论文标题
使用Corryvreckan框架对测试梁数据的有效分析
Efficient Analysis of Test-beam Data with the Corryvreckan Framework
论文作者
论文摘要
在下一代的顶点和高能物理实验的跟踪探测器上提出了严格的要求，以达到可预见的物理目标。针对每种用例的特定需求的各种硅像素传感器在实验室和测试束测量运动中都得到了开发和测试。 Corryvreckan是基于重建链的模块化概念的灵活，快速和轻巧的测试束数据重建和分析框架。它旨在满足在复杂的数据制作环境中结合探测器与不同读数方案的复杂数据构建的要求。它的模块化体系结构将框架核心与重建，分析和探测器特定算法的实现分开。在本文中，提供了软件框架以及重建和分析链的简要概述。使用框架的离线事件构建功能以及改进的事件构建方案，可以更有效地使用MIMOSA26传感器的枢轴像素信息，从而使这是数据集的示例分析以及改进的事件构建方案的示例分析。
Stringent requirements are posed on the the next generations of vertex and tracking detectors for high-energy physics experiments to reach the foreseen physics goals. A large variety of silicon pixel sensors targeting the specific needs of each use case are developed and tested both in laboratory and test-beam measurement campaigns. Corryvreckan is a flexible, fast and lightweight test-beam data reconstruction and analysis framework based on a modular concept of the reconstruction chain. It is designed to fulfil the requirements for offline event building in complex data-taking environments combining detectors with different readout schemes. Its modular architecture separates the framework core from the implementation of reconstruction, analysis and detector specific algorithms. In this paper, a brief overview of the software framework and the reconstruction and analysis chain is provided. This is complemented by an example analysis of a data set using the offline event building capabilities of the framework and an improved event building scheme allowing for a more efficient usage of test-beam data exploiting the pivot pixel information of the Mimosa26 sensors.
