Identifying transient and variable sources in radio images
| العنوان: | Identifying transient and variable sources in radio images |
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| المؤلفون: | P. Zarka, B. Scheers, Y.N. Cendes, Tim D. Staley, John D. Swinbank, Adam Stewart, J.-M. Grießmeier, J. van Leeuwen, Michael Bell, Antonia Rowlinson, Sean Farrell, D. Carbone, Rob Fender, C. J. Law, Gijs Molenaar, Jochen Eislöffel, Ralph A. M. J. Wijers, A. J. van der Horst, J. W. Broderick |
| المساهمون: | Anton Pannekoek Institute for Astronomy, University of Amsterdam [Amsterdam] (UvA), Laboratory for Atmospheric and Space Physics [Boulder] (LASP), University of Colorado [Boulder], Sydney Institute for Astronomy (SIfA), The University of Sydney, University of Washington [Seattle], Department of Physics and Astronomy, Texas Tech University [Lubbock] (TTU), Dunlap Institute for Astronomy and Astrophysics [Toronto], University of Toronto, Oxford Astrophysics, University of Oxford [Oxford], Department of Physics the George Washington University, Department of Physics and Electronics, Rhodes University, Grahamstown, Centrum Wiskunde & Informatica (CWI), Laboratoire de Physique et Chimie de l'Environnement et de l'Espace (LPC2E), Observatoire des Sciences de l'Univers en région Centre (OSUC), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS)-Centre National d’Études Spatiales [Paris] (CNES), University of Technology Sydney (UTS), Thüringer Landessternwarte Tautenburg (TLS), Department of Astronomy [Berkeley], University of California [Berkeley], University of California-University of California, Laboratoire d'études spatiales et d'instrumentation en astrophysique (LESIA (UMR_8109)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université Paris Diderot - Paris 7 (UPD7)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), European Project: 247295,EC:FP7:ERC,ERC-2009-AdG,AARTFAAC(2010), European Project: 267697,EC:FP7:ERC,ERC-2010-AdG_20100224,4PI-SKY(2011), European Project: 617199,EC:FP7:ERC,ERC-2013-CoG,ALERT(2014), Centrum Wiskunde & Informatica, Amsterdam (CWI), The Netherlands, University of Oxford, University of California [Berkeley] (UC Berkeley), University of California (UC)-University of California (UC), Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université d'Orléans (UO)-Observatoire de Paris, PSL Research University (PSL)-PSL Research University (PSL)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université d'Orléans (UO)-Observatoire de Paris, PSL Research University (PSL)-PSL Research University (PSL)-Centre National d’Études Spatiales [Paris] (CNES), PSL Research University (PSL)-PSL Research University (PSL)-Université Paris Diderot - Paris 7 (UPD7)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Unité Scientifique de la Station de Nançay (USN), Université d'Orléans (UO)-Observatoire des Sciences de l'Univers en région Centre (OSUC), PSL Research University (PSL)-PSL Research University (PSL)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de Paris, PSL Research University (PSL)-Centre National de la Recherche Scientifique (CNRS), High Energy Astrophys. & Astropart. Phys (API, FNWI) |
| المصدر: | Astronomy and Computing Astronomy and Computing, Elsevier 2019, 27, pp.111-129. ⟨10.1016/j.ascom.2019.03.003⟩ Astronomy and Computing, 27, 111-129 Astronomy and Computing, 2019, 27, pp.111-129. ⟨10.1016/j.ascom.2019.03.003⟩ Astronomy and Computing, 27, 111-129. Elsevier |
| سنة النشر: | 2019 |
| مصطلحات موضوعية: | Computer science, Data analysis, FOS: Physical sciences, Methods Data analysis Methods Statistical Radio continuum General, ComputerApplications_COMPUTERSINOTHERSYSTEMS, computer.software_genre, 01 natural sciences, 0103 physical sciences, Methods, General, 010303 astronomy & astrophysics, Instrumentation and Methods for Astrophysics (astro-ph.IM), computer.programming_language, [PHYS]Physics [physics], 010308 nuclear & particles physics, Anomaly detection algorithm, Astronomy and Astrophysics, LOFAR, Python (programming language), Statistical, Computer Science Applications, Pipeline transport, Radio continuum, Space and Planetary Science, [SDU]Sciences of the Universe [physics], Snapshot (computer storage), Data mining, Astrophysics - Instrumentation and Methods for Astrophysics, [PHYS.ASTR]Physics [physics]/Astrophysics [astro-ph], computer |
| الوصف: | With the arrival of a number of wide-field snapshot image-plane radio transient surveys, there will be a huge influx of images in the coming years making it impossible to manually analyse the datasets. Automated pipelines to process the information stored in the images are being developed, such as the LOFAR Transients Pipeline, outputting light curves and various transient parameters. These pipelines have a number of tuneable parameters that require training to meet the survey requirements. This paper utilises both observed and simulated datasets to demonstrate different machine learning strategies that can be used to train these parameters. The datasets used are from LOFAR observations and we process the data using the LOFAR Transients Pipeline; however the strategies developed are applicable to any light curve datasets at different frequencies and can be adapted to different automated pipelines. These machine learning strategies are publicly available as Python tools that can be downloaded and adapted to different datasets (https://github.com/AntoniaR/TraP_ML_tools). Comment: Astronomy & Computing Accepted, 25 pages, 20 figures |
| وصف الملف: | application/pdf |
| تدمد: | 2213-1337 |
| DOI: | 10.1016/j.ascom.2019.03.003⟩ |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f17ee8cd49534c6c80d4e9518cc001f0 https://hdl.handle.net/10453/135442 |
| Rights: | OPEN |
| رقم الانضمام: | edsair.doi.dedup.....f17ee8cd49534c6c80d4e9518cc001f0 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 22131337 |
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| DOI: | 10.1016/j.ascom.2019.03.003⟩ |