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RIS citation export for TUPAB216: Modeling Particle Stability Plots for Accelerator Optimization Using Adaptive Sampling

TY  - CONF
AU  - Schenk, M.
AU  - Coyle, L.
AU  - Giovannozzi, M.
AU  - Krymova, E.
AU  - Mereghetti, A.
AU  - Obozinski, G.
AU  - Pieloni, T.
ED  - Liu, Lin
ED  - Byrd, John M.
ED  - Neuenschwander, Regis T.
ED  - Picoreti, Renan
ED  - Schaa, Volker R. W.
TI  - Modeling Particle Stability Plots for Accelerator Optimization Using Adaptive Sampling
J2  - Proc. of IPAC2021, Campinas, SP, Brazil, 24-28 May 2021
CY  - Campinas, SP, Brazil
T2  - International Particle Accelerator Conference
T3  - 12
LA  - english
AB  - One key aspect of accelerator optimization is to maximize the dynamic aperture (DA) of a ring. Given the number of adjustable parameters and the compute-intensity of DA simulations, this task can benefit significantly from efficient search algorithms of the available parameter space. We propose to gradually train and improve a surrogate model of the DA from SixTrack simulations while exploring the parameter space with adaptive sampling methods. Here we report on a first model of the particle stability plots using convolutional generative adversarial networks (GAN) trained on a subset of SixTrack numerical simulations for different ring configurations of the Large Hadron Collider at CERN.
PB  - JACoW Publishing
CP  - Geneva, Switzerland
SP  - 1923
EP  - 1926
KW  - network
KW  - simulation
KW  - collider
KW  - resonance
KW  - dynamic-aperture
DA  - 2021/08
PY  - 2021
SN  - 2673-5490
SN  - 978-3-95450-214-1
DO  - doi:10.18429/JACoW-IPAC2021-TUPAB216
UR  - https://jacow.org/ipac2021/papers/tupab216.pdf
ER  -