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RIS citation export for MOPV048: Fast Multipole Method (FMM)-Based Particle Accelerator Simulations in the Context of Tune Depression Studies

AU  - Langston, M.H.
AU  - Lethin, R.
AU  - Letourneau, P.D.
AU  - Wei, J.
ED  - Furukawa, Kazuro
ED  - Yan, Yingbing
ED  - Leng, Yongbin
ED  - Chen, Zhichu
ED  - Schaa, Volker R.W.
TI  - Fast Multipole Method (FMM)-Based Particle Accelerator Simulations in the Context of Tune Depression Studies
J2  - Proc. of ICALEPCS2021, Shanghai, China, 14-22 October 2021
CY  - Shanghai, China
T2  - International Conference on Accelerator and Large Experimental Physics Control Systems
T3  - 18
LA  - english
AB  - As part of the MACH-B (Multipole Accelerator Codes for Hadron Beams) project, we have developed a Fast Multipole Method (FMM**)-based tool for higher fidelity modeling of particle accelerators for high-energy physics within Fermilab’s Synergia* simulation package. We present results from our implementations with a focus on studying the difference between tune depression estimates obtained using PIC codes for computing the particle interactions and those obtained using FMM-based algorithms integrated within Synergia. In simulating the self-interactions and macroparticle actions necessary for accurate simulations, we present a newly-developed kernel inside of a kernel-independent FMM in which near-field kernels are modified to incorporate smoothing while still maintaining consistency at the boundary of the far-field regime. Each simulation relies on Synergia with one major difference: the way in which particles interactions were computed. Specifically, following our integration of the FMM into Synergia, changes between PIC-based computations and FMM-based computations are made by changing only the method for near-field (and self) particle interactions.
PB  - JACoW Publishing
CP  - Geneva, Switzerland
SP  - 271
EP  - 276
KW  - simulation
KW  - multipole
KW  - space-charge
KW  - hadron
DA  - 2022/03
PY  - 2022
SN  - 2226-0358
SN  - 978-3-95450-221-9
DO  - doi:10.18429/JACoW-ICALEPCS2021-MOPV048
UR  - https://jacow.org/icalepcs2021/papers/mopv048.pdf
ER  -