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Pattern recognition, tracking and ve...

Fruhwirth, Rudolf.

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Pattern recognition, tracking and vertex reconstruction in particle detectors

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Pattern recognition, tracking and vertex reconstruction in particle detectors/ by Rudolf Fruhwirth, Are Strandlie.
作者:	Fruhwirth, Rudolf.
其他作者:	Strandlie, Are.
出版者:	Cham :Springer International Publishing : : 2021.,
面頁冊數:	xvii, 203 p. :ill., digital ;24 cm.
內容註:	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.
Contained By:	Springer Nature eBook
標題:	Nuclear track detectors. -
電子資源:	https://doi.org/10.1007/978-3-030-65771-0
ISBN:	9783030657710

Pattern recognition, tracking and vertex reconstruction in particle detectors
Fruhwirth, Rudolf.

Pattern recognition, tracking and vertex reconstruction in particle detectors[electronic resource] /by Rudolf Fruhwirth, Are Strandlie. - Cham :Springer International Publishing :2021. - xvii, 203 p. :ill., digital ;24 cm. - Particle acceleration and detection,1611-1052. - Particle acceleration and detection..

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.

ISBN: 9783030657710

Standard No.: 10.1007/978-3-030-65771-0doiSubjects--Topical Terms:

1002865
Nuclear track detectors.

LC Class. No.: QC787.N83

Dewey Class. No.: 539.77

Pattern recognition, tracking and vertex reconstruction in particle detectors
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505 0 $a 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.
506 $a Open access.
520 $a 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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