IN2P3/IRFU Machine Learning workshop 2026

Session

AI for Scientific Instruments and Accelerators

16 nov. 2026, 16:00

Amphitheatre (LPSC)

Description

AI methods for the design, optimization, operation, and control of scientific facilities.

Examples include:
- Accelerator diagnostics and control
- Detector and instrument optimization
- Surrogate models
- Digital twins
- Experimental design
- Scientific control systems

194. Physical and ML models for simulating spectroscopy instruments

Julien Zoubian (Aix Marseille Univ, CNRS/IN2P3, CPPM, Marseille, France)

16/11/2026 16:00

AI for Scientific Instruments and Accelerators

Standard talks

In the ANR DISPERS project, we use a physics-first approach to simulate spectroscopy instruments. Each physical stage of the instrument, such as optics, source catalogs, detector response, and calibration, is modeled based on physical principles wherever possible. Machine learning is only used to complement these models where physics alone is insufficient or too expensive. These model...

209. Unsupervised Machine Learning for Anomaly Detection in Beam Position Monitors Data

Quentin Bruant (CEA/IRFU/DACM)

16/11/2026 16:20

AI for Scientific Instruments and Accelerators

Standard talks

Turn-by-turn beam position monitors (TbT-BPMs) are the primary
diagnostic for optics measurement and correction in high-luminosity colliders.
Reliable identification of faulty sensors is essential to any optics
reconstruction pipeline, yet manual inspection does not scale to the hundreds
of monitors in current rings or the thousands expected in future machines such
as the FCC. We apply...

186. ARTIFACT network

Dr Adnan Ghribi ({CNRS}UPR3266)

16/11/2026 16:40

AI for Scientific Instruments and Accelerators

Standard talks

The ARTificial Intelligence For Accelerators, user Communities and associated Technologies (ARTIFACT) network—a collaborative, open-science network connecting research infrastructures, institutes, and universities— addresses these challenges by coordinating a concerted strategy for AI in accelerator science. Beyond accelerator physics, ARTIFACT establishes bridges with adjacent disciplines,...

187. The iRIS project : intelligent research infrastructures

Dr Adnan Ghribi ({CNRS}UPR3266)

16/11/2026 17:00

AI for Scientific Instruments and Accelerators

Standard talks

iRIS positions Research Infrastructures as testbeds and innovation engines for the green and digital transitions . Motivated by the Future Circular Collider and the Einstein Telescope, this project aims at demonstrating AI-powered environmental technologies and sustainability-by-design across the infrastructure lifecycle. Its relevance extends beyond fundamental-science RIs: AI approaches...

193. Machine learning surrogate models for collective effects studies in the FCC-ee High-Energy Booster

Keon Hee Kim (CNRS/GANIL)

16/11/2026 17:20

AI for Scientific Instruments and Accelerators

Lightning talks

Accurate beam dynamics simulations including collective effects are essential for the design of future particle accelerators, but high-fidelity macroparticle tracking can become computationally expensive, especially when large parameter scans are required. We investigate machine learning surrogate models for the evolution of beam distributions in the FCC-ee High-Energy Booster.

Rather than...