학술논문
SKA Science Data Challenge 2: analysis and results
Document Type
Author
Hartley, Philippa; Bonaldi, A.; Braun, Robert; Aditya, J. N.H.S.; Aicardi, S.; Alegre, L.; Chakraborty, A.; Chen, X.; Choudhuri, S.; Clarke, A. O.; Coles, J.; Collinson, J. S.; Cornu, D.; Darriba, L.; Delli Veneri, M.; Forbrich, J.; Fraga, B.; Galan, A.; Garrido, J.; Gubanov, F.; Håkansson, Henrik; Hardcastle, M. J.; Heneka, C.; Herranz, D.; Hess, K. M.; Jagannath, M.; Jaiswal, Sumit; Jurek, R. J.; Korber, D.; Kitaeff, S.; Kleiner, D.; Lao, B. Q.; Lu, X.; Mazumder, A.; Moldon, J.; Mondal, R.; Ni, S.; Önnheim, Magnus, 1985; Parra, M.; Patra, N.; Peel, A.; Salomé, P.; Sánchez-Expósito, S.; Sargent, M.; Semelin, B.; Serra, P.; Shaw, A. K.; Shen, A. X.; Sjöberg, Anders; Smith, L.; Soroka, A.; Stolyarov, V.; Tolley, E.; Toribio Perez, Maria Carmen, 1981; van der Hulst, J. M.; Vafaei Sadr, A.; Verdes-Montenegro, L.; Westmeier, T.; Yu, K.; Yu, L.; Zhang, L.; Zhang, X.; Zhang, Y.; Alberdi, Antxon; Ashdown, M.; Bom, C. R.; Brüggen, M.; Cannon, J.; Chen, R.; Combes, Françoise; Conway, John, 1963; Courbin, Frédéric; Ding, J.; Fourestey, G.; Freundlich, J.; Gao, L.; Gheller, C.; Guo, Q.; Gustavsson, Emil, 1987; Jirstrand, Mats, 1968; Jones, M. G.; Józsa, G. I.G.; Kamphuis, Peter; Kneib, J.P.J.P.; Lindqvist, Michael, 1960; Liu, B.; Liu, Y.; Mao, Y.; Marchal, Antoine; Márquez, I.; Meshcheryakov, A.; Olberg, Michael, 1956; Oozeer, N.; Pandey-Pommier, M.; Pei, W.; Peng, B.; Sabater, J.; Sorgho, A.; Starck, J. L.; Tasse, C.
Source
Onsala rymdobservatorium infrastruktur Monthly Notices of the Royal Astronomical Society. 523(2):1967-1993
Subject
Language
English
ISSN
0035-8711
1365-2966
1365-2966
Abstract
The Square Kilometre Array Observatory (SKAO) will explore the radio sky to new depths in order to conduct transformational science. SKAO data products made available to astronomers will be correspondingly large and complex, requiring the application of advanced analysis techniques to extract key science findings. To this end, SKAO is conducting a series of Science Data Challenges, each designed to familiarize the scientific community with SKAO data and to drive the development of new analysis techniques. We present the results from Science Data Challenge 2 (SDC2), which invited participants to find and characterize 233 245 neutral hydrogen (H i) sources in a simulated data product representing a 2000 h SKA-Mid spectral line observation from redshifts 0.25-0.5. Through the generous support of eight international supercomputing facilities, participants were able to undertake the Challenge using dedicated computational resources. Alongside the main challenge, 'reproducibility awards' were made in recognition of those pipelines which demonstrated Open Science best practice. The Challenge saw over 100 participants develop a range of new and existing techniques, with results that highlight the strengths of multidisciplinary and collaborative effort. The winning strategy - which combined predictions from two independent machine learning techniques to yield a 20 per cent improvement in overall performance - underscores one of the main Challenge outcomes: that of method complementarity. It is likely that the combination of methods in a so-called ensemble approach will be key to exploiting very large astronomical data sets.