Configurable calorimeter simulation for AI applications

Abstract A configurable calorimeter simulation for AI (CoCoA) applications is presented, based on the GEANT4 toolkit and interfaced with PYTHIA event generator. This open-source project aimed to support development of machine learning algorithms in high energy physics that rely realistic particle shower descriptions, such as reconstruction, fast simulation, low-level analysis. Specifications granularity material its nearly hermetic geometry are user-configurable. The tool supplemented simple processing including topological clustering, jet algorithms, a nearest-neighbors graph construction. Formatting also provided visualise events using Phoenix display software.