Speaker
Description
High-precision muographic imaging of targets with thicknesses up to a
few meters requires the accurate measurement of the angular and energy
dependent flux of cosmic-ray muons in the low-energy regime (up to a few
GeV). We designed a muon spectrometer, called NEWCUT [1]. It is a
six-meter-length tracking system consists of nineteen Multi-wire
Proportional Chambers (MWPCs) and lead plates. The rotatable support
structure allows to tracking the charged particle between the horizontal
and vertical directions. A machine learning-assisted muon energy
classifier was implemented and trained using coordinate and energy
deposit data simulated on chamber-by-chamber in GEANT4 framework. The
comparison of simulated and reconstructed muon spectra suggest that the
actual arrangement of NEWCUT is applicable to measure the muon spectra
up to an energy of 6 GeV. The data analysis methods and first
experimental results will be discussed.
[1] Oláh et al. Development of Machine Learning-Assisted Spectra
Analyzer for the NEWCUT Muon Spectrometer, Journal of Advanced
Instrumentation in Science, vol. 2022,
https://doi.org/10.31526/jais.2022.264 (2022).
