Application of ML tools for extraction of BPM-Q and transverse beam matching
Year: 2025
Type: conference-paper
Abstract: Data inaccuracies make training an accurate Beam Quadrupole Moment at BPM (BPMQ) model challenging. Similarly, reconstructing Courant-Snyder (CS) parameters from BPMQ predictions is difficult due to BPMQ model limitations. Increasing the number of BPMQ predictions helps mitigate overfitting in CS inference caused by inaccurate BPMQ predictions. We present Bayesian Active Learning (BAL) to acquire measurements strategically, improving CS parameter inference despite model limitations.
Source: JACOW
Authors: Hwang,Kilean, Plastun,Alexander, Fukushima,Kei, Ostroumov,Peter, Zhao,Qiang, Maruta,Tomofumi, Zhang,Tong
Language: English
Subfield: Aerospace Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W7090935483
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