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RIS citation export for WEZAS0106: Methods and Experiences of Automated Tuning of Accelerators

TY  - CONF
AU  - Huang, X.
ED  - Biagini, Maria Enrica
ED  - Chrin, Jan
ED  - Giabbai, Manuela
ED  - Iungo, Massimiliano
ED  - Schaa, Volker R.W.
TI  - Methods and Experiences of Automated Tuning of Accelerators
J2  - Proc. of eeFACT2022, Frascati, Italy, 12-16 September 2022
CY  - Frascati, Italy
T2  - ICFA Advanced Beam Dynamics Workshop on High Luminosity Circular e+e- Colliders
T3  - 65
LA  - english
AB  - Automated tuning, or beam-based optimization, is a general approach to improve accelerator performances. The approach is different from the other common approach of beam-based correction. The differences between these two approaches and the advantages of the optimization approach are discussed. Two online optimization methods, the robust conjugate direction search (RCDS) and the multi-generation Gaussian process optimizer (MG-GPO), are described. Experiences of apply the methods to storage ring nonlinear dynamics optimization at SPEAR3 and APS storage rings, as well as application to other machines, are presented.
PB  - JACoW Publishing
CP  - Geneva, Switzerland
SP  - 183
EP  - 187
KW  - storage-ring
KW  - target
KW  - emittance
KW  - linac
KW  - controls
DA  - 2022/02
PY  - 2022
SN  - 2673-7027
SN  - 978-3-95450-236-3
DO  - doi:10.18429/JACoW-eeFACT2022-WEZAS0106
UR  - https://jacow.org/eefact2022/papers/wezas0106.pdf
ER  -