Repository logo
 

Calorimetric classification of track-like signatures in liquid argon TPCs using MicroBooNE data

Published version
Peer-reviewed

Change log

Authors

Abratenko, P 
An, R 
Anthony, J 
Asaadi, J 
Ashkenazi, A 

Abstract

jats:titleAjats:scbstract</jats:sc> </jats:title>jats:pThe MicroBooNE liquid argon time projection chamber located at Fermilab is a neutrino experiment dedicated to the study of short-baseline oscillations, the measurements of neutrino cross sections in liquid argon, and to the research and development of this novel detector technology. Accurate and precise measurements of calorimetry are essential to the event reconstruction and are achieved by leveraging the TPC to measure deposited energy per unit length along the particle trajectory, with mm resolution. We describe the non-uniform calorimetric reconstruction performance in the detector, showing dependence on the angle of the particle trajectory. Such non-uniform reconstruction directly affects the performance of the particle identification algorithms which infer particle type from calorimetric measurements. This work presents a new particle identification method which accounts for and effectively addresses such non-uniformity. The newly developed method shows improved performance compared to previous algorithms, illustrated by a 93.7% proton selection efficiency and a 10% muon mis-identification rate, with a fairly loose selection of tracks performed on beam data. The performance is further demonstrated by identifying exclusive final states in jats:italicν</jats:italic>jats:subjats:italicμ</jats:italic></jats:sub>jats:italicCC</jats:italic> interactions. While developed using MicroBooNE data and simulation, this method is easily applicable to future LArTPC experiments, such as SBND, ICARUS, and DUNE.</jats:p>

Description

Keywords

Regular Article - Experimental Physics, Other experiments

Journal Title

Journal of High Energy Physics

Conference Name

Journal ISSN

1029-8479
1029-8479

Volume Title

2021

Publisher

Springer Science and Business Media LLC