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RIS citation export for TUPOST048: Development of a Virtual Diagnostic for Estimating Key Beam Descriptors

TY  - CONF
AU  - Baker, K.R.L.
AU  - Basak, S.
AU  - Cha, J.
AU  - Finch, I.D.
AU  - Lawrie, S.R.
AU  - Saoulis, A.A.
AU  - Thiyagalingam, J.
ED  - Zimmermann, Frank
ED  - Tanaka, Hitoshi
ED  - Sudmuang, Porntip
ED  - Klysubun, Prapong
ED  - Sunwong, Prapaiwan
ED  - Chanwattana, Thakonwat
ED  - Petit-Jean-Genaz, Christine
ED  - Schaa, Volker R.W.
TI  - Development of a Virtual Diagnostic for Estimating Key Beam Descriptors
J2  - Proc. of IPAC2022, Bangkok, Thailand, 12-17 June 2022
CY  - Bangkok, Thailand
T2  - International Particle Accelerator Conference
T3  - 13
LA  - english
AB  - Real-time beam descriptive data such as emittance, envelope and loss, are central to accelerator operations, including online diagnostics, maintenance and beam quality control. However, these cannot always be obtained without disrupting user runs. Physics-based simulations, such as particle tracking codes, can be leveraged to provide estimates of these beam descriptors. However, such simulation-based methods are computationally intensive requiring access to high performance computing facilities, and hence, they are often non-realistic for real-time purposes. The proposed work explores the feasibility of using machine learning to replace these simulations with fast-executing inference models based on surrogate modelling. The approach is intended to provide the operators with estimates of key beam properties in real time. Bayesian optimisation is used to generate a synthetic dataset to ensure the input space is efficiently sampled and representative of operating conditions. This is used to train a surrogate model to predict beam envelope, emittance and loss. The methodology is applied to the ISIS MEBT as a case study to evaluate the performance of the surrogate model.
PB  - JACoW Publishing
CP  - Geneva, Switzerland
SP  - 969
EP  - 972
KW  - simulation
KW  - diagnostics
KW  - MEBT
KW  - real-time
KW  - controls
DA  - 2022/07
PY  - 2022
SN  - 2673-5490
SN  - 978-3-95450-227-1
DO  - doi:10.18429/JACoW-IPAC2022-TUPOST048
UR  - https://jacow.org/ipac2022/papers/tupost048.pdf
ER  -