Alison Lister

The Standard Model of particle physics is a powerful theory of nature, yet it does not account for all physical observations. Notably, the nonzero masses of the three neutrino flavours and their transformations into one another suggest the need for an extension of the Standard Model. One such extension postulates the existence of Heavy Neutral Leptons (HNLs, ?) — right-handed neutrino states that do not interact with other particles except through mixing with Standard Model neutrinos. HNLs may generate light neutrino masses through the so-called “seesaw mechanism.”This dissertation presents a direct search for long-lived HNLs using 139 fb⁻¹ of √s=13 TeV pp collision data collected by the ATLAS detector at the Large Hadron Collider. In this search, the ? is produced via W → ? μ or W → ? e and decays into a neutrino and two charged leptons, which form a displaced vertex in the inner detector. No signal is observed, and limits are set on the squared mixing angles of the ? with the Standard Model neutrinos in the mass range 3 GeV m? 15 GeV. For the first time in a collider search, results are presented in the context of realistic HNL mixing models consistent with neutrino oscillation data.Such a displaced vertex search relies heavily upon nonstandard reconstruction algorithms. An additional pass of the track reconstruction algorithm with relaxed collision vertex pointing requirements is executed on a subset of the recorded data to improve sensitivity to long-lived particles in the inner detector. This Large-Radius Tracking (LRT) configuration is effective yet computationally expensive due to the reconstruction of many “fake” tracks not formed from individual charged particles. This algorithm was optimized in preparation for the Run 3 data-taking period, which began in July 2022. Fake LRT tracks are reduced by 95%, drastically improving the purity and reducing the computational load such that LRT is now run in the default reconstruction pipeline. This optimization is expected to substantially improve the sensitivity and reduce the complexity of long-lived particle analyses in ATLAS, including future HNL searches.

View record

This dissertation presents a search for long-lived heavy neutral leptons (HNLs) in proton-proton collisions at the Large Hadron Collider (LHC). The Standard Model (SM) of particle physics is an extremely successful theory and many of its major predictions have been precisely confirmed. However, the existence of neutrinos, with small nonzero masses, suggests that the SM is incomplete. Introducing HNLs into the SM is a natural way to generate the light neutrino masses through a seesaw mechanism. Theories that postulate the existence of such particles can also explain the asymmetry between matter and anti-matter in our universe and models with at least three HNLs provide a dark matter candidate. This experimental search uses ATLAS data collected between 2015 and 2018 at a centre-of-mass energy of 13 TeV. A non-standard technique is used to search for a displaced vertex from particle trajectories produced in the HNL decay to leptons. The dominant background from uncorrelated leptons crossing in the ATLAS detector is estimated using an object shuffling method. The reconstructed HNL mass is used to discriminate between signal and background. No excess of events is observed and constraints on the strength of the interactions between HNLs and neutrinos are imposed in various scenarios.This dissertation also presents new methods to study the readout system and performance of a silicon strip tracking detector. The LHC is currently undergoing upgrades that will enable it to produce more than ten times the data that has already been collected. To meet the requirements of this challenging new environment, an all-silicon particle tracking system will be installed in ATLAS.

View record

The Standard Model (SM) has been hugely successful at explaining our natural world at the smallest scales, including the fundamental particles and forces. However, experimental evidence, such as dark matter and baryon asymmetry point to the SM as being an incomplete model. One such candidate to extend the SM are hidden sectors, in which long-lived particles could be the missing link between the SM and a group of hidden particles. Firstly, work on performance expectations of the upgrade to the ATLAS Inner Detector to enable data taking for the next decade will be presented, showing increases in reconstruction efficiency at high momentum and particle density compared to the current detector. Then, a search for hidden sector particles in 2016 ATLAS data, totalling 33.0 fb⁻¹ from LHC proton-proton collisions at center-of-mass energy of 13 TeV, will be discussed. This search focuses on long-lived particles decaying back to SM particles in the ATLAS calorimeters. No significant excess was found, and limits were set on cross section times branching fraction as a function of proper decay length. For the 125 GeV mediator, a few cm to a few m are excluded, assuming a branching fraction of 10%. For higher mass mediators, up to 1 TeV, cross section times branching fraction of 0.1 pb are typically excluded between a few cm to a few m. Finally, a search for these same long-lived hidden sector particles was also performed for the full Run 2 ATLAS dataset, totalling 139.0 fb⁻¹. Novel machine learning techniques were used, such as an adversarial neural network which greatly reduced the impact of simulation mis-modelling. No significant excess was found, and for a 125 GeV Higgs Boson mediator, assuming a 10% branching ratio to long-lived particles, proper decay lengths between about 1 cm and a few tens of meters are excluded, improving 2016 results by about an order of magnitude. For higher mass mediators, cross section times branching fraction of 0.1 pb can be excluded for a proper decay length between 1 cm to a few tens of meters, improving 2016 limits by a factor of 2-3 depending on the model.

View record

The standard model of particle physics (SM) describes all the fundamental particles and their interactions. It is a very successful theory; however, many experimental observations - such as the origin of neutrino mass, particle origin of dark matter, e.t.c. - are either not consistent or not explained by the SM. So, it is inevitable that there has to be a (physics) model beyond the SM which will consistently explain all these observations, not covered by the SM. Several of such extensions predict new heavy particles that can interact with SM particles. This dissertation presents searches for the resonant production of such high-mass particles in dielectron and top-antitop final states. These searches use proton-proton collision data at the center-of-mass energy of 13 TeV collected by the ATLAS detector at the Large Hadron Collider (LHC) between 2015 and 2018. Electrons are stable and easy to reconstruct, but top-quarks decay instantaneously. Two dominant top-decay final states, all-hadronic and semi-leptonic, are studied in this dissertation. The combined mass distributions of all the final-state particles are used to perform model-dependent and model-independent statistical searches. No evidence for the existence of new particles is found in any of the explored final states. Hence, upper limits on production cross-section times branching ratio and lower limits on the mass of heavy Z' particles, predicted by the BSM models, are placed at a 95% confidence level. The dilepton resonance search excludes Z' boson below 3.6 TeV. The resonance search in the boosted all-hadronic top-antitop final state excludes Z' bosons with a mass lower than 4.1 TeV. Whereas in the semi-leptonic search, the same signal is expected to be excluded up to 3.6 TeV.The dissertation also presents a new algorithm for splitting the merged charge clusters in the ATLAS pixel detector, based on a Mixture Density Network (MDN). The performance of this new algorithm is found to be better than the existing algorithm. As a result, the MDN-based algorithm is expected to be used as a default algorithm in ATLAS during the next data collection period, which will start in 2022.

View record

The precise understanding of elementary particle properties and theory parameters predicted by the Standard Model of Particle Physics (SM) as well as the revelation of new physics phenomena beyond the scope of that successful theory are at the heart of modern fundamental particle physics research. The Large Hadron Collider (LHC) and modern particle detectors provide the key to probing nature at energy scales never achieved in an experimental controlled setup before. The assumption that the SM describes nature only up to a certain energy scale Λ can be relaxed if new particles are present. This helps in particular with the so called "fine-tuning" problem which requires large corrections -- in the SM -- to the bare mass of the Higgs boson in order to be consistent with the observed mass. A possible solution to this problem is the existence of partner particles of the heaviest known fundamental particle, the top-quark. The new partner particles are expected to be up to ten times heavier. Popular examples of theories predicting heavier top-quark partners are supersymmetric theories and theories that add an additional quark sector to the SM which might be a result of an additional spontaneously broken global symmetry. This dissertation documents two searches for heavy top-quark partners, namely vector-like quarks (VLQs), based on the proton proton pp collision data collected in 2015 and 2016, corresponding to an integrated luminosity of 36.1 fb-¹ at a center of mass energy of 13 TeV. It also elaborates on the work that contributed to a successful data taking campaign related to the alignment of the inner most part of the ATLAS detector with emphasis on the identification and mitigation of track parameter biases.No signs for VLQs were found. The strongest lower mass limits on the pair-produced VLQs decaying into W bosons and top- or bottom-quarks are set to 1.35 TeV at the 95% Confidence Interval exceeding the one TeV scale for the first time. In addition, the analyses were re-interpreted for other expected VLQ decay signatures.

View record