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LIBRIS Formathandbok  (Information om MARC21)
FältnamnIndikatorerMetadata
00004048naa a2200769 4500
001oai:DiVA.org:su-220838
003SwePub
008230914s2023 | |||||||||||000 ||eng|
024a https://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-2208382 URI
024a https://doi.org/10.3847/1538-4365/accd6a2 DOI
040 a (SwePub)su
041 a engb eng
042 9 SwePub
072 7a ref2 swepub-contenttype
072 7a art2 swepub-publicationtype
100a Hlozek, R.4 aut
2451 0a Results of the Photometric LSST Astronomical Time-series Classification Challenge (PLAsTiCC)
264 1c 2023
338 a print2 rdacarrier
520 a Next-generation surveys like the Legacy Survey of Space and Time (LSST) on the Vera C. Rubin Observatory (Rubin) will generate orders of magnitude more discoveries of transients and variable stars than previous surveys. To prepare for this data deluge, we developed the Photometric LSST Astronomical Time-series Classification Challenge (PLAsTiCC), a competition that aimed to catalyze the development of robust classifiers under LSST-like conditions of a nonrepresentative training set for a large photometric test set of imbalanced classes. Over 1000 teams participated in PLAsTiCC, which was hosted in the Kaggle data science competition platform between 2018 September 28 and 2018 December 17, ultimately identifying three winners in 2019 February. Participants produced classifiers employing a diverse set of machine-learning techniques including hybrid combinations and ensemble averages of a range of approaches, among them boosted decision trees, neural networks, and multilayer perceptrons. The strong performance of the top three classifiers on Type Ia supernovae and kilonovae represent a major improvement over the current state of the art within astronomy. This paper summarizes the most promising methods and evaluates their results in detail, highlighting future directions both for classifier development and simulation needs for a next-generation PLAsTiCC data set.
650 7a NATURVETENSKAPx Fysikx Astronomi, astrofysik och kosmologi0 (SwePub)103052 hsv//swe
650 7a NATURAL SCIENCESx Physical Sciencesx Astronomy, Astrophysics and Cosmology0 (SwePub)103052 hsv//eng
700a Malz, A. I.4 aut
700a Ponder, K. A.4 aut
700a Dai, M.4 aut
700a Narayan, G.4 aut
700a Ishida, E. E. O.4 aut
700a Allam Jr, T.4 aut
700a Bahmanyar, A.4 aut
700a Bi, X.4 aut
700a Biswas, Rahulu Stockholms universitet4 aut
700a Boone, K.4 aut
700a Chen, S.4 aut
700a Du, N.4 aut
700a Erdem, A.4 aut
700a Galbany, L.4 aut
700a Garreta, A.4 aut
700a Jha, S. W.4 aut
700a Jones, D. O.4 aut
700a Kessler, R.4 aut
700a Lin, M.4 aut
700a Liu, J.4 aut
700a Lochner, M.4 aut
700a Mahabal, A. A.4 aut
700a Mandel, K. S.4 aut
700a Margolis, P.4 aut
700a Martinez-Galarza, J. R.4 aut
700a McEwen, J. D.4 aut
700a Muthukrishna, D.4 aut
700a Nakatsuka, Y.4 aut
700a Noumi, T.4 aut
700a Oya, T.4 aut
700a Peiris, H. V.4 aut
700a Peters, C. M.4 aut
700a Puget, J. F.4 aut
700a Setzer, Christian N.,d 1990-u Stockholms universitet,Fysikum,Oskar Klein-centrum för kosmopartikelfysik (OKC)4 aut0 (Swepub:su)chse9649
700a Siddhartha, S.4 aut
700a Stefanov, S.4 aut
700a Xie, T.4 aut
700a Yan, L.4 aut
700a Yeh, K. -h.4 aut
700a Zuo, W.4 aut
710a Stockholms universitetb Fysikum4 org
773t Astrophysical Journal Supplement Seriesg 267:2q 267:2x 0067-0049x 1538-4365
856u https://doi.org/10.3847/1538-4365/accd6ay Fulltext
8564 8u https://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-220838
8564 8u https://doi.org/10.3847/1538-4365/accd6a

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