large variety of astronomical applications. This is demonstrated by the recent huge increase in the number of publications making use of this new approach. The usage of machine learning methods, however is still far from trivial and many problems still need to be solved. Using the evaluation of photometric redshifts as a case study, we outline the main problems and some ongoing efforts to solve them.

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The Euclid Data Processing Challenges

Cited by 7 publications

References 8 publications

Euclid mission status after mission critical design

Euclid mission status after mission critical design

Euclid: Identification of asteroid streaks in simulated images using StreakDet software

Data Deluge in Astrophysics: Photometric Redshifts as a Template Use Case

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