将大型强子对撞机开放数据转为计算机科学常用格式，促跨学科合作。
Introduction to the Usage of Open Data from the Large Hadron Collider for Computer Scientists in the Context of Machine Learning
- 将物理领域ROOT格式数据转化为计算机常用pandas DataFrame
- 提供数据内容说明与解读指南，降低跨领域使用门槛
- 适合想参与粒子物理机器学习研究的计算机科学家
近年来深度学习技术迅速发展，深刻影响了实验粒子物理等多个科学领域。要有效利用计算机科学最新成果推动粒子物理研究，计算机科学家与物理学家之间的紧密协作至关重要。由于所有机器学习方法都依赖于大规模数据的可获取性与可理解性，清晰的数据描述和通用数据格式是成功合作的前提。本研究将大型强子对撞机（LHC）公开数据从高能物理领域常用的ROOT格式转换为计算机科学界广泛使用的pandas DataFrames格式，并简要介绍数据内容及其解读方式。本文旨在为未来计算机科学家与物理学家之间的跨学科合作提供起点，促进更紧密的联系与高效的知识交流。
原文摘要 · Abstract (English)
Deep learning techniques have evolved rapidly in recent years, significantly impacting various scientific fields, including experimental particle physics. To effectively leverage the latest developments in computer science for particle physics, a strengthened collaboration between computer scientists and physicists is essential. As all machine learning techniques depend on the availability and comprehensibility of extensive data, clear data descriptions and commonly used data formats are prerequisites for successful collaboration. In this study, we converted open data from the Large Hadron Collider, recorded in the ROOT data format commonly used in high-energy physics, to pandas DataFrames, a well-known format in computer science. Additionally, we provide a brief introduction to the data's content and interpretation. This paper aims to serve as a starting point for future interdisciplinary collaborations between computer scientists and physicists, fostering closer ties and facilitating efficient knowledge exchange.
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