19–24 May 2024
Music City Center
US/Central timezone

Machine learning for data analysis and control of an MeV ultrafast electron diffraction system and a photocathode laser and gun system: updates

TUPS76
21 May 2024, 16:00
2h
Blues (MCC Exhibit Hall A)

Blues

MCC Exhibit Hall A

Poster Presentation MC6.D13 Machine Learning Tuesday Poster Session

Speaker

Trudy Bolin (University of New Mexico)

Description

An MeV ultrafast electron diffraction (MUED) in-strument system is a unique characterization technique used to study ultrafast processes in a variety of mate-rials by a pump-probe method. Combining this tech-nology with rapid data science and artificial intelli-gence/machine learning (AI/ML) technologies in con-junction with high-performance computing can create a turnkey, automated instrument. AI-based system controls can also provide real-time electron beam optimization or provide virtual diagnostics of the beamline operational parameters. Deep learning can be applied to the MUED diffraction patterns to recover valuable information on subtle lattice variations Such a data-science-enabled MUED facility will open this technique to a wider user base with a wider variation of experience, providing an automated or semi-automated state-of-the-art instrument, with a beamline scientist orchestrating the overall data collection pro-cess. Updates on research and development efforts pri-marily in the realm of initial studies of network con-nection between the ALCF and the Accelerator Test Facility (ATF) at Brookhaven National Laboratory are presented.

Region represented North America
Paper preparation format Word

Primary author

Trudy Bolin (University of New Mexico)

Co-authors

Aasma Aslam (University of New Mexico) Manel Martinez-Ramon (University of New Mexico) Marcus Babzien (Brookhaven National Laboratory) Mark Palmer (Brookhaven National Laboratory) Mikhail Fedurin (Brookhaven National Laboratory) Robert Malone (Brookhaven National Laboratory) Sandra Biedron (University of New Mexico) William Li (Brookhaven National Laboratory)

Presentation materials

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