Error Propagation of the Track Model and Track Fitting Strategy for the Iron CALorimeter Detector in India-based Neutrino Observatory

Abstract

A Kalman filter package has been developed for reconstructing muon (${\mu }^{\pm }$) tracks (coming from the neutrino interactions) in ICAL detector. Here, we describe the algorithm of muon track fitting, with emphasis on the error propagation of the elements of Kalman state vector along the muon trajectory through dense materials and inhomogeneous magnetic field. The higher order correction terms are included for reconstructing muon tracks at large zenith angle $\theta$ (measured from the perpendicular to the detector planes). The performances of this algorithm and its limitations are discussed.

27 pages, published version

References in corpus (3)

• The mass hierarchy with atmospheric neutrinos at INO
• Track fitting by Kalman Filter method for a prototype cosmic ray muon detector
• A GEANT-based study of atmospheric neutrino oscillation parameters at INO

Cited by in corpus (12)

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• Simulations Study of Muon Response in the Peripheral Regions of the Iron Calorimeter Detector at the India-based Neutrino Observatory
• Prospects of Indirect Searches for Dark Matter at INO
• Detection techniques and investigation of different neutrino experiments
• Study of neutrino oscillation parameters at the INO-ICAL detector using event-by-event reconstruction
• Matter vs Vacuum oscillations in Atmospheric Neutrinos
• Simulation of muon-induced neutral particle background for a shallow depth Iron Calorimeter detector
• Atmospheric muons charge ratio analysis at the INO-ICAL detector
• Optimisation and Characterisation of Glass RPC for India-based Neutrino Observatory Detectors
• Analytical computation of process noise matrix in Kalman filter for fitting curved tracks in magnetic field within dense, thick scatterers
• Neutrino Oscillation parameter determination at INO-ICAL using track and hit information from GEANT