Speaker
Description
Over the past years, the beam quality delivered by the CERN Proton Synchrotron (PS) has significantly improved, driven by major upgrades to both the accelerator and its controls infrastructure. As a result, user requirements have become increasingly demanding, particularly for high-brightness beams for the LHC, but also for fixed-target beams. The PS, known for its versatility in supplying beams with widely varying characteristics to multiple facilities, must now meet tighter performance specifications while maintaining reliability and operational efficiency.
To address these challenges, a new beam quality monitoring framework has been developed, building on recent enhancements in data acquisition and online analysis capabilities. The system defines key beam quality metrics in real time, enabling early detection of drifts, root-cause fault analysis, and provides the foundation for automated corrections and machine learning–based optimisation. Complementing this analytical layer, a dedicated graphical interface provides operators with live observability of key parameters and short-term trends, facilitating rapid decision-making in the control room.
This new approach represents a step change in the way beam quality is monitored and maintained in the PS, from reactive diagnostics to proactive control, supporting both operational stability and the increasingly stringent demands of CERN’s experimental program
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