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Pattern Recognition, Tracking and Vertex Reconstruction in Particle Detectors [electronic resource] / by Rudolf Frühwirth, Are Strandlie.

Por: Colaborador(es): Tipo de material: TextoTextoSeries Particle Acceleration and DetectionEditor: Cham : Springer International Publishing : Imprint: Springer, 2021Edición: 1st ed. 2021Descripción: XVII, 203 páginas86 ilustraciones, 39 ilustraciones in color. online resourceTipo de contenido:
  • texto
Tipo de medio:
  • computadora
Tipo de soporte:
  • recurso en línea
ISBN:
  • 9783030657710
Tema(s): Formatos físicos adicionales: Printed edition:: Sin título; Printed edition:: Sin título; Printed edition:: Sin títuloClasificación CDD:
  • 539.73 23
Recursos en línea:
Contenidos:
Part 1. Introduction -- Chapter 1. Tracking Detectors -- Chapter 2. Event Reconstruction -- Chapter 3. Statistics and Numerical Methods -- Part 2. Track Reconstruction -- Chapter 4. Track Models -- Chapter 5. Track Finding -- Chapter 6. Track Fitting -- Part 3. Vertex Reconstruction -- Chapter 7. Vertex Finding -- Chapter 8. Vertex Fitting -- Chapter 9. Secondary Vertex Reconstruction -- Part 4. Case Studies -- Chapter 10. LHC Experiments.
En: Springer Nature eBookResumen: This open access book is a comprehensive review of the methods and algorithms that are used in the reconstruction of events recorded by past, running and planned experiments at particle accelerators such as the LHC, SuperKEKB and FAIR. The main topics are pattern recognition for track and vertex finding, solving the equations of motion by analytical or numerical methods, treatment of material effects such as multiple Coulomb scattering and energy loss, and the estimation of track and vertex parameters by statistical algorithms. The material covers both established methods and recent developments in these fields and illustrates them by outlining exemplary solutions developed by selected experiments. The clear presentation enables readers to easily implement the material in a high-level programming language. It also highlights software solutions that are in the public domain whenever possible. It is a valuable resource for PhD students and researchers working on online or offline reconstruction for their experiments. .
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Part 1. Introduction -- Chapter 1. Tracking Detectors -- Chapter 2. Event Reconstruction -- Chapter 3. Statistics and Numerical Methods -- Part 2. Track Reconstruction -- Chapter 4. Track Models -- Chapter 5. Track Finding -- Chapter 6. Track Fitting -- Part 3. Vertex Reconstruction -- Chapter 7. Vertex Finding -- Chapter 8. Vertex Fitting -- Chapter 9. Secondary Vertex Reconstruction -- Part 4. Case Studies -- Chapter 10. LHC Experiments.

Open Access

This open access book is a comprehensive review of the methods and algorithms that are used in the reconstruction of events recorded by past, running and planned experiments at particle accelerators such as the LHC, SuperKEKB and FAIR. The main topics are pattern recognition for track and vertex finding, solving the equations of motion by analytical or numerical methods, treatment of material effects such as multiple Coulomb scattering and energy loss, and the estimation of track and vertex parameters by statistical algorithms. The material covers both established methods and recent developments in these fields and illustrates them by outlining exemplary solutions developed by selected experiments. The clear presentation enables readers to easily implement the material in a high-level programming language. It also highlights software solutions that are in the public domain whenever possible. It is a valuable resource for PhD students and researchers working on online or offline reconstruction for their experiments. .

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