Particle tracking in the DUNE-SAND detector: an extended Kalman filter approach

DUNE is a next-generation long-baseline neutrino oscillation experiment designed primarily to measure the CP violation phase and determine the neutrino mass ordering. The experiment features a Far Detector consisting of four multi-kiloton Liquid Argon Time Projection Chambers (LArTPCs) and a Near Detector (ND) complex located close to the neutrino source at Fermilab. Within the ND complex, the SAND detector plays a crucial role of on-axis beam monitoring, constraining uncertainties in neutrino oscillation analysis, and conducting precision neutrino physics measurements. SAND comprises a 0.6 T superconductive magnet, an electromagnetic calorimeter, a 1-ton liquid Argon detector and a modular, low-density straw tube target tracker system. This thesis presents the development and evaluation of a track reconstruction algorithm using the Extended Kalman Filter (EKF), customized for use in SAND. The EKF is an iterative algorithm that produces an estimate of the system state as a weighted average of the predicted state and the new measurement, extended for non-linear systems like charged particle tracking in a magnetized environment. The algorithm validation involved reconstructing ideal particle trajectories in magnetic fields with varying momentum, subsequently including energy loss and multiple scattering effects. A comprehensive simulation of charge-current muon neutrino interactions was performed to assess the algorithm performance in reconstructing primary particle trajectories and vertices.