Journals of Accelerator Conferences Website (JACoW)
JACoW
is a publisher in Geneva, Switzerland that publishes the
proceedings of accelerator conferences held around the world
by an international collaboration of editors.
| URL | https://doi.org/10.18429/JACoW-IPAC2026-THP5347 |
|---|---|
| Title | Learning Beam Dynamics in the Latent Space of Beam Distributions |
| Authors |
|
| Abstract | Beam dynamics under collective effects such as space charge remains a computationally expensive challenge. We present a latent space surrogate model for collective beam dynamics that significantly accelerates these simulations. The method uses a variational autoencoder to compress 6D particle distributions into a low-dimensional latent space. A learned latent-space dynamical model then predicts beam evolution directly in the latent space, bypassing expensive space charge solvers. Using simulated data from a space charge dominated lattice, this approach reproduces beam envelope evolution with good agreement to particle-in-cell codes while offering substantial speedups. This framework provides a flexible path towards fast beam prediction for online accelerator modeling. |
| Paper | download: THP5347.pdf |
| Cite | BibTeX, LaTeX, Text/Word, RIS, EndNote |
| Conference | 17th International Particle Accelerator Conference |
| Series | |
| Location | Deauville, France |
| Date | 17-22 May 2026 |
| Publisher | JACoW Publishing, Geneva, Switzerland |
| Editorial Board | Editorial Board |
| Online ISBN | 978-3-95450-252-3 |
| Online ISSN | 2673-5350 |
| Received | 13 May 2026 |
| Revised | 22 May 2026 |
| Accepted | 30 May 2026 |
| Issued | 20 July 2026 |
| DOI | 10.18429/JACoW-IPAC2026-THP5347 |
| Pages | 4776-4779 |
| 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. |