Pattern Recognition, Tracking and Vertex Reconstruction in Particle Detectors

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

Pattern Recognition, Tracking and Vertex Reconstruction in Particle Detectors

The book describes methods of track and vertex resonstruction in particle detectors. The main topics are pattern recognition and statistical estimation of geometrical and physical properties of charged particles and of interaction and decay vertices

Complexity-reduced hardware-based track-trigger for CMS upgrade

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonThe Compact Muon Solenoid (CMS) detector at the Large Hadron Collider (LHC) is designed to study the results of proton-proton collisions. The Tracker sub-detector is designed to detect and reconstruct the trajectories of charged particles produced by the collisions. During the lifetime of the CMS detector, there have been several upgrades aimed at increasing the chance of discovering new physics through increased luminosity levels and instrumentation of advanced technology. The High-Luminosity upgrade optimises the LHC to accelerate high-energy particles with an average of 200 proton-proton interactions per bunch crossing. The Level-1 Trigger system promptly analyses and filters collisions using hardware to reduce the data volume in real-time. For the upgrade, the trigger mechanism will use a particle trajectory estimator that discriminates between particles based on their transverse momentum (pT ). Particles with pT ≥ 2 GeV/c will be transmitted to the Level-1 Track-Trigger system for trajectory reconstruction within a fixed 3 μs latency. This thesis presents a novel Hardware-based Multivariate Linear Fitter (MVLF) system focusing on robustness in tracking efficiency and reduction in logic resource usage within the specified latency. The system components are implemented in Field Programmable Gate Arrays (FPGA), targeting 16 nm FinFET UltraScale+ silicon technology. The development was performed using the High-Level Synthesis (HLS) automation tools and the Hardware acceleration platform for Application-Specific Integrated Circuits (ASIC). A firmware demonstrator has been assembled to verify the feasibility and compatibility of the scaled system with the CMS Level-1 Track-Trigger infrastructure. The system’s performance is compared to past and current system developments, and the results are presented accordingly

A GridPix TPC readout for the ILD experiment at the future International Linear Collider

In the quest for a more complete theory of nature, the precise investigation of the Higgs boson at a future electron positron collider has the highest priority. The best tracking performance for a TPC at the proposed International Linear Collider is offered by a TPC with a GridPix readout. The viability of a GridPix TPC readout has been demonstrated in the two detector tests described in this thesis, and the expected performance is established in a comprehensive simulation. In conclusion, the GridPix has a lot of potential for experiments at the next generation of high-energy electron positron colliders

Measurement of the Prompt Double J/psi Production Cross Section in pp Collisions at sqrt(s) = 7 TeV

The simultaneous production of two J/psi mesons has been significantly observed in proton-proton collisions at a center-of-mass energy of 7 TeV with the CMS detector. The two J/psi mesons are fully reconstructed in their decay to muons. The signal yield is extracted with an extended maximum likelihood fit based on four event variables. A method was developed to correct for detector acceptances and efficiencies based on the measured momenta of the J/psi and their decay muons to maintain the least model dependence possible. The measurement is performed in an acceptance region defined by the individual J/psi transverse momentum and rapidity. From the measured signal yield of 446 events corresponding to an integrated luminosity of 4:7 inverse femtobarn. The total cross section is found to be 1:49 nanobarn, with 0:07 statistical and 0:13 nb systematic error, and unpolarizaed production was assumed. Most predictions for particle production at the LHC assume dominance of single parton interaction for proton-proton collisions, which can be tested with the final state measured in this analysis. The differential cross section is measured in bins of the double J/psi invariant mass, the double J/psi transverse momentum, and the absolute difference in rapidity of the two J/psi. The reconstruction of the four charged muon trajectories heavily relies on the Pixel subdetector located close to the beampipe. Systematic studies with cosmic muons and tracks from collision events are presented. The development of the Pixel RawToDigi package, data quality monitoring packages, commissioning studies of Pixel data and tracks in first collisions, and realistic simulations of decay signals in the pixel subdetector were all performed as a part of this dissertation work

Statistical analysis of bacteria locomotion

Many bacteria swim by employing their helical appendages, the flagella. We studied the statistics of this locomotion. To obtain more natural and especially long trajectories compared to two-dimensional tracking strategies, we developed a measurement-setup suitable to track bacteria in three-dimensions.The main component of this setup is an electrically focus tunable lens (ETL), able to adapt it’s shape via an applied electrical current, resulting in a change of the current focal plane. This setup has no mechanical interaction with the sample to avoid adulteration of the measured trajectories. We found that for times smaller than the average running-time, the slope of the mean-squared displacement MSD of the tracked bacteria obeys a ballistic behavior, whereas for longer times we saw a clear diffusive behavior. To allow for a more efficient evaluation of the measured trajectories we introduce the Kalman-Filter. By using simulated trajectories we could show that the Kalman-Filter allows a more accurate determination of the rotational-diffusion coefficient than conventional methods. Furthermore we could show that evaluation of three-dimensional trajectories obeys slightly different statistics than the evaluation of projected two-dimensional trajectories due to missing information.Through the qualitative simulation of bacteria locomotion we could show that the flagella-positioning has a crucial impact on the tumbling dynamics.Viele Bakterien schwimmen durch Nutzung ihrer spiralförmigen Anhänge,den Flagellen. Wir untersuchten die Statistik dieser Bewegung. Um natürlichere und vor allem längere Trajektorien - verglichen mit konventionellen zweidimensionalen Trackingmethoden - zu erhalten, haben wir einen Messaufbau zum dreidimensionalen tracken von Bakterien entwickelt. Die Hauptkomponente dieses Setups ist eine elektrische, fokusanpassbare Linse (ETL),welche ihre Form durch Anlegen eines elektrischen Stroms ändern kann,was zu einer Änderung der Fokusebene führt. Dieser Messaufbau hat keine mechanischen Wechselwirkungen mit der Probe, wodurch Verfälschungender gemessenen Trajektorien verhindert werden. Wir konnten zeigen dassfür Zeiten kleiner als die durchschnittlicherunning-Zeit (dt.Renn-Zeit), die mittlere quadratische Verschiebung (MSD) der getrackten Bakterien ein ballistisches Verhalten zeigt, wohingegen für längere Zeiten ein diffusives Verhalten vorliegt. Um eine effizientere Auswertung der gemessenen Trajektorien zu erlauben, führten wir den Kalman-Filter ein. Durch Nutzung simulierterTrajektorien konnten wir zeigen dass der Kalman-Filter eine genauere Bestimmung des Rotations-Diffusionskoeffizienten - verglichen mit konventionellen Methoden - erlaubt.Weiterhin konnten wir zeigen, dass die Auswertung dreidimensionaler Trajektorien leicht andere Statistiken als die Auswertung zweidimensionaler Trajektorien liefert, was durch den Verlust an Information zu erklären ist. Durch die qualitative Simulation der Bewegung von Bakterien konnten wir zeigen, dass die Position der Flagellen einen wesentlichen Einfluss auf die Tumbling-Dynamik (dt.Taumel-Dynamik) hat

Novel Methodologies for Pattern Recognition of Charged Particle Trajectories in the ATLAS Detector

By 2029, the Large Hadron Collider will enter its High Luminosity phase (HL- LHC) in order to achieve an unprecedented capacity for discovery. As this phase is entered, it is essential for many physics analyses that the efficiency of the re- construction of charged particle trajectories in the ATLAS detector is maintained. With levels of pile-up expected to reach = 200, the number of track candidates that must be processed will increase exponentially in the current pattern matching regime. In this thesis, a novel method for charged particle pattern recognition is developed based on the popular computer vision technique known as the Hough Transform (HT). Our method differs from previous attempts to use the HT for tracking in its data-driven choice of track parameterisation using Principal Component Analysis (PCA), and the division of the detector space in to very narrow tunnels known as sectors. This results in well-separated Hough images across the layers of the detector and relatively little noise from pile-up. Additionally, we show that the memory requirements for a pattern-based track finding algorithm can be reduced by approximately a factor of 5 through a two-stage compression process, without sacrificing any significant track finding efficiency. The new tracking algorithm is compared with an existing pattern matching algorithm, which consists of matching detector hits to a collection of pre-defined patterns of hits generated from simulated muon tracks. The performance of our algorithm is shown to achieve similar track finding efficiency while reducing the number of track candidates per event