BEM-Based Magnetic Field Reconstruction by Ensemble Kálmán Filtering

• DOI: 10.1515/cmam-2022-0121
• Publication Date: 2022-12-14T11:37:38Z
• Authors: Melvin Liebsch; Stephan Russenschuck; Stefan Kurz
• Keywords: bayesian inference; mittaus; bayesilainen menetelmä; particle accelerator magnets; magneettikentät; 01 natural sciences; mittauslaitteet; boundary element methods; magnetic measurements; fysiikka; 0101 mathematics; data assimilation

AbstractMagnetic fields generated by normal or superconducting electromagnets are used to guide and focus particle beams in storage rings, synchrotron light sources, mass spectrometers, and beamlines for radiotherapy. The accurate determination of the magnetic field by measurement is critical for the prediction of the particle beam trajectory and hence the design of the accelerator complex. In this context, state-of-the-art numerical field computation makes use of boundary-element methods (BEM) to express the magnetic field. This enables the accurate computation of higher-order partial derivatives and local expansions of magnetic potentials used in efficient numerical codes for particle tracking. In this paper, we present an approach to infer the boundary data of an indirect BEM formulation from magnetic field measurements by ensemble Kálmán filtering. In this way, measurement uncertainties can be propagated to the boundary data, magnetic field and potentials, and to the beam related quantities derived from particle tracking. We provide results obtained from real measurement data of a curved dipole magnet using a Hall probe mapper system.