Search for new heavy charged gauge bosons with the ATLAS detector

Particle physics deals with the most fundamental level at which nature can be understood. Experiments in high energy conditions allow for precise study and measurements of the structure and dynamics of matter. In particle colliders, such as the Large Hadron Collider (LHC) at CERN unprecedented center-of-mass energies can be achieved in proton-proton collisions. By recording the products of these collisions, the processes that occurred can be reconstructed. The ATLAS detector allows for detection and storage of vast numbers of collision events, and offers precise measurements of properties of the particles produced in these events. Using this approach, the Standard Model (SM) can be tested. This theoretical framework consists of a mathematical description of particle physics and allows for precise calculations and predictions. Even though the SM has proven to be highly successful, it does not explain everything observed in nature. Extensions of the SM can remedy this incompleteness. Using the same colliders, searches for these new phenomena can be conducted. This thesis describes the search for new heavy charged gauge bosons. These bosons, collectively referred to as W' bosons, would appear as resonance structures on top of the expectation from the SM alone. Searches of this kind have been carried out in previous experiments, but 2015 saw the first collisions at the highest center-of-mass energy of 13 TeV achieved at the time of writing. This analysis uses the entire data collected in 2015 and 2016. Interference effects between the hypothesized W' bosons and the charged W gauge bosons of the weak interaction in the SM are considered in this analysis. In the absence of a clear signal, upper limits on the relative coupling strength of new W' bosons can be calculated using a Bayesian statistics approach. These upper limits can be translated into a lower limit on the pole mass of the hypothesized boson under the assumption of a specific model. Below this pole mass the new particle can be excluded by the observed data at 95% confidence level

Student Session

An empirically founded and widely established driving force in opinion dynamics is homophily i.e. the tendency of "birds of a feather" to "flock together". The closer our opinions are the more likely it is that we will interact and converge. Models using these assumptions are called bounded confidence models (BCM) as they assume a tolerance threshold after which interaction is unlikely. They are known to produce one or more clusters, depending on the size of the bound, with more than one cluster being possible only in the deterministic case. Introducing noise, as is likely to happen in a stochastic world, causes BCM to produce consensus which leaves us with the open problem of explaining the emergence and sustainance of opinion clusters and polarisation. We investigate the role of heterogeneous priors in opinion formation, introduce the concept of opinion copulas, argue that it is well supported by findings in Social Psychology and use it to show that the stochastic BCM does indeed produce opinion clustering without the need for extra assumptions

Development of TRatioPlot in ROOT

The ROOT data analysis and visualization framework is a software package which is widely used in physics, especially in high energy physics. A common visualization which has so far been lacking a direct implementation is the ratio plot, as well as a few similar types of plots. The scope and goal of the summer student project at CERN was to implement a class in ROOT itself, that can take care of the most common types of calculations, and produces high quality visuals

Development and improvement of track reconstruction software and search for disappearing tracks with the ATLAS experiment

High-energy particle physics concerns itself with the most fundamental level at which the laws of nature can be understood. Using particle collisions, it is possible to probe and measure the properties of particles and their interactions. The Standard Model of particle physics is a set of theories describing three of the four fundamental interactions, and is the baseline with which observations are interpreted. Even though the Standard Model allows precise calculations of particle phenomena, it is thought to be incomplete, as certain observations like dark matter or neutrino oscillations remain unexplained. The analysis of particle collisions requires the measurement of particles produced in these collisions. One major part of these measurements is the reconstruction of the trajectories of charged particles, called tracks. Dedicated sensitive elements are used to obtain measurements of the particle along its trajectory, in order to ultimately reconstruct the track using software algorithms. Track reconstruction is a complex application, which grows in complexity with event activity. Therefore, future increases of the instantaneous luminosity of the LHC pose a challenge and require advancements in both the computational and physics peformance of track reconstruction algorithms. One part of this thesis presents work toward the development and improvement of track reconstruction in the context of the ATLAS experiment, and an experiment-independent software toolkit called ACTS. Additionally, the effort to use ACTS components in the ATLAS software is described. Specific contributions that were made to both domains are shown, which address the aforementioned challenge. Prominent examples are the description of current and future ATLAS tracker geometries, concurrent handling of misalignments, and the improvement of data structures used for reconstruction. Another part of this thesis describes a concrete application of these reconstructed particle tracks, in the form of an analysis of data from proton-proton collisions at $\sqrt{s} = 13$ TeV recorded by ATLAS, searching for an extension of the Standard Model. In this theoretical scenario, particles travel through the innermost part of the tracker, the Pixel detector, before decaying, resulting in so-called disappearing tracks. The analysis described here uses recent developments in the dedicated techniques used to reconstruct these short tracks to evaluate their expected sensitivity. An increase in expected sensitivity in the form of a higher expected mass limit is found to result from inclusion of new shorter tracks than were used in previous analyses. Potential for further developments is discussed in light of the LHC upgrade, and future colliders

The Open Data Detector Tracking System

Charged particle reconstruction in High Energy Physics experiments is a significant part of overall event reconstruction. Depending on the physics environment, for instance in collider experiments with high multiplicities or luminosities, the tracking problem increases in complexity and often poses not only an algorithmic, but also a computational challenge. With the high-luminosity phase of the LHC at CERN approaching, research for new approaches and algorithms for track reconstruction has seen an increased interest. Both new technological approaches like hardware accelerators, as well as machine learning are being developed. However, testing and developing these new approaches against the existing experiments’ software stacks can prove to be challenging, as they typically focus on stable data taking, discouraging disruptive changes. This document presents a virtual tracking detector that is designed to be a simplified, but realistic model of a real-world detector, that can serve as a robust testbed for new developments

Going standalone and platform-independent, an example from recent work on the ATLAS Detector Description and interactive data visualization

Until recently, the direct visualization of the complete ATLAS experiment geometry and final analysis data was confined within the software framework of the experiment. To provide a detailed interactive data visualization capability to users, as well as easy access to geometry data, and to ensure platform independence and portability, great effort has been recently put into the modernization of both the core kernel of the detector description and the visualization tools. In this talk we will present the new tools, as well as the lessons learned while modernizing the experiment's code for an efficient use of the detector description and for user-friendly data visualization

Going standalone and platform-independent, an example from recent work on the ATLAS Detector Description and interactive data visualization

Until recently, the direct visualization of the complete ATLAS experiment geometry and final analysis data was confined within the software framework of the experiment. To provide a detailed interactive data visualization capability to users, as well as easy access to geometry data, and to ensure platform independence and portability, great effort has been recently put into the modernization of both the core kernel of the detector description and the visualization tools. In this proceedings we will present the new tools, as well as the lessons learned while modernizing the experiment’s code for an efficient use of the detector description and for user-friendly data visualization.Until recently, the direct visualization of the complete ATLAS experiment geometry and physics objects was confined within the software framework of the experiment. To provide a detailed interactive data visualization capability to users, as well as easy access to geometry data, and to ensure platform independence and portability, great effort has been recently put into the modernization of both the core kernel of the detector description and the visualization tools. In this proceedings we will present the new tools, as well as the lessons learned while modernizing the experiment’s code for an efficient use of the detector description and for user-friendly data visualization

Going standalone and platform-independent, an example from recent work on the ATLAS Detector Description and interactive data visualization

Until recently, the direct visualization of the complete ATLAS experiment geometry and physics objects was confined within the software framework of the experiment. To provide a detailed interactive data visualization capability to users, as well as easy access to geometry data, and to ensure platform independence and portability, great effort has been recently put into the modernization of both the core kernel of the detector description and the visualization tools. In this proceedings we will present the new tools, as well as the lessons learned while modernizing the experiment’s code for an efficient use of the detector description and for user-friendly data visualization