Efficient Analysis of Test-beam Data with the Corryvreckan Framework

TL;DR

Corryvreckan is a modular, efficient framework for test-beam data analysis in high-energy physics, enabling flexible offline event building and improved data utilization.

Contribution

The paper introduces Corryvreckan, a novel modular software framework designed for efficient, flexible, and complex test-beam data reconstruction and analysis in high-energy physics experiments.

Findings

Successful demonstration of offline event building capabilities

Implementation of an improved event building scheme

Enhanced efficiency in test-beam data analysis

Abstract

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.