Bayesian optimization of a free-electron laser J Duris, D Kennedy, A Hanuka, J Shtalenkova, A Edelen, P Baxevanis, ... Physical review letters 124 (12), 124801, 2020 | 187 | 2020 |
Machine learning for orders of magnitude speedup in multiobjective optimization of particle accelerator systems A Edelen, N Neveu, M Frey, Y Huber, C Mayes, A Adelmann Physical Review Accelerators and Beams 23 (4), 044601, 2020 | 161 | 2020 |
Neural networks for modeling and control of particle accelerators AL Edelen, SG Biedron, BE Chase, D Edstrom, SV Milton, P Stabile IEEE Transactions on Nuclear Science 63 (2), 878-897, 2016 | 155 | 2016 |
Machine learning-based longitudinal phase space prediction of particle accelerators C Emma, A Edelen, MJ Hogan, B O’Shea, G White, V Yakimenko Physical Review Accelerators and Beams 21 (11), 112802, 2018 | 144 | 2018 |
Demonstration of model-independent control of the longitudinal phase space of electron beams in the linac-coherent light source with femtosecond resolution A Scheinker, A Edelen, D Bohler, C Emma, A Lutman Physical review letters 121 (4), 044801, 2018 | 118 | 2018 |
Opportunities in machine learning for particle accelerators A Edelen, C Mayes, D Bowring, D Ratner, A Adelmann, R Ischebeck, ... arXiv preprint arXiv:1811.03172, 2018 | 79 | 2018 |
Toward the end-to-end optimization of particle physics instruments with differentiable programming T Dorigo, A Giammanco, P Vischia, M Aehle, M Bawaj, A Boldyrev, ... Reviews in Physics 10, 100085, 2023 | 62 | 2023 |
Multiobjective Bayesian optimization for online accelerator tuning R Roussel, A Hanuka, A Edelen Physical Review Accelerators and Beams 24 (6), 062801, 2021 | 57 | 2021 |
Physics model-informed Gaussian process for online optimization of particle accelerators A Hanuka, X Huang, J Shtalenkova, D Kennedy, A Edelen, Z Zhang, ... Physical Review Accelerators and Beams 24 (7), 072802, 2021 | 56 | 2021 |
Phase space reconstruction from accelerator beam measurements using neural networks and differentiable simulations R Roussel, A Edelen, C Mayes, D Ratner, JP Gonzalez-Aguilera, S Kim, ... Physical Review Letters 130 (14), 145001, 2023 | 44 | 2023 |
First steps toward incorporating image based diagnostics into particle accelerator control systems using convolutional neural networks AL Edelen, SG Biedron, SV Milton, JP Edelen arXiv preprint arXiv:1612.05662, 2016 | 40 | 2016 |
C Demonstration Research and Development Plan EA Nanni, M Breidenbach, C Vernieri, S Belomestnykh, P Bhat, ... arXiv preprint arXiv:2203.09076, 2022 | 37 | 2022 |
Turn-key constrained parameter space exploration for particle accelerators using Bayesian active learning R Roussel, JP Gonzalez-Aguilera, YK Kim, E Wisniewski, W Liu, P Piot, ... Nature communications 12 (1), 5612, 2021 | 31 | 2021 |
Uncertainty quantification for deep learning in particle accelerator applications AA Mishra, A Edelen, A Hanuka, C Mayes Physical Review Accelerators and Beams 24 (11), 114601, 2021 | 28 | 2021 |
Using a neural network control policy for rapid switching between beam parameters in an FEL AL Edelen, SV Milton, SG Biedron, JP Edelen, PJM van der Slot Los Alamos National Laboratory (LANL), Los Alamos, NM (United States), 2017 | 28 | 2017 |
Xopt: A simplified framework for optimization of accelerator problems using advanced algorithms R Roussel, C Mayes, A Edelen, A Bartnik Proceedings of 14th International Particle Accelerator Conference (IPAC 2023 …, 2023 | 27 | 2023 |
Differentiable preisach modeling for characterization and optimization of particle accelerator systems with hysteresis R Roussel, A Edelen, D Ratner, K Dubey, JP Gonzalez-Aguilera, YK Kim, ... Physical Review Letters 128 (20), 204801, 2022 | 25 | 2022 |
Bayesian optimization algorithms for accelerator physics R Roussel, AL Edelen, T Boltz, D Kennedy, Z Zhang, F Ji, X Huang, ... Physical review accelerators and beams 27 (8), 084801, 2024 | 24 | 2024 |
Improving surrogate model accuracy for the LCLS-II injector frontend using convolutional neural networks and transfer learning L Gupta, A Edelen, N Neveu, A Mishra, C Mayes, YK Kim Machine Learning: Science and Technology 2 (4), 045025, 2021 | 24 | 2021 |
Online tuning and light source control using a physics-informed Gaussian process Adi A Hanuka, J Duris, J Shtalenkova, D Kennedy, A Edelen, D Ratner, ... arXiv preprint arXiv:1911.01538, 2019 | 23 | 2019 |