A configurable calorimeter simulation for AI (COCOA) applications is presented, based on the \textsc{Geant4} toolkit and interfaced with the \textsc{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：本文提出了一种基于\textsc{Geant4}工具包并与\textsc{Pythia}事件生成器接口的面向AI（COCOA）应用的可配置量热器模拟。这一开源项目旨在支持高能物理领域中依赖真实粒子簇射描述的机器学习算法开发，例如重建、快速模拟及低层次分析。其近封闭几何结构的颗粒度和材质等规格可由用户配置。该工具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。同时，提供了利用Phoenix事件显示软件对事件进行可视化的格式化输出。