Journal article 82 views 8 downloads
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
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© 2026 The Author(s). Released under the terms of the Creative Commons Attribution 4.0 licence.
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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 (Joint ECFA, NuPECC, APPEC) communities and as part of the Euro...
| 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 (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. |
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| Keywords: |
artificial intelligence, AI infrastructure, fundamental physics, particle physics, nuclear physics, astroparticle physics, science policy |
| College: |
Faculty of Science and Engineering |
| Issue: |
1 |
| Start Page: |
013002 |

