Design of an atmospheric muon tomographer for material identification based on CORSIKA+GEANT4 simulations

TL;DR

This paper presents the design and simulation of a portable muon tomography detector using CORSIKA and GEANT4, demonstrating its ability to differentiate materials like lead from aluminum within days.

Contribution

It introduces a novel, easy-to-construct muon detector design and evaluates its effectiveness for material identification through simulation-based methods.

Findings

Lead can be distinguished from other materials within days.

Absorption method outperforms scattering in material differentiation.

Differentiation time for lead vs. aluminum is approximately 5 to 10 days.

Abstract

In recent years, muon tomography has turned into a powerful and innovative technique for non-invasive imaging of large and small structures with applications in different areas like geology, archaeology, security, etc. We present the design and simulation of a transportable and easy to construct detector based on plastic scintillator and Silicon photomultipliers current technology. From a flux of cosmic rays reaching the atmosphere we simulated atmospheric muons at ground using CORSIKA. The detector and the object to analyze are simulated with GEANT4, where the previously obtained muon flux is transported. We use two methods for muon tomography to differentiate objects made of different materials: absorption and scattering. The statistical differences for several object sizes and materials are quantified. Using a threshold of 3 $\sigma$ in the first method, we conclude that materials made of lead can be differentiated from objects made of other materials. The observation time needed to differentiate an object made of lead from one of aluminum was 4.9 and 9.9 days using the first and second method, respectively. In general, the absorption method gives the best results.