JACoW is a publisher in Geneva, Switzerland that publishes the proceedings of accelerator conferences held around the world by an international collaboration of editors.
@inproceedings{biedron:ipac2022-mopopt057,
author = {S. Biedron and M. Babzien and T.B. Bolin and M.G. Fedurin and J.J. Li and D. Martin and M. Martínez-Ramón and M.A. Palmer and M.E. Papka and S.I. Sosa Guitron},
% author = {S. Biedron and M. Babzien and T.B. Bolin and M.G. Fedurin and J.J. Li and D. Martin and others},
% author = {S. Biedron and others},
title = {{Updates in Efforts to Data Science Enabled MeV Ultrafast Electron Diffraction System}},
booktitle = {Proc. IPAC'22},
% booktitle = {Proc. 13th International Particle Accelerator Conference (IPAC'22)},
pages = {397--399},
eid = {MOPOPT057},
language = {english},
keywords = {electron, network, gun, laser, experiment},
venue = {Bangkok, Thailand},
series = {International Particle Accelerator Conference},
number = {13},
publisher = {JACoW Publishing, Geneva, Switzerland},
month = {07},
year = {2022},
issn = {2673-5490},
isbn = {978-3-95450-227-1},
doi = {10.18429/JACoW-IPAC2022-MOPOPT057},
url = {https://jacow.org/ipac2022/papers/mopopt057.pdf},
abstract = {{MeV ultrafast electron diffraction (MUED) is a pump-probe characterization technique to study ultrafast phenomena in materials with high temporal and spatial resolution. This complex instrument can be advanced into a turn-key, high-throughput tool with the aid of machine learning (ML) mechanisms and high-performance computing. The MUED instrument at the Accelerator Test Facility in Brookhaven National Laboratory was employed to test different ML approaches for both data analysis and control. We characterized different materials using MUED, mainly polycrystalline gold and single crystal Ta2NiS5. Diffraction patterns were acquired in single shot mode and convolutional neural network autoenconder models were evaluated for noise reduction and the reconstruction error was studied to identify anomalous diffraction patterns. Electron beam energy jitter was analyzed from single shot diffraction patterns to be used as a novel diagnostic tool. The MUED beamline was also simulated using VSim to construct a surrogate model for control of beam shape and energy. Progress towards ML-based controls leveraging off Argonne Leadership Computing Facility resources will also be presented.}},
}