Strategic White Paper on AI Infrastructure for Particle, Nuclear, and Astroparticle Physics: Insights from JENA and EuCAIF

Sascha Caron, Andreas Ipp, Gert Aarts, Gábor Bíró, Daniele Bonacorsi +14 more
3/18/2025
astro-ph.IMastro-ph.HEcs.AI

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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 communities-ECFA, NuPECC, and APPEC-and as part of the EuCAIF 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 (R&D) to production. This white paper provides a strategic roadmap, informed by a community survey, to address these barriers. It outlines critical infrastructure requirements, prioritizes training initiatives, and proposes funding strategies to scale AI capabilities across fundamental physics over the next five years.

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@article{caron2025strategic,
  title  = {Strategic White Paper on AI Infrastructure for Particle, Nuclear, and Astroparticle Physics: Insights from JENA and EuCAIF},
  author = {Sascha Caron and Andreas Ipp and Gert Aarts and Gábor Bíró and Daniele Bonacorsi and Elena Cuoco and Caterina Doglioni and Tommaso Dorigo and Julián García Pardiñas and Stefano Giagu and Tobias Golling and Lukas Heinrich and Ik Siong Heng and Paula Gina Isar and Karolos Potamianos and Liliana Teodorescu and John Veitch and Pietro Vischia and Christoph Weniger},
  year   = {2025},
  eprint = {2503.14192},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2503.14192v1}
}

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