Selection and processing of calibration samples to measure the particle identification performance of the LHCb experiment in Run 2

TL;DR

This paper discusses the development of a novel calibration sample selection and processing strategy for measuring particle identification performance in the LHCb experiment during Run 2, leveraging online and offline reconstruction techniques.

Contribution

It introduces a new calibration sample selection and processing method integrated with the LHCb trigger system, enhancing PID performance measurement accuracy.

Findings

Effective calibration sample processing scheme implemented

Improved PID performance measurement across decay channels

Calibration samples used for data quality monitoring

Abstract

Since 2015, with the restart of the LHC for its second run of data taking, the LHCb experiment has been empowered with a dedicated computing model to select and analyse calibration samples to measure the performance of the particle identification (PID) detectors and algorithms. The novel technique was developed within the framework of the innovative trigger model of the LHCb experiment, which relies on online event reconstruction for most of the datasets, reserving offline reconstruction to special physics cases. The strategy to select and process the calibration samples, which includes a dedicated data-processing scheme combining online and offline reconstruction, is discussed. The use of the calibration samples to measure the detector PID performance, and the efficiency of PID requirements across a large range of decay channels, is described. Applications of the calibration samples in data-quality monitoring and validation procedures are also detailed.