Sprecher
Beschreibung
SIS-SYS develops beam-based feedback, automated control and expert-diagnostic systems for SIS18 and SIS100, combining classical DSP and control methods with numerical models and, increasingly, ML/AI-based approaches.
A central focus is how beam-data-driven algorithms are qualified and maintained over the long term through physics-informed digital twins that provide a reproducible environment for replay, stress testing and direct benchmarking ML/AI-based against established classic algorithms and measurable ground truth, as well as online/offline data analysis and offline debugging.
ML/AI-based methods are not privileged, but only one of many solutions; all must demonstrably match or outperform existing classical approaches while satisfying requirements for reproducibility, robustness, diagnosability, bounded failure behaviour and long-term maintainability.
This talk presents selected examples from beam-based diagnostics and feedback systems and GREMLIN, illustrating this approach towards a dependable 24/7 FAIR accelerator operation.