In this talk I would like to present an overview of the progress made at Diamond Light Source since the 2023 meeting at the ALS. Since April 2023 we have internally held two workshops in order to come up with a roadmap, which I will discuss, as well as delivering internal training, in collaboration with the Scientific Machine Learning group on our campus.
In addition to this we have...
Modern light sources produce too many signals for a small operations team to monitor in real time. As a result, recovering from faults can require long downtimes, or even worse subtle performance issues may persist undiscovered. Existing automated methods tend to rely on pre-set limits which either miss subtle problems or produce too many false positives. AI methods can solve both problems,...
In this work we present Hermes, a code repository designed to facilitate the development of autonomous materials science. Many common machine learning algorithms have biases or assumptions that do not account for the physics of many materials science problems. It is therefore often necessary to adapt common machine learning tools into physics-informed algorithms. The idea behind Hermes is to...
