This title appears in the Scientific Report :
2023
Please use the identifier:
http://dx.doi.org/10.1088/1748-0221/18/04/P04010 in citations.
Please use the identifier: http://hdl.handle.net/2128/34347 in citations.
Optimization of the injection beam line at the Cooler Synchrotron COSY using Bayesian Optimization
Optimization of the injection beam line at the Cooler Synchrotron COSY using Bayesian Optimization
The complex non-linear processes in multi-dimensional parameter spaces, that are typical for an accelerator, are a natural application for machine learning algorithms. This paper reports on the use of Bayesian optimization for the optimization of the Injection Beam Line (IBL) of the Cooler Synchrotr...
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Personal Name(s): | Awal, A. |
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Hetzel, J. / Gebel, R. / Kamerdzhiev, V. / Pretz, Jörg (Corresponding author) | |
Contributing Institute: |
Kernphysikalische Großgeräte; IKP-4 Experimentelle Hadrondynamik; IKP-2 |
Published in: | Journal of Instrumentation, 18 (2023) 04, S. P04010 - |
Imprint: |
London
Inst. of Physics
2023
|
DOI: |
10.1088/1748-0221/18/04/P04010 |
Document Type: |
Journal Article |
Research Program: |
Cosmic Matter in the Laboratory |
Link: |
OpenAccess |
Publikationsportal JuSER |
Please use the identifier: http://hdl.handle.net/2128/34347 in citations.
The complex non-linear processes in multi-dimensional parameter spaces, that are typical for an accelerator, are a natural application for machine learning algorithms. This paper reports on the use of Bayesian optimization for the optimization of the Injection Beam Line (IBL) of the Cooler Synchrotron storage ring COSY at the Forschungszentrum Jülich, Germany. Bayesian optimization is a machine learning method that optimizes a continuous objective function using limited observations. The IBL is composed of 15 quadrupoles and 28 steerers. The goal is to increase the beam intensity inside the storage ring. The results showed the effectiveness of the Bayesian optimization in achieving better/faster results compared to manual optimization. |