Muography background sources: simulation, characterization, and machine-learning rejection
J. Peña Rodríguez*, R. de'León-Barrios, A. Ramírez-Muñóz, D. Villabona-Ardila, M. Suárez-Durán, A. Vásquez-Ramírez, H. Asorey and L.A. Núñez
August 01, 2021
March 18, 2022
Muography scans large-size objects, natural or anthropic, by recording the atmospheric muon flux crossing them. The traversing muon flux, four orders of magnitude lower than the vertical muon flux, suffers an overwhelming background. The background sources are scattered muons, electromagnetic particles, reverse trajectory particles, and particles arriving simultaneously. We carried out Monte Carlo simulations to characterize such background sources. We estimated the scattered muon energy-angular spectrum and the cosmic ray components impinging the Muon Telescope --MuTe. We quantified the muography background using the Time-of-Flight and Water Cherenkov detector measurements of MuTe. We explored machine learning techniques to reject the background events.
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