An initiative of the European Commission

AI in Astronomy &​ Fundamental Physics​

SCIANCE is gathering evidence on scientific challenges, AI capabilities, infrastructures and emerging practices in “AI in Astronomy &​ Fundamental Physics​”​, supporting the identification of strategic priorities for RAISE.

Context and scope​

Astronomy and fundamental physics seek to understand the fundamental laws of nature, from subatomic particles to the large-scale structure of the Universe. This review covers five major research domains where AI is playing an increasingly important role: high-energy particle physics, astrophysics and cosmology, gravitational wave astronomy, nuclear physics, and quantum science and technologies. These fields share common challenges associated with extreme data volumes, complex simulations, rare-event detection and the need for advanced computational methods.​

State-of-the-Art Insights​

Scientific research challenges​

  • Extracting weak signals from large and complex datasets
  • Accelerating computationally intensive simulations
  • Detecting rare and unexpected phenomena​
  • Supporting real-time scientific operations​
  • Scaling analysis for next-generation research facilities​

AI approaches and maturity​

  • Operational: Event reconstruction, triggering systems, fast simulation and large-scale astronomy data processing
  • Emerging: Simulation-based inference, gravitational-wave parameter estimation, astronomy foundation models and AI-supported facility operations
  • Frontier: Large Physics Models, scientific AI agents, autonomous scientific workflows and quantum machine learning.​

Structural barriers​

  • Simulation-to-data and distribution-shift challenges
  • Growing need for specialised computing infrastructure​
  • Explainability and uncertainty quantification requirements​
  • Transition from research prototypes to operational services​
  • Skills shortages, software sustainability and cross-community coordination​

European ecosystem​

Europe hosts world-leading scientific infrastructures and communities including CERN, Euclid, EuCAIF, JENA, Virgo, Einstein Telescope initiatives and EuroHPC. Together they provide unique datasets, facilities and coordination mechanisms supporting AI-enabled research across physics and astronomy.​

Emerging trends​

  • Physics-informed AI​
  • Scientific foundation models and Large Physics Models
  • AI-supported scientific facilities​
  • Shared benchmarks and FAIR data ecosystems​
  • Coordinated European AI infrastructure for physics and astronomy​
  • Autonomous scientific workflows​

Outlook

AI is progressing from specialised analytical tools towards an integral component of scientific discovery. Realising its full potential will require trusted infrastructures, sustainable software, shared datasets and coordinated European investments supporting AI-enabled research ecosystems.​

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