Ph.D. - Physics

Permanent URI for this collectionhttps://hdl.handle.net/10125/2136

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Forbush decreases with AMS-02 data and 2D time-dependent modeling
(University of Hawai'i at Manoa, 2025) Wang, Siqi; Bindi, Veronica; Physics
Galactic cosmic rays (GCRs) are high-energy charged particles originating outside the solar system. Their transport through the heliosphere is significantly influenced by solar activity, leading to both long-term modulation over the solar cycle and short-term disturbances such as Forbush decreases (FDs) caused by transient solar events like Interplanetary Coronal mass ejections (ICMEs). This thesis presents an integrated observational study of solar modulation, with a particular focus on FDs observed by the Alpha Magnetic Spectrometer (AMS-02). A detailed event-level analysis was performed using daily flux measurements of protons and helium nuclei, enabling the identification and characterization of FD properties such as amplitude, rigidity dependence, and correlation with solar wind parameters. To interpret these observations, a two-dimensional Stochastic Differential Equation (SDE) numerical model was developed to solve Parker’s transport equation under realistic heliospheric conditions. The model includes both diffusion and drift transport mechanisms, and the diffusion and drift coefficient scaling factors were set as free parameters and optimized using Bayesian optimization to match AMS-02 data for each month. The model was further extended to simulate short-term modulation effects from ICMEs by incorporating radially propagating diffusion barriers. The additionally introduced free parameters related to ICME geometry factors were obtained from satellite observation or tuned using Bayesian Optimization with the AMS daily flux on the ICME onset day. The result model was used to reproduce the daily fluxes during the recovery phase for the same FD. The combination of high-precision AMS-02 observations and physically grounded modeling offers new insight into the interaction between GCRs and transient solar phenomena. The methodology developed here provides a robust framework for studying space weather–driven modulation and supports future advancements in real-time forecasting and heliospheric transport modeling.
Towards a cosmic-ray and atmospheric deuteron search with the GAPS experiment
(University of Hawai'i at Manoa, 2025) Gerrity, Cory Christopher; von Doetinchem, Philip; Physics
The primary purpose of the balloon-borne General Anti-Particle Spectrometer (GAPS) experiment is to conduct a low-energy ($<$0.25 GeV/$n$) cosmic antinuclei search, optimized for the detection of antideuterons in particular. GAPS seeks to shed light on the potential particle nature of dark matter via indirect detection of these light cosmic-ray antiparticles, which are expected to be produced in dark matter annihilations or decays. This thesis focuses on deuterons for a number of reasons detailed as follows. Deuterons have high statistics relative to cosmic antinuclei and are essential to study GAPS detector effects. To claim an understanding of the complex GAPS reconstruction and identification, it is crucial to perform a deuteron analysis in conjunction with its primary proton background. There are a few reasons for this. A primary reason is because matter particles, such as deuterons, allow for the study of charged-particle energy depositions in the absence of annihilation phenomena. Therefore, a study of these particles will critically inform antideuteron identification, which is essential for the GAPS experiment’s primary mission as a low-energy antinuclei search. Deuterons and their background protons also provide a measurement for single-particle trigger events. In addition, in the GAPS energy range, the great majority of deuterons seen at the GAPS flight altitude will be atmospheric in origin. This provides an opportunity to quantify atmospheric effects for all GAPS measurements, and also to perform an atmospheric deuteron study based on its own merit. Therefore, a simulation-based study was performed for the deuteron analysis for the GAPS experiment. In addition, the process and results of the GAPS detector mass calibration effort, co-led by the author, is expounded upon. The primary goal of the calibration effort is to quantify the relative quality of the GAPS detector modules. This is accomplished via the use of an X-ray source with energies on the order of the exotic atom transition X-rays for antiparticles that are central to the GAPS technique. The successful results of this calibration effort are presented.
Directional recoil detection
(University of Hawai'i at Manoa, 2025) Ghrear, Majd; Vahsen, Sven E.; Physics
Dark matter remains one of the most profound mysteries in modern physics. Despite extensive astrophysical and cosmological evidence supporting its existence, its fundamental nature continues to elude us, driving the need for more sensitive experiments. Among these, direct detection experiments seeking to detect Weakly Interacting Massive Particles (WIMPs) through nuclear recoils have made significant progress, ruling out large regions of parameter space. As detectors increase sensitivity to probe lower masses and smaller cross sections, the once negligible neutrino background, known as the neutrino fog, becomes increasingly significant. For conventional detection methods, this background will eventually overshadow potential WIMP signals, limiting their ability to continue searching for WIMP dark matter. This dissertation focuses on directional recoil detection as a means to overcome the neutrino fog and extend dark matter searches into uncharted parameter space. This technique leverages the unique directional signature of galactic dark matter, which enables distinguishing the signal from backgrounds and unambiguously confirming the galactic origin of a positive signal. In this dissertation are four papers addressing different aspects of future directional recoil detection experiments and an exposition of the next generation detector in the Vahsen lab, the CYGNUS HD40. This dissertation presents several key contributions across the four papers and the detector exposition. A new gas mixture is proposed to enhance particle identification, along with a set of observables that can improve identification performance by up to two orders of magnitude. A novel deep learning method is developed for probabilistically predicting 3D direction, and an application of the method to electron recoil simulations demonstrates that it is capable of significantly enhancing directional performance while estimating directional uncertainty accurately. A detailed experimental comparison of various x/y strip readout configurations is conducted, providing insights for the design of future detectors and uncovering previously overlooked effects. A new method is developed for predicting the angular resolution of electrons in gas. The method is easy to compute if the electron energy and basic detector properties are known, making it a valuable tool for predicting detector performance and optimizing detector design. Finally, this dissertation introduces the CYGNUS HD40 detector, a step that could pave the way for scalable directional detectors in the future.
Thermodynamics of physical observers
(University of Hawai'i at Manoa, 2025) Daimer, Dorian; Still, Susanne; Physics
Observers are not abstract entities but physical systems subject to physical laws and limitations. This dissertation investigates the thermodynamics of physical observers, focusing on how physical limits shape intelligent information processing and decision-making under uncertainty. Two model classes of generalized, partially observable information engines are introduced and analyzed. They extend Szilárd’s classic thought experiment to settings where the observer must infer relevant information from available data. Observers memorize information and use it to take actions. A simple physical model for making the memory is introduced and the thermodynamic costs of different encoding strategies are analyzed. Thermodynamically rational encodings maximize the net engine work output. They are probabilistic in general and outperform naive coarse graining based encodings. Through analytical and numerical studies, physical codebooks for rational decision-making are developed, characterizing thermodynamically optimal decision-making strategies in two classes of binary decision problems under uncertainty. A mapping is established between abstract binary decision problems and partially observable Szilárd engines. This makes the physical framework used here widely applicable, intimately linking decision theory and thermodynamics. Extending the analysis of classical physical observers to quantum observers requires a description in terms of quantum thermodynamics. This is not a straightforward extension, as important thermodynamic concepts such as work and heat are not uniquely defined in quantum thermodynamics. Two definitions of thermodynamic work are compared for qubit systems and it is shown that they only agree under specific conditions. Their comparison reveals a discrepancy in the work costs required for perfect preparation of qubit states, with possible implications for high fidelity information processing in quantum systems. The research presented in this dissertation opens the door to a principled approach to understanding information processing, learning, and decision-making in physical systems, both biological and artificial. By incorporating the observer into the thermodynamic analysis, it provides a novel perspective on the interplay between physics, information processing and decision making under uncertainty.
Characterization of detection efficiency uncertainties in the measurement of reactor antineutrino absolute flux with the prospect experiment
(University of Hawai'i at Manoa, 2025) Meyer, Andrew Murphy; Maricic, Jelena; Physics
The Precision Reactor Oscillation and Spectrum Experiment (PROSPECT) was designed to investigateanomalies relating to the absolute flux and energy spectrum shape of antineutrinos emitted by 235U fissions in nuclear reactors, with a particular focus on searching for signs of sterile neutrino oscillations. The PROSPECT detector collected data from March to October 2018 at Oak Ridge National Laboratory’s High Flux Isotope Reactor. Although considerable work has been done to improve the measurements and models of the reactor antineutrino flux and spectrum, significant questions remain. This dissertation characterizes these anomalies and makes significant progress towards resolving them by using the PROSPECT dataset to measure the 235U antineutrino absolute flux, with a goal of obtaining a level of precision of roughly 2%, similar to the most precise measurement to date of the absolute flux made by the STEREO collaboration in 2023, through precise characterization of the uncertainties in the antineutrino detection efficiency.
Novel techniques and prospects for the indirect detection of dark matter
(University of Hawai'i at Manoa, 2025) Christy, Katharena Gertrude; Kumar, Jason; Physics
The microphysics of dark matter remains elusive nearly a century after its discovery. However,a promising window into the unknown is opened at the intersection of cosmology, particle physics, and astrophysics. The indirect detection of dark matter through its annihilation products is sensitive to the dark matter mass, annihilation cross section, and coupling properties to the standard model. Notably, secondary gamma rays are expected from annihilating thermal relic WIMPs that may be observable with current gamma-ray observatories. Here, we discuss the underpinnings of indirect detection and methods to enhance its discriminative power. We begin by testing the consistency of dark matter velocity distributions obtained from dark matter-only numerical simulations with analytic predictions, using the publicly available Via Lactea 2 dataset as an example. Next, we assess the ability of future MeV-range observatories to constrain the hadronic final states produced by light quark-coupling dark matter annihilation or decay. The unique spectral features of resulting π0 and η decays provide statistical resolving power and insight into the dark matter to quark current coupling. We then consider constraints on p-wave dark matter in a density spike surrounding the supermassive black hole at the center of M87. Due to the large velocity dispersion of dark matter particles in the spike, it is possible to place tight constraints on p-wave annihilation with Fermi-LAT and MAGIC data. By applying Approximate Bayesian Computation to a mock analysis of the diffuse gamma-ray background, we show that parameter constraints can be tightened beyond those possible in exact likelihood analysis. In our model of isotropic backgrounds and dark matter annihilation in galactic subhalos, this method allows for the inclusion of energy information in posterior estimates, whereas the corresponding likelihood is computationally intractable. Finally, we develop a method for analyzing the Fermi Galactic Center gamma-ray excess that relies on simulation-based inference with neural posterior models to jointly analyze photon directional and spectral information. We demonstrate the ability to significantly differentiate between the millisecond pulsar and annihilating dark matter hypotheses.
Scalar fields in cosmology and their applications beyond the standard cosmological model
(University of Hawai'i at Manoa, 2025) Ramadan, Omar Fawzy Muhammed; Sakstein, Jeremy; Physics
This dissertation investigates key challenges in cosmology and astrophysics through the development and analysis of models for early dark energy, dynamical dark energy, and CP-violating axion-like particles (ALPs). First, we introduce a novel early dark energy (EDE) model, @EDE, aimed at resolving the Hubble tension by injecting energy before recombination to reduce the sound horizon size and increase the inferred value of H0, thereby addressing the tension between early- and late-time cosmological measurements. We analyze the model’s impact on the Universe’s expansion history and test its viability against cosmological data. Next, we examine two dynamical dark energy models—the single-exponential quintessence model and the pixelated dark energy model—in light of recent DESI BAO observations, which show a growing preference for time-varying dark energy over a cosmological constant. While the w0–wa parameterization provides a better fit to the DESI data than ΛCDM, the quintessence model fails to replicate the rapid low-redshift transition in the equation-of-state implied by the data. In contrast, the pixelated model, in its simplest form with a constant pixel growth rate, is marginally preferred over ΛCDM. However, extending it to allow for time-dependent growth significantly enhances its ability to match the observed equation-of-state behavior. Lastly, we explore the cosmological and astrophysical effects of CP-violating axion-like particles, deriving constraints on their properties and evaluating their influence on neutron star structure and the mass-radius relationship. This work provides fresh theoretical perspectives and practical tools to address unresolved questions in modern cosmology and astrophysics.
DNN-based NMR Artifact Correction Method
(University of Hawai'i at Manoa, 2024) Nam, Sejin; Browder, Thomas TB; Physics
Nuclear Magnetic Resonance (NMR) spectroscopy, a pivotal analytical technique in physics, chemistry, biology, and medicine, is frequently challenged by spectral distortions arising from various artifacts. These distortions can significantly hinder the accurate interpretation of NMR data, necessitating advanced correction methods. Thus, there have been many analytical methods to correct NMR artifacts, such as baseline distortion correction. This work introduces a deep learning-based approach for correcting NMR artifacts with bidirectional recurrent neural networks (BRNN) and convolutional neural networks (CNN). By simulating different types of datasets and applying these neural network architectures, this work demonstrates remarkable success in mitigating persistent NMR artifacts, mainly baseline and phase shift distortions. The proposed model was evaluated by calculating the accuracy of peak integration on real-world NMR spectra corrected by both the model and the conventional methods. The symmetricity of peaks from artifact-corrected spectra on actual NMR samples was calculated. Then, symmetricity was used to numerically assess the peak amplitude values for both distorted and symmetric peaks and calculate the accuracy of both correction methods. Compared to traditional analytical methods, the proposed deep learning approach offers alternative ways to deal with NMR artifacts. Since the DNN approach is an automated NMR artifact correction, by applying consistent algorithms to identify and address artifacts, automated methods eliminate the potential for human bias. For a new type of NMR samples where the nature of baseline and phase shift distortion artifacts are different from previously known artifacts, researchers can focus on generating large sets of such data instead of developing computational methods to correct the artifacts. In order to facilitate such an approach, the model architecture is tested for memory efficiency for GPUs that are easily obtainable at the time of this writing, which allows training on GPUs with limited VRAM, unlike other DNN models designed for tasks of a similar nature.
Direct Dark Matter Search with the DarkSide Experiment
(University of Hawai'i at Manoa, 2024) Goicoechea Casanueva, Víctor; Maricic, Jelena; Physics
While the existence of dark matter has been largely accepted in the scientific community, its fundamental nature remains a mystery. Numerous experiments and collaborations aim to measure dark matter interactions arising from different theories, yet dark matter continues to elude us. Despite this, weakly interacting massive particles (WIMPs) stand out as one of the most compelling candidates that may explain the dark matter mystery. The DarkSide program aims to directly detect WIMPs with dual-phase argon time projection chamber (LAr TPC) technology. Currently in the construction phase at LNGS, Italy, the next-generation detector DarkSide-20k will be a 20-tonne fiducial volume argon TPC and is expected to set the best WIMP limits for masses above 1 TeV/c^2. This work focuses on three main aspects of the DarkSide program: calibration strategies and event position reconstruction methods for the DarkSide-20k detector, and a heavy dark matter (HDM) search with DarkSide-50, in which the case of composite HDM with varying dark nucleon masses is considered for the first time in the dual-phase argon TPCs.
NTC, NuLat, and miniTimeCube: The Development of Compact, Mobile, Neutral Particle Detectors
(University of Hawai'i at Manoa, 2019) Dorrill, Ryan Christopher; Learned, John G.; Physics
"Neutrinos remain a subject of fascination and mystery in the field of particle physics. Their masses are still unknown, it's uncertain whether they are their own anti-particles, and it is still possible that there is a fourth 'sterile' neutrino. On top of this, they are one of nature's most difficult phenomena to detect, often passing through ordinary matter without leaving a trace. Nonetheless, these particles have been undergoing investigation since their discovery in 1956 and detector technology has been steadily improving since then. Most traditional detectors are very large structures such as Super-K or Ice Cube, but a new generation of compact detectors is being developed to allow for investigation of these and other particles at new baselines and in new locations. Here we describe miniTimeCube (mTC), NuLat, and NTC, three compact particle detectors developed by UH with collaborators across the globe."
Multiclass Search for Cosmic Ultra-High Energy Neutrinos with ANITA-IV
(University of Hawaii at Manoa, 2023) Russell, John Walsh; Learned, John G.; Physics
The Antarctic Impulsive Transient Antenna (ANITA) is a balloon-borne experiment that suspends over the Antarctic ice sheet to detect upcoming radio pulses. Its goal is to see radio pulses originating from a rare interaction between Ultra-High Energy (UHE) neutrinos and ice to produce a shower of charged particles. The electromagnetic radiation produced from this shower is known as Askaryan radiation. The sensitivity at which ANITA needs to detect these events means most of the data ANITA collects is background. This background comes from multiple sources, from natural sources like the sun and electromagnetic discharge aboard the instrumentation to anthropogenic sources like satellites and research base communication. Also collected by ANITA are signals associated with radiation from charged particle showers produced in the air interacting with the Earth's magnetic field. In contrast to the radio pulses in the ice that are expected to be vertically polarized, these events are found to be horizontally polarized. Past analyses have focused on designing final cuts to remove thermal background, considering it to dominate over other types of background. However, after selecting events that look most like signals of interest, I estimate an upper limit to how many of them could be misclassified background. My exploratory analysis found 33 events, with 32 estimated as belonging to classes with horizontal polarization and one with vertical polarization.
Development of Digital Architectures for Pixelated Readout of Time Projection Chambers: Q-Pix
(University of Hawaii at Manoa, 2023) Keefe, Kevin; Nishimura, Kurtis; Physics
The Standard Model (SM) of physics has proven successful over the past decades, despite several measurements that indicate its incomplete description of nature.The search for New Physics (NP) continues at higher energies with larger detectors. One such future detector is the Deep Underground Neutrino Experiment (DUNE). DUNE is a combination of two detectors, a near detector (ND) and a far detector (FD), which will be used together to search for Charge-Parity Violations (CPV) in the lepton sector. The DUNE FD will be a combination of four large ($\approx$~10~\unit{kT}) Liquid Argon Time Projection Chambers (LArTPC). Each 10-kT FD requires high precision in both time ($\le~1~\mu s$) and spatial resolution ($\approx$~1~\unit{mm}) for vertex reconstruction and particle identification (PID) of neutrino events. This dissertation discusses the progress and characterization of a novel implementation of a new pixelated LArTPC readout technology that can be used in an FD.This novel readout is based on a pixel-level charge-integrate-reset circuit: Q-Pix. We present the basic pixel-level readout circuit and the implications of such an implementation when used in kiloton LArTPCs. We also show results from the first prototype implementation based on the Q-Pix readout, which was designed using only off-the-shelf electronics. One problem with any pixelated readout is the ability to handle a large number of unique data channels, which in the case of the DUNE-FD is $\approx 10^8$.To address the scaling problem, we have developed and tested a modular digital back-end prototype as a proof of concept. This prototype is based on the first Q-Pix digital ASIC design also presented in this thesis. We discuss the back-end system requirements for a Q-Pix based readout technology to provide neutrino oscillation measurements up to 10~\unit{GeV}, and present the first demonstration of local oscillator calibrations ($\sim$~0.1~\unit{ppm}). Simulations were performed based on radiogenic backgrounds and high-energy neutrino beam line events, providing first constraints on digital back-end requirements in both the quiescent and active states. Finally, based on these results from the simulations and prototypes presented here, we discuss the digital back-end readout of a fully realized Q-Pix implementation within a 10~\unit{kT} DUNE-FD module.
Low-Energy Physics in Liquid Argon Time Projection Chambers
(University of Hawaii at Manoa, 2023) Dvornikov, Olexiy; Maricic, Jelena; Physics
The Deep Underground Neutrino Experiment (DUNE) will be at the frontier of neutrino physics. However, its goals require unprecedented calibrations of charge, light readout, and the detector electric field. Especially for the subcomponents exposed to an intense neutrino beam. Particles traversing liquid argon time projection chambers (LArTPCs) leave behind wakes of ionization electrons. DUNE, whose main components are LArTPCs, will image the topologies of these wakes with ~ 0.5 cm precision and ~500 ns timing resolution and, based on the kinematics, identify the particle species and interaction types. In other words, DUNE will conduct precision neutrino physics. This thesis is a calibration and a study of ~ 10 - 100 MeV electromagnetic interactions in LArTPCs. Although DUNE will be sensitive to a wide range of energies, this work focuses on the low end. Also, this thesis is a calibration of LArTPC electric fields. At the MeV scale, DUNE will be sensitive to solar, supernova, and perhaps even exotic neutrinos. However, this sensitivity rests squarely on detector calibrations. This thesis examines ~ 10 MeV and 236 MeV with measured delta-rays and simulated anomalous kaon decay-at-rest (KDAR) neutrinos respectively. I show that the ~ 10 MeV response differs from predictions by < 10%. This is very encouraging for neutrino astronomy. I also show that DUNE will be sensitive to very low anomalous neutrino fluxes from the Sun. This is exciting for testing dark matter models which can be linked to neutrinos. This work also measures the spatial offsets (at the ~ mm level) due to electric field distortions in DUNE prototypes, highlighting possible defects and the need for meticulous field characterization for future LArTPCs.
Light nuclei and antinuclei production in proton-proton interactions
(University of Hawaii at Manoa, 2023) Shukla, Anirvan; Von Doetinchem, Philip; Physics
Identifying the nature of dark matter is a major unsolved problem in physics. The detection of low-energy cosmic-ray antinuclei could provide a "smoking gun" signature of dark matter annihilation or decay, as they are produced essentially free of the astrophysical background. Such a detection could also indicate new astrophysical phenomena like undiscovered antimatter sources in our Galaxy. The main source of astrophysical antinuclei background are the interactions of cosmic-ray protons with hydrogen in the thin interstellar gas. However, their formation process is poorly understood. The impact of new-physics searches with cosmic-ray antinuclei can be increased by reducing uncertainties related to antinuclei formation modeling. For that purpose, this dissertation discusses how the coalescence mechanism for (anti)deuterons was extended to estimate the production of antihelium in cosmic-ray interactions. The results were used to model how antinuclei are transported in our Galaxy, to predict the antinuclei flux received at Earth. The production mechanism of light antinuclei have been studied in accelerator-based experiments before. However, very few proton-proton measurements exist at energies which are relevant for cosmic-ray antinuclei production. Modeling of antinuclei formation also requires high-precision measurements of antiproton production. These factors motivate the analysis of new large p-p data sets from modern particle accelerator experiments. NA61/SHINE is a fixed-target experiment at the CERN-SPS, which studies hadron-nucleus and nucleus-nucleus collisions for various physics goals. This dissertation presents new measurements of proton, antiproton, as well as pion and kaon spectra, using the high-statistics p-p data from NA61/SHINE. The new results significantly extend the phase space coverage in rapidity and transverse momentum, as compared to previous results. They also dramatically reduce uncertainties in antiproton production. The first measurements of deuteron production at energies relevant for cosmic-ray studies are presented. The viability of measuring antideuteron production and two-particle angular correlations, with the recently-upgraded NA61/SHINE detector, is also shown.
Topics on Dark Matter and Active Galactic Nuclei
(University of Hawaii at Manoa, 2022) Runburg, Jack; Kumar, Jason; Farrah, Duncan; Physics
Despite gravitational evidence at many spatial scales and significant experimental efforts, non-gravitational detection of dark matter has thus far been unsuccessful.Indirect dark matter detection, one of several strategies to find confirmation of the existence of dark matter and untangle its properties, aims to identify dark matter through its self-annihilation products. In particular, self-annihilation processes of thermal relic dark matter candidates (WIMPs) may produce gamma rays, providing a potentially observable signature of dark matter. After 'freezing out' of thermal equilibrium, hierarchical structure formation in cold dark matter models produces abundant `halos' and 'subhalos' of gravitationally bound dark matter clumps that host the galaxies and clusters we see today. Depending on their size and history, these halos are characterized by different dark matter velocity scales, suppressing or enhancing annihilation rates depending on the velocity-dependence of the cross section. This dissertation considers the prospects of detecting dark matter with a velocity-dependent self-annihilation cross section in dwarf spheroidal galaxies, extragalactic halos, the Milky Way center, and in galactic substructure. We will find that the angular distribution of gamma rays from dark matter annihilation and the overall normalization of the flux are sensitive to both the microphysics and the astrophysical distribution of the dark matter. A key challenge in all of these analyses are the considerations of gamma ray backgrounds from other astrophysical sources. Blazars, star-forming galaxies, and cosmic rays all contribute to gamma ray fore-/backgrounds. Without better understanding and modelling of these sources, indirect searches for dark matter are going to be stymied. The luminosity function (LF) of active galactic nuclei (AGN) describes the population of AGN as a function of redshift and luminosity. Estimates of gamma ray backgrounds from unresolved AGN can be obtained from the faint end of the AGN LF. Towards this goal, this dissertation presents the AGN LF constructed using midinfrared and X-ray data in the XMM-LSS field. I close with discussions on how AGN LFs can be used to model gamma ray backgrounds in indirect detection analyses and how newer machine learning methods may overcome some of the challenges of both current AGN LF analyses and dark matter searches.
Unusual Near-Horizon Cosmic-Ray-Like Events Observed by the Fourth Flight of ANITA
(University of Hawaii at Manoa, 2022) Prechelt, Remy; Gorham, Peter W.; Physics
Despite decades of experimental observations, the astrophysical sources producing the measured flux of ultrahigh energy cosmic rays (UHECRs) have yet to be identified. Neutrinos, extremely weakly interacting neutral particles, are expected to be produced inside the astrophysical accelerators responsible for the production of UHECRs, and during the propagation of UHECRs to Earth. As neutral weakly-interacting particles, ultrahigh energy neutrinos are perhaps the best probe of the hadronic and leptonic processes governing these extreme astrophysical environments beyond the local universe. Yet, despite two decades of experimental searches, ultrahigh energy neutrinos have never been definitively detected. ANITA-IV, the fourth flight of the ANtarctic Impulsive Transient Antenna (ANITA), observed four anomalous events extremely close to the horizon. In this dissertation, I present the possibility that one or more of these anomalous “near horizon” events are indeed ultrahigh energy tau neutrinos detected via the unique Earth-skimming “tau air shower channel”. I develop the first “end-to-end” simulation of ANITA-IV’s sensitivity to these unique events and I use this simulation to determine whether these events are observationally consistent with tau-lepton-induced extensive air showers and, if they are, what are the constraints on the implied flux from populations of diffuse and point-like neutrino sources. Finally, I perform a blind search for any statistically significant associations between these four anomalous events and catalogs of astrophysical sources that are considered to be possible ultrahigh-energy neutrino and cosmic ray emitters. I find that these events are not observationally inconsistent with ultrahigh energy tau neutrinos, but that the implied (diffuse) flux and (point-like) fluence necessary to explain these events is in strong tension with limits set by other observatories, such as the Pierre Auger Observatory and IceCube. After unblinding the results of my search for associations between these events and catalogs of sources that have the potential to be UHECR sources, I find no statistically significant associations with any of the considered sources.
From neutrons to dark matter: Directional recoil detection and utilization of deep learning for gaseous time projection chambers
(University of Hawaii at Manoa, 2022) Schueler, Jeffrey Thomas; Vahsen, Sven E.; Physics
Modern gaseous time projection chambers (TPCs) with high readout segmentation are capable of reconstructing detailed 3D ionization distributions with voxel sizes of order (\SI{100}{\um})$^3$. This enables measurements of the 3D momentum vectors of short, mm-scale nuclear recoils, which is of interest for neutron measurements, as well as searches for dark matter, where directionality opens the possibility of identifying the galactic origin of weakly interacting massive particles (WIMPs), even below the so-called neutrino floor. We perform a variety of experiments and simulations with eight miniature TPCs filled with a 70:30 mixture of He:CO$_2$ gas at \SI{1}{atm} pressure. Each so-called BEAST TPC is of identical design and contains two gas electron multiplier (GEM) amplification devices and a $(2.00\times 1.68)~\text{cm}^2$ pixel-ASIC readout. We first detail the measurement of neutron backgrounds at the SuperKEKB $e^+e^-$ collider in Tsukuba Japan. We focus on measurements surrounding SuperKEKB's final focusing magnets (recorded in 2018) and in the accelerator tunnel surrounding the Belle II detector (recorded in 2020-2021). In our analyses we reject large X-ray backgrounds from the accelerator, resulting in $>$99$\%$ pure samples of nuclear recoils down to recoil energies as low as \SI{8.0}{keV_{ee}}. We find excellent agreement between measured and simulated nuclear recoil energy spectra indicating that our simulations model neutron production well. We additionally introduce a correction for charge integration bias in observed recoil tracks with high axial inclination. This correction leads to correct vector directional ``head-tail" (sign of 3D vector) assignment for $91\%$ of simulated He recoils ranging from $\SI{40}{keV_{ee}}$ to about $\SI{1}{MeV_{ee}}$, with a mean angular resolution of 8$^\circ$; a significant improvement over the $72\%$ head-tail efficiency achieved without these corrections. Applying this technique to measurement leads to an agreement between measured and simulated angular distributions that allows us to conclude the existence of a neutron production hotspot in the accelerator tunnel. While the BEAST TPCs are highly sensitive to ionization, and can detect even single electrons, extending directionality to the keV-scale, as is desirable for dark matter searches, requires operating the detectors with lower-density gases, at higher gains, and developing improved analysis techniques. We here focus on the two latter aspects. We improve on existing head-tail classification methods through the introduction of deep-learning computer-vision algorithms called 3D convolutional neural networks (3DCNNs). We first perform a simulation benchmark study where we train a 3DCNN to assign directional head-tail to simulated neutron recoils with energies up to \SI{515}{keV_r} and compare these results to three existing methods of head-tail assignment. We find a head-tail efficiency of $99.9\%$ on this sample using the 3DCNN, compared to $97.8\%$, $93.7\%$, and $79.0\%$ for existing methods. Next, we measure neutrons from a $^{252}$Cf source incident on separate sides of a TPC. We operate both at low gain and high gain. At low gain, the simulation-trained 3DCNN reliably identifies whether the observed recoil points toward or away from the $^{252}$Cf source. On a small sample of identified He recoils between \SI{39}{keV_{ee}} and \SI{49}{keV_{ee}}, before correcting for residual background such as back-scattered events, we observe a head-tail efficiency of $(62.1\pm 11.4)\%$. Using simulation, we show that the true head-tail efficiency after correcting for residual backgrounds should be greater than this, marking the first statistically significant observation of event-level head-tail sensitivity below \SI{50}{keV_{ee}}. At high gain, we attempt to improve our head-tail sensitivity to sub-10-$\rm keV_r$ recoils, and also introduce a 3DCNN for event identification. In simulation, we reject all X-ray backgrounds down to \SI{5}{keV_{ee}} at $50\%$ nuclear recoil selection efficiency and demonstrate head-tail efficiencies above $50\%$ for He recoils down to \SI{3}{keV_r}. These results do not yet generalize to measurement, which is currently being investigated. If the 3DCNN robustness can be improved, this would be the first demonstration of directional recoil detection at energies relevant for the directional detection of $\mathcal{O}(\text{GeV})$ dark matter particles. Finally, we perform a study comparing the keV-scale electron background rejection performance of a 3DCNN to the traditional discriminant of track length, as well as discriminants obtained from state-of-the-art shallow learning methods in a simulated detector with an 80:10:10 mixture of He:CF$_4$:CHF$_3$ at \SI{60}{torr}. We train the 3DCNN classifier using recoil charge distributions with ionization energies ranging from 0.5-\SI{10.5}{keV_{ee}} after \SI{25}{cm} of drift. The charges are initially segmented into (\SI{100}{\um})$^3$ bins when determining track length and the shallow learning discriminants, but are rebinned with a reduced segmentation of (\SI{850}{\um})$^3$ for the 3DCNN. Despite the courser binning, compared to using track length, we find that classifying events with the 3DCNN reduces electron backgrounds by an additional factor of up to 1,000 and effectively reduces the energy threshold of our simulated TPC by $30\%$ for fluorine recoils and $50\%$ for helium recoils. We also find that the 3DCNN reduces electron backgrounds by up to a factor of 20 compared to the shallow machine learning approaches, corresponding to a \SI{2}{keV_{ee}} reduction in the energy threshold. Collectively, the results in this thesis highlight the unique measurements enabled by high-resolution ionization imaging, and how 3D convolutional neural networks appear ideally suited to maximally utilize the rich 3D data from detectors with this capability.
New Approaches to Antineutrino Directionality
(University of Hawaii at Manoa, 2022) Duvall, Mark; Learned, John G.; Physics
The directional detection of electron antineutrinos undergoing inverse beta decay (IBD) has uses ranging from fundamental science (ex. sterile-neutrino searches, supernova physics) to industrial and even nonproliferation applications (ex. reactor analysis, fuel material, location). In this dissertation, we find that even under ideal conditions, the loss of directional information due to neutron scattering during thermalization and capture, limits traditional reactor-IBD detectors to a mean angular agreement of mean[cos(psi)] ~ 0.3, where psi is the difference angle between the true and reconstructed incoming antineutrino directions. We examine a proposed method and corresponding detector design which our simulations indicate could reach mean[cos(psi)] ~ 0.9, but is expected to struggle with background rejection and low data rates. By combining these approaches, we present a survey of novel reactor-IBD detectors designed to beat the limit imposed by neutron scattering while maintaining both a high signal rate and resilience against backgrounds. We discuss new related detection concepts and techniques as well.
Transient Solar Events and Their Effects on the Near-Earth Radiation Environment
(University of Hawaii at Manoa, 2021) Light, Christopher; Bindi, Veronica; Physics
The Sun is comprised of complex, constantly changing plasma and magnetic field structures. Some of these structures can become unstable over time, leading to a number of different eruptive events. Most notable for this work are magnetic reconnection events in the solar corona. These events classically produce a solar flare and a coronal mass ejection (CME). In addition, particles may be accelerated to high energies and ejected from the Sun during these events, we call these particles Solar Energetic Particles (SEPs). As CMEs and SEPs propagate outward through the heliosphere, they have a number of interesting effects. CMEs can have significant effects on the Earth's magnetic field, called geomagnetic storms, and both CMEs and SEPs cause significant changes in the radiation environment. The ionizing radiation environment in space is normally dominated by galactic cosmic rays (GCRs), but an SEP event can suddenly cause a very large increase in ionizing radiation. This radiation poses as serious risk to humans and electronics in space, which makes it an important subject of study as humanity increases its presence in space. The shock wave in front of a CME as it propagates through the heliosphere may also accelerate some solar wind particles to higher energy, but the dominant effect of a CME on the radiation environment is to increase local modulation, reducing the flux of GCRs. This modulation of GCRs is called a Forbush decrease (FD). The Alpha Magnetic Spectromer (AMS) is a particle detector onboard the International Space Station (ISS). The detector measures cosmic rays (CR) in the rigidity range from 0.8 GV up to TV (~300 MeV/nuc into the TeV/nuc) with unprecedented precision. The upper rigidity range of the SEP spectrum can be measured by the lowest rigidity range of AMS. Part of this work is analysis to produce SEP spectra from AMS measurements. These comprise the most precise measurements of SEPs that have been made in this rigidity range. They reveal a continuum of qualitatively similar SEP events, with broad changes in quantitative properties. There is still some question as to how the amplitude of FDs depends upon the rigidity of GCRs modulated, and how this behavior is related to the properties of the CME and the solar wind. This work investigates this question by providing a method for defining FDs, and studying FDs using data from neutron monitors, AMS, and solar wind measurements.
Search for the decay Bs0 → η' Xss̄ Using a Semi-Inclusive Method at the Belle Experiment
(University of Hawaii at Manoa, 2020) Dubey, Shawn; Browder, Thomas; Physics
The decay Bs0 → η' Xss̄ is searched for at Belle, using Belle’s 121.4/fbintegrated luminosity data sample, taken at Υ(5S) resonance. A semi- inclusive reconstruction method whereby the Xss̄ is reconstructed as a system of two kaons and up to four pions, with at most one neutral pion, is used. Using the η' sub-decay mode η'→ η (→ γγ ) π+ π− and examining the Xss̄ mass range M( Xss̄ ) ≤ 2.4 GeV/c^2 , an upper limit at 90% confidence level is set. This mode had been previously unstudied and this analysis partially hopes to motivate future theoretical studies as well as future analyses at the Belle II experiment.

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