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Work: Event-by-event reconstruction of the shower maximum $X_{\mathrm{max}}$ with the Surface Detector of the Pierre Auger Observatory using deep learning

  1. Inference of the Mass Composition of Cosmic Rays with Energies from <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:msup><mml:mn>10</mml:mn><mml:mn>18.5</mml:mn></mml:msup></mml:math> to <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:msup><mml:mrow><mml:mn>10</mml:mn></mml:mrow><mml:mrow><mml:mn>20</mml:mn></mml:mrow></mml:msup><mml:mtext> </mml:mtext><mml:mtext> </mml:mtext><mml:mi>eV</mml:mi></mml:mrow></mml:math> Using the Pierre Auger Observatory and Deep Learning

    Adila Abdul Halim, P. Abreu, M. Aglietta +97

    ArticleAstrophysics and Cosmic PhenomenaPhysical Review Letters20252 citations
    ABI

  2. Measurement of the depth of maximum of air-shower profiles with energies between <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:msup><mml:mn>10</mml:mn><mml:mn>18.5</mml:mn></mml:msup></mml:math> and <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:msup><mml:mn>10</mml:mn><mml:mn>20</mml:mn></mml:msup><mml:mtext> </mml:mtext><mml:mtext> </mml:mtext><mml:mi>eV</mml:mi></mml:math> using the surface detector of the Pierre Auger Observatory and deep learning

    Adila Abdul Halim, P. Abreu, M. Aglietta +97

    ArticleAstrophysics and Cosmic PhenomenaPhysical review. D/Physical review. D.20252 citations
    ABI