Nonlinear dynamics optimization with particle swarm and genetic algorithms for SPEAR3 emittance upgrade

Journal Article · Mon Sep 01 00:00:00 EDT 2014 · Nuclear Instruments and Methods in Physics Research. Section A, Accelerators, Spectrometers, Detectors and Associated Equipment

DOI:https://doi.org/10.1016/j.nima.2014.04.078· OSTI ID:1126910

Huang, Xiaobiao; Safranek, James

Nonlinear dynamics optimization is carried out for a low emittance upgrade lattice of SPEAR3 in order to improve its dynamic aperture and Touschek lifetime. Two multi-objective optimization algorithms, a genetic algorithm and a particle swarm algorithm, are used for this study. The performance of the two algorithms are compared. The result shows that the particle swarm algorithm converges significantly faster to similar or better solutions than the genetic algorithm and it does not require seeding of good solutions in the initial population. These advantages of the particle swarm algorithm may make it more suitable for many accelerator optimization applications.

• Research Organization: SLAC National Accelerator Lab., Menlo Park, CA (United States)
• Sponsoring Organization: USDOE Office of Science (SC), Basic Energy Sciences (BES)
• DOE Contract Number: AC02-76SF00515
• OSTI ID: 1126910
• Report Number(s): SLAC-PUB-15939
• Journal Information: Nuclear Instruments and Methods in Physics Research. Section A, Accelerators, Spectrometers, Detectors and Associated Equipment, Vol. 757, Issue C; ISSN 0168-9002
• Publisher: Elsevier
• Country of Publication: United States
• Language: English

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