A physics-based muon trajectory estimation algorithm for muon tomographic applications

Recently, the use of cosmic ray muons in critical national security applications, e.g., nuclear nonproliferation and safeguard verification, has gained attention due to unique muon properties such as high energy and low attenuation even in very dense materials. Applications where muon tomography has been demonstrated include cargo screening for detection of special nuclear materials smuggling, source localization, material identification, determination of nuclear fuel debris location in nuclear reactors, etc. However, muon image reconstruction techniques are still limited in resolution mostly due to multiple Coulomb scattering (MCS) within the target object. Improving and expanding muon tomography would require development of efficient & flexible physics-based algorithms to model the MCS process and accurately estimate the most probable trajectory of a muon as it traverses the target object. In the present work, we will present and discuss the use of a new algorithmic approach based on Bayesian probability theory and a Gaussian approximation of MCS for estimation of the most likely path of a cosmic ray muon traversing uniform or nonuniform media. Using GEANT4 simulations in a simple homogeneous 10 cm cubes of low, medium and high Z materials as a proof of concept, we show that better resolution and reduced measurement time can be achieved for cosmic ray muons of various energies, zenith angles, and flux.