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{zhang:napac2022-tupa84,
author = {S. Zhang and Ö. Apsimon and N. Majernik and B. Naranjo and J.B. Rosenzweig and C.P. Welsch and M. Yadav},
% author = {S. Zhang and Ö. Apsimon and N. Majernik and B. Naranjo and J.B. Rosenzweig and C.P. Welsch and others},
% author = {S. Zhang and others},
title = {{Reconstructing Beam Parameters from Betatron Radiation Through Machine Learning and Maximum Likelihood Estimation}},
& booktitle = {Proc. NAPAC'22},
booktitle = {Proc. 5th Int. Particle Accel. Conf. (NAPAC'22)},
pages = {527--530},
eid = {TUPA84},
language = {english},
keywords = {radiation, betatron, simulation, diagnostics, plasma},
venue = {Albuquerque, NM, USA},
series = {International Particle Accelerator Conference},
number = {5},
publisher = {JACoW Publishing, Geneva, Switzerland},
month = {10},
year = {2022},
issn = {2673-7000},
isbn = {978-3-95450-232-5},
doi = {10.18429/JACoW-NAPAC2022-TUPA84},
url = {https://jacow.org/napac2022/papers/tupa84.pdf},
abstract = {{The dense drive beam used in plasma wakefield acceleration generates a linear focusing force that causes electrons inside the witness beam to undergo betatron oscillations, giving rise to betatron radiation. Because information about the properties of the beam is encoded in the betatron radiation, measurements of the radiation such as those recorded by the UCLA-built Compton spectrometer can be used to reconstruct beam parameters. Two possible methods of extracting information about beam parameters from measurements of radiation are machine learning (ML), which is increasingly being implemented for different fields of beam diagnostics, and a statistical technique known as maximum likelihood estimation (MLE). We assess the ability of both machine learning and MLE methods to accurately extract beam parameters from measurements of betatron radiation.}},
}