Speaker
Ji Qiang
(Lawrence Berkeley National Laboratory)
Description
High energy colliders provide a critical tool in nuclear physics study by probing the fundamental structure and dynamics of matter. Optimizing the collider’s machine parameters is both computationally and experimentally expensive. A fast and robust optimization framework that includes both beam-beam and the detailed machine lattice will be crucial to attaining the best performance of the collider. In this paper, we report on the development of an integrated framework that includes an advanced Bayesian optimization software GPTune, a self-consistent beam-beam simulation code BeamBeam3D, and the detailed lattice model from MAD-X. Some application results to the RHIC facility optimization will also be presented.
| Region represented | North America |
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Primary author
Ji Qiang
(Lawrence Berkeley National Laboratory)
Co-authors
Yi-Kai Kan
(Lawrence Berkeley National Laboratory)
Xiaoye Li
(Lawrence Berkeley National Laboratory)
Yang Liu
(Lawrence Berkeley National Laboratory)
Xiaofeng Gu
(Brookhaven National Laboratory)
William Fung
(Facility for Rare Isotope Beams)
Yue Hao
(Facility for Rare Isotope Beams)
