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'Journal of Accelerator Conferences Website' (JACoW) is a publisher in Geneva, Switzerland that publishes the proceedings of accelerator conferences held around the world by an international collaboration of editors.


https://doi.org/10.18429/JACoW-LINAC2022-WE2AA04
Title Data Analysis and Control of an MeV Ultrafast Electron Diffraction System using Machine Learning
Authors
  • T.B. Bolin, S. Biedron, M.A. Faziopresenter, M. Martínez-Ramón, S.I. Sosa Guitron
    UNM-ECE, Albuquerque, USA
  • M. Babzien, M.G. Fedurin, J.J. Li, M.A. Palmer
    BNL, Upton, New York, USA
  • S. Biedron
    Element Aero, Chicago, USA
  • S. Biedron
    UNM-ME, Albuquerque, New Mexico, USA
Abstract MeV ultrafast electron diffraction (MUED) is a pump-probe material characterization technique to study ultrafast lattice dynamics with high temporal and spatial resolution. It is a relatively young technology that has the potential to shed light onto some of the most puzzling problems in physics. This complex instrument can be advanced into a turn-key high-throughput tool with the aid of machine learning (ML) mechanisms together with high-performance computing. The MUED instrument located in the Accelerator Test Facility of Brookhaven National Laboratory was employed in this work to test different ML approaches for both data analysis and control. We characterized three materials using MUED: graphite, black phosphorous and gold thin films. Diffraction patterns were acquired in single shot mode and different ML methodologies were applied to reduce image noise. Convolutional neural network autoenconder and variational autoenconder models were utilized to extract the noise features and increase the signal-to-noise ratio. The energy jitter of the electron beam was analyzed after noise reduction of the single shot diffraction patterns.
Paper download WE2AA04.PDF [0.380 MB / 3 pages]
Slides download WE2AA04_TALK.PDF [12.865 MB]
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Conference LINAC2022
Series International Linear Accelerator Conference (31st)
Location Liverpool, UK
Date 28 August-02 September 2022
Publisher JACoW Publishing, Geneva, Switzerland
Editorial Board Peter McIntosh (STFC DL, Daresbury, UK); Graeme Burt (Lancaster Univ., Lancaster, UK); Robert Apsimon (Lancaster Univ., Lancaster, UK); Volker R.W. Schaa (GSI, Darmstadt, Germany)
Online ISBN 978-3-95450-215-8
Online ISSN 2226-0366
Received 30 August 2022
Revised 02 September 2022
Accepted 15 September 2022
Issue Date 20 September 2022
DOI doi:10.18429/JACoW-LINAC2022-WE2AA04
Pages 650-652
Copyright
Creative Commons CC logoPublished by JACoW Publishing under the terms of the Creative Commons Attribution 4.0 International license. Any further distribution of this work must maintain attribution to the author(s), the published article's title, publisher, and DOI.