GSI/FAIR AI Workshop

The ARTIFACT project leverages AI to enhance tuning, calibration, beam focusing, and anomaly detection in accelerator systems. By developing an advanced AI framework, the project aims to improve the efficiency and precision of accelerator operations across various scientific applications. A key feature is the creation of a unified metadata schema to structure and separate metadata from...

Accelerator laboratories across the globe are investigating numerous techniques to achieve this goal, including classical optimization, Bayesian optimization (BO), and reinforcement learning. This presentation will provide an overview of recent activities in these domains at GSI. The implementation of the Generic Optimization Framework & Frontend (GOFF) at GSI, supported by the EURO-Labs...

CRYRNG@ESR is a low-energy ion storage ring and Swedish in-kind contributon to FAIR. It is operational since 2019 serving atomic, nuclear and material physics experiments. Besides this purpose, it serves as a test bench for new FAIR concepts such as novel detectors and control system features. In this context, the "device-automator" application provides an end-user application for implementing...

To improve beam quality and beam intensity at the Cooler Synchrotron COSY several machine learning and artificial intelligence projects were carried out. Highlights include:
- automated beam line control with Reinforcement Learning
- automated intensity optimisation with Bayesian Optimization for Arbitrary Targets
- improved agreement between machine and model with Genetic Optimization
A...