Graduate Courses, Summer 2024 – Spring 2025

Contact


Please direct inquiries about our graduate program to:
grad@math.lsu.edu

Summer 2024

For Detailed Course Outlines, click on course numbers.

7999-1 Problem Sessions in Algebra—practice for PhD Qualifying Exam in Algebra

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7999-2 Problem Sessions in Analysis—practice for PhD Qualifying Exam in Analysis

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  • Prerequisite:
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7999-3 Problem Sessions in Topology—practice for PhD Qualifying Exam in Topology

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  • Prerequisite:
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7999-4 Problem Sessions in Applied Math—practice for PhD Qualifying Exam in Applied Math

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  • Instructor:
  • Prerequisite:
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7999-n Assorted Individual Reading Classes

  • No additional information.

8000-n Assorted Sections of MS-Thesis Research

  • No additional information.

9000-n Assorted Sections of Doctoral Dissertation Research

  • No additional information.

Fall 2024

For Detailed Course Outlines, click on course numbers. Core courses are listed in bold.

4997-1 Vertically Integrated Research: Algebraic geometry for matroids. Profs. Achar and Bălibanu

  • 11:30-12:20 MWF
  • Instructor: Profs. Achar and Bălibanu
  • Prerequisite: Math 4200 or Math 4153 or permission of the instructors
  • Text: None
  • Description: Matroids are objects in combinatorics that capture the key features of the notion of "linear independence" in linear algebra, while also having connections to graph theory, Galois theory, and other subjects. In 2022, June Huh was awarded a Fields Medal in part for his work on resolving a 50-year-old problem in matroid theory called the "Dowling-Wilson conjecture," also called the "top heavy conjecture." The proof involved importing ideas from topology and algebraic geometry, such as intersection cohomology, Kazhdan-Lusztig theory, and Hodge theory. In this course, we'll study some of the ingredients of this proof, and we'll see how to place the work of Huh and his collaborators in the broader context of recent developments in representation theory and algebraic geometry.

4997-2 Vertically Integrated Research: Groups with remarkable origins. Profs. Dani and Schreve

  • 1:30-2:50 TTh
  • Instructors: Profs. Dani and Schreve
  • Prerequisite: Math 4200 or 4023
  • Text: none
  • Description: Groups are ubiquitous in Mathematics. A first course in Algebra usually includes examples such as the symmetric group, matrix groups, or groups that arise as symmetries of some objects (eg. tilings of a plane). This course will introduce a variety of infinite groups that have more unusual origins, such as dynamical systems, logic and computer science, and explore their often surprising geometric and algebraic properties. Topics will include Thompson’s, Self-similar, Lamplighter, and Baumslag-Solitar groups, which are all important examples in geometric group theory.

4997-3 Vertically Integrated Research on Geometry and Topology. Profs. Vela-Vick and ...

  • 12:00-1:20 TTh
  • Instructors: Profs. Vela-Vick and ...
  • Prerequisite: A first course in linear algebra, experience with topology or abstract algebra is helpful but not required
  • Text: none
  • Description: This is a project-based seminar class in geometry and topology. Students work together in small groups to tackle current research problems in topics such as knot theory, differential geometry, symplectic and contact topology, etc.

7001 Communicating Mathematics I. Prof. Shipman and Dr. Ledet

  • TTh 3:00-4:50
  • Instructor: Prof. Shipman and Dr. Ledet
  • Prerequisite: Consent of department. This course is required for all first-year graduate students. It is a lab course meeting for an average of two hours per week throughout the semester for one-semester-hour's credit.
  • This course provides practical training in the teaching of mathematics at the pre-calculus level, how to write mathematics for publication, and treats other issues relating to mathematical exposition. Communicating Mathematics I and II are designed to provide training in all aspects of communicating mathematics. Their overall goal is to teach the students how to successfully teach, write, and talk about mathematics to a wide variety of audiences. In particular, the students will receive training in teaching both pre-calculus and calculus courses. They will also receive training in issues that relate to the presentation of research results by a professional mathematician. Classes tend to be structured to maximize discussion of the relevant issues. In particular, each student presentation is analyzed and evaluated by the class.

7210 Algebra I. Prof. Hoffman

  • 8:30-9:20 MWF
  • Instructor: Prof. Hoffman
  • Prerequisite: Math 4200 or its equivalent
  • Text: Dummit and Foote, Abstract Algebra
  • Description: This is the first semester of the first year graduate algebra sequence. It will cover the basic notions of group, ring, and module theory. Topics will include symmetric and alternating groups, Cayley's theorem, group actions and the class equation, the Sylow theorems, finitely generated abelian groups, polynomial rings, Euclidean domains, principal ideal domains, unique factorization domains, finitely generated modules over PIDs and applications to linear algebra, field extensions, and finite fields.

7230 Topics in Number Theory: Arithmetic of CM Elliptic Curves and Modular Forms. Prof. Tu

  • 10:30-11:20 MWF
  • Instructor: Prof. Tu
  • Prerequisite:

    1. Math 7210 (Algebra), Math 4036 (complex analysis) or equivalent are 
very helpful. You should be comfortable with meromorphic and analytic
 functions, groups theory, group actions, Galois theory, and module theory.

    2. Know how to find resources and references to help you to understand the material better.

    3. Know how to use computer algebra systems (such as Maple, Mathematica, MATLAB, SageMath, or Magma).

  • Text: We will mainly follow chapters 1 and 2 in the book Advanced Topics in the Arithmetic of Elliptic Curves by Joseph H. Silverman.
  • Description: Elliptic curves with complex multiplication (CM) have many special properties. The (arithmetic) properties of CM elliptic curves play an important role in the research of number theory and arithmetic geometry, especially in the class field theory of imaginary quadratic fields, modular forms, L-functions and Galois representations. The course will begin with basic definitions and examples of CM elliptic curves, review important properties in class field theory and modular forms, and will talk about the connection with Grossencharacters (Hecke characters). In the later part of the semester, we will discuss some applications, advanced topics, and open problems, depending on students’ interest.

7240 Algebraic Geometry. Prof. X Wang

  • 2:30-3:20 MWF
  • Instructor: Prof. X Wang
  • Prerequisite:
  • Text: There are no required text, but the following references will be helpful:

    Algebraic Geometry: Notes on a Course, Michael Artin, Graduate Studies in Mathematics 222

    Algebraic Geometry, Robin Hartshorne, Graduate Texts in Mathematics, Spring-Verlag, 52.

  • Description: This is a beginning graduate course in the topics of Algebraic Geometry, including the introduction to classical complex algebraic varieties and its modern form using the methods of schemes and cohomology. The course goal is to enable the students to understand the basic notions and properties in algebraic varieties in an affine or projective space over an algebraically closed field and to be familiar with the methods of schemes and cohomology to study topics in the classical theory of algebraic curves and surfaces.

7311 Real Analysis (a.k.a. Analysis I). Prof. Tarfulea

  • 9:30-10:20 MWF
  • Instructor: Prof. Tarfulea
  • Prerequisite: Undergraduate real analysis
  • Text: Stein and Shakarchi : Real Analysis
  • Description: This is a standard introductory course on analysis based on measure theory and integration. We start by introducing sigma algebras and measures. We will then discuss measurable functions and integration of real and complex valued functions. As an example we discuss the Lebesgue integral on the line and n-dimensional Euclidean space. We also discuss the Lebesgue integral versus the Riemann integral. Important topics here are the convergence theorems, product measures and Fubini’s theorem and the Radon-Nikodym derivative. We give a short discussion of Banach spaces and Hilbert spaces. We then introduce Lp spaces and discuss the main properties of those spaces. Further topics include functions of bounded variations Lebesgue differentiation theorems, Lp and its dual. Other topics might be included depending on the time.

7325 Numerical Analysis and Applications. Prof. Walker

  • 1:30-2:50 TTh
  • Instructor: Prof. Walker
  • Prerequisite: Analysis (MATH 4031, 4032), Numerical Linear Algebra (MATH 7710)

    Some basic functional analysis and PDE theory (MATH 4340, or MATH 7386 or equivalent) will be reviewed. Prior exposure to numerical analysis (MATH 4065 or 4066) and Python would be useful but not mandatory.

  • Text: Instructor will use course notes.

    Various Reference Texts: The Finite Element Method for Elliptic Problems, (Classics in Applied Mathematics, 2002) by Philippe G. Ciarlet;
    Finite Elements: Theory, Fast Solvers, and Applications in Solid Mechanics, 3rd edition (2007) by D. Braess;
    The Mathematical Theory of Finite Element Methods, 3rd or 4th Edition (2008) by S. Brenner, R. Scott.

  • Description: The finite element method (FEM) is one of the most successful computational tools in dealing with partial differential equations (PDE) arising in science and engineering (solid and fluid mechanics, electromagnetism, mathematical physics, etc.). The formulation of the FEM, its properties, stability, and convergence will be discussed. Implementation and programming of the FEM will also be addressed mainly via Python programming projects. We will also use open source software for this.

    Additional topics will be introduced depending on the interests of the class.

7350 Complex Analysis. Prof. Antipov

  • 12:30-1:20 MWF
  • Instructor: Prof. Antipov
  • Prerequisite: Math 7311
  • Text:Lecture notes and Complex Analysis by Elias Stein and Rami Shakarchi, Princeton Lectures in Analysis II.
  • Description: Theory of holomorphic functions of one complex variable; path integrals, power series, singularities, mapping properties, normal families, other topics.

    More specifically: Holomorphic and meromorphic functions of one variable including Cauchy's integral formula, theory of residues, the argument principle, and Schwarz reflection principle. Multivalued functions and applications to integration. Meromorphic functions. The Fourier transform in the complex plane. Paley-Wiener theorem. Wiener-Hopf method and the Riemann-Hilbert problem. Entire functions including Jensen's formula and infinite products. Conformal mapping including the Riemann mapping theorem and the Schwarz-Christoffel integral. In the case of sufficient time, further topics include the Gamma and Zeta functions and an introduction to the theory of elliptic functions.

7360 Probability Theory: Prof. Sundar

  • 11:30-12:20 MWF
  • Instructor: Prof. Sundar
  • Prerequisite: Math 7311
  • Text: Probability and Stochastics by Erhan Cinlar
  • Description: Probability spaces, random variables and expectations, independence, convergence concepts, laws of large numbers, convergence of series, law of iterated logarithm, characteristic functions, central limit theorem, limiting distributions, martingales.

    This is a self-contained introduction to modern probability theory. Starting from the concept of probability measures, it would introduce random variables, and independence. After a study of various modes of convergence, the Kolmogorov strong law of large numbers and results on random series will be established. Weak convergence of probability measures will be discussed in detail, which would lead to the central limit theorem and its applications. A main goal of the course is to develop the concept of conditional probability and its basic properties. Stochastic processes such as Brownian motion and martingales will be introduced, and their essential features, studied.

7365 Applied Stochastic Analysis. Prof. Ganguly

  • 12:00-1:20 TTh
  • Instructor: Prof. Ganguly
  • Prerequisite: Math 7360. This can be taken concurrently with Math 7365, provided that the student has a good background in measure theory and real analysis.
  • Text:
  • Description: Math 7365 is a course on stochastic processes. A stochastic process can be thought of as a random function of time which originates in modeling temporal dynamics of many systems. Detailed modeling of such systems requires incorporation of their inherent randomness which deterministic methods, for example, through differential equations fail to capture. Examples of such systems are numerous and wide ranging - from biological networks to financial markets. Markov processes, in particular, form one of the most important classes of stochastic processes that are ubiquitous in probabilistic modeling. They also lead to probabilistic interpretations of a large class of PDEs. For example, Brownian motion is the underlying Markov process whose probability distribution satisfies the heat equation. The course will cover theory of martingales and Markov processes in discrete-time. Some specific topics include Doob's decomposition theorem, Doob's inequalities, Burkholder-Davis-Gundy inequality, Kolmogorov's equations, generators, stationary measures and some elementary stability theory. If time permits, we will also make some remarks about the continuous-time case and briefly discuss some stochastic algorithms like Markov Chain Monte Carlo, importance sampling, stochastic approximation methods which are instrumental in probabilistic approach to data-science. The course is also a gateway to the course on stochastic analysis (Math 7366).

7380 Seminar in Functional Analysis: Spherical Harmonics and Integral Geometry. Prof. Rubin

  • 10:30-11:20 MWF
  • Instructor: Prof. Rubin
  • Prerequisite: Real analysis (MATH 7311); Functional Analysis (MATH 7330)
  • Text: B. Rubin, Introduction to Radon transforms: With elements of fractional calculus and harmonic analysis (Encyclopedia of Mathematics and its Applications), Cambridge University Press, 2015, ISBN-10: 0521854598, ISBN-13: 978-0521854597.
  • Description: This course-seminar is focused on the Fourier analysis on the unit sphere and related operators of integral geometry in the n-dimensional real Euclidean space. Operators of this kind arise in PDE, harmonic analysis, group representations, mathematical physics, geometry, and many other areas of mathematics and applications.

7382 Introduction to Applied Mathematics. Prof. Massatt

  • 9:00-10:20 TTh
  • Instructor: Prof. Massatt
  • Prerequisite: Simultaneous enrollment in Math 7311
  • Text: Lecture notes
  • Description: Overview of modeling and analysis of equations of mathematical physics, such as electromagnetics, fluids, elasticity, acoustics, quantum mechanics, etc. There is a balance of breadth and rigor in developing mathematical analysis tools, such as measure theory, function spaces, Fourier analysis, operator theory, and variational principles, for understanding differential and integral equations of physics.

7386 Theory of Partial Differential Equations. Prof. Bulut

  • 10:30-11:50 TTh
  • Instructor: Prof. Bulut
  • Prerequisite: Math 7330
  • Text: Partial Differential Equations by L. C. Evans
  • Description: Sobolev spaces. Theory of second order scalar elliptic equations: existence, uniqueness and regularity. Additional topics such as: Direct methods of the calculus of variations, parabolic equations, eigenvalue problems.

7390 Seminar in Analysis: Optimization, Calculus of Variations, and Optimal Control. Prof. Wolenski

  • 1:30-2:20 MWF
  • Instructor: Prof. Wolenski
  • Prerequisite:
  • Text: Lecture Notes Fundamentals of Optimization by R.T. Rockafellar
  • Description: This course will cover Lecture Notes written by R.T. Rockafellar. The rough outline of the course is:
    I. What is Optimization?
    II. Problem Formulation
    III. Unconstrained Minimization
    IV. Constrained Minimization
    V. Lagrange Multipliers
    VI. Games and Duality
    X. Exercises

7490 Seminar in Combinatorics, Graph Theory, and Discrete Structures: Probabilistic Methods in Combinatorics. Prof. Z Wang

  • 3:00-4:20 MW
  • Instructor: Prof. Z Wang
  • Prerequisite: Familiarity with basic background of combinatorics and probability.
  • Text: Alon and Spencer, The probabilistic method, Wiley, 4th edition, ISBN: 978-1-119-06195-3.

    Other useful resources:

    Luke Postle (from University of Waterloo)’s youtube recordings on Probabilistic Methods Video.

    Yufei Zhao (from MIT)’s lecture notes on Probabilistic Methods PDF.

  • Description: This course is a graduate-level introduction to the probabilistic method, a fundamental and powerful technique in combinatorics and theoretical computer science. The probabilistic method is a nonconstructive method, primarily used in combinatorics and pioneered by Paul Erdös, for proving the existence of a prescribed kind of mathematical object. The essence of the approach is as follows: to show the existence of some combinatorial object, we prove by showing a certain random construction works with positive probability. This method has now been applied to other areas of mathematics such as number theory, linear algebra, and real analysis, as well as in computer science (e.g. randomized rounding), and information theory. The course will focus on methodology as well as combinatorial applications.

    Topics: Linearity of expectations, Alteration, Second Moment Methods, Chernoff bound, Lov´asz local lemma, Correlation inequalities, Janson inequalities, Concentration of measure, Entropy method, Container method, Random graphs.

7510 Topology I. Prof. Dani

  • 10:30-11:50 TTh
  • Instructor: Prof. Dani
  • Prerequisite: Advanced Calculus (Math 4031)
  • Text: Topology (2nd ed.) by James R. Munkres.
  • Description: This course is a preparation course for the Core I examination in topology. It will cover general (point set) topology, the fundamental group, and covering spaces. We will also introduce simplicial complexes and manifolds. A good supplementary reference is Chapter 1 of Algebraic Topology by Allen Hatcher, available online.

7560 Riemannian Geometry. Prof. Vela-Vick

  • 9:00-10:20 TTh
  • Instructor: Prof. Vela-Vick
  • Prerequisite: MATH 7550
  • Text: Riemannian Geometry by Manfredo P. do Carmo
  • Description: Riemannian metrics and connections, geodesics, completeness, Hopf-Rinow theorem, sectional curvature, Ricci curvature, scalar curvature, Jacobi fields, second fundamental form and Gauss equations, manifolds of constant curvature, first and second variation formulas, Bonnet-Myers theorem, comparison theorems, Morse index theorem, Hadamard theorem, Preissmann theorem, and further topics such as sphere theorems, critical points of distance functions.

7590 Seminar in Geometry and Algebraic Topology: Combinatorial Algebraic Topology. Prof. Bibby

  • 9:30-10:20 MWF
  • Instructor: Prof. Bibby
  • Prerequisite: Math 7512: Topology II
  • Text: Combinatorial Algebraic Topology by Kozlov
  • Description: We will learn about some fundamental tools for computing algebraic invariants of a topological space with an underlying combinatorial structure (eg. a partially ordered set). Topics may include, as time and interest allows, discrete Morse theory, shellability, sheaf theory, (homotopy) colimits, and spectral sequences.

7999-n Assorted Individual Reading Classes

  • No additional information.

8000-n Assorted Sections of MS-Thesis Research

  • No additional information.

9000-n Assorted Sections of Doctoral Dissertation Research

  • No additional information.

Spring 2025

For Detailed Course Outlines, click on course numbers.

4997 Vertically Integrated Research: Polyhedral complexes and their automorphism groups. Profs. Dani and Schreve

  • MWF 10:30-11:20
  • Instructors: Prof. Dani and Schreve
  • Prerequisite: Math 4200 or 4023
  • Text: None
  • Description: This is a project-based seminar course in geometry and topology focussing on complexes built out of polyhedra and the groups that act on them. Specific interesting examples that we will see are buildings, lattices in products of trees, and systolic complexes. Students will focus on understanding concrete classical examples through problem-solving.

4997 Vertically Integrated Research: Prof. Drenska

  • TTh 1:30-2:50
  • Instructors: Prof. Drenska
  • Prerequisite: 2085 or equivalent, as well as a 4000-level mathematics course with a grade of C or better, or obtain permission of the department
  • Text: Gilbert Strang: Linear Algebra and Learning from Data
  • Description: This is a project-based course that involves real-world applications of machine learning. The course provides opportunities for students to consolidate their mathematical knowledge, and to obtain a perspective on the meaning and significance of that knowledge. Course work will emphasize communication skills, including reading, writing, and speaking mathematics.

7002 Communicating Mathematics II. Prof. Shipman and Dr. Ledet

  • TTh 3:00-4:50
  • Instructor: Prof. Shipman and Dr. Ledet
  • Prerequisite: Consent of department. This course is required for all first-year graduate students. It is a lab course meeting for an average of two hours per week throughout the semester for one-semester-hour's credit.
  • This course provides practical training in the teaching of mathematics at the pre-calculus level, how to write mathematics for publication, and treats other issues relating to mathematical exposition. Communicating Mathematics I and II are designed to provide training in all aspects of communicating mathematics. Their overall goal is to teach the students how to successfully teach, write, and talk about mathematics to a wide variety of audiences. In particular, the students will receive training in teaching both pre-calculus and calculus courses. They will also receive training in issues that relate to the presentation of research results by a professional mathematician. Classes tend to be structured to maximize discussion of the relevant issues. In particular, each student presentation is analyzed and evaluated by the class.

7211 Algebra II. Prof. Ng

  • MWF 01:30-02:20
  • Instructor: Prof. Ng
  • Prerequisite: Math 7210 or equivalent
  • Text:
  • Description: Fields: algebraic, transcendental, normal, separable field extensions; Galois theory, simple and semisimple algebras, Wedderburn theorem, group representations, Maschke’s theorem, multilinear algebra.

7230 Topics in Number Theory: Hypergeometric Functions. Prof. Long

  • MWF 02:30-03:20
  • Instructor: Prof. Long
  • Prerequisites:
  • Text:
  • Description:

7290 Seminar in Algebra and Number Theory: Derived Algebraic Geometry. Prof. Achar

  • TTh 10:30-11:50
  • Instructor: Prof. Achar
  • Prerequisite:
  • Text:
  • Description:

7290 Seminar in Algebra and Number Theory. Prof. He

  • MWF 08:30-09:20
  • Instructor: Prof. He
  • Prerequisite:
  • Text:
  • Description:

7320 Ordinary Differential Equations. Prof. Wolenski

  • MWF 09:30-10:20
  • Instructor: Prof. Wolenski
  • Prerequisite: Undergraduate ODEs and analysis
  • Text: I will begin with my notes and then follow the text An Introduction to Dynamical Systems: Continuous and Discrete (Pure and Applied Undergraduate Texts), 2nd Edition, by R. Clark Robinson
  • Description: Existence and uniqueness theorems, approximation methods, linear equations, nonlinear equations, stability theory; other topics such as boundary value problems.

7330 Functional Analysis (a.k.a. Analysis II). Prof. Estrada

  • TTh 09:00-10:20
  • Instructor: Prof. Estrada
  • Prerequisite: Math 7311 or its equivalent
  • Text: Trèves, F., Topological Vector Spaces, Distributions, and Kernels; Dover, 2006.
  • Description: A standard first course in functional analysis. Topics include Banach spaces, Hilbert spaces, Banach algebras, topological vector spaces, spectral theory of operators and the study of the topology of the spaces of distributions.

7366 Stochastic Analysis. Prof. Sundar

  • TTh 12:00-01:20
  • Instructor: Prof. Sundar
  • Prerequisite: Math 7311, and Math 7360 or its equivalent
  • Text: Typed lecture notes will be given.
  • Description: First, the essential features of Brownian motion, martingale theory, and Markov processes are studied. Next, stochastic integrals are constructed with respect to Brownian motion and in general, semimartingales. A central role in stochastic analysis is played by the It\^o formula with far-reaching consequences. After its proof and applications, the theory of stochastic differential equations driven by a Brownian motion is presented. The fundamental connection between stochastic differential equations and a class of parabolic partial differential equations will be established.

7375 Wavelets. Prof. Nguyen

  • MWF 10:30-11:20
  • Instructor: Prof. Nguyen
  • Prerequisite: Math 7311
  • Text: Introduction to Fourier Analysis and Wavelets by M. A. Pinsky, Graduate Studies in Mathematics, Volume 102, AMS, and instructor's own notes
  • Description: This course is a basic introduction to Fourier analysis and wavelets. Topics to be covered include Fourier series, Fourier transform, Shannon sampling theorem, Heisenberg uncertainty principle, windowed/short time Fourier transform, and basic wavelet theory (including multiresolution analysis and the construction of various wavelets).

7384 Topics in Material Science: Free fracture theory and non-local differential equations. Prof. Lipton

  • MWF 12:30-01:20
  • Instructor: Prof. Lipton
  • Prerequisite: Math 7311 and Math 7386 or Permission of Instructor
  • Text: Course notes will be provided
  • Description:

    The mechanics of fracture propagation provides essential knowledge for the risk tolerant design of devices, structures, and vehicles. Ideally fracture should emerge naturally from a field theory described by an initial boundary problem. Nonlocal approaches to fracture modeling are formulated along these lines, coupling fracture caused by breaking bonds at the atomic scale with continuous and discontinuous deformation at the macroscopic scale. Both localization and emergent behavior is the hallmark of theory and simulations using nonlocal formulations. The numerical solution of the nonlocal differential equation provides for spectacular results. On the other hand the field theory while promising is in its early stages and needs to recover established results in a mathematically rigorous and systematic way.

    In this course we introduce the nonlocal initial boundary value problem and prove convergence to a sharp fracture theory in the limit of vanishing non-locality. This is a highly nonlinear problem involving methods introduced in the past 15 years. We introduce the generalization of Sobolev space given by the Special Functions of Bounded Variation (SBV) and Special Functions of Bounded Deformation (SBD). We review their fine properties over Lebesgue measurable sets. We define and show Gamma convergence of the nonlocal energy to the classic Griffith fracture energy. Here we apply non-local methods used in the proof of the de Giorgi’s conjecture for the convergence of non-local approximations of the Mumford Shah functional developed by Gobbino. These are used in conjunction with slicing decompositions of SBV and SBD together with the integralgeometric measure of geometric measure theory. Convergence of the dynamics of intact material away from the crack is established with the aid geometric measure theory.

    We conclude the course, showing how the kinetic relations of classic fracture theory, relating the speed of propagation of the crack tip singularity to the energy flowing into it are derived directly from the non-local differential equation and then passing to the local limit.

    This course represents the beginning of the story. For example in the non-local differential equation the notion of regularity of solution, including the rigorous origins of crack branching, remains unanswered. These questions also lie on the frontiers of the physics describing the fracture process.

7390 Seminar in Analysis: Topics in Dispersive Partial Differential Equations. Prof. Bulut

  • TTh 01:30-02:50
  • Instructor: Prof. Bulut
  • Prerequisite: Math 7311 (Additional coursework such as Math 7330 or Math 7386 beneficial but not required. The course will be self contained and no explicit prior coursework in PDE is required.)
  • Materials:
    T. Tao. Nonlinear Dispersive Equations: Local and Global Analysis. CBMS 106 (2006), Amer. Math. Soc. and selected additional references.
    F. Linares and G. Ponce. Introduction to Nonlinear Dispersive Equations.
    C. Sogge. Lectures on Non-Linear Wave Equations.
    T. Cazenave. Semilinear Schrödinger Equations.
    C. Sulem and P.L. Sulem. The Nonlinear Schrödinger Equation: Self-Focusing and Wave Collapse.
    B. Dodson. Defocusing Nonlinear Schrödinger Equations.
  • Description: The course will provide an introduction to nonlinear dispersive PDE, making use of tools from harmonic analysis. The subject is closely related to models arising in mathematical physics as well as a number of areas of contemporary research in analysis. No prior experience with PDE is necessary, as the course will be self-contained. Students working in applied analysis, harmonic analysis, PDE, and related areas are highly encouraged to participate.

7390 Seminar in Analysis: Prof. Wan

  • MWF 01:30-02:20
  • Instructor: Prof. Wan
  • Prerequisite:
  • Text:
  • Description:

7410 Graph Theory. Prof. Z Wang

  • TTh 01:30-02:50
  • Instructor: Prof. Z Wang
  • Prerequisite: None
  • Text: Graph Theory by Reinhard Diestel, Fifth Edition, Springer, 2016
  • Description: The main theme of this course will be graph theory. We will discuss a wide range of topics, including spanning trees, eulerian trails, matching theory, connectivity, hamiltonian cycles, coloring, planarity, integer flows, surface embeddings, Turan theorems, Ramsey theorems, regularity lemma, and graph minors.

7512 Topology II. Prof. Cohen

  • TTh 12:00-01:20
  • Instructor: Prof. Cohen
  • Prerequisite: Math 7510
  • Text: Algebraic Topology by Hatcher
  • Description: This course covers the basics of homology and cohomology theory. Topics discussed may include singular and cellular (co)homology, Brouwer fixed point theorem, cup and cap products, universal coefficient theorems, Poincare duality, Alexander duality, Kunneth theorems, and the Lefschetz fixed point theorem.

7550 Differential Geometry. Prof. Baldridge

  • TTh 09:00-10:20
  • Instructor: Prof. Baldridge
  • Prerequisite: Math 7210 and 7510; or equivalent.
  • Text: An Introduction to Manifolds by L. Tu.
  • Description: Manifolds, vector fields, vector bundles, transversality, deRham cohomology, metrics, other topics.

7590 Seminar in Geometry and Algebraic Topology: L2 Homology. Prof. Schreve

  • MWF 09:30-10:20
  • Instructor: Prof. Schreve
  • Prerequisite: Math 7512: Topology II
  • Text: Lecture notes Introduction to L^2-methods in topology by Beno Eckmann
  • Description: Given a metric space, it is often useful to have homological invariants which depend on the metric. L^2-homology is such an invariant, typically defined on the universal cover of a manifold or cell complex, where one allows infinite chains which satisfy decay conditions. Some operator algebra theory implies that these homology groups come with dimensions, the so-called L^2-Betti numbers. This course will start with the fundamentals of the theory and then go into recent applications to geometric topology and geometric group theory. Additional topics may include: Charney-Davis conjecture, Coxeter groups, homological growth, algebraic fibering, L^2-torsion

7590 Seminar in Geometry and Algebraic Topology: Gromov-Witten Theory. Prof. Baldridge

  • TTh 12:00-01:20
  • Instructor: Prof. Baldridge
  • Prerequisite:
  • Text:
  • Description:

7710 Advanced Numerical Linear Algebra. Prof. Brenner

  • TTh 10:30-11:50
  • Instructor: Prof. Brenner
  • Prerequisite: Linear Algebra and Advanced Calculus and Programming Experience
  • Text: Fundamentals of Matrix Computations (Second Edition), D.S. Watkins (available for download through the LSU library)
  • Description: This is an introductory course in numerical linear algebra at the graduate level. Topics include

    • mathematical tools: norms, projectors, Gram-Schmidt process, orthogonal matrices, spectral theorem, singular value decomposition
    • error analysis: round-off errors, backward stability and conditioning
    • general systems: LU decomposition, partial pivoting, Cholesky decomposition and QR decomposition
    • sparse systems: the methods of Jacobi, Gauss-Seidel, steepest descent and conjugate gradient
    • eigenvalue problems: power methods, Rayleigh quotient iteration and QR algorithm

7999-n Assorted Individual Reading Classes

  • No additional information.

8000-n Assorted Sections of MS-Thesis Research

  • No additional information.

9000-n Assorted Sections of Doctoral Dissertation Research

  • No additional information.