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Study of π0 Events in MicroBooNE and Applications to the Deep Learning LEE Search

Research output: Working paper › Preprint

Published

Standard

Study of π0 Events in MicroBooNE and Applications to the Deep Learning LEE Search. / MicroBooNE Collaboration.
2020.

Research output: Working paper › Preprint

Harvard

MicroBooNE Collaboration 2020 'Study of π0 Events in MicroBooNE and Applications to the Deep Learning LEE Search'. https://doi.org/10.2172/2397310

APA

MicroBooNE Collaboration (2020). Study of π0 Events in MicroBooNE and Applications to the Deep Learning LEE Search. https://doi.org/10.2172/2397310

Vancouver

MicroBooNE Collaboration. Study of π0 Events in MicroBooNE and Applications to the Deep Learning LEE Search. 2020 Jun 15. doi: 10.2172/2397310

Author

MicroBooNE Collaboration. / Study of π0 Events in MicroBooNE and Applications to the Deep Learning LEE Search. 2020.

Bibtex

@techreport{f9ecf9510acf427081a1f5c8eb5a49fe,
title = "Study of π0 Events in MicroBooNE and Applications to the Deep Learning LEE Search",
abstract = "We present a selection of events containing π 0 particles in the MicroBooNE detector. These events are used to understand the important pi0 background in the deep learning (DL) based electron low energy excess (e-LEE) analysis. The selection uses a new shower reconstruction algorithm based on tools in the DL reconstruction chain. We present the efficiency and energy resolution of the selection. We also present the planned use of these events in energy calibration using the reconstructed π 0 mass.",
author = "{MicroBooNE Collaboration} and Jaroslaw Nowak",
year = "2020",
month = jun,
day = "15",
doi = "10.2172/2397310",
language = "English",
type = "WorkingPaper",

}

RIS

TY - UNPB

T1 - Study of π0 Events in MicroBooNE and Applications to the Deep Learning LEE Search

AU - MicroBooNE Collaboration

AU - Nowak, Jaroslaw

PY - 2020/6/15

Y1 - 2020/6/15

N2 - We present a selection of events containing π 0 particles in the MicroBooNE detector. These events are used to understand the important pi0 background in the deep learning (DL) based electron low energy excess (e-LEE) analysis. The selection uses a new shower reconstruction algorithm based on tools in the DL reconstruction chain. We present the efficiency and energy resolution of the selection. We also present the planned use of these events in energy calibration using the reconstructed π 0 mass.

AB - We present a selection of events containing π 0 particles in the MicroBooNE detector. These events are used to understand the important pi0 background in the deep learning (DL) based electron low energy excess (e-LEE) analysis. The selection uses a new shower reconstruction algorithm based on tools in the DL reconstruction chain. We present the efficiency and energy resolution of the selection. We also present the planned use of these events in energy calibration using the reconstructed π 0 mass.

U2 - 10.2172/2397310

DO - 10.2172/2397310

M3 - Preprint

BT - Study of π0 Events in MicroBooNE and Applications to the Deep Learning LEE Search

ER -