hep_tables：HEP的异构阵列编程
hep_tables: Heterogeneous Array Programming for HEP
摘要：
数组操作是表达常见过滤和简单聚合操作的最简洁方式之一，这是粒子物理分析第一步的标志：选择，过滤，基本向量操作和填充直方图。大型强子对撞机（HL-LHC）的高亮度运行计划于2026年开始，将要求物理学家定期浏览大小超过PB的数据集，并反复运行100 TB的数据集-太大而无法容纳在内存中。声明式编程技术是一种将物理学家的意图与查找数据、处理数据以及使用分布式计算来有效地处理数据的机制分离的方法，这是及时提取所需的绘图或数据所必需的。本文描述了一个原型库，它提供了一个框架，不同的子系统合作，在生产这些数据，使用数组编程声明式接口。这个原型有一个ServiceX数据交付子系统和一个笨拙的数组子系统，它们协作生成请求的数据。ServiceX系统针对ATLAS xAOD数据运行。
英文摘要：
Array operations are one of the most concise ways of expressing common filtering and simple aggregation operations that is the hallmark of the first step of a particle physics analysis: selection, filtering, basic vector operations, and filling histograms. The High Luminosity run of the Large Hadron Collider (HL-LHC), scheduled to start in 2026, will require physicists to regularly skim datasets that are over a PB in size, and repeatedly run over datasets that are 100's of TB's - too big to fit in memory. Declarative programming techniques are a way of separating the intent of the physicist from the mechanics of finding the data, processing the data, and using distributed computing to process it efficiently that is required to extract the plot or data desired in a timely fashion. This paper describes a prototype library that provides a framework for different sub-systems to cooperate in producing this data, using an array-programming declarative interface. This prototype has a ServiceX data-delivery sub-system and an awkward array sub-system cooperating to generate requested data. The ServiceX system runs against ATLAS xAOD data.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
