Square Kilometre Array: Mock-observations via generative deep learning
Description
In this project we use generative deep learning methods (GANs and VAEs) to produce realistic astronomical mock-observations of numerically simulated astrophysical objects, as they will be obseved by the Square Kilometre Array Telescope (SKA). This project contributes to the Swiss-wide activities for SKA of the SKACH Consortium.
Key Data
Projectlead
Deputy Projectlead
Project team
Project partners
Ecole polytechnique fédérale de Lausanne EPFL; Universität Zürich; Eidgenössische Technische Hochschule Zürich ETH; Fachhochschule Nordwestschweiz FHNW; Universität Basel; Haute école spécialisée de Suisse occidentale HES-SO
Project status
completed, 09/2021 - 12/2024
Institute/Centre
Institute of Business Information Technology (IWI); Centre for Artificial Intelligence (CAI)
Funding partner
Staatssekretariat für Bildung, Forschung und Innovation SBFI
Project budget
240'000 CHF
Further documents and links
Publications
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Square Kilometre Array Science Data Challenge 3a : foreground removal for an EoR experiment
2025 Bonaldi, A.; Hartley, P.; Braun, R.; Purser, S.; Acharya, A.; Ahn, K.; Resco, M. Aparicio; Bait, O.; Bianco, M.; Chakraborty, A.; Chapman, E.; Chatterjee, S.; Chege, K.; Chen, H.; Chen, X.; Chen, Z.; Conaboy, L.; Cruz, M.; Darriba, L.; De Santis, M.; Denzel, P.; Diao, K.; Feron, J.; Finlay, C.; Gehlot, B.; Ghosh, S.; Giri, S. K.; Grumitt, R.; Hong, S. E.; Ito, T.; Jiang, M.; Jordan, C.; Kim, S.; Kim, M.; Kim, J.; Krishna, S. P.; Kulkarni, A.; López-Caniego, M.; Labadie-García, I.; Lee, H.; Lee, D.; Lee, N.; Line, J.; Liu, Y.; Mao, Y.; Mazumder, A.; Mertens, F. G.; Munshi, S.; Nasirudin, A.; Ni, S.; Nistane, V.; Norregaard, C.; Null, D.; Offringa, A.; Oh, M.; Oh, S. -H.; Parkinson, D.; Pritchard, J.; Ruiz-Granda, M.; López, V. Salvador; Shan, H.; Sharma, R.; Trott, C.; Yoshiura, S.; Zhang, L.; Zhang, X.; Zheng, Q.; Zhu, Z.; Zuo, S.; Akahori, T.; Alberto, P.; Allys, E.; An, T.; Anstey, D.; Baek, J.; Basavraj; Brackenhoff, S.; Browne, P.; Ceccotti, E.; Chen, H.; Chen, T.; Choudhuri, S.; Choudhury, M.; Coles, J.; Cook, J.; Cornu, D.; Cunnington, S.; Das, S.; Acedo, E. De Lera; Delou is, J. -M.; Deng, F.; Ding, J.; Elahi, K. M. A.; Fernandez, P.; Fernández, C.; Alcázar, A. Fernández; Galluzzi, V.; Gao, L. -Y.; Garain, U.; Garrido, J.; Gendron-Marsolais, M. -L.; Gessey-Jones, T.; Ghorbel, H.; Gong, Y.; Guo, S.; Hasegawa, K.; Hayashi, T.; Herranz, D.; Holanda, V.; Holloway, A. J.; Hothi, I.; Höfer, C.; Jelić, V.; Jiang, Y.; Jiang, X.; Kang, H.; Kim, J. -Y.; Koopmans, L. V.; Lacroix, R.; Lee, E.; Leeney, S.; Levrier, F.; Li, Y.; Liu, Y.; Ma, Q.; Meriot, R.; Mesinger, A.; Mevius, M.; Minoda, T.; Miville-Deschenes, M. -A.; Moldon, J.; Mondal, R.; Murmu, C.; Murray, S.; SR, Nirmala; Niu, Q .; Nunhokee, C.; O'Hara, O.; Pal, S. K.; Pal, S.; Park, J.; Parra, M.; tra, N. N. Pa; Pindor, B.; Remazeilles, M.; Rey, P.; Rubino-Martin, J. A.; Saha, S.; Selvaraj, A.; Semelin, B.; Shah, R.; Shao, Y.; Shaw, A. K.; Shi, F.; Shimabukuro, H.; Singh, G.; Sohn, B. W.; Stagni, M.; Starck, J. -L.; Sui, C.; Swinbank, J. D.; Sánchez, J.; Sánchez-Expósito, S.; Takahashi, K.; Takeuchi, T.; Tripathi, A.; Verdes-Montenegro, L.; Vielva, P.; Vitello, F. R.; Wang, G. -J.; Wang, Q.; Wang, X.; Wang, Y.; Wang, Y. -X.; Wiegert, T.; Wild, A.; Williams, W. L.; Wolz, L.; Wu, X.; Wu, P.; Xia, J. -Q.; Xu, Y.; Yan, R.; Yan, Y. -P.
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Deep learning approach for identification of HII regions during reionization in 21-cm observations : III. image recovery
2024 Bianco, Michele; Giri, Sambit. K.; Sharma, Rohit; Chen, Tianyue; Krishna, Shreyam Parth; Finlay, Chris; Nistane, Viraj; Denzel, Philipp; De Santis, Massimo; Ghorbel, Hatem
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Map-to-map translation for SKA mock observations and cosmological simulations
2023 Denzel, Philipp; Schilling, Frank-Peter; Gavagnin, Elena
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Deep learning the SKA : the Square Kilometer Array project
2023 Denzel, Philipp Benedikt; Schilling, Frank-Peter; Gavagnin, Elena
