GraphNeT: Graph neural networks for neutrino telescope event reconstruction
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Published in | Journal of open source software Vol. 8; no. 85; p. 4971 |
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Main Authors | , , , , , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
12.05.2023
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Online Access | Get full text |
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Author | Søgaard, Andreas Iversen, Kaare Endrup Pontén, Axel Neste, Ludwig Andresen, Peter Holmes, Moust DeHolton, Kayla Leonard Rosted, Aske Minh, Martin Ha Hermansen, Andreas Eller, Philipp Petersen, Troels C. Bozianu, Leon Holm, Morten Guggenmos, Tim Ørsøe, Rasmus F. |
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Cites_doi | 10.1051/epjconf/201819101006 10.1016/j.astropartphys.2011.01.003 10.1016/j.nima.2011.06.103 10.1016/j.nima.2012.11.081 10.1016/j.astropartphys.2012.01.004 10.1088/1748-0221/16/07/P07041 10.1088/1748-0221/16/08/P08034 10.1016/j.nima.2013.10.074 10.5281/zenodo.3828935 10.5281/zenodo.3952674 10.1088/1748-0221/9/03/P03009 10.1088/1748-0221/15/10/P10005 10.3847/1538-3881/aa9709 10.1088/1361-6471/abbd48 10.1038/s41550-020-1182-4 10.48550/arXiv.1912.01703 10.1088/1748-0221/12/03/P03012 10.1088/0954-3899/43/8/084001 10.5281/zenodo.6720188 10.1088/1361-6471/44/5/054006 10.1016/j.nima.2004.01.065 |
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References | Søgaard (Sogaard_GraphNeT_2023) 2023 Paszke (NEURIPS2019_9015) 2019 Falcon (Falcon_PyTorch_Lightning_2019) 2019 KM3NeT Collaboration (KM3Net:2016zxf) 2016; 43 IceCube Collaboration (Abbasi:2021ryj) 2021; 16 IceCube Collaboration (IceCube:2021oqo) 2021; 16 Abbasi (Abbasi_2013) 2013; 703 IceCube-Gen2 Collaboration (IceCube:2016xxt) 2017; 44 ANTARES Collaboration (ANTARES:2017ivh) 2017; 154 ANTARES Collaboration (Aguilar:2011zz) 2011; 34 Aartsen (Aartsen:2013bfa) 2014; 736 Eller (Eller:2022xvi) 2022 Pivarski (jim_pivarski_2020_3952674) 2020 IceCube Collaboration (DeepCore) 2012; 35 AMANDA Collaboration (Ahrens:2003fg) 2004; 524 P-ONE Collaboration (P-ONE:2020ljt) 2020; 4 Fey (Fey_Fast_Graph_Representation_2019) 2019 Chirkin (Chirkin:2013avz) 2013 IceCube Collaboration (gnn_icecube) 2022 KM3NeT Collaboration (Aiello:2020orq) 2020; 15 Biewald (wandb) 2020 Baikal-GVD Collaboration (Baikal-GVD:2018isr) 2018; 191 IceCube Collaboration (Aartsen:2013vja) 2014; 9 ANTARES Collaboration (ANTARES:2011hfw) 2011; 656 IceCube Collaboration (Aartsen:2016nxy) 2017; 12 IceCube-PINGU Collaboration (IceCube-PINGU:2014okk) 2014 IceCube Collaboration (IceCube:2022kff) 2022 IceCube-Gen2 Collaboration (IceCube-Gen2:2020qha) 2021; 48 |
References_xml | – volume: 191 year: 2018 ident: Baikal-GVD:2018isr article-title: Baikal-GVD: status and prospects publication-title: EPJ Web Conf. doi: 10.1051/epjconf/201819101006 – volume: 34 year: 2011 ident: Aguilar:2011zz article-title: A fast algorithm for muon track reconstruction and its application to the ANTARES neutrino telescope publication-title: Astropart. Phys. doi: 10.1016/j.astropartphys.2011.01.003 – year: 2020 ident: wandb article-title: Experiment tracking with weights and biases – volume: 656 year: 2011 ident: ANTARES:2011hfw article-title: ANTARES: the first undersea neutrino telescope publication-title: Nucl. Instrum. Meth. A doi: 10.1016/j.nima.2011.06.103 – volume: 703 issn: 0168-9002 year: 2013 ident: Abbasi_2013 article-title: An improved method for measuring muon energy using the truncated mean of dE/dx publication-title: Nucl. Instum. Meth. A doi: 10.1016/j.nima.2012.11.081 – volume: 35 issn: 0927-6505 issue: 10 year: 2012 ident: DeepCore article-title: The design and performance of IceCube DeepCore publication-title: Astropart. Phys. doi: 10.1016/j.astropartphys.2012.01.004 – volume: 16 year: 2021 ident: Abbasi:2021ryj article-title: A Convolutional Neural Network based Cascade Reconstruction for the IceCube Neutrino Observatory publication-title: JINST doi: 10.1088/1748-0221/16/07/P07041 – volume: 16 issue: 08 year: 2021 ident: IceCube:2021oqo article-title: A muon-track reconstruction exploiting stochastic losses for large-scale Cherenkov detectors publication-title: JINST doi: 10.1088/1748-0221/16/08/P08034 – volume: 736 year: 2014 ident: Aartsen:2013bfa article-title: Improvement in Fast Particle Track Reconstruction with Robust Statistics publication-title: Nucl. Instrum. Meth. A doi: 10.1016/j.nima.2013.10.074 – year: 2022 ident: Eller:2022xvi article-title: A flexible event reconstruction based on machine learning and likelihood principles – year: 2019 ident: Falcon_PyTorch_Lightning_2019 article-title: PyTorch Lightning doi: 10.5281/zenodo.3828935 – year: 2014 ident: IceCube-PINGU:2014okk article-title: Letter of Intent: The Precision IceCube Next Generation Upgrade (PINGU) – year: 2020 ident: jim_pivarski_2020_3952674 article-title: Scikit-hep/awkward-array: 0.13.0 doi: 10.5281/zenodo.3952674 – volume: 9 year: 2014 ident: Aartsen:2013vja article-title: Energy Reconstruction Methods in the IceCube Neutrino Telescope publication-title: JINST doi: 10.1088/1748-0221/9/03/P03009 – year: 2013 ident: Chirkin:2013avz article-title: Event reconstruction in IceCube based on direct event re-simulation publication-title: 33rd International Cosmic Ray Conference – volume: 15 issue: 10 year: 2020 ident: Aiello:2020orq article-title: Event reconstruction for KM3NeT/ORCA using convolutional neural networks publication-title: JINST doi: 10.1088/1748-0221/15/10/P10005 – year: 2022 ident: gnn_icecube article-title: Graph Neural Networks for Low-Energy Event Classification & Reconstruction in IceCube – volume: 154 issue: 6 year: 2017 ident: ANTARES:2017ivh article-title: An algorithm for the reconstruction of neutrino-induced showers in the ANTARES neutrino telescope publication-title: Astron. J. doi: 10.3847/1538-3881/aa9709 – volume: 48 issue: 6 year: 2021 ident: IceCube-Gen2:2020qha article-title: IceCube-Gen2: the window to the extreme Universe publication-title: J. Phys. G doi: 10.1088/1361-6471/abbd48 – volume: 4 issue: 10 year: 2020 ident: P-ONE:2020ljt article-title: The Pacific Ocean Neutrino Experiment publication-title: Nature Astron. doi: 10.1038/s41550-020-1182-4 – year: 2019 ident: NEURIPS2019_9015 article-title: PyTorch: An imperative style, high-performance deep learning library publication-title: Advances in neural information processing systems 32 doi: 10.48550/arXiv.1912.01703 – volume: 12 issue: 03 year: 2017 ident: Aartsen:2016nxy article-title: The IceCube Neutrino Observatory: Instrumentation and Online Systems publication-title: JINST doi: 10.1088/1748-0221/12/03/P03012 – year: 2022 ident: IceCube:2022kff article-title: Low Energy Event Reconstruction in IceCube DeepCore – volume: 43 issue: 8 year: 2016 ident: KM3Net:2016zxf article-title: Letter of intent for KM3NeT 2.0 publication-title: J. Phys. G doi: 10.1088/0954-3899/43/8/084001 – year: 2023 ident: Sogaard_GraphNeT_2023 article-title: GraphNeT doi: 10.5281/zenodo.6720188 – volume: 44 issue: 5 year: 2017 ident: IceCube:2016xxt article-title: PINGU: A Vision for Neutrino and Particle Physics at the South Pole publication-title: J. Phys. G doi: 10.1088/1361-6471/44/5/054006 – year: 2019 ident: Fey_Fast_Graph_Representation_2019 article-title: Fast Graph Representation Learning with PyTorch Geometric – volume: 524 year: 2004 ident: Ahrens:2003fg article-title: Muon track reconstruction and data selection techniques in AMANDA publication-title: Nucl. Instrum. Meth. A doi: 10.1016/j.nima.2004.01.065 |
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