Yadav, M.; Oruganti, M.H.; Naranjo, B.; Phillips, J.; Liang, S.; Letko, K.; Andonian, G.; Rosenzweig, J. Machine Learning-Based Spectrum Reconstruction and Modeling Beam Perturbation Effects on Betatron Radiation. Preprints2023, 2023101129. https://doi.org/10.20944/preprints202310.1129.v1
APA Style
Yadav, M., Oruganti, M.H., Naranjo, B., Phillips, J., Liang, S., Letko, K., Andonian, G., & Rosenzweig, J. (2023). Machine Learning-Based Spectrum Reconstruction and Modeling Beam Perturbation Effects on Betatron Radiation. Preprints. https://doi.org/10.20944/preprints202310.1129.v1
Chicago/Turabian Style
Yadav, M., Gerard Andonian and James Rosenzweig. 2023 "Machine Learning-Based Spectrum Reconstruction and Modeling Beam Perturbation Effects on Betatron Radiation" Preprints. https://doi.org/10.20944/preprints202310.1129.v1
Abstract
A new method for multi-shot reconstruction of high-energy photon distributions in the context of studying the interaction between a beam and a plasma in plasma wakefield acceleration (PWFA) experiments is presented. The study investigates the effects of beam perturbations on betatron radiation and analyzes how these perturbations can lead to hosing, a transverse instability that can degrade the quality of the beam. The potential of betatron radiation spectroscopy as a non-invasive diagnostic technique for PWFA experiments is also emphasized.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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