S. C. Kang (Author), Y. Amarea (Author), D. Angelaszek (Author), N. Anthony (Author), G. H. Choi (Author), M. Chung (Author), M. Copley (Author), L. Derome (Author), L. Eraud (Author), C. Falana (Author), J. P. Lundquist (Author)

Abstract

Cosmic Ray Energetics And Mass for the International Space Station (ISS-CREAM) is an experiment for studying the origin, acceleration, and propagation mechanisms of high-energy cosmic rays. The ISS-CREAM instrument was launched on the 14th of August 2017 to the ISS aboard the SpaceX-12 Dragon spacecraft. The Top and Bottom Counting Detectors (TCD/BCD) are parts of the ISS-CREAM instrument and designed for studying electron and gamma-ray physics. The TCD/BCD each consist of an array of 20 × 20 photodiodes on a plastic scintillator. The TCD/BCD can separate electrons from protons by using the difference between the shapes of electromagnetic and hadronic showers in the high energy region. The Boosted Decision Tree (BDT) method, which is a deep learning method, is used in this separation study. We will present results of the electron/proton separation study and rejection power in various energy ranges.

Keywords

instrumentations;high energy cosmic rays;particle detectors;composition;

Data

Language: English
Year of publishing:
Typology: 1.08 - Published Scientific Conference Contribution
Organization: UNG - University of Nova Gorica
UDC: 539.1
COBISS: 50527235 Link will open in a new window
ISSN: 1824-8039
Views: 1559
Downloads: 0
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Other data

URN: URN:SI:UNG
Pages: str. [1], 1-7
Chronology: 2019
ID: 12544192
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