Machine learning for orders of magnitude speedup in multiobjective optimization of particle accelerator systems
Sign Up to like & getrecommendations! Published in 2020 at "Physical Review Accelerators and Beams"
DOI: 10.1103/physrevaccelbeams.23.044601
Abstract: High-fidelity physics simulations are powerful tools in the design and optimization of charged particle accelerators. However, the computational burden of these simulations often limits their use in practice for design optimization and experiment planning. It… read more here.
Keywords: optimization; magnitude speedup; particle accelerator; machine learning ... See more keywords