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RIS citation export for MOPOTK056: Data-Driven Chaos Indicator for Nonlinear Dynamics and Applications on Storage Ring Lattice Design

TY  - CONF
AU  - Li, Y.
AU  - Jiao, Y.
AU  - Liu, A.
AU  - Rainer, R.S.
AU  - Wan, 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  - Data-Driven Chaos Indicator for Nonlinear Dynamics and Applications on Storage Ring Lattice Design
J2  - Proc. of IPAC2022, Bangkok, Thailand, 12-17 June 2022
CY  - Bangkok, Thailand
T2  - International Particle Accelerator Conference
T3  - 13
LA  - english
AB  - A data-driven chaos indicator concept is introduced to characterize the degree of chaos for nonlinear dynamical systems. The indicator is represented by the prediction accuracy of surrogate models established purely from data. It provides a metric for the predictability of nonlinear motions in a given system. When using the indicator to implement a tune-scan for a quadratic Henon map, the main resonances and their asymmetric stop-band widths can be identified. When applied to particle transportation in a storage ring, as particle motion becomes more chaotic, its surrogate model prediction accuracy decreases correspondingly. Therefore, the prediction accuracy, acting as a chaos indicator, can be used directly as the objective for nonlinear beam dynamics optimization. This method provides a different perspective on nonlinear beam dynamics and an efficient method for nonlinear lattice optimization. Applications in dynamic aperture optimization are demonstrated as real world examples.
PB  - JACoW Publishing
CP  - Geneva, Switzerland
SP  - 596
EP  - 599
KW  - resonance
KW  - dynamic-aperture
KW  - storage-ring
KW  - lattice
KW  - linear-dynamics
DA  - 2022/07
PY  - 2022
SN  - 2673-5490
SN  - 978-3-95450-227-1
DO  - doi:10.18429/JACoW-IPAC2022-MOPOTK056
UR  - https://jacow.org/ipac2022/papers/mopotk056.pdf
ER  -