101 citations · 158 across the 9 of their papers we have counts for
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physics.acc-ph2019★ 24 cited
OPAL a Versatile Tool for Charged Particle Accelerator Simulations
Andreas Adelmann, Pedro Calvo, Matthias Frey +9
Many sophisticated computer models have been developed to understand the behaviour of particle accelerators. Even these complex models often do not describe the measured data. Inte…
physics.acc-ph2019★ 101 cited
Machine Learning for Orders of Magnitude Speedup in Multi-Objective Optimization of Particle Accelerator Systems
Auralee Edelen, Nicole Neveu, Yannick Huber +3
High-fidelity physics simulations are powerful tools in the design and optimization of charged particle accelerators. However, the computational burden of these simulations often l…