A Nonstandard Exploration Of Approximate Identity And Unitization,
2026
Harvey Mudd College
A Nonstandard Exploration Of Approximate Identity And Unitization, Tong (Nicole) Wu
HMC Senior Theses
The goal of this senior thesis is to explore general nonstandard analysis and some possible applications to 𝐶*-algebras in functional analysis. More specifically, we shall define an approximate identity of a 𝐶*-algebra using nonstandard analysis and study nonstandard hulls of internal 𝐶*-algebra in the context of different unitizations. We shall also prove a few results for ideals in 𝐶*-algebra using nonstandard definitions of approximate identities. We shall also briefly discuss the history and developments of nonstandard analysis.
Pursuer Evader Surveillance Game,
2026
University of Richmond
Pursuer Evader Surveillance Game, Zijie Mu
Honors Theses
This thesis studies the pursuer evader surveillance game with a triangular obstacle in the short-term. In the game, the pursuer aims to maintain surveillance of the evader as long as possible while the evader aims to break surveillance in a finite time. We classify the player strategies into ideal ones and best admissible ones. The outcome of the game is determined by line of sight. We reduce the 4D game to a 3D game with a boundary separating two different local regimes. When the evader starts inside the threshold, we show that there exists an admissible evader that maintains an …
Education And The Maternal Childcare Gap: Evidence From The Uk Covid-19 Pandemic,
2026
University of Richmond
Education And The Maternal Childcare Gap: Evidence From The Uk Covid-19 Pandemic, Lara Bakhaya
Honors Theses
This paper examines whether college education shapes working mothers’ access to remote work, flexible working, and childcare hours in the United Kingdom, and whether COVID-19 school closures amplified these inequalities. Using data from the UK Time Use Survey (2016–2021), a repeated cross-sectional diary dataset spanning the pre-pandemic period and five COVID-19 waves, this paper estimates weighted logistic and ordinary least squares regressions on a sample of married or cohabiting, employed mothers. School closures serve as a natural experiment, providing an exogenous shock to caregiving demands that affected all mothers simultaneously regardless of education level. College education significantly predicted working from …
Spillover Effects Of Medicare Advantage On Fee-For-Service Post-Acute Care Spending,
2026
University of Richmond
Spillover Effects Of Medicare Advantage On Fee-For-Service Post-Acute Care Spending, Nyel Bangash
Honors Theses
Does the growth of Medicare Advantage reduce fee-for-service post-acute care spending through practice-pattern spillovers, or do observed spending differences primarily reflect favorable selection? Using a county-level panel of roughly 2,700 counties (2014–2023) and a two-way fixed effects specification, I find that a one percentage-point increase in MA penetration is associated with $9.54 less per-capita standardized FFS spending. Spending per episode falls while participation rates remain stable, consistent with practice-pattern spillovers rather than compositional changes from selection. Welfare indicators from County Health Rankings, CDC PLACES, and CMS Care Compare show no evidence that spending reductions harm health or care quality. The …
Soft-Constrained Variants Of T-Distributed Stochastic Neighbor Embedding For Global Structure Preservation,
2026
University of Texas at Arlington
Soft-Constrained Variants Of T-Distributed Stochastic Neighbor Embedding For Global Structure Preservation, Joseph A. Balderas
Mathematics Dissertations
Dimensionality reduction (DR) is a fundamental tool in data science and machine learning that transforms high-dimensional data into a low-dimensional representation while preserving important structural properties of the original data. Among modern DR methods, t-distributed stochastic neighbor embedding (t-SNE) has become one of the most widely used techniques for visualization due to its strong ability to preserve local neighborhood structure and produce visually separated clusters. However, despite its popularity, t-SNE is well known to struggle with preserving global structure of data, often producing embeddings in which distances between clusters and neighborhoods do not accurately reflect relationships in the high-dimensional space. …
Math Anxiety, Math Self-Concept And Math Self-Efficacy: A Study Of The Jingle-Jangle Fallacies,
2026
Andrews University
Math Anxiety, Math Self-Concept And Math Self-Efficacy: A Study Of The Jingle-Jangle Fallacies, Marsha Natasha Durrant-Walker
Dissertations
Problem
The overlap and lack of clear distinction among the constructs of math anxiety, math self-concept, and math self-efficacy presents issues for research and practice. The literature reveals that math anxiety is closely linked to math self-concept (Klee et al., 2022). Additionally, math self-concept and math self-efficacy often overlap and are not easily distinguishable (Kranzler & Pajares, 1997; Pajares & Miller, 1994; Pajares & Urdan, 1996). Each of these constructs has been shown to play a critical role in student math achievement (Timmerman et al., 2016). -- When constructs are not defined or measured distinctly, inconsistencies may emerge in research …
Adaptive Multi-Grade Deep Learning For Highly Oscillatory Fredholm Integral Equations Of The Second Kind,
2026
Sun Yat-sen University
Adaptive Multi-Grade Deep Learning For Highly Oscillatory Fredholm Integral Equations Of The Second Kind, Jie Jiang, Yuesheng Xu
Mathematics & Statistics Faculty Publications
This paper studies the use of Multi-Grade Deep Learning (MGDL) for solving highly oscillatory Fredholm integral equations of the second kind. We provide rigorous error analyses of continuous and discrete MGDL models, showing that the discrete model retains the convergence and stability of its continuous counterpart under sufficiently small quadrature error. We identify the DNN training error as the primary source of approximation error, motivating a novel adaptive MGDL algorithm that selects the network grade based on training performance. Numerical experiments with highly oscillatory (including wavenumber 500) and singular solutions confirm the accuracy, effectiveness and robustness of the proposed approach.
A New Parallel-In-Time Direct Inverse Method For Nonlinear Differential Equations,
2026
Old Dominion University
A New Parallel-In-Time Direct Inverse Method For Nonlinear Differential Equations, Nail K. Yamaleev, Subhash Paudel
Mathematics & Statistics Faculty Publications
We propose a new method for parallelization of the first-order backward difference discretization (BDF1) of the first-order time derivative in nonlinear partial differential equations, such as conservation law equations. The time derivative term is discretized by using the method of lines based on the implicit BDF1 scheme, while the inviscid and viscous terms are approximated by conventional 2nd-order central discretizations of the 1st- and 2nd-order derivatives in each spatial direction. The global system of nonlinear discrete equations in the space-time domain is solved by the Newton method for all time levels simultaneously. For the BDF1 discretization, this all-at-once system at …
Spectral Decimation On The Schreier Graphs Of The Basilica Group: A Thesis In Fractal Analysis,
2026
Scripps College
Spectral Decimation On The Schreier Graphs Of The Basilica Group: A Thesis In Fractal Analysis, Anne D. Bannon
Scripps Senior Theses
This thesis is intended to provide a comprehensive overview of the literature required to fully understand research conducted during the University of Connecticut's Fractals & Stochastics REU in the summer of 2025. The literature review includes a description of Robert Strichartz's seminal work pertaining to the Laplacian spectrum of the Sierpiński Gasket, which provides a framework for how we approach studying the spectrum of the basilica Julia set. Defining the basilica Julia set and the closely-related Basilica group involves graph theory, automata theory, iterated monodromy group theory, and amenable group theory. Further time is dedicated to defining the graph Laplacian …
Real Interpolation: An Approximate Introduction,
2026
Scripps College
Real Interpolation: An Approximate Introduction, Madeline Anderson
Scripps Senior Theses
This thesis provides an introduction to real interpolation. We establish
relevant notions in functional analysis first, and use these concepts to study
real interpolation using J. Peetre’s 𝐾-functional in some detail. We also
explore the basics of approximation theory, in particular the connection
between approximation and interpolation results.
Arrangements Of N Planes Resulting In One Bounded Tetrahedral Chamber,
2026
The University of Akron
Arrangements Of N Planes Resulting In One Bounded Tetrahedral Chamber, Ava Knight
Williams Honors College, Honors Research Projects
This paper investigates the combinatorial geometry of plane arrangements in three-dimensional space, focusing on configurations that produce exactly one bounded tetrahedral chamber. We define T(n) as the number of face-combinatorial equivalence classes of arrangements of n planes in ℝ³ containing exactly one bounded tetrahedral chamber. Known values — T(3) = 0, T(4) = 1, and T(5) = 2 — are established through direct construction, while T(6) remains an open problem. This paper contributes experimental evidence toward resolving T(6) by systematically extending the two valid 5-plane arrangements and verifying, through a plane removal argument, that each yields a valid plane configuration …
Catalan And Hyper-Catalan Numbers: Combinatorial Applications To Polynomial Equations,
2026
The University of Akron
Catalan And Hyper-Catalan Numbers: Combinatorial Applications To Polynomial Equations, Leilani Natale
Williams Honors College, Honors Research Projects
In this paper, we study Catalan numbers and their generalization, hyper-Catalan numbers, and explore how these sequences arise naturally in the context of solving polynomial equations using infinite power series. We begin by introducing the Catalan numbers through their combinatorial interpretation as triangulations of convex polygons. Using this geometric definition, we derive a relation whose recursive structure leads to a quadratic functional equation. Interpreting this relation as a formal power series equation allows us to express solutions to quadratic equations as infinite power series whose coefficients are given by the Catalan numbers. This framework is then extended by allowing polygon …
Memory Effects In Many-Body Systems,
2026
San Jose State University
Memory Effects In Many-Body Systems, Jeffrey Beckstrand
Master's Projects
This thesis investigates memory effects in many-body systems through the MoriZwanzig Formalism for projected dynamics of a Hamiltonian System which yields the Generalized Langevin Equation (GLE). The GLE is a stochastic differential equation (SDE) that studies the dynamics of observables under the effects of many other observables in the system. Although satisfying, the GLE has a term called the Memory Kernel that encodes the past of the system and introduces a computational challenge by introducing a non-Markovian property to the equation. The kernel is often approximated by introducing a delta function, which simplifies the computation, but at the loss of …
Infimum Dimension Nash Embeddings For 2d Projective Shape Analysis,
2026
Missouri University of Science and Technology
Infimum Dimension Nash Embeddings For 2d Projective Shape Analysis, Robert L. Paige, Vic Patrangenaru
Mathematics and Statistics Faculty Research & Creative Works
Vector embeddings make complicated data extracted from networks, words and images, more amendable to data science applications. At the present time, the Veronese-Whitney (VW) matrix embedding of the real projective space is the state of the art for making inference about digital images from an uncalibrated camera, such as a cell phone or security camera. In this work we consider vector embeddings for the projective shape data and in particular determine the minimum dimension isometric (distance-preserving or Nash) vector embedding for a projective space. We determine such an embedding for the projective plane in closed-form. From this embedding we determine …
A Fully Discrete Semi-Implicit Numerical Scheme And Its Optimal Error Estimates For Cahn-Hilliard-Mhd Model With Variable Density,
2026
Missouri University of Science and Technology
A Fully Discrete Semi-Implicit Numerical Scheme And Its Optimal Error Estimates For Cahn-Hilliard-Mhd Model With Variable Density, Dongmei Duan, Fuzheng Gao, Xiaoming He, Yanping Lin
Mathematics and Statistics Faculty Research & Creative Works
This paper proposes and analyzes a fully discrete semi-implicit unconditionally energy stable numerical scheme to solve the Cahn-Hilliard Magnetohydrodynamics (Cahn-Hilliard-MHD) model with variable density. The unconditional energy stability and optimal L2 error estimates are established for the fully discrete scheme. Major challenges in error estimation arise from the variable density, the strong nonlinearities, and the multi-physics coupling of the model. Under the mathematical induction framework, the Ritz quasi-projection and the Stokes quasi-projection, proposed in [SIAM J. Numer. Anal., 61(3):1218-1245, 2023], are utilized to avoid the gradient terms of the projection errors. The H−1 superconvergence error estimates of Ritz …
Integer-Valued Time Series Model Via Copula-Based Bivariate Skellam Distribution,
2026
Qassim University
Integer-Valued Time Series Model Via Copula-Based Bivariate Skellam Distribution, Mohammed Alqawba, Norou Diawara, Mame Mor Sene
Mathematics & Statistics Faculty Publications
Time series analysis is crucial for modeling and forecasting diverse real-world phenomena. Traditional models typically assume continuous-valued data; however, many applications involve integer-valued series, often including negative integers. This paper introduces an approach that combines copula theory with the bivariate Skellam distribution to handle such integer-valued data effectively. Copulas are widely recognized for capturing complex dependencies among variables. By integrating copulas, our proposed method respects integer constraints while modeling positive, negative, and temporal dependencies accurately. Through simulation and an empirical study on a real-life example, we demonstrate that our class of models performs well. This approach has broad applicability in …
Temporal Variational Graph Autoencoder For Influenza Evolution,
2026
University of Arkansas, Fayetteville
Temporal Variational Graph Autoencoder For Influenza Evolution, Soumya Chauhan
2026 Research Poster Competition
Frequent mutations in influenza virus surface proteins can increase infectivity while evading human and vaccine immunity, causing seasonal epidemics. The CDC annually evaluates thousands of virus strains to predict mutated sequences likely to be dominant in the next season, which creates a need for methods that better capture how viral mutations evolve over time. In this study, we represent influenza protein sequences as a network-like graph, creating connections if sequences are collected a week apart and only differ by one mutation. This method explicitly considers time information as part of the evolution, while other existing methods analyze mutated sequences without …
Lie-Galois Theory,
2026
University of Central Florida
Lie-Galois Theory, Giovanni Reed
Honors Undergraduate Theses
Differential equations are a much-studied topic in the field of mathematics, as well as other sciences, such as engineering, economics, and biology. While much is known concerning these, there is still a large gap in our knowledge about such equations. It is important therefore, both to mathematics and other sciences, that we gain a more complete knowledge of differential equations, in particular the nature of their solutions. In this research, we investigate the solution space of linear ordinary differential equations (ODEs) from the standpoint of differential algebra. Differential algebra allows an ODE to be treated similarly to a polynomial, allowing …
Dominating Hadwiger's Conjecture For 2k2-Free Graphs,
2026
University of Central Florida
Dominating Hadwiger's Conjecture For 2k2-Free Graphs, Thomas Tibbetts
Honors Undergraduate Theses
A dominating Kt minor in a graph �� is a sequence (��1,…,��t) of pairwise disjoint non-empty connected subgraphs of ��, such that for 1≤��< ��≤��, every vertex in ��j has a neighbor in ��i. Replacing “every vertex in ��j” by “some vertex in ��j” retrieves the standard definition of a ��t minor. The strengthened notion was introduced by Illingworth and Wood in 2024, who asked whether every graph with chromatic number �� contains a dominating ��t minor. This is a substantial strengthening of the celebrated Hadwiger’s Conjecture, which asserts that every …
Spectral Properties And The Behavior Of The Current-Current Correlation Measure For The Luttinger-Sy Model,
2026
University of Kentucky
Spectral Properties And The Behavior Of The Current-Current Correlation Measure For The Luttinger-Sy Model, Jonathan Benoit
Theses and Dissertations--Mathematics
The Luttinger-Sy Model, sometimes referred to as the Pieces Model, is a Random Schrodinger Operator on L2(R) which is characterized in part by "pieces" whose endpoints are chosen by a Poisson Point Process. The Hamiltonian in this setting is then given as a direct sum of Laplacians with Dirchlet boundary conditions on each piece. In this work, we show several spectral properties of the Luttinger-Sy Model, including proving the deterministic spectrum is [0,infinity) and that a Wegner-type and Minami-type estimate both hold. Additionally, we show that the finite-volume Current-Current Correlation Measure is singular continuous with respect …
