High-fidelity Prediction of Megapixel Longitudinal Phase-space Images of
Electron Beams using Encoder-Decoder Neural Networks

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High-fidelity Prediction of Megapixel Longitudinal Phase-space Images of Electron Beams using Encoder-Decoder Neural Networks

Physical Review Applied (Phys. Rev. Appl.), 2021

25 January 2021

Jun Zhu

ArXiv (abs)PDF HTML

Papers citing "High-fidelity Prediction of Megapixel Longitudinal Phase-space Images of Electron Beams using Encoder-Decoder Neural Networks"

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Title
A conditional latent autoregressive recurrent model for generation and forecasting of beam dynamics in particle accelerators M. Rautela Alan Williams A. Scheinker 188 11 0 19 Mar 2024
Cheetah: Bridging the Gap Between Machine Learning and Particle Accelerator Physics with High-Speed, Differentiable SimulationsPhysical Review Accelerators and Beams (PRAB), 2024 Jan Kaiser Chenran Xu Annika Eichler Andrea Santamaria Garcia 223 16 0 11 Jan 2024
Physics-constrained 3D Convolutional Neural Networks for ElectrodynamicsAPL Machine Learning (AML), 2023 A. Scheinker R. Pokharel 118 16 0 31 Jan 2023
Mixed Diagnostics for Longitudinal Properties of Electron Bunches in a Free-Electron LaserFrontiers of Physics (Front. Phys.), 2022 J. Zhu N. Lockmann M. Czwalinna H. Schlarb 111 5 0 15 Jan 2022
Adaptive Machine Learning for Time-Varying Systems: Low Dimensional Latent Space Tuning A. Scheinker AI4CE 209 31 0 13 Jul 2021