Particle Physics Kalman Filter Implementation
School:
School of Computer and Information Sciences
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ResearchPrimary
Project Overview
One Liner: Implementing a Kalman Filter to reconstruct the trajectories of particles through a magnetic gradient
Abstract
The Kalman filter is a filter used to estimate the values of physical measurements provided time-discrete, noisy data. This technique is performed in steps, weighting the data measured at these discrete times with a prediction function used to estimate these measurements and thus accounting for noise in the measured data. The Kalman filter will be used to reconstruct the paths of particles through a magnetic field gradient induced by a dipole magnet. This reconstruction is part of an experiment designed to measure hadron scattering and production cross sections.
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