Simulating event reconstruction of particles with initial energy of 60 GeV using calorimeters in GEANT4

Abstract

Energy deposition is one of the main parameters used in reconstructing particles that are observed from high-energy physics experiments. We demonstrate this technique using GEANT4, an open-source particle simulation toolkit. Using a two-arm spectrometer, we beamed particles with an initial energy of 60 GeV into a hadronic and an electromagnetic calorimeter, for 1000 times. We then used a decision tree classifier to create three models for (1) π⁰ − γ, (2) e - ē, and (3) p - p̄ classifications, and assess important calorimeter cells using Gini index. We were able to achieve R² ≥ 0.80 and f1-score ≥ 0.95 for all three models. Energy deposition distribution of important calorimeter cells suggest that they are consistent with their main decay modes and their established interactions with matter.