Outlook for artificial intelligence and machine learning at the NSLS-II. Issue 1 (31st March 2021)

• Record Type: Journal Article
• Authors: Campbell, Stuart I; Allan, Daniel B; Barbour, Andi M; Olds, Daniel; Rakitin, Maksim S; Smith, Reid; Wilkins, Stuart B
• Is Part Of: Machine learning: science and technology. Volume 2:Issue 1(2021)
• Publication Date: 2021-03-31
• Subjects: synchrotron x-ray -- scientific Python -- large scale facilities -- strategy; 006.31
• DOI: 10.1088/2632-2153/abbd4e
• Languages: English
• ISSNs: 2632-2153

Abstract

Abstract: We describe the current and future plans for using artificial intelligence and machine learning (AI/ML) methods at the National Synchrotron Light Source II (NSLS-II), a scientific user facility at the Brookhaven National Laboratory. We discuss the opportunity for using the AI/ML tools and techniques developed in the data and computational science areas to greatly improve the scientific output of large scale experimental user facilities. We describe our current and future plans in areas including from detecting and recovering from faults, optimizing the source and instrument configurations, streamlining the pipeline from measurement to insight, through data acquisition, processing, analysis. The overall strategy and direction of the NSLS-II facility in relation to AI/ML is presented.