Deployment and validation of predictive 6-dimensional beam diagnostics through generative reconstruction with standard accelerator elements
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arXiv
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| Autores principales: | , , , , , , , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| _version_ | 1866911300938891264 |
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| author | Kim, Seongyeol Gonzalez-Aguilera, Juan Pablo Roussel, Ryan Kim, Gyujin Edelen, Auralee Cho, Myung-Hoon Kim, Young-Kee Shim, Chi Hyun Heo, Hoon Yang, Haeryong |
| author_facet | Kim, Seongyeol Gonzalez-Aguilera, Juan Pablo Roussel, Ryan Kim, Gyujin Edelen, Auralee Cho, Myung-Hoon Kim, Young-Kee Shim, Chi Hyun Heo, Hoon Yang, Haeryong |
| contents | Understanding the 6-dimensional phase space distribution of particle beams is essential for optimizing accelerator performance. Conventional diagnostics such as use of transverse deflecting cavities offer detailed characterization but require dedicated hardware and space. Generative phase space reconstruction (GPSR) methods have shown promise in beam diagnostics, yet prior implementations still rely on such components. Here we present the first experimental implementation and validation of the GPSR methodology, realized by the use of standard accelerator elements including accelerating cavities and dipole magnets, to achieve complete 6-dimensional phase space reconstruction. Through simulations and experiments at the Pohang Accelerator Laboratory X-ray Free Electron Laser facility, we successfully reconstruct complex, nonlinear beam structures. Furthermore, we validate the methodology by predicting independent downstream measurements excluded from training, revealing near-unique reconstruction closely resembling ground truth. This advancement establishes a pathway for predictive diagnostics across beamline segments while reducing hardware requirements and expanding applicability to various accelerator facilities. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2502_20654 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Deployment and validation of predictive 6-dimensional beam diagnostics through generative reconstruction with standard accelerator elements Kim, Seongyeol Gonzalez-Aguilera, Juan Pablo Roussel, Ryan Kim, Gyujin Edelen, Auralee Cho, Myung-Hoon Kim, Young-Kee Shim, Chi Hyun Heo, Hoon Yang, Haeryong Accelerator Physics Understanding the 6-dimensional phase space distribution of particle beams is essential for optimizing accelerator performance. Conventional diagnostics such as use of transverse deflecting cavities offer detailed characterization but require dedicated hardware and space. Generative phase space reconstruction (GPSR) methods have shown promise in beam diagnostics, yet prior implementations still rely on such components. Here we present the first experimental implementation and validation of the GPSR methodology, realized by the use of standard accelerator elements including accelerating cavities and dipole magnets, to achieve complete 6-dimensional phase space reconstruction. Through simulations and experiments at the Pohang Accelerator Laboratory X-ray Free Electron Laser facility, we successfully reconstruct complex, nonlinear beam structures. Furthermore, we validate the methodology by predicting independent downstream measurements excluded from training, revealing near-unique reconstruction closely resembling ground truth. This advancement establishes a pathway for predictive diagnostics across beamline segments while reducing hardware requirements and expanding applicability to various accelerator facilities. |
| title | Deployment and validation of predictive 6-dimensional beam diagnostics through generative reconstruction with standard accelerator elements |
| topic | Accelerator Physics |
| url | https://arxiv.org/abs/2502.20654 |