  Muography is a non-invasive imaging technique that exploits cosmic-ray muons
to probe various targets by analyzing the absorption or scattering of muons.
The method is particularly useful for applications ranging from geophysical
exploration to security screening, including the identification of nuclear
materials. This study leverages both Monte Carlo simulations and the Point of
Closest Approach (PoCA) algorithm for image reconstruction to specifically
explore the distortions caused by magnetic fields in scattering muography
images. In the PoCA algorithm, it is assumed that all scattering of a muon
during its travel in material occurs at a single point, known as the PoCA
point. Each PoCA point is characterized by a scattering angle, whose
distribution provides insights into the density and elemental composition of
the target material. However, magnetic fields can influence muon trajectories
according to Lorentz law, affecting the estimated positions of the PoCA points
and the calculated scattering angles. This introduces challenges in
applications such as border security control systems. Moreover, the presence of
magnetic fields can lead to what we term "magnetic jamming", where the
resulting muography image is distorted or misleading. This effect further
complicates the accurate identification and interpretation of target materials.
Our findings underline the necessity to account for magnetic field distortions
when utilizing scattering muography in practical scenarios.
