Example of a high-level application developed by ALS-AP for monitoring and controlling source size stability. The unprecedented stability of the vertical electron beam size during user operations is achieved through a machine learning-based insertion device feedforward. The figure displays the operational beam size (red), estimates for uncorrected beam size (purple), and the dispersion wave parameter (DWP) used for the correction process.
Our program enhances ALS’s operational excellence by creating advanced yet intuitive software that supports its intricate operations. These applications are vital for automating complex processes, enabling real-time monitoring of the accelerator’s performance, and facilitating predictive maintenance strategies. This proactive approach to maintenance helps to avert potential issues before they impact the facility’s operations, thereby keeping high uptime and reliability high.
The applications are designed to streamline complex processes, ensuring that operations run smoothly and efficiently. The main objective is to automate previously manual tasks, reducing the likelihood of human error and enhancing the overall precision of experiments. A key element in this endeavor is the ongoing development of the Matlab Middle Layer, a powerful abstraction from the underlying Experimental Physics and Industrial Control System layers. This advancement allows for more convenient and flexible experimentation, enhancing our ability to control the accelerator’s operation.
The ALS Accelerator Physics Program team.
Our commitment to high-level application development extends beyond immediate operational needs. It encompasses a vision for the future where software responds to current demands and adapts to evolving research requirements and technological advancements—for example, by including data streams crucial for machine learning applications. By prioritizing flexibility and scalability in software design, we ensure that the ALS remains at the cutting edge of scientific exploration, ready to meet the challenges and opportunities of tomorrow’s research landscape.
