Strategic white paper on AI infrastructure for particle, nuclear, and astroparticle physics: insights from JENA and EuCAIF

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Authors: Sascha Caron, Andreas Ipp, Gert Aarts, Gabor Biro, Daniele Bonacorsi, Elena Cuoco, Caterina Doglioni, Tommaso Dorigo, Julian Garcia Pardinas, Stefano Giagu, Tobias Golling, Lukas Heinrich
+7 more I. S. Heng, Paula Gina Isar, Karolos Potamianos, Liliana Teodorescu, John Veitch, Pietro Vischia, Christoph Weniger
Cited by: 1
References: 27

Abstract

Abstract Artificial intelligence (AI) is transforming scientific research, with deep learning methods playing a central role in data analysis, simulations, and signal detection across particle, nuclear, and astroparticle physics. Within the JENA (Joint ECFA, NuPECC, APPEC) communities and as part of the European Coalition for AI in Fundamental Physics initiative, AI integration is advancing steadily. However, broader adoption remains constrained by challenges such as limited computational resources, a lack of expertise, and difficulties in transitioning from research and development to production. This white paper provides a strategic roadmap, informed by a community survey, to address these barriers. It outlines critical infrastructure requirements, prioritises training initiatives, and proposes funding strategies to scale AI capabilities across fundamental physics over the next five years.

Fields of Study & Subjects

International Science and Diplomacy Computational Physics and Python Applications Particle physics theoretical and experimental studies

Publication details

Journal / source
Machine Learning Science and Technology
Publisher
IOP Publishing
Volume
7
Issue
1
Pages
013002–013002
Publication date
8 January 2026
Language
EN