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Accepted author manuscript, 1.72 MB, PDF document

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

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Published

### Standard

Calorimetric classification of track-like signatures in liquid argon TPCs using MicroBooNE data. / MicroBooNE Collaboration ; Blake, A.; Devitt, A. et al.

In: Journal of High Energy Physics, Vol. 2021, 153, 21.12.2021.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

### Vancouver

MicroBooNE Collaboration, Blake A, Devitt A, Nowak J, Thorpe C. Calorimetric classification of track-like signatures in liquid argon TPCs using MicroBooNE data. Journal of High Energy Physics. 2021 Dec 21;2021:153. doi: 10.1007/JHEP12(2021)153

### Author

MicroBooNE Collaboration ; Blake, A. ; Devitt, A. et al. / Calorimetric classification of track-like signatures in liquid argon TPCs using MicroBooNE data. In: Journal of High Energy Physics. 2021 ; Vol. 2021.

### Bibtex

@article{48627960d674432990874971321c96d6,
title = "Calorimetric classification of track-like signatures in liquid argon TPCs using MicroBooNE data",
abstract = " 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 94% 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. ",
keywords = "physics.ins-det, hep-ex",
author = "{MicroBooNE Collaboration} and P. Abratenko and R. An and J. Anthony and J. Asaadi and A. Ashkenazi and S. Balasubramanian and B. Baller and C. Barnes and G. Barr and V. Basque and L. Bathe-Peters and Rodrigues, {O. Benevides} and S. Berkman and A. Bhanderi and A. Bhat and M. Bishai and A. Blake and T. Bolton and L. Camilleri and D. Caratelli and Terrazas, {I. Caro} and Fernandez, {R. Castillo} and F. Cavanna and G. Cerati and Y. Chen and E. Church and D. Cianci and Conrad, {J. M.} and M. Convery and L. Cooper-Troendle and Crespo-Anadon, {J. I.} and Tutto, {M. Del} and Dennis, {S. R.} and A. Devitt and R. Diurba and R. Dorrill and K. Duffy and S. Dytman and B. Eberly and A. Ereditato and Evans, {J. J.} and R. Fine and Aguirre, {G. A. Fiorentini} and Fitzpatrick, {R. S.} and Fleming, {B. T.} and N. Foppiani and D. Franco and J. Nowak and C. Thorpe",
year = "2021",
month = dec,
day = "21",
doi = "10.1007/JHEP12(2021)153",
language = "English",
volume = "2021",
journal = "Journal of High Energy Physics",
issn = "1029-8479",
publisher = "Springer-Verlag",

}

### RIS

TY - JOUR

T1 - Calorimetric classification of track-like signatures in liquid argon TPCs using MicroBooNE data

AU - MicroBooNE Collaboration

AU - Abratenko, P.

AU - An, R.

AU - Anthony, J.

AU - Ashkenazi, A.

AU - Balasubramanian, S.

AU - Baller, B.

AU - Barnes, C.

AU - Barr, G.

AU - Basque, V.

AU - Bathe-Peters, L.

AU - Rodrigues, O. Benevides

AU - Berkman, S.

AU - Bhanderi, A.

AU - Bhat, A.

AU - Bishai, M.

AU - Blake, A.

AU - Bolton, T.

AU - Camilleri, L.

AU - Caratelli, D.

AU - Terrazas, I. Caro

AU - Fernandez, R. Castillo

AU - Cavanna, F.

AU - Cerati, G.

AU - Chen, Y.

AU - Church, E.

AU - Cianci, D.

AU - Convery, M.

AU - Cooper-Troendle, L.

AU - Tutto, M. Del

AU - Dennis, S. R.

AU - Devitt, A.

AU - Diurba, R.

AU - Dorrill, R.

AU - Duffy, K.

AU - Dytman, S.

AU - Eberly, B.

AU - Ereditato, A.

AU - Evans, J. J.

AU - Fine, R.

AU - Aguirre, G. A. Fiorentini

AU - Fitzpatrick, R. S.

AU - Fleming, B. T.

AU - Foppiani, N.

AU - Franco, D.

AU - Nowak, J.

AU - Thorpe, C.

PY - 2021/12/21

Y1 - 2021/12/21

N2 - 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 94% 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.

AB - 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 94% 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.

KW - physics.ins-det

KW - hep-ex

U2 - 10.1007/JHEP12(2021)153

DO - 10.1007/JHEP12(2021)153

M3 - Journal article

VL - 2021

JO - Journal of High Energy Physics

JF - Journal of High Energy Physics

SN - 1029-8479

M1 - 153

ER -