发表机构
University of Milan Bicocca; University of Wisconsin-Madison; Technical University of Munich; University of Liverpool; INFN Milan Bicocca（米兰比可卡大学; 威斯康星大学麦迪逊分校; 慕尼黑工业大学; 利物浦大学; 意大利国家核物理研究所米兰比可卡分部）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
pylhe是读写高能物理标准LHE事例数据的轻量级纯Python库，支持多种格式，可高效处理大事例样本，还能与现代分析及机器学习工作流集成。
AI 中文摘要
Les Houches事件文件是高能物理中蒙特卡洛事例产生器的标准格式。pylhe是一个用于读写LHE事例数据的轻量级纯Python库，支持.lhe和压缩的this http URL文件，实现了广泛使用的LHE 3.0特性，包括多事例权重和产生器元数据，还支持基于HDF5的最新LHEH5格式。该库通过Python式迭代器和共享数据结构暴露事例，无需将整个文件加载到内存即可实现对大事例样本的内存高效处理，还支持格式转换，并可与现代分析工作流集成，包括使用Awkward Array的列分析及下游机器学习应用。
英文摘要
Les Houches Event files are a standard format for Monte Carlo event generators in high-energy physics. pylhe is a lightweight pure-Python library for reading and writing LHE event data. It supports .lhe and compressed .lhe.gz files, implements the widely used LHE 3.0 features including multiple event weights and generator metadata, and also supports the recent HDF5-based LHEH5 format. By exposing events through a pythonic iterator and shared data structures, pylhe enables memory-efficient processing of large event samples without loading entire files into memory. The library also supports format conversion and integration with modern analysis workflows, including columnar analysis with Awkward Array and downstream machine-learning applications.
Comments4 pages
Journal refJournal of Open Source Software, 11(126), 11128 (2026)
