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 language | English |
|---|---|
| Article number | 015035 |
| Journal | Machine Learning: Science and Technology |
| Volume | 7 |
| Issue number | 1 |
| DOIs | |
| State | Published - 1 Feb 2026 |
Keywords
- AI infrastructure
- Artificial intelligence
- Astroparticle physics
- Fundamental physics
- Nuclear physics
- Particle physics
- Science policy
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