Combinatorial Kalman Filter and High Level Trigger Reconstruction for the Belle II Experiment [electronic resource] / Nils Braun.
Combinatorial Kalman filters are a standard tool today for pattern recognition and charged particle reconstruction in high energy physics. In this thesis the implementation of the track finding software for the Belle II experiment and first studies on early Belle II data are presented. The track fin...
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| Format: | Electronic eBook |
| Language: | English |
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Springer,
2019.
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| Series: | Springer theses.
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Table of Contents:
- Intro; Supervisor's Foreword; Acknowledgements; Contents; 1 Introduction; 1.1 General Introduction into Belle II and This Work; References; 2 Experimental Setup; 2.1 From Accelerated Electrons to Final State Particles; 2.1.1 Accelerator Complex at KEK; 2.1.2 Detector Design; 2.1.3 Beam-Induced Background; 2.2 From Digital Detector Data via the Trigger to the Storage Drives; 2.2.1 Detector Readout and Hardware Trigger; 2.2.2 Online Software Trigger; 2.2.3 Storage and Offline Reconstruction; 2.3 Belle Analysis Software Framework 2; 2.3.1 Inter-Module, Inter-Process and Inter-Node Communication.
- 6 Combinatorial Kalman Filter6.1 Motivation; 6.2 Principles; 6.3 Application of the CKF at Belle II; 6.4 CKF from CDC to SVD-An Example; 6.4.1 Build Relations; 6.4.2 Tree Search; 6.4.3 Filters; 6.4.4 Final Candidate Selection; 6.5 CKF for SVD Hit Attachment; 6.5.1 Characteristics of CDC Tracks; 6.5.2 Legacy Implementation; 6.5.3 Performance; 6.5.4 Additional Runs of the CKF and VXD Track Finding; 6.6 Merging of CDC and SVD Tracks; 6.6.1 Overall Performance of the SVD CKF Tracking Chain; 6.6.2 Comparison with VXDTF2; 6.6.3 Performance on ROI Finding; 6.7 CKF for PXD Hit Attachment.
- 4.1 Introduction4.1.1 Event Composition; 4.1.2 Level 1 Trigger; 4.1.3 Requirements; 4.2 Processing Time Studies; 4.2.1 Speedup η(p); 4.2.2 Single-Core Reconstruction Time T(1); 4.2.3 Summary; 4.3 Principles of FastReco; 4.3.1 Continuous HLT Decision; 4.3.2 Bhabha Veto; 4.3.3 General Framework; 4.4 Multiprocessing Using the ØMQ Library; 4.4.1 Overview on ØMQ; 4.4.2 Implementation for basf2; 4.4.3 Performance; 4.5 Summary; References; 5 Event Timing; 5.1 The Role of the Event Time; 5.2 Event Timing Using the CDC Information; 5.3 Flight Time Estimation.
- 6.7.1 Influence on B- toD0 π- Decays.
- 5.3.1 Performance of the Track Finding with Wrong T0 Assumptions5.3.2 Track Time Estimation; 5.4 Event Time Extraction Using the Drift Length Information; 5.4.1 Components of the Measured Time in the CDC; 5.4.2 Performance on MC Simulations; 5.5 Event Time Extraction Using χ2 Information; 5.5.1 Minimizing the χ2 Function; 5.5.2 Performance on MC Simulations; 5.6 Event Time Extraction Using Hit Information; 5.7 Combination of the Methods; 5.7.1 Performance on MC Simulations; 5.7.2 Comparison with Other Event Time Extraction Methods at Belle II; 5.8 Summary; References.
- 2.3.2 Monte Carlo Simulation2.4 Time Schedule and Performed Tests; References; 3 Foundations; 3.1 Track Reconstruction; 3.2 Track Finding Concepts at Belle II; 3.2.1 Track Finding in the CDC; 3.2.2 Track Finding in the VXD; 3.2.3 MC Matching and Performance Indicators; 3.3 Track Fitting; 3.3.1 Tracking Parameters; 3.3.2 Track Fit Using χ2; 3.3.3 Kalman Filter; 3.3.4 Deterministic Annealing Filter; 3.3.5 Extrapolation; 3.4 Mathematical Foundations; 3.4.1 Multivariate Analysis (MVA); 3.4.2 Treatment of Statistical Uncertainties; References; 4 Fast Reconstruction for the Highpg Level Trigger.