Identifying transient and variable sources in radio images

Autor: 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
Přispěvatelé: 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)
Rok vydání: 2019
Předmět:
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
Zdroj: 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
ISSN: 2213-1337
Popis: 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
Databáze: OpenAIRE
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