Journal article 20 views
Strategic white paper on AI infrastructure for particle, nuclear, and astroparticle physics: insights from JENA and EuCAIF
Machine Learning: Science and Technology, Volume: 7, Issue: 1, Start page: 013002
Swansea University Author:
Gert Aarts
Full text not available from this repository: check for access using links below.
DOI (Published version): 10.1088/2632-2153/ae35cd
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 i...
| Published in: | Machine Learning: Science and Technology |
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| ISSN: | 2632-2153 |
| Published: |
IOP Publishing
2026
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| Online Access: |
Check full text
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| URI: | https://cronfa.swan.ac.uk/Record/cronfa71411 |
| 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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| College: |
Faculty of Science and Engineering |
| Issue: |
1 |
| Start Page: |
013002 |

