Euclid preparation XLVIII. The pre-launch Science Ground Segment simulation framework
Serrano, S.; Hudelot, P.; Seidel, G.; Pollack, J. E.; Jullo, E.; Torradeflot, F.; Benielli, D.; Fahed, R.; Auphan, T.; Carretero, J.; Aussel, H.; Casenove, P.; Castander, F. J.; Davies, J. E.; Fourmanoit, N.; Huot, S.; Kara, A.; Keihänen, E.; Kermiche, S.; Okumura, K.; Zoubian, J.; Ealet, A.; Boucaud, A.; Bretonnière, H.; Casas, R.; Clément, B.; Duncan, C. A.J.; George, K.; Kiiveri, K.; Kurki-Suonio, H.; Kümmel, M.; Laugier, D.; Mainetti, G.; Mohr, J. J.; Montoro, A.; Neissner, C.; Rosset, C.; Schirmer, M.; Tallada-Crespí, P.; Tonello, N.; Venhola, A.; Verderi, A.; Zacchei, A.; Aghanim, N.; Altieri, B.; Amara, A.; Andreon, S.; Auricchio, N.; Azzollini, R.; Baccigalupi, C.; Baldi, M.; Bardelli, S.; Basset, A.; Battaglia, P.; Bernardeau, F.; Bodendorf, C.; Bonino, D.; Branchini, E.; Brescia, M.; Brinchmann, J.; Camera, S.; Candini, G. P.; Capobianco, V.; Carbone, C.; Casas, S.; Castellano, M.; Castignani, G.; Cavuoti, S.; Cimatti, A.; Cledassou, R.; Colodro-Conde, C.; Congedo, G.; Conselice, C. J.; Conversi, L.; Copin, Y.; Corcione, L.; Courbin, F.; Courtois, H. M.; Crocce, M.; Cropper, M.; Da Silva, A.; Degaudenzi, H.; De Lucia, G.; Di Giorgio, A. M.; Dinis, J.; Dubath, F.; Dupac, X.; Dusini, S.; Farina, M.; Farrens, S.; Ferriol, S.; Frailis, M.; Franceschi, E.; Franzetti, P.; Galeotta, S.; Garilli, B.; Gillard, W.; Gillis, B.; Giocoli, C.; Granett, B. R. (2024-10-03)
EDP sciences
03.10.2024
Euclid Collaboration:, Serrano, S., Hudelot, P., Seidel, G., Pollack, J. E., Jullo, E., Torradeflot, F., Benielli, D., Fahed, R., Auphan, T., Carretero, J., Aussel, H., Casenove, P., Castander, F. J., Davies, J. E., Fourmanoit, N., Huot, S., Kara, A., Keihänen, E., … Zinchenko, I. A. (2024). euclid preparation: Xlviii. The pre-launch science ground segment simulation framework. Astronomy & Astrophysics, 690, A103. https://doi.org/10.1051/0004-6361/202349128.
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© The Authors 2024. 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. This article is published in open access under the Subscribe to Open model. Subscribe to A&A to support open access publication.
https://creativecommons.org/licenses/by/4.0/
© The Authors 2024. 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. This article is published in open access under the Subscribe to Open model. Subscribe to A&A to support open access publication.
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:oulu-202410316540
https://urn.fi/URN:NBN:fi:oulu-202410316540
Tiivistelmä
Abstract
Context
The European Space Agency’s Euclid mission is one of a raft of forthcoming large-scale cosmology surveys that will map the large-scale structure in the Universe with unprecedented precision. The mission will collect a vast amount of data that will be processed and analysed by Euclid’s Science Ground Segment (SGS). The development and validation of the SGS pipeline requires state-of-the-art simulations with a high level of complexity and accuracy that include subtle instrumental features not accounted for previously as well as faster algorithms for the large-scale production of the expected Euclid data products.
Aims
In this paper, we present the Euclid SGS simulation framework as it is applied in a large-scale end-to-end simulation exercise named Science Challenge 8. Our simulation pipeline enables the swift production of detailed image simulations for the construction and validation of the Euclid mission during its qualification phase and will serve as a reference throughout operations.
Methods
Our end-to-end simulation framework started with the production of a large cosmological N-body simulation that we used to construct a realistic galaxy mock catalogue. We performed a selection of galaxies down to IE=26 and 28 mag, respectively, for a Euclid Wide Survey spanning 165 deg2 and a 1 deg2 Euclid Deep Survey. We built realistic stellar density catalogues containing Milky Way-like stars down to H < 26 from a combination of a stellar population synthesis model of the Galaxy and real bright stars. Using the latest instrumental models for both the Euclid instruments and spacecraft as well as Euclid-like observing sequences, we emulated with high fidelity Euclid satellite imaging throughout the mission’s lifetime.
Results
We present the SC8 dataset, consisting of overlapping visible and near-infrared Euclid Wide Survey and Euclid Deep Survey imaging and low-resolution spectroscopy along with ground-based data in five optical bands. This extensive dataset enables end-to-end testing of the entire ground segment data reduction and science analysis pipeline as well as the Euclid mission infrastructure, paving the way for future scientific and technical developments and enhancements.
Context
The European Space Agency’s Euclid mission is one of a raft of forthcoming large-scale cosmology surveys that will map the large-scale structure in the Universe with unprecedented precision. The mission will collect a vast amount of data that will be processed and analysed by Euclid’s Science Ground Segment (SGS). The development and validation of the SGS pipeline requires state-of-the-art simulations with a high level of complexity and accuracy that include subtle instrumental features not accounted for previously as well as faster algorithms for the large-scale production of the expected Euclid data products.
Aims
In this paper, we present the Euclid SGS simulation framework as it is applied in a large-scale end-to-end simulation exercise named Science Challenge 8. Our simulation pipeline enables the swift production of detailed image simulations for the construction and validation of the Euclid mission during its qualification phase and will serve as a reference throughout operations.
Methods
Our end-to-end simulation framework started with the production of a large cosmological N-body simulation that we used to construct a realistic galaxy mock catalogue. We performed a selection of galaxies down to IE=26 and 28 mag, respectively, for a Euclid Wide Survey spanning 165 deg2 and a 1 deg2 Euclid Deep Survey. We built realistic stellar density catalogues containing Milky Way-like stars down to H < 26 from a combination of a stellar population synthesis model of the Galaxy and real bright stars. Using the latest instrumental models for both the Euclid instruments and spacecraft as well as Euclid-like observing sequences, we emulated with high fidelity Euclid satellite imaging throughout the mission’s lifetime.
Results
We present the SC8 dataset, consisting of overlapping visible and near-infrared Euclid Wide Survey and Euclid Deep Survey imaging and low-resolution spectroscopy along with ground-based data in five optical bands. This extensive dataset enables end-to-end testing of the entire ground segment data reduction and science analysis pipeline as well as the Euclid mission infrastructure, paving the way for future scientific and technical developments and enhancements.
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