Skip to main navigation Skip to search Skip to main content

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
  • , Elena Cuoco
  • , Caterina Doglioni
  • , Tommaso Dorigo
  • , Julián García Pardiñas
  • , Stefano Giagu
  • , Tobias Golling
  • , Lukas Heinrich
  • , Ik Siong Heng
  • , Paula Gina Isar
  • , Karolos Potamianos
  • , Liliana Teodorescu
  • , John Veitch
  • , Pietro Vischia
  • , Christoph Weniger
  • Radboud University Nijmegen
  • Science Park 105
  • Technical University of Vienna
  • Swansea University
  • Wigner Research Centre for Physics
  • Eotvos Lorand University (ELTE)
  • DIBINEM, Alma Mater Studiorum, University of Bologna
  • Istituto Nazionale di Fisica Nucleare, Sezione di Bologna
  • University of Manchester
  • Luleå University of Technology
  • Dipartimento di Fisica 'G. Galilei' and INFN
  • Massachusetts Institute of Technology
  • Universita La Sapienza
  • University of Geneva
  • University of Glasgow
  • National Institute for Laser, Plasma and Radiation Physics
  • University of Warwick
  • Brunel University London
  • University of Oviedo
  • Institute for Theoretical Physics Amsterdam

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Article number015035
JournalMachine Learning: Science and Technology
Volume7
Issue number1
DOIs
StatePublished - 1 Feb 2026

Keywords

  • AI infrastructure
  • Artificial intelligence
  • Astroparticle physics
  • Fundamental physics
  • Nuclear physics
  • Particle physics
  • Science policy

Fingerprint

Dive into the research topics of 'Strategic white paper on AI infrastructure for particle, nuclear and astroparticle physics: Insights from JENA and EuCAIF'. Together they form a unique fingerprint.

Cite this