A configurable calorimeter simulation for AI (COCOA) applications is presented, based on the Geant4 toolkit and interfaced with the Pythia event generator. This open-source project is aimed to support the development of machine learning algorithms in high energy physics that rely on realistic particle shower descriptions, such as reconstruction, fast simulation, and low-level analysis. Specifications such as the granularity and material of its nearly hermetic geometry are user-configurable. The tool is supplemented with simple event processing including topological clustering, jet algorithms, and a nearest-neighbors graph construction. Formatting is also provided to visualise events using the Phoenix event display software.

翻译：本文介绍了一种基于Geant4工具包并与Pythia事件生成器接口的可配置量热器模拟（COCOA）系统，专门用于AI应用。该开源项目旨在支持高能物理中依赖真实粒子簇射描述的机器学习算法开发，如重建、快速模拟和底层分析。其近密闭几何结构的粒度和材质等规格参数均可由用户配置。该工具还辅以简单的事件处理功能，包括拓扑聚类、喷注算法和最近邻图构建。此外，提供了利用Phoenix事件显示软件进行事件可视化的格式化输出功能。