Reconstruction of cosmic-ray properties with uncertainty estimation using graph neural networks in GRAND

Arsène Ferrière; Aurélien Benoit-Lévy; Jaime Alvarez-Muñiz; Rafael Alves Batista; T. Bister; Martina Boháčová; M. Bustamante; W. Carvalho; Y. Chen; L. Cheng; S. Chiche; J.-M. Colley; P. Correa; Nicoleta Cucu Laurenciu; Z. Dai; R. M. de Almeida; B. d'Errico; J. R. T. de Mello Neto; Krijn D. de Vries; V. Decoene; Peter B. Denton; B Duan; K Duan; R. Engel; William Erba; Y. Fan; Q. Gou; J. Gu; Marion Guelfand; G. Guo; J. Guo; Y. Guo; Claire Guépin; Lukas Gülzow; Andreas Haungs; M. Havelka; H. He; E. Hivon; H. Hu; G. Huang; X. Huang; Y. Huang; Tim Huege; W. Jiang; S. Kato; R. Koirala; K. Kotera; J. Köhler; B. L. Lago; Z. Lai; J Lavoisier; F. Legrand; A. Leisos; R. Li; X. Li; C. Liu; R. Liu; W. Liu; P Ma; O. Macias; F. Magnard; Alexandre Marcowith; Olivier Martineau-Huynh; Z Mason; T Mckinley; P. Minodier; M. Mostafá; K. Murase; V. Niess; S Nonis; S. Ogio; F. Oikonomou; H Pan; Konstantinos Papageorgiou; Tanguy Pierog; Alexander Wickham-Piotrowski; S. Prunet; C Prevotat; X. Qian; M. Roth; T. Sako; S. Shinde; Dániel Szálas-Motesiczky; S Sławiński; Takéo Takahashi; X. Tian; C. Timmermans; P. Tobiska; Apostolos Tsirigotis; Matías Tueros; George Vittakis; V. Voisin; H. Wang; J. Wang; S. Wang; X. Wang; D. Wei; F. Wei; E Weissling; J. Wu; X. Wu; X. Xu; F. Yang; L. Yang; X. Yang; Q. Yuan; P. Zarka; H. Zeng; C. Zhang; J. Zhang; K. Zhang; P. Zhang; Q. Zhang; S. Zhang; Y. Zhang; H. Zhou

Reconstruction of cosmic-ray properties with uncertainty estimation using graph neural networks in GRAND

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Open Access

Reconstruction of cosmic-ray properties with uncertainty estimation using graph neural networks in GRAND

Arsène Ferrière, Aurélien Benoit-Lévy, Jaime Alvarez-Muñiz, Rafael Alves Batista, T. Bister, Martina Boháčová, M. Bustamante, W. Carvalho, Y. Chen, L. Cheng, …

Proceedings of Science (PoS)

ICRC2025 - 39th International Cosmic Ray Conference (Genève, Switzerland, 14/07/2025–24/07/2025)

14/07/2025

Résumé

training

instrumentation

detector

Trustworthy Artificial intelligence

modeling

robustness

consistency

reliability

angular resolution

arrival direction

neutrinos

neural network

graph neural network

simulation

denoising

artificial intelligence

machine learning

spectrum analysis

signal processing

reconstruction

cosmic rays

prototype

air shower

radio emissions

The Giant Radio Array for Neutrino Detection (GRAND) aims to detect and study ultra-high energy (UHE) neutrinos by observing the radio emissions produced in extensive air showers. The GRANDProto300 prototype primarily focuses on UHE cosmic rays to demonstrate the autonomous detection and reconstruction techniques that will later be applied to neutrino detection. In this work, we propose a method for reconstructing the arrival direction and energy with high precision using state-of-the-art machine learning techniques from noisy simulated voltage traces. For each event, we represent the triggered antennas as a graph structure, which is used as input for a graph neural network (GNN). To significantly enhance precision and reduce the required training set size, we incorporate physical knowledge into both the GNN architecture and the input data. This approach achieves an angular resolution of 0.14° and a primary energy reconstruction resolution of about 15%. Additionally, we employ uncertainty estimation methods to improve the reliability of our predictions. These methods allow us to quantify the confidence of the GNNpredictions and provide confidence intervals for the direction and energy reconstruction.Finally, we explore strategies to evaluate the consistency and robustness of the model when applied to real data. Our goal is to identify situations where predictions remain trustworthy despite domain shifts between simulation and reality.

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Titre: Reconstruction of cosmic-ray properties with uncertainty estimation using graph neural networks in GRAND
Créateurs - sans rôle: Arsène Ferrière - Laboratoire de Physique Nucléaire et de Hautes Énergies
Aurélien Benoit-Lévy - Laboratoire Intelligence Artificielle de Confiance pour l’Instrumentation (CEA, LIST)
Jaime Alvarez-Muñiz - Universidade de Santiago de Compostela
Rafael Alves Batista - Institut d'Astrophysique de Paris
T. Bister - Radboud University [Nijmegen]
Martina Boháčová - FZU ‒ Institute of Physics of the Academy of Sciences of the Czech Republic
M. Bustamante - Niels Bohr Institute [Copenhagen]
W. Carvalho - University of Warsaw
Y. Chen - Purple Mountain Observatory
L. Cheng - National Astronomical Observatories
S. Chiche - Université Libre de Bruxelles
J.-M. Colley - Sorbonne Université
P. Correa - Sorbonne Université
Nicoleta Cucu Laurenciu - Radboud University [Nijmegen]
Z. Dai - University of Science and Technology of China [Hefei]
R. M. de Almeida - Universidade Federal do Estado do Rio de Janeiro
B. d'Errico - Universidade Federal do Estado do Rio de Janeiro
J. R. T. de Mello Neto - Universidade Federal do Estado do Rio de Janeiro
Krijn D. de Vries - Vrije Universiteit Brussel
V. Decoene - Laboratoire de Physique Subatomique et des Technologies Associées
Peter B. Denton - Brookhaven National Laboratory
B Duan - Purple Mountain Observatory
K Duan - Purple Mountain Observatory
R. Engel - Karlsruhe Institute of Technology
William Erba - International Laboratory for Astrophysics, Neutrino and Cosmology Experiments
Y. Fan - Purple Mountain Observatory
Q. Gou - Chinese Academy of Sciences [Beijing]
J. Gu - National Astronomical Observatories
Marion Guelfand - Institut d'Astrophysique de Paris
G. Guo - China University of Geosciences
J. Guo - Purple Mountain Observatory
Y. Guo - Chinese Academy of Sciences [Beijing]
Claire Guépin - Université de Montpellier, Laboratoire Univers et Particules de Montpellier - LUPM
Lukas Gülzow - Karlsruhe Institute of Technology
Andreas Haungs - Karlsruhe Institute of Technology
M. Havelka - FZU ‒ Institute of Physics of the Academy of Sciences of the Czech Republic
H. He - Purple Mountain Observatory
E. Hivon - Institut d'Astrophysique de Paris
H. Hu - Chinese Academy of Agricultural Sciences
G. Huang - China University of Geosciences
X. Huang - Purple Mountain Observatory
Y. Huang - National Astronomical Observatories
Tim Huege - Vrije Universiteit Brussel
W. Jiang - School of Electronic Engineering [Xidian University]
S. Kato - Institut d'Astrophysique de Paris
R. Koirala - Nepal Academy of Science and Technology
K. Kotera - Institut d'Astrophysique de Paris
J. Köhler - Karlsruhe Institute of Technology
B. L. Lago - Centro Federal de Educação Tecnológica Celso Suckow da Fonseca [Rio de Janeiro]
Z. Lai - San Francisco State University
J Lavoisier - Institut d'Astrophysique de Paris
F. Legrand - Sorbonne Université
A. Leisos - Hellenic Open University
R. Li - School of Electronic Engineering [Xidian University]
X. Li - China University of Geosciences
C. Liu - Chinese Academy of Sciences [Beijing]
R. Liu - Nanjing University
W. Liu - Chinese Academy of Sciences [Beijing]
P Ma - Purple Mountain Observatory
O. Macias - San Francisco State University
F. Magnard - Institut d'Astrophysique de Paris
Alexandre Marcowith - Université de Montpellier, Laboratoire Univers et Particules de Montpellier - LUPM
Olivier Martineau-Huynh - Institut d'Astrophysique de Paris
Z Mason - San Francisco State University
T Mckinley - San Francisco State University
P. Minodier - International Laboratory for Astrophysics, Neutrino and Cosmology Experiments
M. Mostafá - Temple University
K. Murase - Pennsylvania State University
V. Niess - Laboratoire de Physique de Clermont
S Nonis - Hellenic Open University
S. Ogio - University of Tokyo [Tokyo] = Tōkyō teikoku daigaku
F. Oikonomou - Norwegian University of Science and Technology
H Pan - School of Electronic Engineering [Xidian University]
Konstantinos Papageorgiou - University of the Aegean
Tanguy Pierog - Karlsruhe Institute of Technology
Alexander Wickham-Piotrowski - University of Warsaw
S. Prunet - Observatoire de la Côte d’Azur
C Prevotat - Institut d'Astrophysique de Paris
X. Qian - Shandong Management University
M. Roth - Karlsruhe Institute of Technology
T. Sako - University of Tokyo [Tokyo] = Tōkyō teikoku daigaku
S. Shinde - San Francisco State University
Dániel Szálas-Motesiczky - Radboud University [Nijmegen]
S Sławiński - University of Warsaw
Takéo Takahashi - Equations aux dérivées partielles
X. Tian - University of Tokyo [Tokyo] = Tōkyō teikoku daigaku
C. Timmermans - Radboud University [Nijmegen]
P. Tobiska - FZU ‒ Institute of Physics of the Academy of Sciences of the Czech Republic
Apostolos Tsirigotis - Hellenic Open University
Matías Tueros - Instituto de Física La Plata
George Vittakis - University of the Aegean
V. Voisin - Sorbonne Université
H. Wang - School of Electronic Engineering [Xidian University]
J. Wang - School of Electronic Engineering [Xidian University]
S. Wang - Purple Mountain Observatory
X. Wang - Nanjing University
X. Wang - Shandong Management University
D. Wei - Purple Mountain Observatory
F. Wei - School of Electronic Engineering [Xidian University]
E Weissling - San Francisco State University
J. Wu - China University of Geosciences
X. Wu - National Astronomical Observatories
X. Wu - Purple Mountain Observatory
X. Xu - School of Electronic Engineering [Xidian University]
X. Xu - Purple Mountain Observatory
F. Yang - School of Electronic Engineering [Xidian University]
L. Yang - National Sun Yat-sen University
X. Yang - Shanghai Astronomical Observatory
Q. Yuan - Purple Mountain Observatory
P. Zarka - Observatoire de Paris
H. Zeng - Purple Mountain Observatory
C. Zhang - Peking University
J. Zhang - National Astronomical Observatories
K. Zhang - Purple Mountain Observatory
P. Zhang - School of Electronic Engineering [Xidian University]
Q. Zhang - School of Electronic Engineering [Xidian University]
S. Zhang - Purple Mountain Observatory
Y. Zhang - Purple Mountain Observatory
H. Zhou - Shanghai Jiao Tong University
Détails de publication: Proceedings of Science (PoS)
Colloque: ICRC2025 - 39th International Cosmic Ray Conference (Genève, Switzerland, 14/07/2025–24/07/2025)
Identifiants: 9994109909311
Unité académique: Laboratoire Univers et Particules de Montpellier - LUPM
Langue: English
Type de ressource: Conference proceeding
Champs locaux: cea-05186769