Calorimetric classification of track-like signatures in liquid argon TPCs using MicroBooNE data Abratenko, P. García Gámez, Diego MicroBooNE Collaboration Other experiments This research is supported by the U.S. Department of Energy, Office of Science, Office of High Energy Physics, under the Award Number DE-SC0007881. This document was prepared by the MicroBooNE collaboration using the resources of the Fermi National Accelerator Laboratory (Fermilab), a U.S. Department of Energy, Office of Science, HEP User Facility. Fermilab is managed by Fermi Research Alliance, LLC (FRA), acting under Contract No. DE-AC02-07CH11359. MicroBooNE is supported by the following: the U.S. Department of Energy, Office of Science, Offices of High Energy Physics and Nuclear Physics; the U.S. National Science Foundation; the Swiss National Science Foundation; the Science and Technology Facilities Council (STFC), part of the United Kingdom Research and Innovation; and The Royal Society (United Kingdom). Additional support for the laser calibration system and cosmic ray tagger was provided by the Albert Einstein Center for Fundamental Physics, Bern, Switzerland. N.F. dedicates this paper to Federico Tonielli, a physicist, peer, and friend who inspired and taught many young physicists but disappeared too early for the contribution he could have made to science. The 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 nu mu CC interactions. While developed using MicroBooNE data and simulation, this method is easily applicable to future LArTPC experiments, such as SBND, ICARUS, and DUNE. 2022-01-26T07:52:31Z 2022-01-26T07:52:31Z 2021-12-21 info:eu-repo/semantics/article The MicroBooNE collaboration... [et al.]. Calorimetric classification of track-like signatures in liquid argon TPCs using MicroBooNE data. J. High Energ. Phys. 2021, 153 (2021). [https://doi.org/10.1007/JHEP12(2021)153] http://hdl.handle.net/10481/72484 10.1007/JHEP12(2021)153 eng http://creativecommons.org/licenses/by/3.0/es/ info:eu-repo/semantics/openAccess Atribución 3.0 España Springer