Halim, Adila Binti Abdul 
; Catalani, Fernando ; Souza, Vitor de ; Santos, Edivaldo Moura ; Oliveira, Cainã de ; Peixoto, Carlos Jose Todero
Source: Physical Review Letters. Unidades: EEL, IFSC, IF
Subjects: RAIOS CÓSMICOS, APRENDIZAGEM PROFUNDA, ASTROFÍSICA, OBSERVATÓRIOS
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HALIM, Adila Binti Abdul et al. Inference of the mass composition of cosmic rays with energies from 10^18.5 to 10^20 eV using the Pierre Auger Observatory and deep learning. Physical Review Letters, v. 134, n. Ja 2025, p. 021001-1-021001-10, 2025Tradução . . Disponível em: https://doi.org/10.1103/PhysRevLett.134.021001. Acesso em: 04 nov. 2025.APA
Halim, A. B. A., Catalani, F., Souza, V. de, Santos, E. M., Oliveira, C. de, & Peixoto, C. J. T. (2025). Inference of the mass composition of cosmic rays with energies from 10^18.5 to 10^20 eV using the Pierre Auger Observatory and deep learning. Physical Review Letters, 134( Ja 2025), 021001-1-021001-10. doi:10.1103/PhysRevLett.134.021001NLM
Halim ABA, Catalani F, Souza V de, Santos EM, Oliveira C de, Peixoto CJT. Inference of the mass composition of cosmic rays with energies from 10^18.5 to 10^20 eV using the Pierre Auger Observatory and deep learning [Internet]. Physical Review Letters. 2025 ; 134( Ja 2025): 021001-1-021001-10.[citado 2025 nov. 04 ] Available from: https://doi.org/10.1103/PhysRevLett.134.021001Vancouver
Halim ABA, Catalani F, Souza V de, Santos EM, Oliveira C de, Peixoto CJT. Inference of the mass composition of cosmic rays with energies from 10^18.5 to 10^20 eV using the Pierre Auger Observatory and deep learning [Internet]. Physical Review Letters. 2025 ; 134( Ja 2025): 021001-1-021001-10.[citado 2025 nov. 04 ] Available from: https://doi.org/10.1103/PhysRevLett.134.021001
