Prediction of Muon Energy using Deep Neural Network with Multiple Coulomb Scattering Data
[ N/A ]
Tarih
2022
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
TUBITAK
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
This study is based on determining muon beam energies using multiple Coulomb scattering data in artificial neural networks. Muon particles were scattered off a 50-layer lead object by using the G4beamline simulation program which is based on Geant4. Before working with deep neural networks, average scattering angle distributions regarding the number of crossed layers were analyzed with the fit method using the well-known formula for multiple Coulomb scattering to estimate muon beam energies. Subsequently, average scattering angles over the number of crossed layers from 1 to 10 were used in deep neural network structures to estimate the muon beam energy. It has been observed that deep neural networks significantly improve the resolutions compared to the ones obtained with the fit method. © 2022, TUBITAK. All rights reserved.
Açıklama
Anahtar Kelimeler
deep neural network, multiple Coulomb scattering, muon beam, Unfolding momentum spectrum
Kaynak
El-Cezeri Journal of Science and Engineering
WoS Q Değeri
Scopus Q Değeri
Q4
Cilt
9
Sayı
3
