Physics-based deep neural networks for beam dynamics in charged particle accelerators
This paper presents a novel approach for constructing neural networks which model charged particle beam dynamics. In our approach, the Taylor maps arising in the representation of dynamics are mapped onto the weights of a polynomial neural network. The resulting network approximates the dynamical sy...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
American Physical Society
2020-07-01
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| Series: | Physical Review Accelerators and Beams |
| Online Access: | http://doi.org/10.1103/PhysRevAccelBeams.23.074601 |