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Browsing by Subject "HEP"

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  • thumbnail.journal.alt
    Item type:Article, Access status: Open Access ,
    The ATLAS experiment simulations as the computing challenge for the ACK CYFRONET AGH
    (Wydawnictwa AGH, 2008) Kaczmarska, Anna Ewa; Małecki, Paweł; Szymocha, Tadeusz; Richter-Wąs, Elżbieta
    The present High Energy Physics (HEP) experiments require unprecedented amount of computing power and storage space. We present the WLCG structure of the LHC computing, which will be used to perform data processing required by the ATLAS collaboration. We also describe the ATLAS detector full simulation chain. Finally, we quantify the computing needs and up-to-date usage of the ACK CYFRONET AGH resources by the ATLAS detector simulations.
  • thumbnail.journal.alt
    Item type:Article, Access status: Open Access ,
    Track finding with Deep Neural Networks
    (Wydawnictwa AGH, 2019) Kucharczyk, Marcin; Wolter, Marcin
    High energy physics experiments require fast and efficient methods for reconstructing the tracks of charged particles. The commonly used algorithms are sequential and the required CPU power increases rapidly with the number of tracks. Neural networks can speed up the process due to their capability of modeling complex non-linear data dependencies and finding all tracks in parallel. In this paper, we describe the application of the deep neural network for reconstructing straight tracks in a toy two-dimensional model. It is planned to apply this method to the experimental data obtained by the MUonE experiment at CERN.