Reconstruction of interactions in the ProtoDUNE-SP detector with Pandora

TL;DR

This paper discusses the use of Pandora software for reconstructing particle interactions in the ProtoDUNE-SP liquid argon detector, achieving over 80% efficiency in complex event scenarios with good agreement between simulation and real data.

Contribution

It presents tailored Pandora reconstruction algorithms for ProtoDUNE-SP and demonstrates high efficiency and accuracy in particle identification in a complex experimental environment.

Findings

Reconstruction and identification efficiency exceeds 80% for most particles.

Simulated efficiencies for 1 GeV/c pions and protons are 86.1% and 84.1%.

Measured efficiencies agree within 5% of simulation predictions.

Abstract

The Pandora Software Development Kit and algorithm libraries provide pattern-recognition logic essential to the reconstruction of particle interactions in liquid argon time projection chamber detectors. Pandora is the primary event reconstruction software used at ProtoDUNE-SP, a prototype for the Deep Underground Neutrino Experiment far detector. ProtoDUNE-SP, located at CERN, is exposed to a charged-particle test beam. This paper gives an overview of the Pandora reconstruction algorithms and how they have been tailored for use at ProtoDUNE-SP. In complex events with numerous cosmic-ray and beam background particles, the simulated reconstruction and identification efficiency for triggered test-beam particles is above 80% for the majority of particle type and beam momentum combinations. Specifically, simulated 1 GeV/$c$ charged pions and protons are correctly reconstructed and identified with efficiencies of 86.1$\pm0.6$% and 84.1$\pm0.6$%, respectively. The efficiencies measured for test-beam data are shown to be within 5% of those predicted by the simulation.