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An Alternative Approach To Non-Relativistic Quantum Mechanics In Curved Space, Robert A. Hulsey

Dissertations

In the research presented in this dissertation, we propose an alternative formulation of non-relativistic quantum mechanics in curved spaces (Riemannian manifolds). Some toy quantum models (2D quantum harmonic oscillator in Poincaré half-plane model and the flat chart model of hyperbolic 2-space) are studied to understand the physical implications of this alternative formulation.

Μ-Distributions And Μ-Distributed Sequences, Noah Graham Giddings

Undergraduate Honors Thesis Collection

The project attempts to generalize the notion of a uniform distribution for a broader class of probability measures and illustrate one construction of a sequence that satisfies these properties. A sequence ⟨a_n⟩ is uniformly distributed if the limiting relative frequency of sequence elements in any interval I ⊆ [0,1] corresponds with length(I). We generalize the notion of “uniform distribution” for an atomless Borel probability measure µ. We say that a sequence ⟨a_n⟩ is µ-distributed if the limiting relative frequency of sequence elements in any interval I ⊆ [0,1] equals µ( …

A Study Of Complex Analysis After Whittaker And Watson, Crystal Steed

All Graduate Reports and Creative Projects, Fall 2023 to Present

The goal of this report is to provide solutions to the exercises found in chapter five of the book titled, A Course of Modern Analysis: An Introduction to the General Theory of Infinite Processes and of Analytic Functions with an Account of the Principal Transcendental Functions by E.T. Whittaker and G.N. Watson. The fifth chapter is titled, "The Fundamental Properties of Analytic Functions; Taylor's, Laurent's and Liouville's Theorems." This report solves the end-of-chapter exercises in addition to providing details for some in-chapter exercises, which are left to the reader. Many of these exercises are results from famous mathematicians.

Traffic Prediction For Research And Education Networks: Anomaly-Aware Deep Learning And Benchmarking, Mohammad Arafath Uddin Shariff

School of Computing: Dissertations, Theses, and Student Research

Research and Education Networks (RENs) and High-Performance Computing (HPC) environments are critical infrastructures for modern scientific discovery, demanding sustained high-throughput and low-latency data transfers. Unlike commercial networks, RENs exhibit unique traffic characteristics, including predominant “elephant flows,” inherent burstiness, and complex temporal-spatial dynamics often decoupled from human-driven cycles. Traditional traffic forecasting methods, tailored for commercial Wide Area Networks (WANs), consistently fail to capture these distinct REN dynamics, leading to inefficient resource management and potential impediments to scientific progress.

This thesis addresses this critical gap by developing and validating a robust, scalable, and anomaly-aware traffic forecasting framework specifically tailored for REN/HPC networks. …

Analysis Of Popular Songs In The Us Market, Michael Myers

Theses, Dissertations and Culminating Projects

In today’s digitally driven music landscape, understanding what drive’s a song’s popularity requires insight not only into its acoustic and lyrical content, but also into patterns of listener engagement across platforms. This thesis explores the predictive and descriptive dimensions of song popularity by applying supervised and unsupervised machine learning models to a multi-source dataset integrating audio features, sentiment analysis, and temporal consumption behavior. Drawing from a novel, multi-platform dataset that includes Billboard Hot 100 rankings, Spotify acoustic features and popularity scores, streaming, airplay, and sales metrics as reported on Luminate’s Music Connect, and lyrics from AZLyrics, the study investigates the …

Twisted Equivariant Matrix Factorizations, Jan-Luca Spellmann

All Graduate Theses and Dissertations, Fall 2023 to Present

We introduce and study categories of twisted equivariant matrix factorizations MF^α_G(R, w), which are categories of matrix factorizations of a potential w over the local ring R = C[x₁, . . . , x_n] together with an action by a finite group G that is twisted via a 2-cocycle α. These categories provide rich examples of Z/2Z-differentially graded categories in the context of non-commutative geometry and come up naturally in the study of boundary conditions of 3d Rozansky–Witten theories. We prove that under certain assumptions on (R, w …

Analysis Of Multi Grade Deep Learning, Ronglong Fang

Mathematics & Statistics Theses & Dissertations

Multi-Grade Deep Learning (MGDL) is a training framework that incrementally builds deep neural networks. It does this by dividing the training process into multiple “grades,” where each grade sequentially trains a shallow neural network to learn the residue from the previous one, using the outputs of prior grades as input. This approach progresses from shallow to deep architectures. This dissertation offers a comprehensive theoretical and numerical analysis of the MGDL methodology.

We first demonstrate that MGDL can effectively learn target functions within the sum-composition learning format. In this context, MGDL approximates high-frequency components by composing multiple low-frequency functions. This unique …

Utilizing The Horseshoe Prior In Exploratory Factor Analysis And Gaussian Graphical Networks, James Thomas Roddy

Graduate Theses and Dissertations

High-dimensional data analysis frequently involves extracting meaningful structure from noisy, sparse signals. In recent years, Bayesian shrinkage priors—particularly global-local shrinkage priors—have emerged as powerful tools for inducing sparsity while preserving signal fidelity. Among these, the Horseshoe prior has gained notable attention for its capacity to simultaneously shrink irrelevant parameters and retain substantial signals. This dissertation explores the Horseshoe prior as a unified framework for sparse Bayesian inference across theory, simulation, and real-world application. The first component develops new theoretical results establishing the asymptotic Bayes optimality of the Horseshoe prior in Gaussian graphical models (GGMs). We consider sparse precision matrix estimation …

Analysis Of Graph-Based Decoders For Quantum Low Density Parity Check Codes, Kirsten Morris

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

Quantum computing has the potential for radically increased computational ability. However, the physical realization of quantum states are fragile and susceptible to noise and decoherence. For this reason, robust quantum error correction is imperative to achieve quantum computation at scale.

Of particular interest in realizing effective quantum error correction are quantum low density parity check (QLDPC) codes. Classical LDPC codes were invented by Robert Gallager in the 1960s and came in to prominence in the 1990s. Due to Daniel Gottesman’s stabilizer formalism and the invention of Calderbank-Shor-Steane (CSS) codes, we can apply LDPC codes to the quantum setting.

As in …

Certified Approximation Algorithms Of Algebraic Curves, Michael Byrd Jr.

All Dissertations

One of the fundamental problems in mathematics is to determine the set of solutions to a system of equations. In algebraic geometry, the equations studied are polynomials, and the solution set is called an algebraic variety. For single variable polynomials of degree less than five, the roots can be determined exactly using algebraic methods, but for polynomials of degree five or higher, numerical methods are required. When using numerical methods, it is important to know when the computed approximation is indeed a correct solution, which leads to the idea of a certified algorithm. An algorithm is said to be …

Active Calculus: Single Variable, 2nd Edition, Matthew Boelkins, David Austin, Christina Safranski, Steven Schlicker

Open Textbooks

Active Calculus is different from most existing calculus texts in at least the following ways: the text is freely readable online in HTML format and is also freely available for in PDF; in the electronic formats, graphics are in full color and there are live links to java applets; there are live WeBWorK exercises in each chapter, which are fully interactive in the HTML format and included in print in the PDF; the text is open source, and interested users can gain access to the original source files on GitHub; the style of the text requires students to be active …

Rethinking Iterative Proportional Fitting: Scalable And Hybrid Approaches To Joint Distribution Fitting, William Ofosu Agyapong

Open Access Theses & Dissertations

The Iterative Proportional Fitting (IPF) algorithm is widely used in contingency table estimation, survey weighting, and synthetic population generation due to its simplicity and strong theoretical foundation for matching observed marginal distributions. However, in high-dimensional settings, IPF faces substantial computational and memory demands, as well as statistical instability caused by sparse contingency tables. Moreover, IPF is less useful in modern population synthesis tasks that require both scalability and realism because, despite its superiority in matching known marginal distributions, it cannot produce realistic out-of-sample data points. To address these limitations, we first propose a blockwise IPF framework, in which the feature …

Laser Scan Path Design For Controlled Microstructure In Additive Manufacturing With Integrated Reduced-Order Phase-Field Modeling And Deep Reinforcement Learning, Augustine Twumasi

Open Access Theses & Dissertations

Laser Powder Bed Fusion (L-PBF) is a well-established additive manufacturing technique for fabricating intricate metal components with exceptional precision. A significant challenge in L-PBF is the formation of complex microstructures that influence final material properties. We propose a physics-guided, machine learning-aided approach to optimize scan paths for desired microstructure outcomes, such as equiaxed grains. We employed a phase-field method (PFM) to model the evolution of the crystalline grain structure. To reduce computational costs, we trained a surrogate machine learning model, a 3D U-Net convolutional neural network, using single-track phase-field simulations with varying laser powers to predict crystalline grain orientations based …

An Introduction To Reverse Mathematics Through The Weakened Base System Rca_0^*., Kaden Dvorak

Boise State University Theses and Dissertations

The purpose of reverse mathematics, a field of mathematical logic, is to determine which axioms are required to prove particular mathematical theorems. Gödel's first incompleteness theorem states that within any standard consistent formal system of mathematics, there are statements for which neither themselves nor their negations can be proven. Thus, the goal of reverse mathematics cannot be the discovery of some formal system which underlies all mathematics, which was that of Hilbert's program. Instead, the questions lie in how much mathematical reasoning can be represented and how strong the formal systems are required to be to conduct said reasoning. In …

Quantifying The Sensitivity Of Land Use Land Cover Metrics Through Simulation Techniques, Haley Burger

All Graduate Theses and Dissertations, Fall 2023 to Present

As human activities and climate change continue to reshape our landscape, understanding how land use changes over time is becoming increasingly important. Accurate ways to track and analyze these changes are essential for governments, businesses, and communities to make informed decisions. Monitoring agricultural land is particularly critical, as shifts in land use can impact food production and environmental pollutants. One of the primary tools used in the United States to monitor agricultural land is the Cropland Data Layer (CDL), an annual map created by the United States Department of Agriculture (USDA) from satellite images. While the CDL is highly accurate, …

Studies In Number Theory: Reciprocity Laws And Fundamental Domains, C. Xavier Parent

All Graduate Theses and Dissertations, Fall 2023 to Present

This thesis consists of two sections. The first section is an introductory survey of number theory discussing the reciprocity laws with a focus on accessibility. Number Theory has always been a fundamental area of mathematical study, with Gauss calling it “the queen of mathematics”. The reciprocity laws are a classical set of results from number theory which have driven number theory for quite a long time. Unfortunately, these results, while important, have always been very inaccessible to undergraduate students, making it hard to start studying the field. This survey attempts to help bridge that gap, giving a resource for novices …

Multiple Monochromatic Subgraphs In Edge-Colored Graphs, Emma Felicity Jent

Dissertations

Ramsey theory, though a relatively young branch of mathematics, has captivated the attention of graph theorists, combinatorialists, and theoretical computer scientists alike through its raw beauty, versatility, and powerful applications. Before it emerged as a branch of mathematics, the central idea of Ramsey theory appeared in the form of three lemmas in three separate papers by three different mathematicians working on three distinct areas of research. The first such lemma was published by David Hilbert in 1892, followed by the second lemma published by Issai Schur in 1916. However, Frank Ramsey’s renowned lemma, published in 1930, compelled mathematicians to establish …

Preservation Of The Bernstein Property For Sums Of Independent Random Variables, Iosif Pinelis

Michigan Tech Publications

It is shown that Bernstein-type conditions on independent random variables are preserved by their sum. Some optimality properties of such preservation are proved.

(A,B,C) Tilings With Prescribed Symmetry Groups From Regular Triangle Or Hexagon Tiling, Mark D. Tomenes, Ma. Louise Antonette N. De Las Penas

Mathematics Faculty Publications

A tiling T of the Euclidean plane (E2) is a countable collection of closed topological disks called tiles T = {Ti : i ∈ N} that is a covering (Ui Ti = E2) as well as a packing (Int(Ti) ∩ Int(Tj) = ∅ if i ̸= j, Int(T) denotes the interior of tile T). One of the problems of interest in discrete geometry is the classification of tilings based on transitivity properties of their vertices, edges and tiles. This talk presents a family of tilings whose vertices, edges and tiles have exactly a, b and c orbits, respectively, under the …

Congruences For Quotients Of Klein Forms, Jeffery Opoku

Theses and Dissertations

This dissertation investigates the arithmetic properties of some modular forms and eta quotients, focusing on the divisibility properties and congruence relations satisfied by these. The first part examines quotients of the Rogers-Ramanujan and Rogers-Selberg functions, defined by \[ f(\tau) = q^{r} (q^5; q^5)^{a_0} (q, q^4; q^5)^{a_1} (q^2, q^3; q^5)^{a_2}= \sum_{n=r}^{\infty} P_{a_0,a_1,a_2}(n-r) q^n, \] and \[ g(\tau) = q^{s} (q^7; q^7)^{a_0} (q, q^6; q^7)^{a_1} (q^2, q^5; q^7)^{a_2} (q^3, q^4; q^7)^{a_3}= \sum_{n=s}^{\infty} P_{a_0,a_1,a_2,a_3}(n-s) q^n, \] respectively. We establish conditions on the exponents \(a_0, a_1, a_2, a_3\) and residue classes \(r\) and $s$ modulo $p$ such that \(P_{a_0, a_1, a_2}(pn - r) \equiv …

Certified Computation Of Julia Sets Via Numerical Methods, Hannah Kaufman

All Theses

The chaotic and fractal nature of Julia sets makes them difficult to graph. This research aims to provide graphical approximations of Julia sets with known and guaranteed levels of accuracy. We implement three methods to approximate Julia sets with c values chosen from the main cardioid of the Mandelbrot set. Each method utilizes different properties of these Julia sets. The exclusion method makes use of the fact that a Julia set of this type is topologically a circle. Attracting and repelling fixed points are used to find a region on the interior of the Julia set and a region on …

On The Garoufalidis-Kashaev State-Integral Invariant, Amelia Palmer Dusenbury

Boise State University Theses and Dissertations

This thesis explores a construction of the family of topological invariants for certain oriented 3-manifolds based on the state-integral approach developed by Andersen, Garoufalidis, and Kashaev in the Archimedean setting. Starting from an ideal triangulation of a 3-manifold equipped with angle data, variables are assigned to the faces and tetrahedra, taking values in a so-called 'Gaussian group'. The invariant is defined by integrating a distribution defined from the combinatorics of the triangulation and a special function over a product of the Gaussian group. The special function is a quantum dilogarithm, whose valuable feature, the pentagon relation, ensures the resulting integral …

Optimal Quantization For Nonuniform Discrete Distributions, Russel Cabasag, Samir Huq, Eric Mendoza, Mrinal Kanti Roychowdhury

School of Mathematical & Statistical Sciences Faculty Publications

This paper explores the process of optimal quantization for several types of discrete probability distributions. Quantization is a technique used to approximate a complex distribution with a smaller set of representative points, which is important in fields such as data compression and signal processing. We begin by examining two specific nonuniform distributions over a finite set of values and identify the best representative points for different levels of approximation. We then extend our analysis to two infinite discrete distributions: one supported on the reciprocals of natural numbers and another on the natural numbers themselves. For these distributions, we compute the …

Constructing Code-Based Zero-Knowledge Proofs Leveraging Generic Errors And Bounded Vectors, Freeman Slaughter

All Dissertations

Quantum computing is developing at an expeditious rate, and once fully scalable quantum computers become realized, classical cryptographic systems face obsolescence. This approaching peril has prompted a paradigm shift away from pre-quantum cryptography and towards post-quantum primitives, such as those that arise from the field of coding theory. Among these, zero-knowledge proofs have emerged as a dynamic tool instrumental in constructing quantum-resilient digital signature schemes.

We being by introducing HammR, a pre-quantum zero-knowledge proof protocol designed to verify Hamming weight and entry constraints of error vectors, and comprehensively establish its security. Subsequently, we extend HammR to the multi-party computation setting, …

Online Multiobjective Optimization, Kristen Joyce

All Dissertations

Online optimization (OO) is an iterative process of decision making under uncertainty. At every step, a decision is made before the outcome of this decision is known. For the online optimization model, the objective function is unknown at the time the decision is being made. It is very likely that the taken decision is not optimal, so the decision maker incurs a loss, called regret, in every iteration. The goal of the online optimization algorithm is to compute a decision at every step so that the overall regret cost is minimized. In particular, the average regret produced by an ideal …

Interpolation In Weighted Projective Spaces, Shahriyar Roshan Zamir

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

Over an algebraically closed field, the double point interpolation problem asks for the vector space dimension of the projective hypersurfaces of degree $d$ singular at a given set of points.

After being open for 90 years, a series of papers by J. Alexander and A. Hirschowitz in 1992–1995 settled this question in what is referred to as the Alexander-Hirschowitz theorem. In this thesis, we use commutative algebra to prove analogous statements in the weighted projective space, a natural generalization of the projective space.

A main contribution of this work is the careful adaption of several classical algebro-geometric techniques to the …

On Kernels And Antiderivatives Of Nonlocal Derivatives, Alex John Heitzman

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

Nonlocal operators are mathematical operators taking functions to other functions f → Df , where to evaluate the operator Df at a point x, one must know the value of f in some region around x, and that region cannot be arbitrarily small. Nonlocal derivatives are like derivatives in that they measure the deviation of a function f(z) from f(x) when z is close to x. In this thesis, we will study nonlocal operators of the form

D_kf(x) = [integral]_Ω [f(x) …

Homomesies And Toggleability Spaces, Alec Mertin

All Dissertations

We study the homomesy phenomenon under the rowmotion operator acting on order ideals of posets. We provide details for the extensions of several results in the literature concerning homomesies of toggleability statistics from finite to infinite orbits, which allows us to obtain homomesies for piecewise-linear and birational rowmotion, even in the case of infinite orbits. Integral to this is a novel generalization of a result in the literature, which relaxes the conditions needed to lift a statistic.

We completely describe the order ideal (resp. antichain) toggleability space for general fences: the space of statistics which are linear combinations of …

2-Adic Quantum Mechanics, Continuous-Time Quantum Walks, And The Space Discreteness, Wilson A. Zuniga-Galindo

School of Mathematical & Statistical Sciences Faculty Publications

The authors show that a large class of 2-adic Schrödinger equations is the scaling limit of certain continuous-time quantum Markov chains (CTQMCs). Practically, a discretization of such an equation gives a CTQMC. As a practical result, new types of continuous-time quantum walks (CTQWs) on graphs using two symmetric matrices are constructed. The transport between nodes in one direction is described by one matrix, while the transport between nodes in the opposite direction. This construction includes, as a particular case, the CTQWs constructed using adjacency matrices. The final goal of this work is to contribute to the understanding of the foundations …

Properties Of A Class Of Analytic Functions Associated With Exponentially Convex Functions, K. R. Karthikeyan, Elangho Umadevi, G. Thirupathi, Dharmaraj Mohankumar

All Works

Studies in univalent function theory comprising the exponential of differential characterizations are rarely considered. The prominent study in this direction is the study of so-called α-exponentially convex functions. Here we study a class of analytic functions which satisfy an analytic characterization influenced by the definition of the multiplicative derivative and α-exponentially convex functions. Integral representation and coefficient inequalities of the defined function class are the main results of the paper.