Speaker
Yongjun Li
(Brookhaven National Laboratory)
Description
We present a method to construct high-order polynomial approximate invariants (AI) for non-integrable Hamiltonian dynamical systems, and apply it to a modern ring-based particle accelerator. Taking advantage of a special property of one-turn transformation maps in the form of a square matrix, AIs can be constructed order-by-order iteratively. Evaluating AI with simulation data, we observe that AI's fluctuation is actually a measure of chaos. Through minimizing the fluctuations, the stable region of long-term motions, i.e., the dynamic aperture of the accelerator, could be enlarged.
Funding Agency
Supported by the U.S. DoE under Contract No. DE-SC0012704, FWP 2025-BNL-PS040-Funding, and HEP award DE-SC0019403.
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Author
Yongjun Li
(Brookhaven National Laboratory)
Co-authors
Derong Xu
(Brookhaven National Laboratory)
Yue Hao
(Facility for Rare Isotope Beams)