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Beam stripping interactions implemented in cyclotrons with opal simulation code
Calvo, P., Oliver, C., Adelmann, A., Frey, M., Gsell, A., & Snuverink, J. (2020). Beam stripping interactions implemented in cyclotrons with opal simulation code. In L. Conradie, J. Garrett De Villiers, & V. R. W. Schaa (Eds.), International conference on cyclotrons and their applications: Vol. 22. CYC2019. 22nd international conference on cyclotrons and their applications (pp. 109-112). https://doi.org/10.18429/JACoW-Cyclotrons2019-MOP034
Machine learning for orders of magnitude speedup in multiobjective optimization of particle accelerator systems
Edelen, A., Neveu, N., Frey, M., Huber, Y., Mayes, C., & Adelmann, A. (2020). Machine learning for orders of magnitude speedup in multiobjective optimization of particle accelerator systems. Physical Review Accelerators and Beams, 23(4), 044601 (23 pp.). https://doi.org/10.1103/PhysRevAccelBeams.23.044601
On architecture and performance of adaptive mesh refinement in an electrostatics Particle-In-Cell code
Frey, M., Adelmann, A., & Locans, U. (2020). On architecture and performance of adaptive mesh refinement in an electrostatics Particle-In-Cell code. Computer Physics Communications, 247, 106912 (18 pp.). https://doi.org/10.1016/j.cpc.2019.106912
Matching of turn pattern measurements for cyclotrons using multiobjective optimization
Frey, M., Snuverink, J., Baumgarten, C., & Adelmann, A. (2019). Matching of turn pattern measurements for cyclotrons using multiobjective optimization. Physical Review Accelerators and Beams, 22(6), 064602 (13 pp.). https://doi.org/10.1103/PhysRevAccelBeams.22.064602
Global sensitivity analysis on numerical solver parameters of particle-in-cell models in particle accelerator systems
Frey, M., & Adelmann, A. (2020). Global sensitivity analysis on numerical solver parameters of particle-in-cell models in particle accelerator systems. Computer Physics Communications, 258, 107577 (17 pp.). https://doi.org/10.1016/j.cpc.2020.107577
Input beam matching and beam dynamics design optimizations of the IsoDAR RFQ using statistical and machine learning techniques
Koser, D., Waites, L., Winklehner, D., Frey, M., Adelmann, A., & Conrad, J. (2022). Input beam matching and beam dynamics design optimizations of the IsoDAR RFQ using statistical and machine learning techniques. Frontiers in Physics, 10, 875889 (10 pp.). https://doi.org/10.3389/fphy.2022.875889
Sparse grid-based adaptive noise reduction strategy for particle-in-cell schemes
Muralikrishnan, S., Cerfon, A. J., Frey, M., Ricketson, L. F., & Adelmann, A. (2021). Sparse grid-based adaptive noise reduction strategy for particle-in-cell schemes. Journal of Computational Physics: X, 11, 100094 (31 pp.). https://doi.org/10.1016/j.jcpx.2021.100094
Evolution of a beam dynamics model for the transport line in a proton therapy facility
Rizzoglio, V., Adelmann, A., Baumgarten, C., Frey, M., Gerbershagen, A., Meer, D., & Schippers, J. M. (2017). Evolution of a beam dynamics model for the transport line in a proton therapy facility. Physical Review Accelerators and Beams, 20(12), 124702 (12 pp.). https://doi.org/10.1103/PhysRevAccelBeams.20.124702