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RIS citation export for SUPAF12: Surrogate Models for Beam Dynamics in Charged Particle Accelerators

AU  - Edelen, A.L.
AU  - Acharya, D.
AU  - Adelmann, A.
AU  - Frey, M.
AU  - Neveu, N.R.
ED  - Schaa, Volker RW
ED  - Makino, Kyoko
ED  - Snopok, Pavel
ED  - Berz, Martin
TI  - Surrogate Models for Beam Dynamics in Charged Particle Accelerators
J2  - Proc. of ICAP2018, Key West, FL, USA, 20-24 October 2018
CY  - Key West, FL, USA
T2  - International Computational Accelerator Physics Conference
T3  - 13
LA  - english
AB  - High-fidelity, PIC-based beam dynamics simulations are time and resource intensive. Consider a high dimensional search space, that is far too large to probe with such a high resolution simulation model. We demonstrate that a coarse sampling of the search space can produce surrogate models, which are accurate and fast to evaluate. In constructing the surrogate models, we use artificial neural networks [1] and multivariate polynomial chaos expansion [2]. The performance of both methods are demonstrated in a comparison with high-fidelity simulations, using OPAL, of the Argonne Wakefield Accelerator [3]. We claim that such surrogate models are good candidates for accurate on-line modeling of large, complex accelerator systems. We also address how to estimate the accuracy of the surrogate model and how to refine the surrogate model under changing machine conditions. [1] A. L. Edelen et al., arXiv:1610.06151[physics.acc- ph] [2] A. Adelmann, arXiv:1509.08130v6[physics.acc- ph] [3] N. Neveu et al., 2017 J. Phys.: Conf. Ser. 874 012062
PB  - JACoW Publishing
CP  - Geneva, Switzerland
ER  -