Local field reconstruction from rotating coil measurements in particle accelerator magnets

TL;DR

This paper presents a Bayesian inversion method for reconstructing 3D magnetic fields in particle accelerator magnets from distributed measurements, enabling uncertainty quantification and regularization.

Contribution

It introduces a novel local discretization of the Laplace equation combined with Bayesian inversion for magnetic field reconstruction from rotating coil data.

Findings

Effective field reconstruction from rotating coil measurements.

Quantification of uncertainty in the reconstructed fields.

Flexible approach extendable to other measurement techniques.

Abstract

In this paper a general approach to reconstruct three dimensional field solutions in particle accelerator magnets from distributed magnetic measurements is presented. To exploit the locality of the measurement operation a special discretization of the Laplace equation is used. Extracting the coefficients of the field representations yields an inverse problem which is solved by Bayesian inversion. This allows not only to pave the way for uncertainty quantification, but also to derive a suitable regularization. The approach is applied to rotating coil measurements and can be extended to any other measurement procedure.