Pattern recognition, tracking and vertex reconstruction in particle detectors / Rudolf Frühwirth, Are Strandlie.

Format:

Book

Author/Creator:

Frühwirth, R. (Rudolf), author.

Strandlie, Are, author.

Series:

Particle acceleration and detection 1611-1052

Particle acceleration and detection, 1611-1052

Language:

English

Subjects (All):

Nuclear track detectors.

Vertex detectors.

Particle accelerators.

Genre:

Electronic books.

Physical Description:

1 online resource : illustrations.

Place of Publication:

Cham : Springer, [2021]

System Details:

text file PDF

Summary:

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. .

Contents:

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.

Notes:

Includes bibliographical references and index.

Online resource; title from PDF title page (SpringerLink, viewed March 30, 2021).

ISBN:

9783030657710

303065771X

9783030657727

3030657728

9783030657734

3030657736

OCLC:

1240210729

Access Restriction:

Open access

Restricted for use by site license.