Background Track reconstruction is necessary for time projection chamber(TPC),because TPCs usually face the measure-ment error that impedes gaining precise spacial and angular resolution.Purpose Kalman filter is a wel...Background Track reconstruction is necessary for time projection chamber(TPC),because TPCs usually face the measure-ment error that impedes gaining precise spacial and angular resolution.Purpose Kalman filter is a well-performed and applicable algorithm to denoise and reconstruct the event track.Methods In this paper,we develop a six-dimensional Kalman filter to reconstruct the particle track in high-energy physics experiments,while the most common form of Kalman filter used in many research fields is four-dimensional.The modelisation is based on a gaseous TPC,and the whole reconstruction process is first tested by a toy Monte Carlo simulation.Results The results show the Kalman filter can effectively reduce the noise and improve the detector resolution.Then,the performance of the Kalman filter is also verified with the data produced by the Geant4 toolkit.展开更多
文摘Background Track reconstruction is necessary for time projection chamber(TPC),because TPCs usually face the measure-ment error that impedes gaining precise spacial and angular resolution.Purpose Kalman filter is a well-performed and applicable algorithm to denoise and reconstruct the event track.Methods In this paper,we develop a six-dimensional Kalman filter to reconstruct the particle track in high-energy physics experiments,while the most common form of Kalman filter used in many research fields is four-dimensional.The modelisation is based on a gaseous TPC,and the whole reconstruction process is first tested by a toy Monte Carlo simulation.Results The results show the Kalman filter can effectively reduce the noise and improve the detector resolution.Then,the performance of the Kalman filter is also verified with the data produced by the Geant4 toolkit.
