دورية أكاديمية
SKA Science Data Challenge 2: analysis and results
| العنوان: | SKA Science Data Challenge 2: analysis and results |
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| المؤلفون: | Hartley, P, Bonaldi, A, Braun, R, 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, H, Hardcastle, M.J, Heneka, C, Herranz, D, Hess, K.M, Jagannath, M, Jaiswal, S, Jurek, R.J, Korber, D, Kitaeff, S, Kleiner, D, Lao, B, Lu, X, Mazumder, A, Moldón, J, Mondal, R, Ni, S, Önnheim, M, Parra, M, Patra, N, Peel, A, Salomé, P, Sánchez-Expósito, S, Sargent, M, Semelin, B, Serra, P, Shaw, A.K, Shen, A.X, Sjöberg, A, Smith, L, Soroka, A, Stolyarov, V, Tolley, E, Toribio, M.C, van der Hulst, J.M, Sadr, A. Vafaei, Verdes-Montenegro, L, Westmeier, T, Yu, K, Yu, L, Zhang, L, Zhang, X, Zhang, Y, Alberdi, A, Ashdown, M, Bom, C.R, Brüggen, M, Cannon, J, Chen, R, Combes, Francoise, Conway, J, Courbin, F, Ding, J, Fourestey, G, Freundlich, J, Gao, L, Gheller, C, Guo, Q, Gustavsson, E, Jirstrand, M, Jones, M.G, Józsa, G, Kamphuis, P, Kneib, J.-P, Lindqvist, M, Liu, B, Liu, Y, Mao, Y, Marchal, A, Márquez, I, Meshcheryakov, A, Olberg, M, Oozeer, N, Pandey-Pommier, M, Pei, W, Peng, B, Sabater, J, Sorgho, A, Starck, J.L, Tasse, C, Wang, A, Wang, Y, Xi, H, Yang, X, Zhang, H, Zhang, J, Zhao, M, Zuo, S |
| المساهمون: | Observatoire de Paris - Site de Paris (OP), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de Paris, Université Paris Sciences et Lettres (PSL)-Université Paris Sciences et Lettres (PSL)-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'Etude du Rayonnement et de la Matière en Astrophysique et Atmosphères = Laboratory for Studies of Radiation and Matter in Astrophysics and Atmospheres (LERMA), École normale supérieure - Paris (ENS-PSL), Université Paris Sciences et Lettres (PSL)-Université Paris Sciences et Lettres (PSL)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de Paris, Université Paris Sciences et Lettres (PSL)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-CY Cergy Paris Université (CY), Collège de France - Chaire Galaxies et cosmologie, Collège de France (CdF (institution)), Observatoire astronomique de Strasbourg (ObAS), Université de Strasbourg (UNISTRA)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), Laboratoire Univers et Particules de Montpellier (LUPM), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM), Galaxies, Etoiles, Physique, Instrumentation (GEPI), Université Paris Sciences et Lettres (PSL)-Université Paris Sciences et Lettres (PSL)-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS) |
| المصدر: | ISSN: 0035-8711. |
| بيانات النشر: | HAL CCSD Oxford University Press (OUP): Policy P - Oxford Open Option A |
| سنة النشر: | 2023 |
| المجموعة: | HAL-IN2P3 (Institut national de physique nucléaire et de physique des particules) |
| مصطلحات موضوعية: | methods: data analysis, techniques: imaging spectroscopy, surveys, software: simulations, galaxies: statistics, radio lines: galaxies, [PHYS.PHYS.PHYS-INS-DET]Physics [physics]/Physics [physics]/Instrumentation and Detectors [physics.ins-det], [PHYS.ASTR]Physics [physics]/Astrophysics [astro-ph] |
| الوصف: | International audience ; 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 familiarise 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 characterise 233245 neutral hydrogen (Hi) sources in a simulated data product representing a 2000~h SKA MID spectral line observation from redshifts 0.25 to 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 percent 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 datasets. |
| نوع الوثيقة: | article in journal/newspaper |
| اللغة: | English |
| العلاقة: | info:eu-repo/semantics/altIdentifier/arxiv/2303.07943; hal-04049530; https://hal.science/hal-04049530Test; https://hal.science/hal-04049530/documentTest; https://hal.science/hal-04049530/file/stad1375.pdfTest; ARXIV: 2303.07943; INSPIRE: 2642230 |
| DOI: | 10.1093/mnras/stad1375 |
| الإتاحة: | https://doi.org/10.1093/mnras/stad1375Test https://hal.science/hal-04049530Test https://hal.science/hal-04049530/documentTest https://hal.science/hal-04049530/file/stad1375.pdfTest |
| حقوق: | info:eu-repo/semantics/OpenAccess |
| رقم الانضمام: | edsbas.1459199D |
| قاعدة البيانات: | BASE |
| DOI: | 10.1093/mnras/stad1375 |
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