BRIEF RESEARCH REPORT article
Front. Phys.
Sec. Fusion Plasma Physics
Volume 13 - 2025 | doi: 10.3389/fphy.2025.1553993
This article is part of the Research TopicVisualizing Offline and Live Data with AI (VOLDA) Workshop first edition Princeton 11-13th June 2024View all 7 articles
Exploring NAS for Anomaly Detection in Superconducting Cavities of Particle Accelerators
Provisionally accepted
- German Electron Synchrotron, Helmholtz Association of German Research Centres (HZ), Hamburg, Germany
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The European X-Ray Free Electron Laser is the largest particle accelerator for X-ray laser generation worldwide. To ensure a safe and efficient operation, the plant uses various monitoring systems, especially in the linear accelerator. The low-level radio frequency system has shown reliability in diagnostics, particularly in quench detection. A quench refers to a superconducting radio frequency cavity losing its superconductivity and possibly causing a downtime. The diagnostics solution, however, can be enhanced in terms of robustness and functionality. Currently, the focus is on integrating artificial intelligence to improve quench identification. Thus, a lightweight machine learning-assisted approach targeting FPGA deployment is developed. It relies on the augmentation of a physical model-based anomaly detection approach with neural network models to distinguish the quenches from the other anomalies. This paper presents the solution in which neural architecture search is applied, and elaborates on how visualizing and analyzing the anomaly detection results can provide critical insights for both short-term diagnostics and long-term pattern identification.
Keywords: anomaly detection, Particle Accelerators, Neural architecture search, data visualization, Superconductivity
Received: 31 Dec 2024; Accepted: 05 May 2025.
Copyright: © 2025 Boukela, Branlard and Eichler. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Lynda Boukela, German Electron Synchrotron, Helmholtz Association of German Research Centres (HZ), Hamburg, Germany
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