Journals of Accelerator Conferences Website (JACoW)
JACoW
is a publisher in Geneva, Switzerland that publishes the
proceedings of accelator conferences held around the world
by an international collaboration of editors.
| URL | https://doi.org/10.18429/JACoW-IPAC2024-TUPS49 |
|---|---|
| Title | Enhancing plasma wakefield accelerator analysis through machine learning |
| Authors |
|
| Abstract | In this groundbreaking study, an advanced particle-in-cell (PIC) simulation code,QuickPIC, is used to explore beam physics within Plasma Wakefield Accelerators (PWFA). The primary aim is to comprehensively analyze beam distributions, particularly those exhibiting perturbations with significant instabilities. To connect simulated beam distributions to physical observables, the study uses cutting-edge neural networks. This research underscores the transformative potential of machine learning (ML) in unraveling PWFA complexities and enhancing our capabilities in the development of advanced accelerators. |
| Paper | download: TUPS49.pdf |
| Cite | BibTeX, LaTeX, Text/Word, RIS, EndNote |
| Conference | 15th International Particle Accelerator Conference |
| Series | |
| Location | Nashville, TN |
| Date | 19-24 May 2024 |
| Publisher | JACoW Publishing, Geneva, Switzerland |
| Editorial Board | Fulvia Pilat - Oak Ridge National Laboratory Wolfram Fischer - Brookhaven National Laboratory Robert Saethre - Oak Ridge National Laboratory Petr Anisimov - Los Alamos National Laboratory Ivan Andrian - Elettra-Sincrotrone Trieste S.C.p.A. |
| Online ISBN | 978-3-95450-247-9 |
| Online ISSN | 2673-5490 |
| Received | 16 May 2024 |
| Revised | 22 May 2024 |
| Accepted | 23 May 2024 |
| Issued | 01 July 2024 |
| DOI | 10.18429/JACoW-IPAC2024-TUPS49 |
| Pages | 1774-1777 |
| 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. |