Multi-objective optimization of the dynamic aperture for the Swiss Light Source upgrade

TL;DR

This paper presents a multi-objective genetic algorithm approach combined with tracking simulations to optimize the dynamic aperture of the Swiss Light Source upgrade, aiming to enhance beam injection and lifetime.

Contribution

It introduces a novel optimization framework integrating parallel genetic algorithms with constraint handling for lattice design in synchrotron upgrades.

Findings

Optimized magnet configurations for two lattice phases.

Significant improvement over manual optimization in phase-1 lattice.

Enhanced dynamic aperture and beam lifetime prospects.

Abstract

The upgrade of the Swiss Light Source, called SLS 2.0, is scheduled for 2023-24. The current storage ring will be replaced by one based on multi-bend achromats, allowing for about 30 times higher brightness. Due to the stronger focusing and the required chromatic compensation, finding a reasonably large dynamic aperture (DA) for injection, as well as an energy acceptance for a sufficient beam lifetime, is challenging. In order to maximize the DA and prolong the beam lifetime, we combine the well-known tracking code tracy with a massively parallel implementation of a multi-objective genetic algorithm (MOGA), and further extend this with constraint-handling methods. We then optimize the magnet configuration for two lattices: the lattice that will be used in the commissioning phase (phase-1), and the lattice that will be used afterwards, in the completion phase (phase-2). Finally, we show and further analyze the chosen magnet configurations and in the case of the phase-1 lattice compare it to a pre-existing, manually optimized solution.