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Signal-background separation and energy reconstruction of gamma rays using pattern spectra and convolutional neural networks for the Small-Sized Telescopes of the Cherenkov Telescope Array

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68378271%3A90247%2F24%3A00604760" target="_blank" >RIV/68378271:90247/24:00604760 - isvavai.cz</a>

  • Result on the web

    <a href="https://doi.org/10.1016/j.nima.2023.168942" target="_blank" >https://doi.org/10.1016/j.nima.2023.168942</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1016/j.nima.2023.168942" target="_blank" >10.1016/j.nima.2023.168942</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Signal-background separation and energy reconstruction of gamma rays using pattern spectra and convolutional neural networks for the Small-Sized Telescopes of the Cherenkov Telescope Array

  • Original language description

    Imaging Atmospheric Cherenkov Telescopes (IACTs) detect very-high-energy gamma rays from ground level by capturing the Cherenkov light of the induced particle showers. Convolutional neural networks (CNNs) can be trained on IACT camera images of such events to differentiate the signal from the background and to reconstruct the energy of the initial gamma ray. Pattern spectra provide a 2-dimensional histogram of the sizes and shapes of features comprising an image and they can be used as an input for a CNN to significantly reduce the computational power required to train it. In this work, we generate pattern spectra from simulated gamma-ray and proton images to train a CNN for signal-background separation and energy reconstruction for the Small-Sized Telescopes (SSTs) of the Cherenkov Telescope Array (CTA).

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    10303 - Particles and field physics

Result continuities

  • Project

  • Continuities

Others

  • Publication year

    2024

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Nuclear Instruments & Methods in Physics Research Section A

  • ISSN

    0168-9002

  • e-ISSN

    1872-9576

  • Volume of the periodical

    1059

  • Issue of the periodical within the volume

    Feb

  • Country of publishing house

    NL - THE KINGDOM OF THE NETHERLANDS

  • Number of pages

    10

  • Pages from-to

    168942

  • UT code for WoS article

    001128192000001

  • EID of the result in the Scopus database

    2-s2.0-85178488947