Optimization Algorithms for Inverse Problems in the Simulation of Accelerator Magnets

Bachelor thesis

Particle accelerators rely on electromagnets for deflecting and focusing the particle beams. The simulation of the magnetic field, generated by normal conducting accelerator magnets depends among others on material and geometry parameters of the iron yoke. While the forward simulation of the magnetic field given the parameters is well understood, the inverse problem, that means the recalculation of physical meaningful parameters given field measurements, remains challenging. Nevertheless, solving the inverse problem is interesting for reverse engineering as well as for updating parameters in order to improve the simulations.

TU Darmstadt, together with the European Organization for Nuclear Research (CERN) formulated optimization problems that correspond to these inverse prob- lems. The investigation of optimization algorithms suitable for these problems is the goal of this thesis.