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Graduate

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The Dark matter Experiment using Argon Pulse-shape discrimination will be a tonne scale liquid argon experiment to detect scintillation light produced by interactions with weakly interacting massive particles, leading dark matter candidates. The detector will be constructed out of acrylic and use a spherical array of 266 photo-multiplier tubes (PMTs) to count photons produced by an event and will use properties of liquid argon to discriminate signals from background events. There is currently a smaller prototype in operation underground at SNOLAB an underground laboratory in eastern Canada. The goal of the prototype detector is to understand the sources of background signals in a detector of our design and to validate our method of distinguishing different types of background radiation. The work presented herein is a series of studies with the common goal of understanding the source of background signals, and improving the resolution and efficiency of the detector.

Un des principaux objectifs de l'expérience ATLAS auprès du LHC est l'observations ou l'exclusion de nouvelle physique au-delà du Modèle Standard, en passant par les mesures de sections efficaces de production de processus du Modèle Standard. Sachant que le taux de production d'une particule dépends de sa section efficace de production ainsi que de la luminosité, il est necessaire de mesurer cette luminosité avec une grande précision. L'expérience ATLAS possède plusieurs détecteurs capable de mesurer la luminosité, dont les deux principaux: LUCID (Luminosity measurement Using Cerenkov Integrating Detector), et BCM (Beam Condition Monitor). Ces détecteurs sont calibrés absolument pendant des prises de données dédiées appelés van der Meer scans, qui ont permis d'obtenir une erreur systématique sur la détermination de la luminosité de 3.4% en 2010. Afin d'obtenir un maximum de différentes approches à la luminosité, plusieurs autres détecteurs contribuent aux différentes comparaisons. Ce document présente les calorimètres à argon liquide du détecteur ATLAS, et en particulier la mise en route et l'opération de leur système haute-tension. Il est montré qu'en mesurant les courant de ce système haute-tension pendant les prises de données de collisions de protons, il est possible d'obtenir des signaux proportionnels a la luminosité. En calibrant ces courants par rapport a un autre luminomètre, il est montré que cette calibration est stable au niveau de 0.5%. / The main goals of the ATLAS scientific programme are the observation or exclusion of physics beyond the Standard Model (SM), as well as the measurement of production cross-sections of SM processes. As the rate of events N of a given physics process is linked to the cross-section through the luminosity, it is important to measure the luminosity with great precision. The ATLAS experiment has two major luminosity monitors, LUCID (Luminosity measurement Using Cerenkov Integrating Detector), which consists of Cerenkov tubes located around the beam axis 17m away from the interaction point, and BCM (Beam Condition Monitor) which is a diamond-based detector and has both beam-abort and luminosity capabilities. As these detectors provide a relative luminosity measurement, they were absolutely calibrated in 2010 using the van der Meer procedure, achieving a total systematic uncertainty of 3.4%. The ultimate plan is to provide an absolute calibration using the ALFA detector during a run with special beam optics. In order to provide more cross-checks and a better control on the systematic uncertainties, other luminosity handles are always needed. In particular, an independent measurement using the liquid argon forward calorimeter (FCal), based on the readout current of its high-voltage system, has been developed. This document presents the commissioning and operations of the ATLAS liquid argon calorimeter high-voltage system, as well as its usage to perform a luminosity determination. Analysis of the high-voltage currents during LHC collisions and comparisons with other luminosity detectors have led to a calibration of these currents with a precision better than 0.5%.

The anomalous Low Energy Excess (LEE) of electron neutrinos and antineutrinos in MiniBooNE has inspired both theories and entire experiments to probe the heart of its mystery. One such experiment is MicroBooNE. This dissertation presents an important facet of its LEE investigation: how a powerful systematic can be levied on this signal through parallel study of a highly correlated channel in muon neutrinos. This constraint serves to strengthen MicroBooNE's ability to confirm or validate the cause of the LEE and will lay the groundwork for future oscillation experiments in Liquid Argon Time Projection Chamber (LArTPC) detector experiments like SBN and DUNE. In addition, this muon channel can be used to test oscillations directly, demonstrated through the world's first muon neutrino disappearance search with LArTPC data.

Liquid Argon Time Projection Chambers (LArTPCs) represent one of the most widely utilized neutrino detection techniques in neutrino experiments, for instance, in the Short Baseline Neutrino (SBN) program and the future large-scale LArTPC: Deep Underground Neutrino Experiment (DUNE). The high-end technique, facilitating excellent spatial and calorimetric reconstruction resolution, also enables testing exotic Beyond Standard Model (BSM) theories, such as baryon number violation (BNV) processes (e.g., proton-decay, neutron-antineutron oscillation). At the same time, Machine Learning (ML) techniques have demonstrated their ubiquitous use in recent decades; ML techniques have also become some of the most powerful tools in high-energy physics (HEP) analyses. Furthermore, the development of algorithms to cater to the needs of problems in HEP (i.e., triggering, reconstruction, improving sensitivity, etc.) has also become an active area of research. By developing a combined approach using Convolutional Neural Network (CNN) and Boosted Decision Tree (BDT) techniques, the sensitivity of neutron-antineutron oscillation in DUNE is evaluated for a projected exposure of 400kton⋅ years. Additionally, to meet the triggering requirement to select such rare events in DUNE, such a search is only supported with highly efficient self-triggering algorithms. An ML-based self-triggering scheme for large-scale LArTPCs, such as DUNE, is also developed with the intention of implementation on field-programmable gate arrays (FPGAs). The ML-based approach for searching for neutron-antineutron oscillation can be demonstrated and validated on the current LArTPC MicroBooNE. The analysis in MicroBooNE represents the first-ever search for neutron-antineutron oscillation in a LArTPC. DUNE's projected 90％ C.L. sensitivity to the neutron antineutron oscillation lifetime is 6.45✕10³² years, assuming 1.327✕10³⁵ neutron⋅ years, equivalent to 10 years of DUNE far detector exposure (400kton⋅ years). For MicroBooNE, assuming 372 seconds of exposure (equivalent to 3.13✕10³⁶ neutron⋅ years), the 90% C.L. lifetime sensitivity is found at 3.07✕10²⁵ yrs, after accounting for Monte-Carlo statistical uncertainty and systematic uncertainty from detector effects.

MicroBooNE is a liquid argon time projection chamber that collected neutrino data at Fermilab's Booster Neutrino Beam from 2015 to 2020. One of its primary goals is to investigate the “Low Energy Excess” of neutrino events observed by the MiniBooNE experiment, for which candidate photon-like interpretations include an underestimation of neutrino neutral current (NC) resonant Δ production with subsequent radiative decay or another anomalous source of single photon production in neutrino interactions. In particular, NC Δ radiative decay is poorly constrained background process to electron neutrino measurements and could be a sizable contribution to the “Low Energy Excess.” This thesis will present the analysis developed to search for NC Δ → N𝛾 events in MicroBooNE, consisting of a boosted decision tree based event selection with an NC neutral pion background constraint, using data from the first three years of operations corresponding to 6.9 × 10²⁰ POT.

A test-bench is created that injects digital pulses that emulate ATLAS LAr Front End Board electronic signal pulses in order to test prototypes. The prototypes are for new electronics for an upgrade to the CERN Large Hadron Collider that increases the rate of proton-proton collisions by an order of magnitude. This High-Luminosity Large Hadron Collider requires a completely new Trigger and Data Acquisition system to deal with information from detectors. One such system that is currently being developed is the Liquid Argon Signal Processor (LASP) whose architecture is based on Field Programmable Gate Arrays (FPGA). Validation of individual modules of the LASP are of key importance in the development cycle. Additionally, verification of module behaviour with real ATLAS pulses will not be available until much later in the project timeline. The injector project is implemented on an Intel Stratix 10 FPGA, using a soft-core NIOS II processor for TCP/IP communication with a workstation in order to transfer Monte Carlo simulation pulses to the FPGA, where it is then stored in a 2 GB DDR3 external memory. The pulses are then retrieved into internal memory buffers and are transmitted to the LASP at 40 MHz. The user is in complete control of the data pulses injected which is a vital property that would test LASP behaviour for different cases and possible failure modes. / Graduate