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@inproceedings{fazio:ipac2021-mopab286,
author = {M.A. Fazio and M. Babzien and S. Biedron and K.A. Brown and J. Chen and M.G. Fedurin and A.J. Hurd and J.J. Li and D. Martin and M. Martínez-Ramón and D.J. Monk and N.A. Moody and M.A. Palmer and M.E. Papka and R. Prasankumar and S.I. Sosa Guitron and C. Sweeney and T. Talbott and J. Tao},
% author = {M.A. Fazio and M. Babzien and S. Biedron and K.A. Brown and J. Chen and M.G. Fedurin and others},
% author = {M.A. Fazio and others},
title = {{Towards a Data Science Enabled MeV Ultrafast Electron Diffraction System}},
booktitle = {Proc. IPAC'21},
pages = {906--908},
eid = {MOPAB286},
language = {english},
keywords = {electron, network, experiment, real-time, laser},
venue = {Campinas, SP, Brazil},
series = {International Particle Accelerator Conference},
number = {12},
publisher = {JACoW Publishing, Geneva, Switzerland},
month = {08},
year = {2021},
issn = {2673-5490},
isbn = {978-3-95450-214-1},
doi = {10.18429/JACoW-IPAC2021-MOPAB286},
url = {https://jacow.org/ipac2021/papers/mopab286.pdf},
note = {https://doi.org/10.18429/JACoW-IPAC2021-MOPAB286},
abstract = {{A MeV ultrafast electron diffraction (MUED) instrument is a unique characterization technique to study ultrafast processes in materials by a pump-probe technique. This relatively young technology can be advanced further into a turn-key instrument by using data science and artificial intelligence (AI) mechanisms in conjunctions with high-performance computing. This can facilitate automated operation, data acquisition and real time or near- real time processing. AI based system controls can provide real time feedback on the electron beam which is currently not possible due to the use of destructive diagnostics. Deep learning can be applied to the MUED diffraction patterns to recover valuable information on subtle lattice variations that can lead to a greater understanding of a wide range of material systems. A data science enabled MUED facility will also facilitate the application of this technique, expand its user base, and provide a fully automated state-of-the-art instrument. We will discuss the progress made on the MUED instrument in the Accelerator Test Facility of Brookhaven National Laboratory.}},
}