3 citations · 3 across the 4 of their papers we have counts for
4 papers
A Cosmic Muon Tomography System with Machine Learning based Momentum Measurement for Multi-Object Reconstruction and Material Characterization
Bharat Kumar Sirasva, Rohit Gupta, Satyajit Jena
Cosmic muon tomography is a powerful non-destructive imaging technique for inspecting dense and shielded materials through multiple Coulomb scattering. In this work, we present the…
Particle tracking at high luminosities using a novel reconstruction approach
B. K. Sirasva, S. Dugad, Y. Kumar +2
Tracking charged particles with high precision is of vital importance for collider experiment like those operating at the Large Hadron Collider (LHC), CERN. The tracking detector i…
Using graph neural networks to reconstruct charged pion showers in the CMS High Granularity Calorimeter
M. Aamir, G. Adamov, T. Adams +568
A novel method to reconstruct the energy of hadronic showers in the CMS High Granularity Calorimeter (HGCAL) is presented. The HGCAL is a sampling calorimeter with very fine transv…
Study of density independent scattering angle and energy loss for low- to high-Z material using Muon Tomography
Bharat Kumar Sirasva, Satyajit Jena, Rohit Gupta
Cosmic ray muon, as they pass through a material, undergoes Multiple Coulomb Scattering (MCS). The analysis of muon scattering angle in a material provides us with an opportunity t…