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| URL | https://doi.org/10.18429/JACoW-IPAC2023-WEPA065 |
|---|---|
| Title | Towards fully differentiable accelerator modeling |
| Authors |
|
| Abstract | Optimization and design of particle accelerators is challenging due to the large number of free parameters and the corresponding lack of gradient information available to the optimizer. Thus, full optimization of large beamlines becomes infeasible due to the exponential growth of free parameter space the optimization algorithm must navigate. Providing exact or approximate gradient information to the optimizer can significantly improve convergence speed, enabling practical optimization of high-dimensional problems. To achieve this, we have leveraged state-of-the-art automatic differentiation techniques developed by the machine learning community to enable end-to-end differentiable particle tracking simulations. We demonstrate that even a simple tracking simulation with gradient information can be used to significantly improve beamline design optimization. Furthermore, we show the flexibility of our implementation with various applications that make use of different kinds of derivative information. |
| Paper | download: WEPA065.pdf |
| Cite | BibTeX, LaTeX, Text/Word, RIS, EndNote |
| Conference | 14th International Particle Accelerator Conference |
| Series | |
| Location | Venice, Italy |
| Date | 07-12 May 2023 |
| Publisher | JACoW Publishing, Geneva, Switzerland |
| Editorial Board | Ralph Assmann - Deutsches Elektronen-Synchrotron DESY Peter McIntosh - Science and Technology Facilities Council (STFC/DL/ASTeC) Giovanni Bisoffi - Istituto Nazionale di Fisica Nucleare (INFN/LNL) Alessandro Fabris - Elettra-Sincrotrone Trieste S.C.p.A. Ivan Andrian - Elettra-Sincrotrone Trieste S.C.p.A. Giulia Vinicola - Istituto Nazionale di Fisica Nucleare (INFN/LNF) |
| Online ISBN | 978-3-95450-231-8 |
| Online ISSN | 2673-5490 |
| Received | 03 May 2023 |
| Revised | 18 May 2023 |
| Accepted | 22 June 2023 |
| Issued | 26 September 2023 |
| DOI | 10.18429/JACoW-IPAC2023-WEPA065 |
| Pages | 2797-2800 |
| Copyright | Published by JACoW Publishing under the terms of the Creative Commons Attribution 4.0 license. Any further distribution of this work must maintain attribution to the author(s), the published article's title, publisher, and DOI. |