English

Quadrupole Magnet Design based on Genetic Multi-Objective Optimization

Accelerator Physics 2023-12-01 v2 Neural and Evolutionary Computing

Abstract

This work suggests to optimize the geometry of a quadrupole magnet by means of a genetic algorithm adapted to solve multi-objective optimization problems. To that end, a non-domination sorting genetic algorithm known as NSGA-III is used. The optimization objectives are chosen such that a high magnetic field quality in the aperture of the magnet is guaranteed, while simultaneously the magnet design remains cost-efficient. The field quality is computed using a magnetostatic finite element model of the quadrupole, the results of which are post-processed and integrated into the optimization algorithm. An extensive analysis of the optimization results is performed, including Pareto front movements and identification of best designs.

Keywords

Cite

@article{arxiv.2211.09580,
  title  = {Quadrupole Magnet Design based on Genetic Multi-Objective Optimization},
  author = {Eric Diehl and Moritz von Tresckow and Lou Scholtissek and Dimitrios Loukrezis and Nicolas Marsic and Wolfgang F. O. Müller and Herbert De Gersem},
  journal= {arXiv preprint arXiv:2211.09580},
  year   = {2023}
}

Comments

22 pages, 7 figures

R2 v1 2026-06-28T06:07:35.728Z