Pattern Recognition and Reconstruction
Chapter Concepts
| Keywords | Pattern Recognition and Reconstruction; charged particle trajectory; detector alignment; jet reconstruction; kinematic fitting; momentum resolution; pattern recognition; pattern reconstruction; track finding; track fitting; track parameter; vertex finding; vertex fitting; vertex reconstruction |
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| Main Subjects | Track reconstruction; Vertex reconstruction |
| Secondary Subjects | Bremsstrahlung; Conformal mapping; Detector alignment; Energy loss; Gauss-Newton method; HIP Algorithm; Hough transform; Jet reconstruction; Kalman filter; Kinematic Fitting; Lagrange multiplier method; Least-squares methods; Levenberg-Marquardt method; Millepede Algorithm; Multiple Coulomb scattering; Neural networks; Newton-Raphson method; Outlier removal; Pattern recognition; Total momentum resolution; Track following; Track models; Track parameters; Track quality; Track road; Vertex constraint; Vertex finding; Vertex fitting; Vertex quality |
Source
| Title | Pattern Recognition and Reconstruction |
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| In | Data Treatment and Analysis Methods |
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| Author | R. Frühwirth, A. Strandlie | |
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| Part of | Landolt-Börnstein - Group I Elementary Particles, Nuclei and Atoms | |
| Numerical Data and Functional Relationships in Science and Technology | ||
| Volume | 21B1: Detectors for Particles and Radiation. Part 1: Principles and Methods |
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| Edited by | C. W. Fabjan, H. Schopper | |
| Chapter-DOI | 10.1007/978-3-642-03606-4_13 | |
| Book-DOI | 10.1007/978-3-642-03606-4 (Volume in Bookshelf) |
Cite as
| RIS-Export | Frühwirth, R., Strandlie, A.: Pattern Recognition and Reconstruction. Fabjan, C. W., Schopper, H. (ed.). SpringerMaterials - The Landolt-Börnstein Database (http://www.springermaterials.com). Springer-Verlag Berlin Heidelberg, 2011. DOI: 10.1007/978-3-642-03606-4_13 |
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Abstract
| Pattern Recognition and Reconstruction in 'Data Treatment and Analysis Methods', part of 'Landolt-Börnstein - Group I Elementary Particles, Nuclei and Atoms: Numerical Data and Functional Relationships in Science and Technology, Volume 21B1: Detectors for Particles and Radiation. Part 1: Principles and Methods'. | |
| This document is part of Part 1 'Principles and Methods' of Subvolume B 'Detectors for Particles and Radiation' of Volume 21 'Elementary Particles' of Landolt-Börnstein - Group I 'Elementary Particles, Nuclei and Atoms'. It contains the Section '4.3 Pattern Recognition and Reconstruction' of Chapter '4 Data Treatment and Analysis Methods' with the content: 4.3 Pattern Recognition and Reconstruction 4.3.1 Track reconstruction 4.3.1.1 Introduction 4.3.1.2 Pattern recognition 4.3.1.2.1 Global methods 4.3.1.2.1.1 Conformal mapping 4.3.1.2.1.2 Hough transform 4.3.1.2.1.3 Neural networks 4.3.1.2.2 Local methods 4.3.1.2.2.1 Track road 4.3.1.2.2.2 Track following 4.3.1.2.2.3 Kalman filter 4.3.1.3 Estimation of track parameters 4.3.1.3.1 Magnetic field representation 4.3.1.3.2 Track models 4.3.1.3.3 Material Effects 4.3.1.3.3.1 Multiple Coulomb scattering 4.3.1.3.3.2 Energy loss 4.3.1.3.3.3 Bremsstrahlung 4.3.1.3.4 Estimation methods 4.3.1.3.5 Track quality and robust estimation 4.3.1.3.6 Jet reconstruction 4.3.1.4 Detector alignment 4.3.1.4.1 General overview 4.3.1.4.2 Two examples 4.3.1.4.2.1 The HIP Algorithm 4.3.1.4.2.2 The Millepede Algorithm 4.3.1.5 Total momentum resolution 4.3.1.5.1 Two-arm spectrometer 4.3.1.5.2 Cylindrical spectrometer 4.3.2 Vertex reconstruction 4.3.2.1 Introduction 4.3.2.2 Vertex finding 4.3.2.2.1 Clustering methods 4.3.2.2.2 Topological methods 4.3.2.2.3 Iterated estimators 4.3.2.3 Vertex fitting 4.3.2.3.1 Least-squares methods 4.3.2.3.1.1 Gauss-Newton method 4.3.2.3.1.2 Newton-Raphson method 4.3.2.3.1.3 Levenberg-Marquardt method 4.3.2.3.1.4 Fast vertex fits 4.3.2.3.1.5 Adding prior information 4.3.2.3.2 Vertex quality and outlier removal 4.3.2.3.3 Robust and adaptive estimators 4.3.2.4 Kinematic Fitting 4.3.2.4.1 Lagrange multiplier method 4.3.2.4.2 Vertex constraint 4.3.3 Conclusion |
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