Speaker
Description
A 4th generation, 6-GeV high energy synchrotron radiation light source, High Energy Photon Source (HEPS), is being built in suburban Beijing, China. The complexity level and high accuracy requirements for the accelerator and beamlines will need a state-of-art controls approach such as machine learning technology. It is essential to design a modern software architecture with proper modularization to utilize software reusability with sensible API sets. A Python based Machine Learning (ML) Platform for Accelerator High-Level Applications is one of the three planned software platforms. To simplify a converted physicist programmer’s work load, the ML platform provides common functions such as data query, cleaning, graphing and interfaces to popular ML packages like Scikit-Learn and TensorFlow. The data query includes access to EPICS-based archiver systems as well as live data. Possible ideas for ML applications will also be presented.
