Robust errant beam prognostics with conditional modeling for particle accelerators

Robust errant beam prognostics with conditional modeling for particle accelerators

Particle accelerators are complex and comprise thousands of components, with many pieces of equipment running at their peak power. Consequently, they can fault and abort operations for numerous reasons, lowering efficiency and science output. To avoid these faults, we apply anomaly detection techniq...

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Bibliographic Details
Main Authors: Kishansingh Rajput, Malachi Schram, Willem Blokland, Yasir Alanazi, Pradeep Ramuhalli, Alexander Zhukov, Charles Peters, Ricardo Vilalta
Format: Article
Language:English
Published: IOP Publishing 2024-01-01
Series:Machine Learning: Science and Technology
Subjects:
anomaly prediction
siamese model
variational autoencoder
conditional
SNS
spallational neutron source
Online Access:https://doi.org/10.1088/2632-2153/ad2e18

Internet

https://doi.org/10.1088/2632-2153/ad2e18

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