| Title |
Applications of Artificial Intelligence in Laser Accelerator Control System |
| Authors |
- F.N. Li, K.C. Chen, Z. Guopresenter, Q.Y. He, C. Lin, Q. Wang, Y. Xia, M.X. Zang
PKU, Beijing, People’s Republic of China
|
| Abstract |
Ultra-intense laser-plasma interactions can produce TV/m acceleration gradients, making them promising for compact accelerators. Peking University is constructing a proton radiotherapy system prototype based on PW laser accelerators, but transient processes challenge stability control, critical for medical applications. This work demonstrates artificial intelligence’s (AI) application in laser accelerator control systems. To achieve micro-precision alignment between the ultra-intense laser and target, we propose an automated positioning program using the YOLO algorithm. This real-time method employs a convolutional neural network, directly predicting object locations and class probabilities from input images. It enables precise, automatic solid target alignment in about a hundred milliseconds, reducing experimental preparation time. The YOLO algorithm is also integrated into the safety interlocking system for anti-tailing, allowing quick emergency response. The intelligent control system also enables convenient, accurate beam tuning. We developed high-performance virtual accelerator software using "OpenXAL" and GPU-accelerated multi-particle beam transport simulations. The software allows real-time or custom parameter simulations and features control interfaces compatible with optimization algorithms. By designing tailored objective functions, desired beam size and distribution can be achieved in a few iterations.
|
| Funding |
the National Natural Science Foundation of China (Grants No. 11975037, NO. 61631001 and No. 11921006), and the National Grand Instrument Project (No. 2019YFF01014400 and No. 2019YFF01014404). |
| Paper |
download TUMBCMO13.PDF [1.381 MB / 7 pages] |
| Slides |
download TUMBCMO13_TALK.PDF [1.158 MB] |
| Poster |
download TUMBCMO13_POSTER.PDF [1.007 MB] |
| Cite |
download ※ BibTeX
※ LaTeX
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※ EndNote |
| Conference |
ICALEPCS2023 |
| Series |
International Conference on Accelerator and Large Experimental Physics Control Systems (19th) |
| Location |
Cape Town, South Africa |
| Date |
09-13 October 2023 |
| Publisher |
JACoW Publishing, Geneva, Switzerland |
| Editorial Board |
Volker RW Schaa (GSI, Darmstadt, Germany); Andy Götz (ESRF, Grenoble, France); Johan Venter (SARAO, Cape Town, South Africa); Karen White (SNS, Oak Ridge, TN, USA); Marie Robichon (ESRF, Grenoble, France); Vivienne Rowland (SARAO, Cape Town, South Africa) |
| Online ISBN |
978-3-95450-238-7 |
| Online ISSN |
2226-0358 |
| Received |
04 October 2023 |
| Revised |
12 October 2023 |
| Accepted |
23 November 2023 |
| Issued/td>
| 23 November 2023 |
| DOI |
doi:10.18429/JACoW-ICALEPCS2023-TUMBCMO13 |
| Pages |
372-378 |
| Copyright |
 Published by JACoW Publishing under the terms of the Creative Commons Attribution 4.0 International license. Any further distribution of this work must maintain attribution to the author(s), the published article's title, publisher, and DOI. |
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