Analysis Commons^™

Supersymmetric Quantum Fields Via Quantum Probability, Radhakrishnan Balu

Journal of Stochastic Analysis

The super version of imprimitivity theorem is available now to describe global supersymmetry of systems using the representations of super Lie groups (SLG). This result uses the equivalence between super Harish- Chandra pairs and super Lie groups, at the categorical level, and is applicable to super Poincaré group and generalizes a smooth SI to super context. We apply the result to build supersymmetric quantum fields. Towards this end, we set up a super Fock space of a disjoint union of super Hilbert spaces which is equivalent to super tensoring of boson (even) part symmetrically and that of fermion (odd) part …

Convergence To Fractional Brownian Motion For Weighted Random Sums In Besov Space, Ibrahima Mendy

Journal of Stochastic Analysis

We consider infinite sums of weighted i.i.d. random variables, with finite variance and arbitrary distribution, and we derives conditions for the weak convergence in Besov space of normalized sums to fractional Brownian motion (fBm).

Pricing Variance Swaps Using Extended Heston Model, Semere Gebresilasie, Mulue Gebreslasie, Indranil Sengupta

Journal of Stochastic Analysis

Abstract. In this study, we introduce a variance swap for the underlying asset utilizing the Heston model, incorporating a long-term variance that is treated as a stochastic function of time. We develop a closed-form solution for the variance swap under this framework, where the log returns are driven by a compound Poisson process. Our analysis of historical data reveals that long-term variance is not constant; instead, it fluctuates over time, reflecting market dynamics more accurately. By integrating this time-varying long-term variance into the model, we achieve an improvement in prediction performance of approximately 60%. Furthermore, we perform model calibration using …

Uniform Stability Of Katyusha In Strongly-Convex Settings, Don Li

University Honors Theses

Acceleration of convergence and reduction of variance constitute a trade-off in the design of stochastic optimization machine learning algorithms. Katyusha was introduced to address this trade-off, synthesizing Nesterov Accelerated Gradient (NAG) and Stochastic Variance-Reduced Gradient (SVRG) into a single first-order optimizer with promising empirical performance. However, the generalization properties of Katyusha remain largely unexplored. We conjecture that, in the smooth quadratic regime (i.e., under assumptions of strong convexity and smoothness of the loss function, and boundedness of gradients), Katyusha is uniformly stable in the sense of Bousquet and Elisseeff. Instantiating our framework for NAG, we extend the use of Lyapunov …

On The Fractional Laplacian Type Operator, Maysam Abdulnaser Zain

Thesis/ Dissertation Defenses

In this thesis, we study analytical structures arising from Dunkl theory and their applications to harmonic analysis and fractional Laplacian operators. Dunkl operators are differential-difference operators associated with finite reflection groups, providing a natural generalization of the classical Fourier analysis through the introduction of root systems and multiplicity functions. Within this framework, several classical transforms appear as special cases of the (k,a)-generalized Fourier transform. We study the generalized Fourier transform, its kernel, and the associated translation operator and convolution structures. Using these tools, we construct the corresponding heat kernel and analyze the associated heat semigroup. Our main contribution concerns the …

Constructing Orthonormal Bases With The Residuals Of Successive Approximations, An Introduction To Multiresolution Analysis, Elijah J. Guptill

Master's Theses

Wavelets and wavelet analysis are used in the study of signal processing, quantum field theory, functional analysis, multifractal analysis, and various other areas of mathematics. Multiresolution analysis provides a framework for building a wavelet basis of $\mathcal{L}^{2}(\mathbb{R})$ from a scaling function $\phi$, whose dyadic dilations and translations, $\{2^{j /2}\phi(2^{j}x-k):j,k\in \mathbb{Z}\}$, approximate $\mathcal{L}^{2}(\mathbb{R})$. One of the key properties of  $\phi$ is that it must satisfy $\phi(x)=\sum_{k\in \mathbb{Z}}{p_{k}2^{j /2}\phi(2^{j}x-k)}$ with respect to the norm on $\mathcal{L}^{2}(\mathbb{R})$. This equation is called a two-scale difference equation. Such equations enforce a regularity on the ordinary generating function $2^{-1 /2}\sum_{k\in \mathbb{Z}}{p_{k}z^{k}}$, known as the quadrature condition. …

Introduction To Mathematical Analysis Ii, Beatriz Lafferriere, Gerardo Lafferriere, Mau Nam Nguyen

PDXOpen: Open Educational Resources

These lecture notes complement the book Introduction to Mathematical Analysis I, Third Edition, with sections on integration, numerical series, series of functions, and selected advanced topics. Together, both volumes support a one semester or two-quarter course on introductory mathematical analysis.

Adopt/Adapt

If you are an instructor adopting or adapting this PDXOpen textbook, please help us understand your use by filling out this form.

Variational Methods For Semilinear Pdes With Dirac Singularities, Samuel J. Magill

Dissertations, Theses, and Capstone Projects

This dissertation utilizes a variational framework for semilinear elliptic equations in two dimensions with Dirac measure data. The central objects of study are equations of the form −ΔU = f(U) + Σ_j=1^N α_jδ_pj on bounded Lipschitz domains Ω ⊂ ℝ² with homogeneous Dirichlet boundary condition, and on a flat torus 𝕋², where α_j is positive for the Dirichlet setting and α_j is negative on the torus. Solutions are obtained by minimizing the restriction of an energy functional to an order interval determined by explicit sub- and supersolutions; the Euler–Lagrange equation is recovered …

Whitney Extension Problem For Fractional Sobolev Spaces And Besov Spaces, Han Li

Dissertations, Theses, and Capstone Projects

In the dissertation, we go through the development of the Whitney extension problem and prove a type of results for the Whitney extension problem for homogeneous fractional Sobolev spaces and homogeneous Besov spaces.

This dissertation consists of four chapters:

Chapter 1: We recall the history of the Whitney extension problem and talk about some early works which have been done for the Whitney extension problem. We also mention our new results.

Chapter 2: We introduce some basic notations, definitions and preliminary results.

Chapter 3: We show the existence of a bounded linear extension operator for homogeneous fractional Sobolev space L …

Effectiveness Of The Guided Discovery Method In Teaching The Surface Area Of A Cylinder, Paul Ahortu

2026 Symposium

This study investigates the impact of the guided discovery instructional method on students’ understanding of the surface area of a cylinder. A quasi-experimental pre-test–post-test design was conducted with 100 senior high school students in Cape Coast, Ghana, divided into experimental and comparison groups..

Results showed a substantial improvement in performance for students exposed to guided discovery, with mean scores increasing from 1.25 (pre-test) to 9.43 (post-test) and a large effect size (Cohen’s d = 2.70). Statistical analysis also revealed significant gender differences in achievement.

These findings indicate strong improvement following the guided discovery intervention and suggest its potential to enhance …

Momentum Space Algorithm For Electronic Structure Of Double-Incommensurate Trilayer Graphene, Kenneth Silver Beard

LSU Doctoral Dissertations

Numerical algorithms for computing the electronic structure of incommensurate 2D-materials using ab initio models are critical for predicting material properties and guiding experiments. For bilayers, momentum space and continuum models have been introduced to approximate observables of ab initio tight-binding models using a momentum description, despite the lack of periodicity in the tight-binding model required for Bloch theory. A similar structure has been introduced for double-incommensurate trilayers using a continuum model, where the three lattices are mutually incommensurate. However, this description leads to a four-dimensional lattice space, and numerical convergence of the density of states has been observed to be …

Bounded Multiplication And Composition Operators On Sequence Besov Spaces, Robert Anderson

Mathematical Sciences Undergraduate Honors Theses

The sequence Besov space $b_p$, $p>1$, is the space of analytic functions $f(z)=\sum_{n=0}^{\infty} a_n\, z^n$ on the open unit disk

$\mathbb D$ with $$\sum_{n=0}^{\infty} n^{p-1}\, |a_n|^p< \infty\, .$$

We will give a brief introduction to the space $b_p$, as well as explore how certain operators behave on the space. For example, let $\varphi$ be an analytic self-map of $\mathbb D$. We study the multiplication operator $M_\varphi$ on $b_p$ and look at examples including when $\varphi$ is a polynomial. We also study the composition operator $C_\varphi$ on $b_p$, and in more depth on $b_2$ the Dirichlet space. The culmination will be an …

A New Approach To Generate Combinatorial Patterns In Logical Analysis Of Data And Its Application To Predict College Retention, Salihah Ahmed E. Jaafari

Theses and Dissertations

Student retention and degree completion remain central challenges for higher-education institutions, with significant implications for student success, institutional effectiveness, and public accountability. While advances in predictive analytics have enabled earlier identification of students at risk of withdrawal, many commonly used machine learning approaches suffer from limited interpretability, constraining their practical usefulness for advising, intervention, and policy decision making. This dissertation addresses the problem of predicting student persistence by developing and evaluating optimization based, interpretable classification models within the Logical Analysis of Data (LAD) framework. Building on existing LAD formulations, this research introduces two novel pattern generation models, the Best Term …

Lebesgue’S Theory Of Integration: An Introduction To Modern Integration Theory, Nathanael C. Krug

Senior Honors Theses

The depth and richness of integration theory far surpasses the introductory material presented in an elementary calculus classroom. The work of Bernhard Riemann and Henri Lebesgue demonstrates just a small sample of the richness of the field of analysis. In formulating and contrasting the Riemann and Lebesgue integrals, students can gain an enriched and well-rounded introduction to integration theory. This not only deepens understanding and love for previously learned material, but also enables further study within the fields of analysis and measure theory. An introductory primer to integration theory equips students with the tools needed to continue their exploration of …

From Counting To Advanced Math: How Five Simple Axioms Shape The Mathematical Landscape, Joy Skaggs

ATU Scholars Symposium

In the late nineteenth and early twentieth centuries, mathematics faced a foundational crisis: Greog Cantor’s set theory led to an interesting self-referencing paradox in math and questions about the logical consistency of mathematics. From this crisis, two opposing viewpoints emerged: the Formalists and the Intuitionists. The Formalists praised Cantor’s work as a way to place math on a secure logical foundation, ensuring the discipline’s purity, however the Intuitionists despised Cantor’s work and heralded Cantor as a charlatan and corrupter of the youth. The leader of the Formalists, David Hilbert, proposed a formal system of rigorous proofs to build a complete …

Employing Effective Solution Methods For Caputo-Based Sequential Fractional Models, Eman A. A. Ziada, Mohamed F. Abouelenein, Hijaz Ahmad, Monica Botros

Mathematical Modelling and Numerical Simulation with Applications

This paper investigates a class of nonlinear sequential singular fractional differential equations (FDEs) involving Caputo derivatives. This type of equation has several key advantages that enhance its value, such as capturing memory and hereditary effects. Viscoelastic materials and anomalous diffusion, as well as biological systems, can take advantage of this feature. In addition, fractional derivatives possess a sequential structure that enables the implementation of multiscale processes and hierarchical memory responses. Moreover, it provides an effective and flexible framework for solving differential equations compared to classical differential equations. It can therefore be used to model complex systems in physics, biology, and …

On Links Between A Theorem Of Schoenberg, Rohlin Decompositions Of Measures, The Bochner-Minlos Theorem And The Fock Space, Daniel Alpay, Paula Cerejeiras, Palle Jorgensen, Uwe Kaehler

Mathematics, Physics, and Computer Science Faculty Articles and Research

The main goal of this paper is to gain new results in stochastics by drawing on, and combining, different areas that are normally not considered to be related. Thus, in this paper we extend the previous class of Gaussian-like functions ML which will allow for future generalized stochastic processes in infinite dimensional analysis. We show that an approach similar to the one by the classical Bochner-Minlos theorem for the white-noise case can be achieved by using Gaussian-like functions belonging to a large family -the ML_r classes (0 < r ≤∞). We show how Schoenberg’s theorem for positive definite functions on a Hilbert space allows to go beyond the classical setting of Bochner-Milnos theorem. Furthermore, we show that the application of the Rohlin’s disintegration theorem allows for a decomposition of the associated probability measures , see Theorems 3.2 and 4.3. We end this paper with several important examples of functions in these classes ML_r and provide some interesting counterexamples, e.g. Theorem 7.4, to get a …

Empirical Validation Of Einstein’S Coefficient For The Deflection Of Light Due To Gravitational Forces, Alexandra R. Mcdowell

Honors College Theses

Einstein’s formula to calculate the deflection angle of light through space as it interacts with gravity was introduced in his 1916 publication on general relativity. This was not a new idea, but his equation was, and it was correct. Just 3 years after this publication, it was empirically validated by Sir Arthur Eddington and Sir Frank Dyson. Since that experiment in 1919, at least seven others have been performed that also gave definitive answers in support of Einstein’s deflection constant of 1.751 arcseconds. The two most recent ones made groundbreaking contributions to this effort. The 2017 eclipse showed reproducible results …

Norm-Variation Of Triple Ergodic Averages For Commuting Transformations, Polona Durcik, Lenka Slavíková, Christoph Thiele

Mathematics, Physics, and Computer Science Faculty Articles and Research

We prove an r-variation estimate, r>4, in the norm for ergodic averages with respect to three commuting transformations. It is not known whether such estimates hold for all r≥2 as in the analogous cases for one or two commuting transformations, or whether such estimates hold for any r< ∞ for more than three commuting transformations.

Minimal Supersolution Of Bsdes Driven By Continuous Martingales In A General Filtration, Badr Elmansouri, Mohamed El Otmani

Journal of Stochastic Analysis

In this paper, we study minimal supersolutions of backward stochastic differential equations (BSDEs) driven by a continuous local martingale in a general filtration. We establish existence, uniqueness, and stability results under various mild conditions on the terminal value and the generator. Additionally, we explore the connection between the concept of non-linear expectation and minimal supersolutions, emphasizing the specific properties that are relevant to our framework. We also prove a general monotonic limit theorem and apply this result to determine the smallest constrained supersolution of a BSDE with a possibly non-convex constraint.