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GRANDlib: A simulation pipeline for the Giant Radio Array for Neutrino Detection (GRAND)

Authors :
GRAND Collaboration
Batista, Rafael Alves
Benoit-Lévy, Aurélien
Bister, Teresa
Bohacova, Martina
Bustamante, Mauricio
Carvalho, Washington
Chen, Yiren
Cheng, LingMei
Chiche, Simon
Colley, Jean-Marc
Correa, Pablo
Laurenciu, Nicoleta Cucu
Dai, Zigao
de Almeida, Rogerio M.
de Errico, Beatriz
de Jong, Sijbrand
Neto, João R. T. de Mello
de Vries, Krijn D.
Decoene, Valentin
Denton, Peter B.
Duan, Bohao
Duan, Kaikai
Engel, Ralph
Erba, William
Fan, Yizhong
Ferrière, Arsène
Gou, QuanBu
Gu, Junhua
Guelfand, Marion
Guo, Jianhua
Guo, Yiqing
Guépin, Claire
Gülzow, Lukas
Haungs, Andreas
Havelka, Matej
He, Haoning
Hivon, Eric
Hu, Hongbo
Huang, Xiaoyuan
Huang, Yan
Huege, Tim
Jiang, Wen
Koirala, Ramesh
Kong, ChuiZheng
Kotera, Kumiko
Köhler, Jelena
Lago, Bruno L.
Lai, Zhisen
Coz, Sandra Le
Legrand, François
Leisos, Antonios
Li, Rui
Li, Xingyu
Li, YiFei
Liu, Cheng
Liu, Ruoyu
Liu, Wei
Ma, Pengxiong
Macias, Oscar
Magnard, Frédéric
Marcowith, Alexandre
Martineau-Huynh, Olivier
McKinley, Thomas
Minodier, Paul
Mitra, Pragati
Mostafá, Miguel
Murase, Kohta
Niess, Valentin
Nonis, Stavros
Ogio, Shoichi
Oikonomou, Foteini
Pan, Hongwei
Papageorgiou, Konstantinos
Pierog, Tanguy
Piotrowski, Lech Wiktor
Prunet, Simon
Qian, Xiangli
Roth, Markus
Sako, Takashi
Schoorlemmer, Harm
Szálas-Motesiczky, Dániel
Sławiński, Szymon
Tian, Xishui
Timmermans, Anne
Timmermans, Charles
Tobiska, Petr
Tsirigotis, Apostolos
Tueros, Matías
Vittakis, George
Wang, Hanrui
Wang, Jiale
Wang, Shen
Wang, Xiangyu
Wang, Xu
Wei, Daming
Wei, Feng
Wu, Xiangping
Wu, Xuefeng
Xu, Xin
Xu, Xing
Yang, Fufu
Yang, Lili
Yang, Xuan
Yuan, Qiang
Zarka, Philippe
Zeng, Houdun
Zhang, Chao
Zhang, Jianli
Zhang, Kewen
Zhang, Pengfei
Zhang, Qingchi
Zhang, Songbo
Zhang, Yi
Zhou, Hao
Publication Year :
2024

Abstract

The operation of upcoming ultra-high-energy cosmic-ray, gamma-ray, and neutrino radio-detection experiments, like the Giant Radio Array for Neutrino Detection (GRAND), poses significant computational challenges involving the production of numerous simulations of particle showers and their detection, and a high data throughput. GRANDlib is an open-source software tool designed to meet these challenges. Its primary goal is to perform end-to-end simulations of the detector operation, from the interaction of ultra-high-energy particles, through -- by interfacing with external air-shower simulations -- the ensuing particle shower development and its radio emission, to its detection by antenna arrays and its processing by data-acquisition systems. Additionally, GRANDlib manages the visualization, storage, and retrieval of experimental and simulated data. We present an overview of GRANDlib to serve as the basis of future GRAND analyses.<br />Comment: 11 pages, 9 figures, plus appendices

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2408.10926
Document Type :
Working Paper