May 24 – 28, 2021
America/Vancouver timezone

Improvement in Material Discrimination Using Muon Momenta Information in Muon Scattering Tomography

May 27, 2021, 5:00 AM
Poster Technology Transfer Tech Transfer Posters


Mr Sridhar Tripathy (Saha Institute of Nuclear Physics) Prasant Kumar Rout (Saha Institute of Nuclear Physics (IN))


Muon Scattering Tomography is a major non-destructive technique to discriminate materials by finding deviation in muon tracks which depends on atomic number (Z) and density (⍴) of the target material. Based on scattering parameters obtained from Geant4 simulation, a Pattern Recognition Method has been devised which is able to distinguish high-Z and low-Z materials with more than 5𝜎 accuracy [S. Tripathy et al., 2020 JINST 15 P06029]. The scattering angle also depends on the incoming muon momentum which is a key to distinguish multiple small deviations through large path-lengths of low-Z material from significant deviations through smaller path lengths of a high-Z target. In this work, an analytical function, derived by fitting the muon momentum distribution in selected ranges, has been used to determine the momentum of individual events. It has been used as weighting parameter to normalize the scattering angle of the respective event to improve the accuracy of material discrimination.

TIPP2020 abstract resubmission? No, this is an entirely new submission.

Primary authors

Mr Sridhar Tripathy (Saha Institute of Nuclear Physics) Mr Prasant Kumar Rout (Saha Institute Of Nuclear Physics) Jaydeep Datta Nayana Majumdar (Saha Institute of Nuclear Physics (IN)) Supratik Mukhopadhyay (Saha Institute of Nuclear Physics (IN))

Presentation materials