Investigating the Magnetic Field outside small Accelerator Magnet Analogs via Experiment, Simulation, and Theory

TL;DR

This study explores the magnetic fields outside small-scale accelerator magnet analogs through theoretical modeling, experimental verification using smartphone sensors, and simulation with Magpylib, providing accessible insights into complex magnetic principles.

Contribution

It introduces a low-cost, multi-method approach combining theory, experiment, and simulation to understand accelerator magnet fields using simple magnetic analogs.

Findings

Magnetic field strength follows a $1/r^{l+2}$ power law for different multipole moments.

Experimental data using smartphone sensors confirms theoretical power-law dependence.

Simulations with Magpylib align well with theoretical and experimental results.

Abstract

Particle accelerators use powerful and complex magnetic fields to turn, shape, and eventually collide beams of near-light-speed particles, yet the fundamental magnetic principles behind the accelerator magnets can be understood by undergraduate students. In this paper we use small-scale accelerator magnet analogs in a multi-faceted, low-cost exploration of the magnetic field exterior to accelerator magnets. These fields are best understood using the multipole expansion of the field. If we assume that the magnetic field is created by ideal magnetic dipoles, we can derive a theoretical model that shows that each accelerator magnet configuration is dominated by a single multipole moment and obeys $B \propto 1/r^{l+2}$, where $l$ is the multipole order (with $l = 1, 2, 3, 4$ for the dipole, quadrupole, octopole, and hexadecapole moments, respectively). Using commercially available NdFeB magnets and the magnetic field sensor inside a smartphone, we experimentally verify the power-law dependence of the accelerator magnet configurations. Finally, we use the open-source Python library Magpylib to simulate the magnetic field of the permanent magnet configurations, showing good agreement between theory, experiment, and simulation.