Optimizing the lattice design for a diffraction-limited storage ring with a rational combination of particle swarm and genetic algorithms

TL;DR

This paper demonstrates that combining particle swarm and genetic algorithms effectively optimizes the lattice design of a diffraction-limited storage ring, achieving ultralow emittance and good nonlinear performance.

Contribution

It introduces a hybrid optimization approach that outperforms individual algorithms in designing compact multi-bend achromats for storage rings.

Findings

Achieved a natural emittance of about 50 pm.rad for HEPS.

Ensured sufficient ring acceptance for beam accumulation.

Hybrid optimization is more effective than single algorithms.

Abstract

In the design of a diffraction-limited storage ring (DLSR) consisting of compact multi-bend achromats (MBAs), it is challenging to simultaneously achieve an ultralow emittance and a satisfactory nonlinear performance, due to extremely large nonlinearities and limited tuning ranges of the element parameters. Nevertheless, taking the High Energy Photon Source (HEPS) as an example, we demonstrate that the potential of a DLSR design can be explored with a successive and iterative implementation of the particle swarm optimization (PSO) and multi-objective genetic algorithm (MOGA). It turns out that with a hybrid MBA lattice, it is feasible for the HEPS to attain a natural emittance of about 50 pm.rad, and meanwhile, realize a sufficient ring acceptance for beam accumulation with an on-axis longitudinal injection scheme. Particularly, this study indicates that a rational combination of the PSO and MOGA is more effective than either of them alone in approaching the true global optima, for an explorative multi-objective problem with many optimizing variables and local optima.