FunTuple: A new N-tuple component for offline data processing at the LHCb experiment

TL;DR

FunTuple is a new component for offline data processing in the LHCb experiment, enabling flexible computation and storage of observables to improve analysis consistency and efficiency for future collider runs.

Contribution

The paper introduces FunTuple, a novel, flexible component that enhances offline data processing by enabling customizable observable computation and ensuring consistency with trigger data.

Findings

Validated through comprehensive unit tests

Supports diverse observables for reconstructed and simulated events

Facilitates consistent offline analysis for future LHCb runs

Abstract

The offline software framework of the LHCb experiment has undergone a significant overhaul to tackle the data processing challenges that will arise in the upcoming Run 3 and Run 4 of the Large Hadron Collider. This paper introduces FunTuple, a novel component developed for offline data processing within the LHCb experiment. This component enables the computation and storage of a diverse range of observables for both reconstructed and simulated events by leveraging on the tools initially developed for the trigger system. This feature is crucial for ensuring consistency between trigger-computed and offline-analysed observables. The component and its tool suite offer users flexibility to customise stored observables, and its reliability is validated through a full-coverage set of rigorous unit tests. This paper comprehensively explores FunTuple's design, interface, interaction with other algorithms, and its role in facilitating offline data processing for the LHCb experiment for the next decade and beyond.