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| URL | https://doi.org/10.18429/JACoW-IPAC2025-MOPB038 |
|---|---|
| Title | Bayesian optimization for generating attosecond X-ray FEL pulses |
| Authors |
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| Abstract | Ångström and attosecond represent fundamental spatiotemporal scales for studying electron dynamics in various materials. Recently, high-power attosecond hard X-ray pulses have been successfully demonstrated at the European XFEL using the self-chirping operation mode. However, the current process heavily depends on manual tuning by experienced operators, which is time-intensive and less scalable. In this work, we report recent advancements in automating and optimizing the generation of high-power attosecond X-ray pulses using Bayesian optimization techniques. By leveraging machine-learning-based approach, we aim to enhance pulse energy, spectral quality, and operational efficiency, paving the way for more accessible and reproducible attosecond X-ray experiments. |
| Paper | download: MOPB038.pdf |
| Cite | BibTeX, LaTeX, Text/Word, RIS, EndNote |
| Conference | 16th International Particle Accelerator Conference |
| Series | |
| Location | Taipei, Taiwan |
| Date | 01-06 Jun 2025 |
| Publisher | JACoW Publishing, Geneva, Switzerland |
| Editorial Board | * Ming-Chyuan Lin - National Synchrotron Radiation Research Center * Yoichi Sato - KEK * Jui-Che Huang - National Synchrotron Radiation Research Center * David Button - Australian Nuclear Science and Technology Organisation * Ping-Shun Chuang - National Synchrotron Radiation Research Center |
| Online ISBN | 978-3-95450-248-6 |
| Online ISSN | 2673-5490 |
| Received | 28 May 2025 |
| Revised | 02 June 2025 |
| Accepted | 03 June 2025 |
| Issued | 05 November 2025 |
| DOI | 10.18429/JACoW-IPAC2025-MOPB038 |
| Pages | 146-149 |
| 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. |