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

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,...

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Veröffentlicht in:	Comput.Phys.Commun 2025-03, Vol.308, p.109461, Article 109461
Hauptverfasser:	Alves Batista, R., Benoit-Lévy, A., Bister, T., Bohacova, M., Bustamante, M., Carvalho, W., Chen, Y., Cheng, L., Chiche, S., Colley, J.M., Correa, P., Cucu Laurenciu, N., Dai, Z., de Almeida, R.M., de Errico, B., de Jong, S., de Mello Neto, J.R.T., de Vries, K.D., Decoene, V., Denton, P.B., Duan, B., Duan, K., Engel, R., Erba, W., Fan, Y., Ferrière, A., Gou, Q., Gu, J., Guelfand, M., Guo, J., Guépin, C., Gülzow, L., Havelka, M., He, H., Hivon, E., Hu, H., Huang, X., Huang, Y., Huege, T., Jiang, W., Koirala, R., Kong, C., Köhler, J., Lago, B.L., Lai, Z., Le Coz, S., Legrand, F., Leisos, A., Li, R., Li, X., Li, Y., Liu, C., Liu, R., Ma, P., Marcowith, A., Martineau-Huynh, O., McKinley, T., Minodier, P., Mitra, P., Mostafá, M., Niess, V., Nonis, S., Ogio, S., Oikonomou, F., Pan, H., Papageorgiou, K., Pierog, T., Prunet, S., Qian, X., Sako, T., Szálas-Motesiczky, D., Sławiński, S., Tian, X., Timmermans, A., Timmermans, C., Tobiska, P., Tsirigotis, A., Tueros, M., Vittakis, G., Wang, H., Wang, J., Wang, S., Wang, X., Wei, D., Wei, F., Wu, X., Xu, X., Yang, F., Yang, L., Yang, X., Yuan, Q., Zarka, P., Zeng, H., Zhang, C., Zhang, K., Zhang, Y., Zhou, H.
Format:	Artikel
Sprache:	eng
Schlagworte:	Astroparticle Cosmic ray Experiment GRAND High Energy Physics - Experiment High Energy Physics - Phenomenology Instrumentation and Detectors Neutrino Physics Ultra-high energy physics
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Zusammenfassung:	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.
ISSN:	0010-4655
DOI:	10.1016/j.cpc.2024.109461