Physical Sciences and Mathematics Commons^™

Quantum Control Of Qubits And Qudits In Neutral Atom Systems, Sri Datta Vikas Buchemmavari

Physics & Astronomy ETDs

This dissertation explores control of neutral atom quantum systems across multiple levels of abstraction, from atomic physics to system-level fault tolerance, using optimal control to improve performance. First, we propose a Rydberg entangling gate based on dressing with only the qubit control field; an interaction energy near the Rabi frequency benefits both gate speed and Rydberg decay. Second, with Sandia National Laboratories, we show that leakage errors in neutral atom systems can be converted to atom loss errors and detected using two entangling gates with an auxiliary atom, where a SWAP-based leakage detection unit outperforms the standard design. Next, we …

Strategies For Large Dynamic Range, Entanglement-Enhanced Quantum Metrology With Experimentally Demonstrated Resources, Tyler G. Thurtell

Physics & Astronomy ETDs

Quantum metrology studies the use of quantum mechanical systems as measurement devices or sensors. Surprisingly, preparing a sensor in an entangled state can enhance measurement precision. The simplest protocols for entanglement enhancement sense only small changes in a quantity. The range of values over which a measurement protocol works is called its dynamic range. For many types of sensors we require end-to-end protocols that describe how to use entanglement to achieve enhanced precision over a large dynamic range. In this dissertation, we describe two approaches to achieving entanglement-enhanced sensing over a large dynamic range. The first approach uses entangling resources …

Extending The Discovery Space Of Tess: Probing Underexplored Exoplanet Populations, Mallory L. Harris

Physics & Astronomy ETDs

This dissertation investigates how cold exoplanets can be identified despite the strong observational bias of exoplanet surveys toward short-period systems. Planets at wider orbital separations remain comparatively poorly constrained, limiting tests of planetary-system formation and the prevalence of outer architectures beyond compact systems. To address this gap, I use two complementary approaches. First, I develop a transit-search pipeline for TESS Full-Frame Images that identifies both isolated and repeated transit-like signals around nearby M dwarfs and characterizes the dominant false-positive classes that limit sensitivity in this regime. I then present TOI-904 c, the coldest planet discovered by TESS around an M …

An Investigation Of Tess M&Ms And The Occurrence Rate Of Transiting Circumbinary Planets, Dominic Oddo

Physics & Astronomy ETDs

Circumbinary planets (CBPs) are worlds which orbit two stars simultaneously. CBPs are excellent tests of the tenacity of planet formation, but are difficult to detect. The space-based NASA Transiting Exoplanet Survey Satellite (TESS) mission is a nearly all-sky survey designed to detect exoplanets transiting nearby stars. In this dissertation, I analyze the performance of TESS by comparing to the photometric precision of the ESA CHEOPS mission. Then, I define a catalog of low-mass eclipsing binaries (M&Ms), which are the best sources to search for CBPs. I describe my custom transit search methodology and apply it to the M&M catalog. I …

Simulating Quantum Field Theories On Fault-Tolerant Quantum Computers, Mason L. Rhodes

Physics & Astronomy ETDs

Quantum field theories are an essential framework in modeling fundamental interactions in nature, yet reliable simulations consume large portions of the world's most powerful supercomputers. In this Dissertation, we explore an alternative simulation paradigm on fault-tolerant quantum hardware, discussing both algorithmic and model advancements. In the former, we construct state-of-the-art algorithmic subroutines that take advantage of useful properties of the Hamiltonian describing the theory to achieve an exponential improvement in resources over prior quantum algorithms. In the latter, we simplify the structure of the Hamiltonian, making it more amenable to quantum simulation. First, we present an improved regularization of the …

Measurements And Studies For Rare Event Searches Using Directional Detectors, Elizabeth Tilly

Physics & Astronomy ETDs

Measuring topology and initial direction of low-energy (keV-MeV) particle tracks is interesting to rare-event searches. While directional dark matter searches have been one of the largest drivers for R&D for low-energy directional detectors, this work is interested in its application to Migdal searches. The Migdal effect—a nuclear recoil and an electron recoil sharing a vertex—has been used as a detection channel for low-mass dark matter but has only recently been measured. Low-energy directional detectors are ideal to measure the canonic Migdal topology. This dissertation discusses 3D reconstruction algorithms developed for the Migdal In Galactic Dark mAtter expLoration (MIGDAL) experiment and …

Exploring The Role Of A Mushy, Crustal Compliant Region In Volcano Deformation, Grant A. Block

Physics & Astronomy ETDs

Volcanoes are both creative and destructive forces that have shaped and continue to shape our world from early geologic time to the present day. Continued study of volcanic processes not only better prepares us for monitoring volcanic hazards but also allows us to better understand processes fundamental to Earth as we know it, such as the generation of the atmosphere and accretion of the continents. This dissertation focuses on an integral part of volcanic processes: the trans-crustal magmatic transport system. Specifically, we investigate regions of these transport systems where magma pools in melt-rich lenses within broader regions of low melt-fraction, …

New Distance Distributions Of Asymptotic Giant Branch Stars And Their Role In Tracing Galactic Structure, Rajorshi Bhattacharya

Physics & Astronomy ETDs

Asymptotic giant branch (AGB) stars are among the final evolutionary stages of low- and intermediate-mass stars and among the most luminous cool stellar populations in the Milky Way (MW). Their strong infrared emission allows them to be observed through regions of high interstellar extinction, making them useful tracers of the inner MW. However, their use is limited by unreliable distances because many are dust-obscured and variable, while geometric parallaxes are often unavailable or uncertain. This thesis develops statistical distance-estimation methods for large samples of oxygen-rich AGB stars. The resulting distances broadly agree with literature estimates, supporting their statistical reliability for …

Mining Legacy And Wildfires: Interfacial Reactions Affecting Metal Mobility, Eresay Alcantar-Velasquez

Earth and Planetary Sciences ETDs

We identified water labile interfacial reactions between laboratory burned pinewood ash and mine waste solids that influence metal mobilization. The Upper Gallinas Creek Watershed in New Mexico is affected by wildfires and mining legacy. Pinewood and mine waste sediments were sampled from the area, and the pinewood was burned at 350°C to simulate medium burn intensity ignition. Rapid desorption and gradual dissolution of Mn and Fe was detected by ICP-MS as pH decreased over time. After reacting 18 MΩ ultra-pure water with a mixture of pinewood ash and mine waste sediments Fe (143%) and Mn (89.2%) concentrations increased over time. …

Information Theory Analysis Of Water Vapor Stable Isotopes From The Sail Campaign, Matthew John Rybecky

Earth and Planetary Sciences ETDs

Understanding the processes that control water vapor isotopic composition in mountain environ- ments is essential for interpreting isotope records and predicting water resource responses to cli- mate change. This thesis applies information theory to continuous, high-resolution water vapor stable isotope measurements from the Surface Atmosphere Integrated Field Laboratory (SAIL) campaign in the East River watershed of Colorado’s Upper Gunnison Basin, spanning the winter- to-spring transition of 2022–2023. The analysis employs Shannon entropy, mutual information, transfer entropy, and joint transfer en- tropy (JTE) to quantify how environmental variables, including surface meteorology, radiation, tur- bulent fluxes, and ERA5 reanalysis products, transfer information …

Pebble Accretion: Compositions And Water Origins Of Terrestrial Planets, Susmita Garai

Earth and Planetary Sciences ETDs

Two leading models of planet formation invoke either stochastic collisions among km-sized planetesimals, or pebble accretion of sub-mm-cm solids regulated by gas drag. While collision based models typically require tens to hundreds of millions of years to assemble terrestrial planets, pebble accretion can produce Mars to Jupiter-mass bodies within the lifetime of the protoplanetary disk. Although widely accepted for the rapid growth of giant planet cores, the role of pebble accretion in forming terrestrial planets, including Earth, remains debated. Here, we investigate the consequences of pebble accretion for Earth’s origin. Here, I combine numerical models and laboratory experiments to find …

Gradients Of Abandonment, William Tatman

Geography ETDs

As urban-rural disparities drive depopulation in rural areas worldwide, local strategies emerge as pathways for resilience. Research on Ojika, a Japanese island that has lost 75% of its population since the 1960s, reveals an Abandonment Gradient: a nuanced pattern of disuse adapted to modern polycrises. Extending the concept of "lying fallow" to homes and infrastructure, this thesis focuses on abandonment practices that reflect complex realities of labor, capital, and climate uncertainty. Rather than viewing depopulating communities as passive victims of out-migration, this paper argues they are critical sites for generating crisis response. Communally crafted attitudes toward unused space and more-than-human …

Wildfire Impacts On Fluvial Hydrology From Watershed To National Scales, Paige G. Tunby

Civil Engineering ETDs

Wildfires alter the water quantity and quality in downstream river networks. Fires promote biodiversity, maintain habitat, and provide many ecosystem services in a fire-adapted landscape. However, changes in the natural fire regimes can alter ecosystem function and threaten the water security of impacted downstream communities. The magnitude, timing, and persistence of these impacts are difficult to predict due to the lack of high-resolution datasets with adequate coverage to evaluate spatiotemporal trends after a fire. This dissertation moves us beyond the status quo to evaluate post-fire fluvial responses across scales, from the event-scale impacts after the Hermit’s Peak-Calf Canyon wildfire in …

Boundary Integral Method For A Modified Mullins–Sekerka System, Ly Le

Mathematics & Statistics ETDs

This thesis develops a boundary integral method for a modified Mullins–Sekerka system arising as the sharp-interface limit of a nonreciprocal Cahn–Hilliard model. Nonreciprocal coupling changes the classical Cahn–Hilliard structure by introducing an additional conserved field, leading to coupled elliptic and parabolic dynamics at the interface. Using matched asymptotic expansions, we formally derive the modified Mullins–Sekerka model and then apply the boundary integral method to rewrite it on the moving interface. The elliptic component is represented using the periodic Green’s function for the Laplace equation, while the parabolic component is represented using the periodic heat kernel. This method reduces the bulk …

Nerve Constructions And Mapper, Alexander Bram Fritschi

Mathematics & Statistics ETDs

Mapper is a data visualization tool commonly used in topological data analysis to study large, often high-dimensional datasets. Mapper operates through the selection of a lens function, a clustering algorithm, and a cover. The Mapper graph is constructed using the nerve of the cover after the clustering algorithm is performed; it is therefore useful to study nerves to better understand Mapper. In this thesis, we will utilize the properties of nerves to find the minimal point set that produces a given graph. We will then extend this to Mapper to determine what Mapper graphs may be constructed over a given …

Interpretable Case-Control Inference Through Log-Linear General Location Models, Zacharia Stuart

Mathematics & Statistics ETDs

This dissertation analyzes one of the few publicly available NFL injury datasets to study field type and non-contact lower-limb injuries. Field type is studied jointly with other risk factors to understand how these factors interact to affect injury risk. The data were gathered through a case-control sampling scheme, which limits direct inference on absolute injury probabilities. While not the most common approach for case-control data, this dissertation models the retrospective distribution directly through Log-Linear General Location Models (Log-Linear GLOMs). Through a log-linear structure placed on a log-odds-ratio reparameterization, the model provides directly interpretable marginal and interaction contributions to injury log-odds …

The Uncertainty Principles, Lee Michael Felicetti

Mathematics & Statistics ETDs

The Heisenberg uncertainty principle is a central aspect of quantum mechanics, but also illustrates an essential quality of the Fourier transform. After Heisenberg, a variety of uncertainty inequalities emerged in the fields of physics and mathematics. In this thesis we will analyze the Heisenberg uncertainty principle in both the setting of quantum mechanics and Fourier analysis. We will then look at how the work of Heisenberg has been expanded upon in both physics and mathematics. Particularity, we will see how uncertainty principles can be applied to signal recovery and explore current research in this field.

Simulations Of Atmospheric Pressure Streamer Discharges: Mechanisms Of Streamer Propagation And Related Physics, Dejan Nikic

Electrical and Computer Engineering ETDs

Gas discharge simulations are performed with particular focus on photoionization process in a positive streamer discharge. The effects of this process are investigated by isolating the change in photoionization mean free path (MFP) and keeping the additional processes constant. Furthermore, comparison are made between various effects of simulation parameters, such as initial conditions, geometry extent, simula- tion particle count etc. All of these simulations are performed using a modern Direct Simulation Monte Carlo Particle-in-Cell (DSMC-PIC) code developed by Sandia Na- tional Laboratories. Large scale simulations including 1 cm and 5 cm electrode gaps are performed under standard atmospheric condition air. …

Ionophore-Based Plga Nanosensor For Selective Ion Detection And Imaging, Zhiyu Tang

Electronic Theses and Dissertations 2020 - Present

Accurate detection of electrolyte ions is essential for biological research, disease diagnosis, and the investigation of cellular function. In this study, we developed ionophore-based PLGA nanosensors for the optical detection of biologically important ions. The nanosensors were prepared by encapsulating ionophores, chromoionophore III, and ion exchangers within PLGA nanoparticles. The resulting nanosensors showed uniform morphology, good colloidal stability, and concentration-dependent optical responses toward Na⁺, K⁺, and Ca²⁺ over the range of 10⁻⁶ to 10⁻¹ M. Reversible fluorescence responses under repeated ion concentration changes confirmed the stability and robustness of the sensors. The nanosensors also demonstrated reliable analytical performance for K⁺ …

A Hybrid Deep Learning Model Combining Cnn And Extreme Learning Machine For Cyberattack Classification, Israa S. Kamil

Journal of Intelligent Informatics, Networking, and Cybersecurity

As ransomware attacks and zero-day exploits grow sophisticated, the need for intelligent, accurate systems to detect such threats becomes clearer. In this paper, a hybrid learning model based on Convolutional Neural Networks (CNNs) and Extreme Learning Machine (ELM) is presented to improve multiclass classification performance for cybersecurity applications. The framework combines CNNs' hierarchical feature learning with ELMs' fast classification. An attention mechanism that assigns weights to each feature based on importance is included in the final model. The hybrid model performed well on the metrics: precision = 0.97, recall = 0.98, and F1- score = 0.97, and, as expected from …

Towards Intelligent Iot-Ndn Security: Ai-Driven Pit Attack Detection And Cache Attack Analysis, Sura Haidar Ali, Alaa Shawqi Jaber

Journal of Intelligent Informatics, Networking, and Cybersecurity

Beginning with Named Data Networking (NDN), an early form of information-centric networks, the paradigm of how data is transmitted over a network was changed through the use of ``content-based'' communication instead of ``host-based'', while creating native caching at intermediate points along the path to each destination, and improving upon the security of all previous paradigms. NDN contains many inherent benefits such as caching, security, etc., but like any other paradigm, NDN creates new types of vulnerabilities, particularly within some of the key elements of this paradigm; namely the Content Store (CS), Pending Interest Table (PIT), and the Forwarding Information Base …

Escaping The Cyberstorm: A Gamified Social Engineering Training Program, Noah Mcclanahan, Fadi Abu-Amara, Ali Khattab, Travis Jett, Andre Jackson

Journal of Cybersecurity Education, Research and Practice

In this research work, we explored the effectiveness of gamification in improving cybersecurity awareness and training users on targeted social engineering attacks. Traditional cybersecurity training focuses on lectures and videos. These training methods may not actively engage employees, which reduces their knowledge retention and ability to recognize social engineering attacks. This lack of involvement is a concern, as social engineering continues to be one of the most prevalent attack methods faced by end-users. A gamified training program, Escaping the Cyberstorm, was developed using the Godot game engine to address key challenges in spreading cybersecurity awareness. The game includes real-life …

Stop Blaming My Users: Illumination Of The Technocentric Mythos Bias, Ervin H. Frenzel, Richard Lightcap

Journal of Cybersecurity Education, Research and Practice

 Abstract -This conceptual essay addresses the need for systemic and systematic transdisciplinary analytical techniques within cybersecurity and technical security. This conceptual essay is contingent upon recognition that cybersecurity is not simply technical in nature, it does not need an adversary, and more importantly it is based upon systems engineering and systems thinking.  The essay contributes a socio-technical attribution chain and field-specific ontology/taxonomy which distinguish user-triggered events from root causes, latent conditions, technical debt, validation failures, governance failures, and attribution bias before assigning responsibility to end users. It systematically defines an ontology inclusive of developer technical debt, organizational debt arising from …

Artificial Intelligence Mechanisms In The Limit Of Crimes And Law Enforcement, Saad Mefleh Alsuwaileh

Journal of Police and Legal Sciences

This study explores the potential of employing technological mechanisms and modern innovations brought about by the Fourth Industrial Revolution, particularly advancements in the field of information technology, in the domains of criminal investigation, crime prevention, and law enforcement. It aims to analyze the impact of these technologies on crime control efforts and the promotion of justice.

The significance of the study lies in highlighting the power of technology in processing and analyzing massive volumes of data with greater speed and accuracy, thereby enhancing the efficiency of criminal investigations and the ability to predict and prevent crimes. The core research question …

Applying Artificial Intelligence Within Decision Support Systems And Its Role In Improving Proactive Thinking And Reducing Security Threats: The Mediating Role Of Data Quality, Hany Shaaban El Anany

Journal of Police and Legal Sciences

The study aimed to identify the impact of applying artificial intelligence within decision support systems in improving the level of proactive thinking and reducing security threats in government institutions in the Arab Republic of Egypt, as well as to examine the mediating role of data quality in this relationship, at a significance level of (α ≤ 0.05). The study sample consisted of (360) participants working in the departments of information technology, decision support, and cybersecurity within government institutions and national authorities that rely on AI-enhanced decision support systems.

The study adopted the descriptive analytical method and used a questionnaire as …

Spatial Heterogeneity And Temporal Trends Of California Extreme Heat Using High-Resolution Earth System Model Simulations, Eleni Konstantelos

Master's Theses

Extreme heat threatens California’s diverse landscapes and populations through intensifying and geographically shifting patterns. This study examined the temporal trend and spatial heterogeneities of California’s extreme heat for 1994–2015. The analysis was based on the fully coupled Energy Exascale Earth System Model version 2 (E3SMv2), specifically its 25-km regionally refined configuration. While the Desert/Inland region exhibited the highest number of days ≥ 35 °C and the highest heatwave severity, Central Valley showed the fastest increase in the number of days ≥ 35 °C and heatwave events, as well as the fastest increases of days exceeding various heat index thresholds over …

Match Made In Ml: Developing Compatibility Relationships In Evidential Reasoning Approaches With Machine Learning, Ella Jolie Thomas

Master's Theses

The presented expectation maximization informed evidential reasoning model extends the ability of the evidential reasoning calculus to support decision making by integrating an adaptive model learning capability. Compatibility relationships in Evidential Reasoning models are traditionally built by human domain experts. This process is labor-intensive, especially for large and complex models. Additionally, when new data becomes available, compatibility relationships must be reconstructed. Using machine learning and the expectation maximization algorithm, it is demonstrated that compatibility relationships can be constructed that learn relationships between domain knowledge that is used to make decisions. Using drug development as a domain of application, a traditional …

Superresolution Spectroscopy Of Atomically Thin Semiconductors And Moiré Heterostructures, Chien-Chu (Charity) Wei

Master's Theses

Atomically thin semiconductors and moir’e heterostructures provide an important platform for studying quantum phenomena shaped by reduced dimensionality, interlayer coupling, strain, and local structure. In MoS2, the transition from bulk to monolayer form changes the material from an indirect to a direct band gap, while stacked and strain-engineered systems can produce spatially varying moir’e potentials on nanometer length scales. Because these effects are highly localized, conventional far-field optical spectroscopy is often limited in its ability to resolve them directly. This thesis explores superresolution vibrational spectroscopy as a route toward probing local behavior in atomically thin semiconductors and moir’e heterostructures. Far-field …

Error-Tolerant Metric Dimension, Leander Ten Hoff

Master's Theses

Metric dimension is a graph parameter that measures the smallest distance-based unique coordinate system on a graph. Fault-tolerant metric dimension is a variant that requires redundancy. Inspired by this idea, we propose and investigate a new variant we call error-tolerant metric dimension. We first prove some fundamental results to gain familiarity with this more complex variant. Then, we use these tools to study relative behaviors of error-tolerant metric dimension. We prove explicit computations for simple graph families, including bipartite complete graphs and paths. Finally, we extend extremal results from previous papers on metric dimension, including a full correction of an …

The Characterization Of Bridging Waters And Ions In Protein-Rna Complexes, Leslie Duong

Master's Theses

Here we explore the role of bridging waters and ions in protein-RNA complexes. From an initial set of 33 high-resolution X-ray crystal structures, 17 were identified such that protein-RNA complex and component protein and RNA chains were found within 1 pH unit as indicated by crystallization conditions and their diffraction temperatures meeting one of two ranges: above or below freezing. To define an even more realistic set, 12 unbound-unbound and unbound-pseudo-unbound complexes from the 17-set were studied, showing the large fraction of complexes indicating more protein and RNA water hydrogen bonding in their actual interfacial regions as opposed to those …