Machine learning for orders of magnitude speedup in multiobjective optimization of particle accelerator systems
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 also precludes their use as on-line mode...
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| Glavni autori: | , , , , , |
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| Format: | Artigo |
| Jezik: | Inglês |
| Izdano: |
American Physical Society
2020-04-01
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| Serija: | Physical Review Accelerators and Beams |
| Online pristup: | http://doi.org/10.1103/PhysRevAccelBeams.23.044601 |
| Oznake: |
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