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4th ICFA Beam Dynamics Mini-Workshop on Machine Learning Applications for Particle Accelerators

Mar 5 – 8, 2024
Lahan Select Gyeongju, South Korea
Asia/Seoul timezone

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Multi objective Bayesian optimization of ECR ion source at the Linear IFMIF Prototype Accelerator.

Mar 7, 2024, 3:00 PM
2h
Lahan Select Gyeongju, South Korea

Lahan Select Gyeongju, South Korea

Lahan Select Gyeongju, South Korea
Poster/Demo Optimization & Control Poster/Demos

Speaker

Andrea De Franco (National Institutes for Quantum Science and Technology (QST))

Description

The Linear IFMIF Prototype Accelerator (LIPAc) is designed to validate the main key technical solutions for the particle accelerator of the International Fusion Materials Irradiation Facility, which will answer the need of the fusion community for a high energy (14.1 MeV) high intensity neutron source. LIPAc is jointly developed under the EU-Japan Broader Approach agreement to accelerate 125mA of D+ to 9MeV in Continuous Wave. Its Electron Cyclotron Resonance (ECR) ion source was developed by CEA and successfully demonstrated >150mA D+ beam at 100 keV in CW. In this work we present the multi objective Bayesian optimization of several of its tunable parameter (confinement magnetic field, RF power, gas flow, etc.) to find the most suitable compromise between average extracted beam current and its stability over time.

Primary Keyword bayesian optimization
Secondary Keyword ML-based optimization

Primary author

Andrea De Franco (National Institutes for Quantum Science and Technology (QST))

Co-authors

Dr Tomoya Akagi (National Institutes for Quantum Science and Technology (QST)) Benoit Bolzon (2French Alternative Energies and Atomic Energy Commission (CEA)) Nicolas Chauvin (2French Alternative Energies and Atomic Energy Commission (CEA)) Fabio Cismondi (Fusion for Energy (F4E)) Herve Dzitko (Fusion for Energy (F4E)) Tomonobu Itagaki (National Institutes for Quantum Science and Technology (QST)) Antti Jokinen (Fusion for Energy (F4E)) Keitaro Kondo (National Institutes for Quantum Science and Technology (QST)) Kai Masuda (National Institutes for Quantum Science and Technology (QST)) Takahide Nakayama (National Institutes for Quantum Science and Technology (QST)) Masayoshi Sugimoto (National Institutes for Quantum Science and Technology (QST))

Presentation materials

2024_02_20_DeFranco_FlashSlide.pdf
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