On the treatment of energy loss in track fitting
type: Item
instance of: scholarly article
title: On the treatment of energy loss in track fitting
zbMATH Open document ID: 0939.65008
DOI: 10.1016/S0010-4655(97)00157-4
published in: Computer Physics Communications
publication date: 2000-03-22T00:00:00Z
review text: In track reconstruction with Kalman filter, both measurement and process noise are implicitly assumed to be Gaussian. However, what concerns the energy loss of electrons in matter, this is not always true and the loss is usually described by strongly non-Gaussian distribution. In such a case the Kalman filter is not necessarily the optimal filter, even if the model is perfectly linear. Therefore, in this short paper the authors examine two nonlinear estimators by means of a simulation experiment, i.e. the Gaussian-sum filter and the Metropolis-Hastings algorithm. It is shown, based on a simulation experiment, that in the studied case the momentum resolution of electrons can be improved by using a nonlinear estimator.
Mathematics Subject Classification ID: 65C35
Mathematics Subject Classification ID: 81V35
Mathematics Subject Classification ID: 65Z05
zbMATH DE Number: 1328293
zbMATH Keywords: energy loss
zbMATH Keywords: electron tracks
zbMATH Keywords: Gaussian-sum filter
zbMATH Keywords: Kalman filter
zbMATH Keywords: MCMC
zbMATH Keywords: Metropolis-Hastings algorithm
zbMATH Keywords: track fitting
zbMATH Keywords: track reconstruction
author: R. Frühwirth
author: Sylvia Frühwirth-Schnatter
reviewed by: Jaromír Antoch
describes a project that uses: MINUIT
MaRDI profile type: Publication
cites work: The two-filter formula for smoothing and an implementation of the Gaussian-sum smoother
cites work: Track fitting with non-Gaussian noise
full work available at URL: s0010-4655(97)00157-4
OpenAlex ID: W1973771490
Wikidata QID: Q127351691
description: scientific article; zbMATH DE number 1328293