SKA Science Data Challenge 2: analysis and results

作者：Philippa Hartley, A Bonaldi, Róbert Braun, J. N. H. S. Aditya, Stéphane Aicardi, L. Alegre, Abhijit Chakraborty, Xuelei Chen, S Choudhuri, A. O. Clarke, J. M. Coles, J S Collinson, David Cornu, Laura Darriba, Michele Delli Veneri, Jan Forbrich, B. Fraga, A. Galan, Julián Garrido, F Gubanov, Helen Håkansson, M. J. Hardcastle, Caroline Heneka, D. Herranz, Kelley M. Hess, M Jagannath, Sumit Jaiswal, R J Jurek, Damien Korber, S Kitaeff, D. Kleiner, Baoqiang Lao, Xiangtao Lu, Aishrila Mazumder, J. Moldón, Rajesh Mondal, Shaoqing Ni, Magnus Önnheim, Manuel Parra-Royón, Nipanjana Patra, Austin Peel, P Salomé, S. Sánchez–Expósito, M. Sargent, B Semelin, P. Serra, Abinash Kumar Shaw, Ao Shen, A Sjöberg, Lani Smith, Anthony Soroka, V. Stolyarov, E. Tolley, M C Toribio, J. M. van der Hulst, Alireza Vafaei Sadr, L. Verdes‐Montenegro, T. Westmeier, Keming Yu, Lei Yu, Lifu Zhang, Xin Zhang, Yingkang Zhang, A Alberdi, M. Ashdown, Clécio R. Bom, M. Brüggen, John M. Cannon, Rurong Chen, F. Combes, James Conway, F. Courbin, Junjun Ding, G Fourestey, Jonathan Freundlich, Li-Yang Gao, C Gheller, Qingyue Guo, E Gustavsson, M Jirstrand, Michael G. Jones, G I G Józsa, P. Kamphuis, J-P Kneib, M. Lindqvist, Bin Liu, Yujun Liu, Yi Mao, Antoine Marchal, I. Márquez, A. V. Meshcheryakov, M Olberg, Nadeem Oozeer, M. Pandey-Pommier, Wenting Pei, Bo Peng, J. Sabater, A. Sorgho, Jean‐Luc Starck, C. Tasse, Ailing Wang, Yougang Wang, Hongwei Xi, Xiaolong Yang, Hui Zhang, Ji-Guo Zhang, Meng Zhao, S Zuo · 发表于：Monthly Notices of the Royal Astronomical Society · 年份：2023 · DOI：10.1093/mnras/stad1375 · 被引用次数：22 · 研究领域：Radio Astronomy Observations and Technology、Astrophysics and Cosmic Phenomena、Computational Physics and Python Applications

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 comp...