Suppr超能文献

大型强子对撞机底夸克实验的清理与分析工作。

The LHCb Sprucing and Analysis Productions.

作者信息

Abdelmotteleb Ahmed, Bertolin Alessandro, Burr Chris, Couturier Ben, Eckstein Ellinor, Fazzini Davide, Grieser Nathan, Haen Christophe, O'Neil Ryunosuke, Rodrigues Eduardo, Skidmore Nicole, Smith Mark, Wiederhold Aidan R, Zhang Shunan

机构信息

Department of Physics, University of Warwick, Coventry, UK.

INFN Sezione di Padova, Padova, Italy.

出版信息

Comput Softw Big Sci. 2025;9(1):15. doi: 10.1007/s41781-025-00144-5. Epub 2025 Aug 4.

Abstract

The LHCb detector underwent a comprehensive upgrade in preparation for the third data-taking run of the Large Hadron Collider (LHC), known as LHCb Upgrade I. With its increased data rate, Run 3 introduced considerable challenges in both data acquisition (online) and data processing and analysis (offline). The offline processing and analysis model was upgraded to handle the factor 30 increase in data volume and the associated demands of ever-growing datasets for analysis, led by the LHCb Data Processing and Analysis (DPA) project. This paper documents the LHCb "Sprucing" - the centralised offline data processing and selections - and "Analysis Productions" - the centralised and highly automated declarative nTuple production system. The DaVinci application used by analysis productions for tupling spruced data is described as well as the apd and lbconda tools for data retrieval and analysis environment configuration. These tools allow for greatly improved analyst workflows and analysis preservation. Finally, the approach to data processing and analysis in the High-Luminosity Large Hadron Collider (HL-LHC) era - LHCb Upgrade II - is discussed.

摘要

大型强子对撞机底夸克实验(LHCb)探测器进行了全面升级,为大型强子对撞机(LHC)的第三次数据采集运行(即LHCb升级I)做准备。随着数据率的提高,第三次运行在数据采集(在线)以及数据处理与分析(离线)方面都带来了巨大挑战。由LHCb数据处理与分析(DPA)项目牵头,离线处理与分析模型进行了升级,以应对数据量增长30倍的情况以及不断增长的数据集分析相关需求。本文记录了LHCb的“整理”(集中式离线数据处理与筛选)和“分析产物”(集中式且高度自动化的声明式元组生成系统)。描述了分析产物用于对整理后的数据进行元组化的DaVinci应用程序,以及用于数据检索和分析环境配置的apd和lbconda工具。这些工具极大地改进了分析师的工作流程和分析保存。最后,讨论了高亮度大型强子对撞机(HL-LHC)时代(LHCb升级II)的数据处理与分析方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/514b/12321665/8bbe81fff3a1/41781_2025_144_Fig1_HTML.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验