Electron Storage Ring Lattice Design And Optimization Using Particle Swarm Optimization Algorithm

For a synchrotron radiation light source, its main performance is directly determined by the parameters in electron storage ring lattice design and optimization. The work of the electron storage ring lattice design and optimization can be divided into two parts:linear lattice design and nonlinear lattice optimization. For synchrotron radiation light sources, the main objectives in the linear lattice design are to obtain electron beam natural emittance as low as possible and satisfactory linear optics functions mainly for increasing synchrotron radiation brightness. The main objectives in the nonlinear lattice optimization are to obtain large enough dynamic aperture (DA) and acceptable momentum aperture for increasing beam injection efficiency and beam lifetime. In this dissertation, the particle swarm optimization (PSO) algorithm, widely used for quickly searching for global optimal solutions, is applied to the electron storage ring lattice design and optimization, and some related methods are proposed.First, the global scan method is applied to study the storage ring of the upgraded Hefei Light Source (HLS) named HLS-II, and the database of its linear lattice solutions and parameters is obtained, which is helpful for lattice study. Several candidate lattice solutions are selected from the database, which have both better linear parameters and better nonlinear performance. Then the PSO algorithm is applied to study the linear lattice of the HLS-Ⅱ storage ring. The comparison of the results obtained by the PSO algorithm and the global scan method, respectively, shows that the PSO algorithm can be used for searching for global optimal information highly efficiently for linear lattice design. The PSO algorithm is naturally applied to study the case of the superperiod lattice for the HLS-Ⅱ storage ring, in which there are more variables, and the results show that the flexibility of the HLS-Ⅱ storage ring lattice is limited. Then the PSO algorithm is also applied to nonlinear lattice optimization. To optimize the DA, a quantitative criterion of DA is proposed for the comparison of different DAs. Based on the characteristic of the change of DA in particle tracing, a strategy named more turns and less turns is proposed for reducing the amount of computation. To more easily search for DAs of better quality, a method is proposed of setting up one aperture specially used for particle tracking in nonlinear lattice optimization, and the determination of the dimensions of the aperture is demonstrated. In addition, a quantitative criterion of momentum aperture is proposed, and the PSO algorithm is applied to simultaneously optimize DA and momentum aperture. As examples of application, the nonlinear lattices of the storage rings of HLS-II and Shanghai Synchrotron Radiation Facility are optimized, and the optimization results show that some lattice solutions with better nonlinear performance can be found more quickly using the PSO algorithm combined with the proposed strategy and method.It is pointed out that there are some deficiencies when directly applying artificial intelligence (AI) algorithms to the linear lattice design. This is because it is very difficult to give a complete set of constraint conditions and objective functions for the linear lattice design. To solve this problem, a method called locating method is proposed, which uses the multi-objective AI algorithms to quickly search for all regions of the lattice solutions satisfying the constraint conditions, thus providing a variety of lattice solutions for storage ring lattice design and optimization. The reason that there are some deficiencies in the step-by-step chromaticity compensation method is explained, and it is pointed out that the deficiencies can be cured by introducing AI algorithms. Thus, a new method used for nonlinear lattice optimization, called chromatic sextupole pair optimization method, is proposed, which overcomes the deficiencies in the step-by-step chromaticity compensation method and thus can obtain better optimization results. Additionally, it is pointed out that the formula of sextupole compensating chromaticity connects the two methods of optimizing chromatic sextupole pair related quantities and chromatic sextupole strengths, respectively, using AI algorithms, and the equivalence of the two AI algorithm based numerical methods is demonstrated.