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(Referência obtida automaticamente do Web of Science, por meio da informação sobre o financiamento pela FAPESP e o número do processo correspondente, incluída na publicação pelos autores.)

Composition Classification of Ultra-High Energy Cosmic Rays

Texto completo
Herrera, Luis Javier [1] ; Todero Peixoto, Carlos Jose [2] ; Banos, Oresti [1] ; Carceller, Juan Miguel [3] ; Carrillo, Francisco [1] ; Guillen, Alberto [1]
Número total de Autores: 6
Afiliação do(s) autor(es):
[1] Univ Granada, Comp Architecture & Technol Dept, Granada 18071 - Spain
[2] Univ Sao Paulo, Dept Basic Sci & Environm, BR-12602810 Lorena, SP - Brazil
[3] Univ Granada, Theoret & Cosmos Phys Dept, Granada 18071 - Spain
Número total de Afiliações: 3
Tipo de documento: Artigo Científico
Fonte: Entropy; v. 22, n. 9 SEP 2020.
Citações Web of Science: 0

The study of cosmic rays remains as one of the most challenging research fields in Physics. From the many questions still open in this area, knowledge of the type of primary for each event remains as one of the most important issues. All of the cosmic rays observatories have been trying to solve this question for at least six decades, but have not yet succeeded. The main obstacle is the impossibility of directly detecting high energy primary events, being necessary to use Monte Carlo models and simulations to characterize generated particles cascades. This work presents the results attained using a simulated dataset that was provided by the Monte Carlo code CORSIKA, which is a simulator of high energy particles interactions with the atmosphere, resulting in a cascade of secondary particles extending for a few kilometers (in diameter) at ground level. Using this simulated data, a set of machine learning classifiers have been designed and trained, and their computational cost and effectiveness compared, when classifying the type of primary under ideal measuring conditions. Additionally, a feature selection algorithm has allowed for identifying the relevance of the considered features. The results confirm the importance of the electromagnetic-muonic component separation from signal data measured for the problem. The obtained results are quite encouraging and open new work lines for future more restrictive simulations. (AU)

Processo FAPESP: 16/19764-9 - Estudos de composição de massa e interações hadrônicas usando o tempo de chegada das partículas do chuveiro detectadas com a rede de tanques do Observatório Pierre Auger
Beneficiário:Carlos Jose Todero Peixoto
Linha de fomento: Bolsas no Exterior - Pesquisa